Search

Background Objective Methods Results and Conclusions The COVID‐19 has accelerated the transition to blended learning (BL) in higher education, prompting a need for further investigation into the efficacy of self‐regulated learning strategies (SRLS) in these new educational environments.The primary goal of this research is to assess the effectiveness of SRLS in BL in higher education over the past five years, with a focus on trends, theoretical underpinnings, methodologies, and their impact on learning outcomes.This paper used the PRISMA 2020 review process for multiple rounds of screening, encompassing identification, screening, eligibility determination, and final inclusion. Following rigorous screening procedures, a total of 15 SSCI articles were ultimately chosen for analysis. The study design incorporated a comprehensive six‐part coding scheme, with the selected articles focusing on SRLS in BL environments within higher education.From 2019 to 2023, research on SRLS in BL environments in higher education has primarily focused on resource management, motivational beliefs, and metacognitive strategies, with a relatively limited emphasis on cognitive strategies. These studies have utilized a diverse range of theoretical frameworks, predominantly employing quantitative and mixed methods. Out of the 15 articles reviewed, 14 clearly indicate that SRLS have a positive impact on learning outcomes. Furthermore, this paper underscores the importance of interdisciplinary research and emphasizes the crucial role played by educators in supporting the implementation of SRLS. Future studies should delve deeper into exploring the effects of individual differences and environmental factors on SRLS. [ABSTRACT FROM AUTHOR]

Background: AI can positively influence teaching by offering support for classroom management, creating inclusive learning environments, enhancing digital skills, personalizing teaching methods, and strengthening teacher‐student relationships. Objectives: This quantitative research study investigates the opportunities, difficulties, and consequences of incorporating AI into teacher education. Methods: Data were collected through structured questionnaires from 202 college students and 68 staff members. The analysis was conducted using SPSS software. Results: The study provides a novel contribution by its thorough investigation of the diverse effects of AI on teacher education. It offers beneficial perspectives on the possible benefits and challenges, illuminating the far‐reaching changes that AI could bring to the terrain of learning and instruction and teaching methods in the time yet to come. The research sought to assess the effect of AI adoption in teacher education across five main dimensions: (i) its influence on teaching support and classroom management, (ii) its role in creating inclusive and accessible learning environments, (iii) its contribution to improving teachers' digital literacy and computer skills, and enhancing access to digital teaching resources, (iv) its positive influence on identifying students' learning styles and facilitating the adoption of diverse teaching methods, and (v) its role in strengthening teacher‐student relationships through improved interactions. Conclusion: The findings elucidate the promising opportunities that AI presents in the field of teacher education, along with the obstacles that require resolution for the effective fusion of AI educational settings. Lay Description: What is currently known about this topic?: AI has the potential to enhance various aspects of teaching, including classroom management and personalizing teaching methods.Incorporating AI into education has garnered significant interest due to its perceived benefits in improving learning outcomes. What does this paper add?: This paper provides a comprehensive investigation into the effects of AI adoption in teacher education, highlighting both the opportunities and challenges associated with its implementation.It offers insights into how AI can influence different dimensions of teaching, such as classroom management, learning environment inclusivity, and teacher‐student relationships. Implications for practice/or policy: The findings of this study underscore the importance of integrating AI into teacher education programs to leverage its potential benefits in enhancing teaching practices.Policymakers and educators should consider the implications of AI adoption in education and develop strategies to address challenges while maximizing the advantages of AI technologies in teaching and learning. [ABSTRACT FROM AUTHOR]

Background: Instructional videos constitute a pivotal component in flipped learning. Despite their significance, there is a dearth of research specifically dedicated to instructional videos within the context of flipped classrooms. This paucity has led to an empirical void in verifying the efficacy of instructional videos in flipped learning environments. Objectives: The present study endeavours to contribute to the extant literature on flipped pedagogical practices by providing empirical evidence regarding the effectiveness of instructional videos in flipped learning environments. Methods: This study employs a convergent mixed‐methods design. Forty‐five instructional videos in three subtypes were administered in two classes over a 15‐week semester. Data, both quantitative (log data from the learning management system) and qualitative (from focus group discussions at two time points), were concurrently collected from a flipped class (n = 25) and a blended class (n = 28) with the aim of gauging student engagement and learning outcomes in the flipped class and understanding video‐viewing features typical of the flipped class. Results: Both datasets corroborated that participants in the flipped class outperformed their counterparts in the blended class in terms of video‐watching, peer interaction, knowledge retention, and transfer skills. Conclusions: The instructional videos within the flipped classroom setting serve to enhance student engagement in the learning process and improve learning outcomes. The efficacy of these instructional videos in flipped learning can be further augmented through strategic approaches in both their design and implementation. Lay Description: What is currently known about this topic: The flipping pedagogy is conducive to learning.Videos play a crucial role in flipped learning.Videos prepared students for classroom activities.However, engaging students with pre‐class videos presents a challenge. What this paper adds: This paper furnishes direct empirical evidence supporting the effectiveness of instructional videos in flipped learning.It uncovers factors affecting student engagement with videos in flipped learning.It offers insights into the design and implementation of videos in flipped learning. Implications for practice: Considering facilitating conditions and affective factors when creating videos.Acknowledging learner characteristics when designing videos.Utilizing instructional strategies when implementing videos. [ABSTRACT FROM AUTHOR]

Background: Online interaction in blended learning is leveraged through social presence and convergence. However, little systematic work currently exists on how researchers have explored these challenges in higher education institutions and no studies have synthesised these challenges. Objectives: The purpose of this study is to give a novel overview of social presence and convergence to improve online interaction in blended learning in higher education. The findings will be synthesised into blended learning design principles. Method: Two systematic literature reviews, one on each challenge, were carried out through the Web of Science databases and consulting cited sources in review articles. Accordingly, 28 distinct studies were selected through the guidelines of the PRISMA statement, using predefined selection criteria. Results and Conclusions: The results show that social presence in blended learning is mostly evoked through course design, introductory f2f meetings, collaborative activities, prompt online feedback, the teacher's presence, and planned facilitation. To establish convergence, it is recommended to make basic theory available online through video clips, web‐lectures, articles, followed by simple online assignments or self‐study to increase understanding, thereby creating opportunities for deep learning during face‐to‐face through discussions and collaborative activities. Implications: This paper adds to the theory on blended learning and instructional design in higher education, and further offers an elaborate set of design principles for educational practice. Future research on instructional design may investigate in particular how a target group or student factors, are affected by the blended learning environment in order to tailor designs for a specific target group. Lay Description: What is known?: Online interaction is pivotal in blended learningOnline interaction is leveraged through social presence and convergenceSocial presence prevents the online student from feeling lonelyConvergence entails deciding the best‐suited delivery mode: online or face‐to‐face What this paper adds: A novel overview and critical analysis of social presence in blended learningA novel overview and critical analysis of convergence in blended learningA synthesis of the findings on social presence and convergenceExtraction of the findings into blended learning design principles Implications for practitioners: The teacher's presence through design and accessibility fosters students' social presencePlacing concepts online leaves room for deep learning during face‐to‐faceCollaborative activities evoke social presence and facilitate deep learningBlended learning designs should be further tailored for the target group [ABSTRACT FROM AUTHOR]

Background: In example‐based learning, examples are often combined with generative activities, such as comparative self‐explanations of example cases. Comparisons induce heavy demands on working memory, especially in complex domains. Hence, only stronger learners may benefit from comparative self‐explanations. While static text‐based examples can be compared easily, this is challenging for transient video‐based modelling examples used in complex domains because simultaneous processing of two videos is not feasible. Objectives: To allow for such comparisons, we combined video‐based modelling examples with static representations (i.e., summarizing tables) of the observed optimal and a suboptimal solution of the problem‐solving process. A comparative self‐explanation prompt asked learners to compare the different solution approaches. Our study investigated the impact of video‐based modelling examples versus independent problem‐solving on cognitive load and problem‐solving skill development. Moreover, we investigated the effects of comparative versus sequential self‐explanation prompts, depending on learners' prior knowledge. Methods: In an experiment, 118 automotive apprentices learned a car malfunction diagnosis strategy. Apprentices were divided into three groups: (1) modelling examples with comparative self‐explanation prompts, (2) modelling examples with sequential prompts, and (3) no examples or prompts. Diagnostic knowledge and skills were assessed before and after the intervention. Cognitive load was measured retrospectively. Results and conclusions: Despite no observed effects on cognitive load, modelling examples enhanced diagnostic knowledge and diagnostic skills with scaffolds, though not independent diagnostic skills without scaffolds. The need for more practice opportunities to foster independent diagnostic skills is assumed. Additionally, comparative prompts seem promising for learners with higher prior knowledge. Takeaways: Video‐based modelling examples were more beneficial for learning than practising to apply the diagnostic strategy. Static representations allow for comparisons of video examples and comparative prompts are promising for learners with higher prior knowledge (cf. expertise‐reversal effect). Further research, especially on the effects on cognitive load, is necessary. Lay Description: What is already known about the topic?: Text and video examples that model how to solve a problem are widely used in education.Text examples often include self‐explanation prompts that ask learners to compare several examples.For video examples, such comparison prompts have seldom been investigated, because comparisons are difficult to implement for transient videos. What does this paper add?: This paper shows that video examples combined with static summaries of processes that have been shown in the video example are effective and allow for comparisons of video examples.Such comparisons seem to be more promising for learners with higher prior knowledge. Implications for practice: Practitioners could combine video examples with static summaries of the processes shown in the video examples to allow for comparisons. [ABSTRACT FROM AUTHOR]

Background: This paper examines the use of augmented reality (AR) as a concept‐association tool in schools, with the aim of enhancing primary school students' learning outcomes and engagement. Conflicting findings exist in previous studies regarding the cognitive load of AR‐enriched learning, with some reporting reduced load and others indicating increased demand and poorer performance. Understanding these implications is essential for effectively leveraging AR in education. The study offers a fresh perspective on the potential of AR technology in improving educational experiences. Objectives: The primary goal of this research was to evaluate the effectiveness of an AR‐assisted concept‐association strategy for improving essential knowledge acquisition and skills outcomes, increasing cognitive load, and increasing self‐efficacy and learning motivation among primary school students. Methods: A quasi‐experimental design with a control group was employed to investigate the effectiveness of the intervention. Results and Conclusions: The results demonstrate that the implementation of the AR‐assisted concept‐association strategy effectively enhanced essential knowledge acquisition and skills outcomes, increased cognitive load, and increased self‐efficacy and learning motivation among primary school students. These findings highlight the potential of AR technology to improve the learning experience and engagement of primary school students. The study contributes to the existing literature on the effectiveness of AR technology in education, suggesting future research directions. Ultimately, it offers a practical solution for improving the learning experience by presenting a new approach for teaching using AR technology. Lay Description: What is currently known about this topic: Augmented reality (AR) technology has been increasingly explored in educational settings.Previous research has shown that AR can enhance learning outcomes and engagement among students.AR applications have the potential to serve as concept‐association tools to improve the learning experience. What this paper adds: This paper investigates the effectiveness of using an AR application as a mobile concept‐association tool in school settings.The study demonstrates that the AR‐assisted concept‐association strategy effectively enhances knowledge acquisition, skills outcomes, cognitive load, self‐efficacy, and learning motivation among primary school students.The findings highlight the potential of AR technology in improving learning experiences and engagement for primary school students.The study offers practical implications for integrating AR technology into educational settings, and suggests avenues for future research in this area. Implications for practice and/or policy: Incorporating AR applications as concept‐association tools can enhance learning outcomes and engagement in primary school settings.AR technology can be used to increase cognitive load, and to increase self‐efficacy and motivation among students.Educators and policymakers should consider integrating AR technology into teaching practices to improve the overall learning experience.Future research and exploration should be conducted to understand the full potential and limitations of AR technology in education. [ABSTRACT FROM AUTHOR]

Background: Both socially regulated learning and cognitive quality are important factors affecting collaborative knowledge building, but the current research lacks a joint quantified evaluation method that combines these two aspects. Objectives: Based on the existing framework, we proposed a joint evaluation method for regulated learning and cognitive quality in collaborative knowledge building, and further extracted the evaluation indicators. Methods: This study involved 74 learners enrolled in a course named 'the Application of Modern Educational Technology' as the subject of study, and made a case analysis with this method. Results and Conclusions: First, the indicators of this joint evaluation method could complement the indicators of traditional frequency statistics methods and facilitate an analysis of regulated learning and cognitive quality in collaborative knowledge building. Second, the group with a higher proportion of high‐level cognitive quality and socially shared regulation in collaborative knowledge building achieved better final scores. Finally, four types of groups were obtained through clustering: excellent, risky, mixed group, and highly collaborative group. This study introduced a joint evaluation method for regulated learning and cognitive quality in collaborative knowledge building and provides suggestions for future research. Lay Description: What is currently known about this topic?: Online collaborative knowledge building is increasingly important.Regulated learning and cognitive quality are considered very important for successful collaborative learning.Without quantitative methods, it is difficult to assess regulated learning and cognitive quality during collaborative knowledge building in a timely manner. What does this paper add?: This paper provided a joint evaluation method of regulated learning and cognitive quality (JERC) for online collaborative knowledge building.A case study was conducted to identify JERC's usefulness. Using descriptive statistics and visualization, it was determined that indicators of JERC can not only capture the state of cognitive quality and regulated learning status, but also elucidate the nature of that status (i.e., comprehensive, dynamic, cyclical).Through clustering analysis, four distinct groups were identified, each exhibiting different characteristics and moving patterns of regulated learning and cognitive quality over time. These patterns indicate that the quality of cognitive and regulatory learning cannot be determined solely by behavioural frequency. Moreover, an excessive proportion of individual regulation cannot predict better learning performance. Implications for practice: A computable representation model of regulated learning and cognitive quality was constructed to support automated perception and intervention in regulated learning and cognitive processing.With JERC, it is possible for researchers to capture, process, analyse and predict dynamic data to examine online collaborative knowledge building combined with shared physiological arousal events.The results of JERC can be used by researchers to develop advanced techniques, such as AI deep learning, for designing adaptive supports that can foster students' online collaborative knowledge building. [ABSTRACT FROM AUTHOR]

Background Study: Asynchronous online discussions are vital venues for collaborative knowledge construction. However, the lack of appropriate instruction designs poses challenges in promoting deep and substantive engagement with the core subject matter. This paper explores how to enhance adult students' knowledge construction in the context of asynchronous online discussions at an open university in Taiwan. Objectives: This study explores instructional designs aimed at promoting online knowledge construction among adult students and overcoming barriers to this process. Methods: This study used a convergent parallel mixed methods design to collect concurrently both quantitative data from the students' online discussion postings for content analysis and qualitative data from the focus group and individual interviews, the online open‐ended questionnaire, and the instructor's observation logs for thematic analysis. Then the results were merged in the interpretation stage. Results and Conclusion: The research highlights the significance of instructional designs in influencing students' level of knowledge construction during online discussions. The findings suggest that instructional designs that provide teacher‐led interim summaries, pose Socratic questions, and incorporate problem‐solving projects can promote higher‐level knowledge construction. However, time constraints, cultural influences, and unfamiliarity with peers negatively affected higher‐order knowledge construction. To address these challenges, culturally responsive and technologically inclusive instructional designs that take into account the specific challenges faced by adult learners are proposed to enhance learning outcomes through active participation. Limitation: The study's limited sample size warrants further research with a larger and more diverse cohort to validate the effectiveness of the proposed instructional designs. Another limitation is the lack of a robust theoretical base for the instructional strategies presented by the current action‐research study. Further examination and broader exploration in online education are needed to prop up proposed pedagogical approaches. Lay Description: What is currently known about this topic: Online discussions are essential for collaborative knowledge construction among adult students.Existing research primarily indicates that online knowledge construction often remains at a basic level, predominantly involving the sharing and comparing of information. What this paper adds: This study explores instructional designs aimed at elevating online knowledge construction among adult students at an open university in Taiwan.It identifies specific instructional strategies, such as teacher‐led interim summaries, the use of Socratic questioning, and the integration of problem‐solving projects, as effective in promoting higher‐level knowledge construction.The paper also sheds light on the challenges hindering higher‐order knowledge construction, including time constraints, cultural influences, and unfamiliarity among peers. Implications for practice and/or policy: The findings underscore the need for culturally responsive and technologically inclusive instructional designs. These should be tailored to the unique challenges faced by adult learners, particularly in asynchronous online environments.The paper suggests that such instructional designs can significantly improve learning outcomes by fostering more active and deeper participation in online discussions.It also highlights the importance of further research to validate these strategies, given the study's limited sample size and the need for a more robust theoretical foundation for the proposed instructional methods. [ABSTRACT FROM AUTHOR]

Background: Measuring students' self‐regulation skills is essential to understand how they approach their learning tasks in order to identify areas where they might need additional support. Traditionally, self‐report questionnaires and think aloud protocols have been used to measure self‐regulated learning skills (SRL). However, these methods are based on students' interpretation, so they are prone to potential inaccuracy. Recently, there has been a growing interest in utilizing learning analytics (LA) to capture students' self‐regulated learning (SRL) by extracting indicators from their online trace data. Objectives: This paper aims to identify the indicators and metrics employed by previous studies to measure SRL in higher education. Additionally, the study examined how these measurements were validated. Methods: Following the protocol of Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA), this study conducted an analysis of 25 articles, published between 2015 and 2022, and sourced from major databases. Results and Conclusions: The results showed that previous research used a variety of indicators to capture learners' SRL. Most of these indicators are related to time management skills, such as indicators of engagement, regularity, and anti‐procrastination. Furthermore, the study found that the majority of the reviewed studies did not validate the proposed measurements based on any theoretical models. This highlights the importance of fostering closer collaboration between learning analytics and learning science to ensure the extracted indicators accurately represent students' learning processes. Moreover, this collaboration can enhance the validity and reliability of data‐driven approaches, ultimately leading to more meaningful and impactful educational interventions. Lay Description: What is already known about this topic?: Measuring students' self‐regulation skills is essential for understanding their learning approaches and identifying areas requiring further support.Traditionally, questionnaires and interviews have been used to measure learners' self‐regulation; however, these methods rely on students' own views, which can sometimes be unreliable.Recently, there has been more interest in using learning analytics to measure students' self‐regulation based on data extracted from their online activities. What this paper adds?: This paper systematically analyses how previous studies used learning analytics to measure students' self‐regulation in higher education.It examines how these measurements were validated. Implications for practise and/or policy: More collaboration is needed between researcher in learning science and learning analytics is essential to ensure that the metrics and methods developed are not only theoretically sound but also practically relevant. This collaboration ultimately contributes to the design of enhanced learning experiences and outcomes. [ABSTRACT FROM AUTHOR]

Background: The emergence of ChatGPT in the education literature represents a transformative phase in educational technology research, marked by a surge in publications driven by initial research interest in new topics and media hype. While these publications highlight ChatGPT's potential in education, concerns arise regarding their quality, methodology, and uniqueness. Objective: Our study employs unconventional methods by combining altmetrics and bibliometrics to explore ChatGPT in education comprehensively. Methods: Two scholarly databases, Web of Science and Altmetric, were adopted to retrieve publications with citations and those mentioned on social media, respectively. We used a search query, "ChatGPT," and set the publication date between November 30th, 2022, and August 31st, 2023. Both datasets were within the education‐related domains. Through a filtering process, we identified three publication categories: 49 papers with both altmetrics and citations, 60 with altmetrics only, and 66 with citations only. Descriptive statistical analysis was conducted on all three lists of papers, further dividing the entire collection into three distinct periods. All the selected papers underwent detailed coding regarding open access, paper types, subject domains, and learner levels. Furthermore, we analysed the keywords occurring and visualized clusters of the co‐occurring keywords. Results and Conclusions: An intriguing finding is the significant correlation between media/social media mentions and academic citations in ChatGPT in education papers, underscoring the transformative potential of ChatGPT and the urgency of its incorporation into practice. Our keyword analysis also reveals distinctions between the themes of the papers that received both mentions and citations and those that received only citations but no mentions. Additionally, we noticed a limitation that authors' choice of keywords might be influenced by individual subjective judgements, potentially skewing results in thematic analysis based solely on author‐assigned keywords such as keyword co‐occurrence analysis. Henceforth, we advocate for developing a standardized keyword taxonomy in the educational technology field and integrating Large Language Models to enhance keyword analysis in altmetric and bibliometric tools. This study reveals that ChatGPT in education literature is evolving from rapid publication to rigorous research. Lay Description: What is currently known about this topic?: ChatGPT in education has seen a surge in publications driven by media hype.Early publications tend to lack rigour and reiterate known advantages/disadvantages.Literature reviews on ChatGPT in education have limitations in scope and depth.Some studies have explored altmetrics and bibliometrics in other fields. What does this paper add?: Combines altmetrics and bibliometrics to analyse publications of ChatGPT in education.Addresses challenges in the discourse by offering unconventional analysis methods.Identifies publication trends and investigates the relationship between media attention and citations.Determines key themes in the literature through keyword co‐occurrence analysis. Implications for practice/or policy: Expectations of continued growth in ChatGPT literature but with evolving publication trends.Distinctive characteristics of ChatGPT in education challenge keyword analysis.Proposes the development of a unified keyword taxonomy for clarity in the field.Suggests enhancing altmetrics and bibliometrics tools using Large Language Models. [ABSTRACT FROM AUTHOR]

Background: Mindfulness practices enhance executive function skills and academic achievement, spurring interest in integrating mindfulness interventions into education. Embedding mindfulness practice into a digital math game may provide a low‐cost, scalable way to induce mindfulness and boost game‐based learning, yet this approach remains unexplored. Objectives: We investigated the learning benefits of integrating mindfulness exercises in a digital math learning game and examined how students' trait mindfulness might moderate the outcomes. Methods: Two classroom studies were conducted with 404 5th and 6th grade students from six public schools in the U.S. (nStudy 1 = 227, nStudy 2 = 177). The two randomized controlled experiments assigned students to one of the three conditions: passive control (playing the digital learning game Decimal Point), story‐enriched active control, or mindfulness‐enriched condition. Trait mindfulness, learning gains, and in‐game problem‐solving (including problem‐solving duration, error count and correctness after reminder) were assessed. Study 2 included a manipulation check to better understand the effects of the mindfulness intervention. Results: Findings showed no significant differences in learning gains, problem‐solving duration or error count among the conditions. Students' trait mindfulness did not moderate these outcomes. Mindfulness reminders in the mindfulness‐enriched game led to more correct answers after errors than jokes in the story‐enriched game. Study 2 revealed that we failed to induce higher state mindfulness through the mindfulness inductions. Conclusions: Mindfulness prompts could be especially beneficial for students experiencing frustration during gameplay, warranting more exploration for digital game‐based instruction. We highlight barriers and future directions for fostering mindfulness through computer‐based instruction in classrooms. Lay Description: What is currently known about this topic?: Researchers focus on digital games as productive learning environments for math, with potential for higher learning gains compared with traditional methods. However, results are mixed, and not all games lead to improved math outcomes.Executive function (EF) skills are crucial for math learning, and mindfulness‐based interventions show promise in enhancing EF skills in school‐aged students.Embedding mindfulness practice into a digital math game may provide a low‐cost, scalable way to induce mindfulness and, in turn, boost EF skills and game‐based learning, yet this approach remains unexplored What does this paper add?: This paper presents the results of two randomized control trials investigating the feasibility and benefits of incorporating mindfulness exercises into a digital math game designed for middle school students. Benefits are compared to those of a story‐enriched and regular version of the same digital math learning game.The paper also explores variations in the effects of the mindfulness‐enriched game based on students' initial trait mindfulness levels.We observe that listening to mindfulness inductions at the beginning of game sessions do not induce mindfulness, and therefore does not benefit math learning.We find that mindfulness prompts received after recurrent errors can be beneficial for students' problem solving. Implications of study findings for practitioners: Our study provides important information on how digital learning game designers should attempt to induce mindfulness in a digital game to promote learning.Digital learning game designers should consider incorporating mindfulness exercises into their games strategically. Presenting mindfulness inductions in audio format at the beginning of game sessions may not induce mindfulness or benefit math learning. Instead, designers should focus on integrating mindfulness prompts at moments when students encounter frustration within the learning game.Beyond embedding audio mindfulness exercises in the game, learning designers should also consider alternative technological and game features to induce mindfulness within a learning game. [ABSTRACT FROM AUTHOR]

Background: Behavioural intention (BI) has been predicted using other variables by adopting the technology acceptance model (TAM). However, few studies have examined whether BI can predict learning performance. Objectives: The present study used an extended TAM to investigate whether students' BI is a predictor of their listening learning performance (LLP) through vocabulary learning performance (VLP) in the context of mobile vocabulary‐assisted listening learning by using two mobile learning tools. Methods: A total of 129 college students with a pre‐intermediate level of English were recruited as participants, and a 10‐week mobile vocabulary‐assisted, listening‐learning course was conducted in 2022. In each task of this course, the students had to learn target words from a listening passage on Quizlet and then engage in listening activities on Randall's ESL Cyber Listening Lab. Quantitative responses obtained through an online questionnaire were analysed through partial‐least‐squares structural equation modelling. Results: The analysis results indicated that BI significantly predicted LLP through VLP. Perceived ease of use (PEU) and perceived usefulness (PU) were significant antecedents of BI. However, PEU did not significantly predict PU because of the difficulty of navigating between the two technological tools used in this study. The extended model demonstrated its effectiveness in explaining listening learning performance, as evidenced by an explained variance (R2) of 69%. Conclusion: The extended model validates the influence of BI on learning performance and it can also draw teachers' focus toward the significance of enhancing students' BI to improve their listening learning performance. Pedagogical implications based on the results are provided in this paper. Lay Description: What is already known about this topic?: TAM was used to study learners' acceptance of mobile‐assisted language learning.TAM incorporates latent variables to explore mobile‐assisted language learning.Investigating factors influencing BI is a primary research focus in extended TAM literature.Mobile tools could improve listening learning and vocabulary retention. What this paper adds to that: Learning performance was considered as a dependent variable in an extended TAM.BI might predict students' learning performance in vocabulary and listening in an extended TAM.Teachers used two mobile tools to design mobile vocabulary‐assisted listening tasks.Pre‐learning the target words facilitate students' listening learning performance. Implications for practice and/or policy: We show the importance of BI on predicting listening learning performance.The impact of BI on other factors became another focus of TAM research.Results highlight pre‐learning target words' importance for better listening performance.Existing mobile tools improve listening performance, avoiding new system development. [ABSTRACT FROM AUTHOR]

Background: Learner profiles detected from digital trace data are typically triangulated with survey data to explain those profiles based on learners' internal conditions (e.g., motivation). However, survey data are often analysed with limited consideration of the interconnected nature of learners' internal conditions. Objectives: Aiming to enable a thorough understanding of trace‐based learner profiles, this paper presents and evaluates a comprehensive approach to analysis of learners' self‐reports, which extends conventional statistical methods with psychological networks analysis. Methods: The study context is a massive open online course (MOOC) aimed at promoting physical activity (PA) for health. Learners' (N = 497) perceptions related to PA, as well as their self‐efficacy and intentions to increase the level of PA were collected before and after the MOOC, while their interactions with the course were logged as digital traces. Learner profiles derived from trace data were further examined and interpreted through a combined use of conventional statistical methods and psychological networks analysis. Results and Conclusions: The inclusion of psychological networks in the analysis of learners' self‐reports collected before the start of the MOOC offers better understanding of trace‐based learner profiles, compared to the conventional statistical analysis only. Likewise, the combined use of conventional statistical methods and psychological networks in the analysis of learners' self‐reports before and after the MOOC provided more comprehensive insights about changes in the constructs measured in each learner profile. Major Takeaways: The combined use of conventional statistical methods and psychological networks presented in this paper sets a path for a comprehensive analysis of survey data. The insights it offers complement the information about learner profiles derived from trace data, thus allowing for a more thorough understanding of learners' course engagement than any individual method or data source would allow. Lay Description: What is already known about this topic: Researchers have made extensive use of data from online learning platforms—often referred to as learning trace data—to understand how learners engage in online learning activities.Surveys are often used to gather information about learners' motivation, perceptions, and other internal factors, to complement the insight gleaned from learning traces and thus create a more complete picture of the learning behaviour.When analysing survey data, the focus is usually on individual factors without considering how different factors are connected and affect one another.Psychological networks analysis is a novel analytic approach to studying complex phenomena both in psychology and education. What this paper adds: The paper uses psychological networks as a method for examining mutual relations among learners' internal factors (e.g., motivation, perceptions) measured through self‐reports before and after a course.By combining conventional statistical analysis of self‐reports with psychological networks analysis, the paper develops a comprehensive picture of learners' internal factors measured through self‐reports, one that accounts for both individual and interconnected nature of those factors.This comprehensive approach to information extraction from surveys allows for better understanding of trace‐based learner profiles, that is, profiles mined from data about learners' interaction with online learning activities. Implications for practice and/or policy: The presented method paves a way for a comprehensive analysis of the data collected from learners through surveys.It helps us gain a better understanding of learners' engagement with online learning activities.It can advance the evaluation of digital educational programs that aim to encourage changes in health‐related behaviour. [ABSTRACT FROM AUTHOR]

Background: With the growing integration of technology in education, the adoption of blended learning (b‐learning) has gained attention. B‐learning combines traditional classroom teaching with online components, holding potential to enhance student outcomes and educational efficiency. Yet, current research predominantly concentrates on higher education institutions in urban areas, creating a void in understanding its impact on K‐12 education, particularly in rural settings. Objectives: This qualitative study aims to propose recommendations for successful implementation of blended learning in rural K‐12 areas by addressing the key stakeholders influencing its adoption and identifying the main factors affecting its success. Methods: We performed a content analysis of grey literature documents detailing the implementation of b‐learning in K‐12 education. Additionally, interviews with crucial stakeholders such as teachers, principals, and experts in rural schools in South America provide insights into the challenges and prospects of b‐learning adoption in these contexts. Results and Conclusions: The study identifies pivotal stakeholders for effective b‐learning implementation, outlining their roles and addressing challenges inherent in rural settings. Recommendations for enhancing b‐learning's implementation in developing countries are also proposed. The research underscores the significance of involving diverse stakeholders such as governmental bodies, school leaders, educators, students, and families to ensure a holistic and efficient approach to blended learning. Lay Description: What is currently known about this topic: Blended Learning Definition and Benefits: Blended learning combines face‐to‐face and online instruction, enhancing student engagement and personalization by providing diverse learning pathways.Growth in K‐12 Implementation: Blended learning gained traction in K‐12 education, boosting academic outcomes, driven by recognition of learner diversity and potential in meeting students' needs.Contextual Challenges: Implementation challenges arise in low‐income households and rural areas, including limited access to technology and internet connectivity, impacting student engagement and success. What does this paper add: Focusing on Rural Dynamics: This study helps to fill a gap by investigating blended learning in rural K‐12 settings, spotlighting key players and success drivers in these unique contexts.Recommendations from Various Sources: By combining interviews and grey literature, this research generates comprehensive, practical recommendations grounded in both empirical insights and real‐world perspectives.Insights into Rural Hurdles: This paper extends the discussion on blended learning by addressing specific rural barriers, proposing family involvement, private sector partnerships for training, and tailored pedagogical strategies. Implications for practice or policy: Leadership and Collaboration: Effective school leadership and collaboration with local governments are pivotal for fruitful blended learning implementation, ensuring defined roles, responsibility, and accountability.Adaptable Curriculum Design: An adaptable, centralized curriculum aligns with recommendations, fostering efficient tracking of student progress and enabling customized learning.Engagement‐Centric Pedagogies: Recommendations spotlight interactive, student‐centered teaching methods, tailored to diverse student needs, nurturing active participation and elevated learning outcomes. [ABSTRACT FROM AUTHOR]

Background: Painting is the foundational expression across all art forms and is one of the key creative practices for fostering students' aesthetic ability and creativity within fine arts courses. Collaborative painting in the form of socially shared regulation of learning (SSRL) can be recognized as an effective strategy for enhancing creativity in both individual and group work. However, the absence of contextual experiences and collaborative spaces poses challenges for students in cultivating their creativity in painting. Objectives: The present study explores students' creativity, socially shared regulation (SSR) and positive painting behaviours using an SSRL‐based collaborative painting approach in the metaverse (Meta‐CP). Methods: Via a quasi‐experimental design, a total of 40 Chinese students in fifth grade were recruited and were randomly divided into an experimental group and a control group, with 20 students utilizing the Meta‐CP approach, while the remaining 20 students followed the conventional SSRL‐based paper‐and‐brush collaborative painting (C‐CP) approach. The Meta‐CP approach not only offers an authentic painting context and a collaborative space but also facilitates the collaborative process through the SSRL framework. The data collection included students' creative tendency, painting works and painting process. Results and Conclusions: The Meta‐CP approach effectively enhances students' creativity concerning adventure, curiosity and imagination, as well as results in the creation of more distinctive and logical artistic works. Furthermore, the approach significantly improved the quality of students' SSR. Additionally, students utilizing the Meta‐CP approach displayed more positive painting behaviours compared with those employing the C‐CP approach. Lay Description: What is already known about this topic:Collaborative painting is an effective strategy for enhancing creativity.Socially shared regulation of learning (SSRL) fosters collaborative learning.Students in collaborative painting may lack a contextual and synchronized painting space.The metaverse benefits in terms of contextual experiences and collaborative spaces. What this paper adds:Using an SSRL‐based collaborative painting approach in the metaverse (Meta‐CP) is effective in improving students' creativity.The Meta‐CP approach has the potential to improve students' quality of socially shared regulation (SSR), and positive painting behaviours. Implications for practice and/or policy:The metaverse provides an immersive synchronized painting space for art education to stimulate students' creative potential.The metaverse with proper learning strategies (e.g., SSRL) provides an effective collaborative learning environment for creation. [ABSTRACT FROM AUTHOR]

Background: Social annotation has emerged as a promising educational technology that fosters collaborative reading and discussion of digital resources among learners. While the positive impact of social annotation on students' learning process and performance is widely acknowledged, students' behavioural patterns in social annotation are underexplored. Objectives: This study investigated patterns in students' use of annotation and response behaviours in social annotation activities. We also explored how students' performance in the behavioural, cognitive, emotional, and social dimensions varied based on their behavioural patterns. Methods: We recruited 93 undergraduates who were enrolled in an elective course at a large North American University. Students were tasked with collaboratively annotating the class readings uploaded to Perusall, a social annotation platform, over 7 weeks. We used metaclustering to determine the optimal number of clusters pertaining to student behaviours. We compared the differences among clusters across multiple performance dimensions. Results and Conclusions: Two distinct clusters were identified and defined as initiators and responders. We found that responders had significantly longer active reading time and exhibited greater social annotation effort compared to initiators. However, initiators received more peer acknowledgement, as evidenced by higher upvotes. No significant difference was found in cognitive insight between initiators and responders, but responders demonstrated significantly higher cognitive discrepancy. Additionally, there were no significant differences in positive and negative tones between initiators and responders; however, responders displayed higher levels of prosocial behaviours than initiators. This study has significant practical implications regarding promoting students' collaborative learning experience in social annotation. Lay Description: What is already known about this topic: Annotation and response behaviours are two primary actions in social annotation.Understanding how students navigate through annotations and respond to their peers' contributions is essential for optimizing their learning experience.Social annotation outcomes can be assessed in the behavioural, cognitive, emotional, and social dimensions. What this paper adds: This paper revealed students' behavioural patterns in social annotation activities.This study offered a comprehensive understanding of the various dimensions of performance among students with different behavioural tendencies. Implications for practice and/or policy: The two student clusters, initiators and responders, revealed distinct engagement patterns in social annotation and informed the design of targeted scaffoldings.Responders were not passive learners since they demonstrated significantly longer active reading time, greater social annotation effort, and higher level of prosocial behaviours.Educators might not need to place significant emphasis on monitoring participants' emotional expressions in social annotation.Social annotation platforms should incorporate features that encourage and reward both initiation and response behaviours. [ABSTRACT FROM AUTHOR]

Background Objective Method Results Conclusion Stealth assessment is a learning analytics method, which leverages the collection and analysis of learners' interaction data to make real‐time inferences about their learning. Employed in digital learning environments, stealth assessment helps researchers, educators, and teachers evaluate learners' competencies and customize the learning experience to their specific needs. This adaptability is closely intertwined with theories related to learning, engagement, and motivation. The foundation of stealth assessment rests on evidence‐cantered design (ECD), consisting of four core models: the Competency Model (CM), Evidence Model, Task Model, and Assembly Model.The first step in designing a stealth assessment entails producing operational definitions of the constructs to be assessed. The CM establishes a framework of latent variables representing the target constructs, as well as their interrelations. When developing the CM, assessment designers must produce clear descriptions of the claims associated with the latent variables and their states, as well as sketch out how the competencies can be measured using assessment tasks. As the designers elaborate on the assessment model, the CM definitions need to be revisited to make sure they work with the scope and constraints of the assessment. Although this is the first step, problems at this stage may result in an assessment that does not meet the intended purpose. The objective of this paper is to elucidate the necessary steps for CM development and to highlight potential challenges in the process, along with strategies for addressing them, particularly for designers without much formal assessment experience.This paper is a methodological exposition, showcasing five examples of CM development. Specifically, we conducted a qualitative retrospective analysis of the CM development procedure, wherein participants unfamiliar with ECD applied the framework and showcased their work. In a stealth assessment course, four groups of students (novice stealth assessment designers) engaged in developing stealth assessments for challenging‐to‐measure constructs across four distinct projects. During their CM development process, we observed various activities to pinpoint areas of difficulty.This paper presents five illustrative examples, including one for assessing physics understanding and four for the development of CMs for four complex competencies: (1) systems thinking, (2) online information credibility evaluation, (3) computational thinking, and (4) collaborative creativity. Each example represents a case in CM development, offering valuable insights.The paper concludes by discussing several guidelines derived from the examples discussed. Emphasizing the importance of dedicating ample time to fine‐tune CMs can significantly enhance the accuracy of assessments related to learners' knowledge and skills. It underscores the significance of qualitative phases in crafting comprehensive stealth assessments, such as CMs, alongside the quantitative statistical modeling and technical aspects of these assessments. [ABSTRACT FROM AUTHOR]

Background: A practical test that measures the information and communication technology (ICT) skills students need for effectively using ICT in primary education has yet to be developed (Oh et al., 2021). This paper reports on the development, validation, and reliability of a test measuring primary school students' ICT skills required for effectively using ICT (the ECC‐ICT test). Objectives: Based on existing literature, three ICT use domains were identified for effectively using ICT: Effective, collaborative, and creativeuse of ICT. For these three domains, 24 corresponding teaching objectives were identified from a widely used digital literacy framework. Thirty‐four test items cover these teaching objectives in an online test. Methods: A mixed‐method approach was used for the ECC‐ICT test. Four pilot rounds (n=25) implemented qualitative interviews for cognitive validity and refining the test items, followed by a qualitative usability study(n=6). Confirmatory factor analysis and ANOVA provided quantitative insight into the large‐scale test administration(n=575). Results and Conclusions: Composite reliability of our conceptual 3‐factor confirmatory model showed that the test reliably measured primary school effective use of ICT (ω = 0.82), collaborative use of ICT (ω = 0.80) and creative use of ICT (ω = 0.64). Convergent validity (ranging from 0.41 to 0.46) was acceptable. Internal consistency (ranging from 0.84 to 0.91) and discriminant validity (HTMT values below 0.90) are good. ANOVA results show that mean test scores are higher for students in higher grade levels (p < 0.001). The post hoc Bonferroni results show that most grade‐by‐grade comparisons are significant (p < 0.001). Lay Description: What is already known about this topic: Information and communication technology (ICT) skills are finding their way into national curriculums as teachers implement more digital learning environments.Teachers currently do not have a measurement instrument for the ICT skills primary education students need to learn in a personalised way. What this paper adds: This paper gives teachers a test that reliably measures the effective, collaborative, and creative ICT skills required for primary school students to learn using ICT.To our knowledge, this test is the first of its kind.Al materials to reproduce the test are available digitally for teachers. The implications of study findings for practitioners: For policy, this test can be used to check if a student is ready to use ICT in a self‐regulated setting.With this test, teachers can assess and support students' growth on the effective, collaborative, and creative ICT skills required for primary school students using ICT. [ABSTRACT FROM AUTHOR]

Background: Virtual reality (VR) offers much potential for learning, but it challenges learners' orientation. Objectives: This paper investigates whether it is possible to use light or movement cues to facilitate orientation in a search task in a desktop‐VR environment so that participants can better attend to the learning content presented simultaneously. Methods: In two pre‐registered online experiments, we investigated the effects of cueing (light and movement) on search time, learning, and several evaluation variables. Participants were asked to find tools in a virtual workshop, while information about the respective tool was narrated. Experiment 1 (N = 60) used a within‐subject design, that is, the objects were alternately highlighted by light, movement or not. For Experiment 2 (N = 159) the narration was substantially shortened, and a between‐subject design was used. Cognitive load and presence were measured additionally. Results and conclusions: In Experiment 1, only the movement cue decreased search time, indicating automatic guidance of learners' attention. There was no effect of cueing on learning, which may be due to the average search time being substantially shorter than the narration, leaving sufficient time to attend to the narration exclusively. In Experiment 2 search times were significantly faster for both cueing methods, but only the light cue resulted in better learning outcomes, which could be explained by the slightly lower presence in the movement cue condition. Implications: Results imply that it is important to develop cues that automatically guide attention without reducing presence. Lay Description: What is already known about this topic: Virtual reality (VR) offers a lot of opportunities for the integration of educational scenarios.VR is challenging for learners with regard to orientation in a 360° environment.Regarding learning outcomes, research on the effects of cues to highlight important content in a 360° environment is still rare.Presence, defined as the feeling of being there in a VR environment, is an important prerequisite for learning in VR. What this paper adds: The influence of light and movement cues on search times and learning outcomes in a desktop‐VR environment was tested.Movement cues can reliably reduce search times (indicating successful orientation), whereas light cues only reduced search times in predictable scenarios.In a predictable scenario, light cues enhanced learning outcomes compared with movement cues.Movement cues reduced presence, which is one potential reason why movement cues did not improve learning. Implications for practice and/or policy: Using light cues might assist orientation and enhance overall performance in predictable scenarios (i.e., when learners know what kind of cue to expect).In an unpredictable setting with variable cues, light cues did not facilitate orientation, whereas movement cues did.However, movement cues reduced presence, which may have negatively affected learning outcomes. It is important to develop cueing methods that also work in more unpredictable settings, but that do not reduce presence. [ABSTRACT FROM AUTHOR]

Background Study: Virtual reality (VR) is becoming a popular technology for safety training in construction. Several VR training prototypes have been designed and tested, which show they can perform better than traditional training tools. However, most of these existing tools are not underpinned by clear pedagogical theory, and studies assessing the impact of pedagogical theories on the effectiveness of VR prototypes are still rare in the literature. Objectives: This study aims to investigate if and how the productive failure theory and the directive instruction theory have an impact on the effectiveness of VR safety training for confined space workers. Methods: The study used a randomized controlled method involving 74 participants. The effectiveness of these two training methods was assessed in terms of knowledge acquisition and retention. Results and Conclusions: The results illustrate that the productive failure training design performed better in terms of knowledge acquisition and retention. This paper introduces the Productive Failure Theory and shows the great potential of this approach for self‐service VR safety training in the field of construction. Lay Description: What is already known about this topic: PF has been proven effective in classroom‐based teaching practice.PF has been proven effective in non‐immersive virtual training.DI is a commonly used pedagogical method for VR training. What this paper adds: The present paper investigates the feasibility of applying PF theory in VR safety training.The present paper examines the pedagogical impacts of the two pedagogical approaches within VR serious games. Implications for practice and/or policy: PF can be applied to self‐help VR safety training, reducing the demand for resources such as teaching staff and venues.PF training design performed better in terms of knowledge acquisition and retention.PF has great potential for self‐help VR safety training in various fields. [ABSTRACT FROM AUTHOR]

Background: Given students' lack of self‐directed learning skills and the growing concern about implementing massive online open courses (MOOCs) in K12 education, learning strategies are needed to facilitate MOOC learning. Many studies have provided different strategies for effective learning in MOOCs. However, there is still limited research to confirm whether these strategies effectively support MOOC learning when deployed by secondary schools, which are not MOOC developers. Objectives: This mixed‐method study examines the provision of different learning strategies, including a learning guide, an academic mentoring programme, a training workshop, and a reimbursement scheme, and investigates the impact of these strategies on student learning in MOOCs. Methods: The study uses two data sources: (1) surveys with 40 participants and (2) semi‐structured interviews with 12 participants. The quantitative data were analysed with descriptive statistics and Fisher's exact test, and the qualitative data were analysed with thematic analysis. Results and Conclusion: The findings indicate that MOOC learners had positive attitudes towards the overall school support, with mentoring enjoying great popularity amongst the students. In terms of the effectiveness of the school support, the mentoring programme and reimbursement scheme were more effective than the university training and learning guide. The paper discusses the implications for researchers and educators. Lay Description: What is already known about this topic: There are a large number of K12 MOOC implementations, which are (i) STEM‐related and computer science courses, and (ii) from Europe and the USA.Limited studies provided different learning strategies for MOOC learning from the perspective of K12 schools, which are not MOOC developers.There is a need to explore MOOC initiatives encompassing a wide variety of subjects, including computer science MOOCs and non‐computer science MOOCs, in regions beyond Europe and the USA.There is also a need for further scrutiny of the effectiveness of learning strategies provided by the K12 school. What this paper adds: Our study launched the first MOOC implementation in K12, encompassing several subject areas beyond computer science in the region of Asia.Our study provided different learning strategies adopted by the K12 school, and the analysis revealed that MOOC learners took positive attitudes towards overall school support with mentoring enjoying great popularity with these students.Our study examined the effectiveness of school support and identified that mentoring and reimbursement are more effective than university training and the learning guide. Implications for practitioners: The insights gained from the study enable other K12 schools and educators to implement MOOC into existing school infrastructures successfully.These strategies provided in the MOOC implementation program can be helpful in many different online learning contexts. [ABSTRACT FROM AUTHOR]

Background: This research paper presents a cross‐sectional study that examinefs the preferences of students for hybrid teaching and learning scenarios. Unlike previous studies that merely describe hybrid scenarios, this research prioritizes them, offering evidence‐based findings for informed policy decisions. Methods: The data collection method involved eight choice‐based tasks using the conjoint analysis technique conducted with 'Sawtooth' software. The study surveyed students at a mid‐sized university across four departments in Central Switzerland. The sample analysed in this article comprised 319 respondents from the Lucerne School of Business. Results and Conclusions: Our survey found that students' own location during a teaching session played a significant role in determining participation preferences, followed by that of the lecturer. Factors that influenced students' preferences whether to attend onsite or online include workload, didactical format, perceived level of difficulty, student residence, and semester. Forms of hybrid collaboration and student–student interaction did not significantly influence student preferences. Takeaways: The value of this study lies in its evidence‐based findings for specific hybrid scenarios, which can provide useful insights for policymakers in degree programs and faculty in hybrid classrooms. This study is one of only a few to use conjoint analysis with such a high respondent rate to determine student preferences for hybrid attendance. Lay Description: What is currently known about this topic?: Student demand for hybrid teaching scenarios remains high, while many faculty find the scenario technically challenging.Opinions as to the precise features of 'hybrid' vary widely.No clear understanding of the conditions under which students will decide to attend any given class.Demand for additional exchange among online students is recommended in the literature, but often not implemented. What does this paper add?: The study uses conjoint analysis to simulate how students make attendance decisions.The study shows empirically which factors are most important to determine students' attendance.Two‐thirds of the students surveyed prefer an online option.Group composition and informal exchange do not significantly impact students' attendance preferences. Implications for practice/or policy: Students appreciate the flexibility of online learning but expect lecturers to be onsite.Difficult subjects are more likely to be attended onsite.Student residence, workload, degree program, and semester impact students' attendance preferences.No additional infrastructure is needed to encourage exchange among students. [ABSTRACT FROM AUTHOR]

Background: Augmented reality (AR) is receiving increasing interest as a tool to create an interactive and motivating learning environment. Yet, it is unclear how instructional support affects performance in AR. Objectives: This study sought to explore how varying the instructional support in AR can affect performance‐related behaviours of students with low cognitive abilities during assembly work. Methods: A total of 90 Belgian secondary school students repeatedly executed four different realistic assembly tasks. Three levels of instructional support (low, medium, and high) in AR as well as a control condition with paper instructions with a high level of detail were systematically varied across tasks and participants. Results and Conclusions: Multilevel regression analyses showed that AR instructions yielded lower assembly times and a lower perceived physical effort than paper instructions. Additionally, participants perceived tasks as less complex when given AR instructions with a high or a medium level of detail than when given a low level of detail. No effects of instructional support were established for other performance‐related behaviours, namely necessary assistance, error‐making, cognitive load, competence frustration, and stress. Effect sizes were small, at least among the instructional support conditions studied, yielding a limited base for adaptivity. Presumably, tailoring the instructional support in AR is only beneficial for highly complex tasks. The results might be useful for the design and implementation of AR in educational settings. Lay Description: What is currently known about the subject matter: Augmented reality is knowing increased use in education.Little is known about how to design effective instructional support in augmented reality. What this paper adds: This study represents an initial insight into how to personalize instructional support.The impact of instructional support on augmented reality performance of students with low cognitive abilities was investigated.The study suggests that varying instructional support may lead to differences in performance outcomes. Implications for practitioners: How instructional support is constructed may affect augmented reality learning.The results may inform the design of effective augmented reality learning environments for students with special needs.How individual, contextual, and task‐specific characteristics moderate the effectiveness of instructional support should be further investigated. [ABSTRACT FROM AUTHOR]

Background: The potential of learning analytics dashboards in virtual reality simulation‐based training environments to influence occupational self‐efficacy via self‐reflection phase processes in the Chemical industry is still not fully understood. Learning analytics dashboards provide feedback on learner performance and offer points of comparison (i.e., comparison with one's own past performance or comparison with peer performance) to help learners make sense of their feedback. Objectives: We present a theoretical framework for describing learning analytics reference frames and investigate the impact of feedback delivered through dashboards with different reference frames on occupational self‐efficacy, while controlling for workplace self‐reflection. Methods: This experimental study engaged 42 chemical operator employees, aged between 18 and 55 years, each with at least one year of experience. We utilised a two‐group design to ask two research question each with three competing hypotheses related to changes in occupational self‐efficacy, employing Bayesian informative hypothesis evaluation. Results and Conclusions: Results for the primary research question suggest that dashboards with progress reference frames do not elicit greater change to self‐efficacy than those with social reference frames, however, they may elicit equal change. Furthermore, dashboards with social reference frames may elicit greater change to self‐efficacy than those with progress reference frames. Exploratory results found that dashboards with progress reference frames may elicit greater positive directional change than those with social reference frames and that they may elicit equal directional change. These findings contribute to the understanding of self‐efficacy beliefs within the Chemical industry, with potential impacts on skill development. The research may inform the design of targeted interventions and training programs to influence self‐efficacy. From a practical perspective, this research suggests that careful consideration is needed when choosing reference frames in learning analytics dashboards due to their potential consequences on the formation of learner self‐efficacy. Lay Description: What is already known about this topic?: Learning analytics dashboards often aim to stimulate self‐regulated learning by providing feedback.Feedback plays a crucial role in simulation‐based learning and learning analytics dashboards can be a valuable tool to deliver feedback and facilitate the learning process by providing learners with insights into their performance and progress.Previous research has highlighted the importance of reference frames as critical design features of learning analytics dashboards, as they assist learners in making sense of learning analytics feedback.Self‐efficacy is a powerful determine factor of workplace performance and is influenced by mastery experiences and social modelling information. What the paper adds?: A theoretical framework describes the mediating role self‐reflection phase processes of the self‐regulated learning cycle plays in the formation of occupational self‐efficacy.This paper introduces the concept of three learning analytics reference frame components which include the performance outcome component, point of comparison component and score delta component.The paper indicates that learning analytics dashboards designed with a progress reference frame does not elicit greater change to occupational self‐efficacy than the social reference frame.Exploratory results suggest dashboards with progress reference frames might produce greater positive directional change compared to social reference frames or elicit equal change. Implications for practice?: Learning analytics system designers who use reference frames to help learners make sense of their feedback should carefully consider which reference frames they use as these decisions likely have consequences on the formation of learner self‐efficacy beliefs.For LAD designers and stakeholders, recognising the absolute change and directional shift in self‐efficacy is crucial, as LAD designs significantly influence these dynamics and guide the tailoring of effective tools.In industries like the chemical sector, where overconfidence can result in severe consequences, understanding the nuance of self‐efficacy changes is especially pertinent. [ABSTRACT FROM AUTHOR]

Background: Driven by the ongoing need to provide high‐quality learning and teaching, universities recently have shown an increased interest in using learning analytics (LA) for improving learning design (LD). However, the evidence of such improvements is scarce, and the maturity of such research is unclear. Objectives: This study is aimed to evaluate the maturity of research discussing LA‐driven LD improvements in higher education. Methods: The systematic review analyses 49 empirical papers, assesses their quality and suggests further research directions. The review elaborates on methodological (research questions, strategy and methods, LA‐LD integration theoretical backgrounds) and substantial (LA‐driven LD improvements, types of data used, LA software development) features of the papers. Results and Conclusions: The findings demonstrated the lack of theoretical alignment between LA and LD, with research tending towards user experience studies. The most frequently used research strategy was a case study; experiments were very rare. Researchers predominantly used parsing for collecting data and AI methods for analysing it; mostly used data types related to registering learners' engagement with learning activities as well as resources and tools provided in digital learning environments. Takeaways: The research area discussing LA‐driven LD improvements still has a way to go before attaining the level of full maturity. Only a third of the papers reported actual LA‐driven LD improvements; moreover, only three papers measured their effectiveness. The presented LA software was mostly at the beta or implementation stages and did not assess the impact of using this software. Lay Description: What is already known about this topic: Universities show an increased interest in using LA for improving LD.The evidence of such improvements being efficient is scarce.Learning analytics is weakly grounded in learning and teaching. What this paper adds: LA‐LD research presented in the reviewed papers cannot yet be considered fully mature.Almost half of the research was carried out using a case study approach, intrinsically challenging in terms of replication and validity. As few as three out of the reviewed studies applied an experimental approach, capable of stating the cause–effect relationship between LA and LD.All the studied papers mentioned improvements in LD, but only around a third of them reported actual improvements, another one‐third suggested potential improvements, and the rest did not come down to describing any.The LA software presented in the papers was mostly at the testing or implementation stages, and the impact of implemented software on LD has yet to be evaluated. Implications for practice and/or policy: Future LA‐LD research to become more mature may well elaborate on theoretical footing, contribute to the cause–effect relationship between LA and LD utilising experimental research design, ensure sufficient sample size.Practitioners' efforts should be directed to operationalising LD for efficient measurements, addressing pedagogical challenges when applying LA, and assessing LA‐driven improvements introduced into LD. [ABSTRACT FROM AUTHOR]

Background: Degree apprenticeships (DA) help employees gain new knowledge and skills by allowing them to study towards a university degree while working full time. For these programmes to be effective, the learning design should be adapted to the needs of these students, who are goal oriented (i.e. they want to gain only knowledge that can be applied within their workplace), have limited time for studying, and usually have not attended formal education for some time. As these programmes are relatively new, there is limited research on how these students can be supported to achieve the programmes' learning goals by using information and communication technologies. Objectives: This paper aims to understand whether a learning design that combines game‐based learning with online flipped classrooms can engage DA students in their learning and help them develop their reflective skills. Methods: Two focus groups were conducted with DA students that study at a UK Business School towards gaining the Chartered Manager status. The focus groups recordings have been analysed using reflexive thematic analysis. Results and Conclusions: The three main themes, "change can be helpful and challenging at the same time", "the ideal game", and "the effect of others", show that DA students find game‐based learning and online flipped classrooms useful, with the right support. Simulation games can be more fulfilling to DA students than quiz games, even if they take more of their out‐of‐class time. In addition, instructors are advised to work more closely with diverse teams to enable students share their work experiences and learn from each other. Lay Description: What is already known about this topic?: Online flipped classrooms offer flexibility in learning, but instructors need to find solutions to challenges, like students' limited e‐learning readiness and lack of motivation.Game‐based learning has been found to facilitate learning in general, but there is a need to identify the specific circumstances (i.e. settings, gaming elements) under which it is effective.Degree apprenticeship students need more support with their learning compared to traditional university students, as they face additional challenges in terms of family life‐work balance and connecting their learning to their working experience. What this paper adds?: Game‐based learning can be useful to degree apprenticeship students providing that focuses on the application of knowledge and provides feedback.Despite facing challenges related to maintaining work‐study‐life balance, degree apprenticeship students are willing to complete the flipped classroom's out‐of‐class activities, if they see a clear benefit from doing so.Online group activities can be challenging for degree apprenticeship students, if they are not able to form teams with other learners that work for the same organisation. The implications of study findings for practitioners: Avoid quiz‐like games and select the ones that use real‐life scenarios for degree apprenticeship students to help them link their learning to their practice.Formative feedback should be provided by both the instructor and the game to motivate degree apprenticeship students to spend the additional time to complete the out‐of‐class activities.Students should be reminded frequently of the purpose of any new learning elements (e.g. learning analytics) as they may not have the time to explore them on their own.When forming student teams based on students' workplace is not possible, spend more time in each breakout room to facilitate the online group discussion and help students bring their different working experiences together. [ABSTRACT FROM AUTHOR]

Background: Cognitive load during AR use has been measured conventionally by performance tests and subjective rating. With the growing interest in physiological measurement using non‐invasive biometric sensors, unbiased real‐time detection of cognitive load in AR is expected. However, a range of sensors and parameters are used in various subject fields, and reported results are fragmented. Objectives: The aim of this review is to analyse systematically how physiological methods have been used to measure cognitive load and what the implications are for the future research on AR‐based tools. Methods: This paper took the systematic review approach. Through screening with 10 exclusion criteria, 23 studies, that contain 3 key elements: AR‐based intervention, cognitive state examination and physiological methods, were identified, analysed and synthesised. Results: Physiological methods in their current form require reference to provide meaningful interpretations and suggestions. Therefore, they are often combined with conventional methods. Many studies investigate the effect of wearable devices in comparison with non‐AR stimuli, which has been controversial, but detection of different causes of cognitive load are on the horizon. Eye‐tracking is the method most used and most consistent in the use of its parameters. Conclusions: A multi‐method approach combining two or more evaluation instruments is essential for the validation of users' cognitive state. In addition to the AR stimuli in question, having another independent variable such as task difficulty in experiment design is useful. Statistical approaches with more data input could help establish a reliable scale. The future research should attempt to dissociate cognitive load caused by different effects such as device, instruction, and other AR techniques as well as intrinsic and extraneous aspects, in a better experimental setup with multiple parameters. Lay Description: What is already known about this topic: The efficacy of AR‐based instructional tools can be evaluated using the concept of cognitive load.Cognitive load has been conventionally measured by self‐reporting and performance.There is a growing interest in physiological measurement of cognitive load with non‐invasive biometric sensors. What this paper adds: This paper systematically analyses how physiological methods are used to measure cognitive load in AR.It synthesises the fragmented results of AR studies conducted with a range of physiological methods. Implications for practice: Combining two or more evaluation instruments is essential for the validation of users' cognitive state.Eye‐tracking is the method most used, and fixation duration is the most consistent parameter.A statistical approach with more biometric data input could help establish a reliable cognitive load scale.Future research should attempt to separate cognitive load caused by different effects and different cognitive aspects. [ABSTRACT FROM AUTHOR]

Background: Previous studies have shown that dynamic illustrations, as compared to their static counterparts, lead to higher achievement levels, especially for hand‐based procedures. Other researchers have investigated how the presence of seductive details (i.e., appealing but irrelevant adjunct displays) influences students' interest positively but their learning negatively. Objectives: The purpose of the two present studies was to investigate the effects of animated versus static presentations, combined with the presence of seductive details, on student performance on a paper‐folding task (i.e., origami) in a naturalistic school environment. Methods: Fifty‐five children (5–6 years old) participated in the first study and were randomly assigned to one of four groups. The second study was conducted with older children (72 s or third graders) and a more complex origami task. Results and Conclusions: In the first study, results demonstrated negative effects of seductive details on children's performance and time on task, but no effects of presentation format. In the second study, no negative effects of seductive details on student achievement were found, but animated illustrations significantly improved children's performance and reduced time on task. However, seductive details tended to impair learning more greatly given the presence of static, as compared to animated, presentations. Task difficulties and pupils' ability to inhibit irrelevant information may explain these results. Lay Description: What is already known about this topic: Seductive details negatively influence young children's performance.Animated illustrations have been shown to improve students' learning for dynamic procedure. What this paper adds: This is the first study investigating the influence of animated vs. static illustrations combined with seductive details on children's learning performance.Animated illustrations improve children's performance for a challenging dynamic procedure.Seductive details tended to impair more learning from static than from animated presentations.Results are discussed in relation to the task's difficulty as well as students' ability to inhibit irrelevant information. Implications for practitioners: Animated illustrations should be used when presenting dynamic procedures.Instructors should use seductive details cautiously in pedagogical documents particularly when the task is difficult. [ABSTRACT FROM AUTHOR]

Background Study: The research discusses the need for a paradigm shift in engineering education current practices to accommodate the digital native students. The paper emphasizes the importance of integrating disruptive technologies, namely Virtual Reality (VR) through Head Mounted Displays VR (HMD VR) and Desktop Based VR (DB VR) and comparing it with the traditional teaching methods. The research focuses on second‐year undergraduate students enrolled in a concrete structures course. Objectives: The objective of the study is to analyse the impact of DB VR and HMD VR on students' motivation, performance and workload in comparison with traditional 2D drawings. The study also aims to investigate how simulation sickness and system usability could impact students' motivation and performance when interpreting concrete structures. Methods: The study divided second‐year civil engineering students into three groups, 2D, DB VR and HMD VR. The performance and motivation levels of students were assessed based on the number of mistakes identified and an intrinsic motivation survey. Furthermore, data on system usability and simulation sickness were collected. Spearman rank correlation was conducted to analyse the relationships between the variables tested. Results: The results have shown that students' motivation and performance were much higher when using VR in general and HMD VR specifically, students' efficiency and accuracy were also observed. On the other hand, usability was found to be moderately correlated with motivation, with students rating HMD VR as the most usable approach. A moderate inverse correlation was observed between simulation sickness and motivation, indicating that higher simulation sickness led to lower motivation levels. Conclusion: The study concludes that integrating VR in general, DB VR, or HMD VR into a concrete structures course for undergraduate students can significantly improve students' performance and motivation. Furthermore, enhancing usability of any of the methods used can also improve the performance and motivation. On the other hand, simulation sickness inversely affects motivation and performance, therefore, VR developers and educators should not neglect it. Lay Description: What is already known about the topic: Traditional teaching methods in engineering education require improvement.Integrating digital technologies into engineering education enhances performance.Digital technologies can potentially enhance motivation. What this paper adds: Compares traditional teaching methods for concrete structures interpretation with virtual reality.Establishes correlations between motivation, performance and usabilityIntroduces how desktop‐based VR and head‐mounted display VR can produce varying results. Implications for practice and/or policy: Decision‐makers can use the information to integrate updated pedagogy into engineering curricula.Allows for further exploration of different digital technologies that can be used for concrete structure interpretation.Allows instructors to introduce virtual reality in their courses. [ABSTRACT FROM AUTHOR]

Background: The emergence of ChatGPT in the education literature represents a transformative phase in educational technology research, marked by a surge in publications driven by initial research interest in new topics and media hype. While these publications highlight ChatGPT's potential in education, concerns arise regarding their quality, methodology, and uniqueness. Objective: Our study employs unconventional methods by combining altmetrics and bibliometrics to explore ChatGPT in education comprehensively. Methods: Two scholarly databases, Web of Science and Altmetric, were adopted to retrieve publications with citations and those mentioned on social media, respectively. We used a search query, "ChatGPT," and set the publication date between November 30th, 2022, and August 31st, 2023. Both datasets were within the education-related domains. Through a filtering process, we identified three publication categories: 49 papers with both altmetrics and citations, 60 with altmetrics only, and 66 with citations only. Descriptive statistical analysis was conducted on all three lists of papers, further dividing the entire collection into three distinct periods. All the selected papers underwent detailed coding regarding open access, paper types, subject domains, and learner levels. Furthermore, we analysed the keywords occurring and visualized clusters of the co-occurring keywords. Results and Conclusions: An intriguing finding is the significant correlation between media/social media mentions and academic citations in ChatGPT in education papers, underscoring the transformative potential of ChatGPT and the urgency of its incorporation into practice. Our keyword analysis also reveals distinctions between the themes of the papers that received both mentions and citations and those that received only citations but no mentions. Additionally, we noticed a limitation that authors' choice of keywords might be influenced by individual subjective judgements, potentially skewing results in thematic analysis based solely on author-assigned keywords such as keyword co-occurrence analysis. Henceforth, we advocate for developing a standardized keyword taxonomy in the educational technology field and integrating Large Language Models to enhance keyword analysis in altmetric and bibliometric tools. This study reveals that ChatGPT in education literature is evolving from rapid publication to rigorous research.

Background: Learner profiles detected from digital trace data are typically triangulated with survey data to explain those profiles based on learners' internal conditions (e.g., motivation). However, survey data are often analysed with limited consideration of the interconnected nature of learners' internal conditions. Objectives: Aiming to enable a thorough understanding of trace-based learner profiles, this paper presents and evaluates a comprehensive approach to analysis of learners' self-reports, which extends conventional statistical methods with psychological networks analysis. Methods: The study context is a massive open online course (MOOC) aimed at promoting physical activity (PA) for health. Learners' (N = 497) perceptions related to PA, as well as their self-efficacy and intentions to increase the level of PA were collected before and after the MOOC, while their interactions with the course were logged as digital traces. Learner profiles derived from trace data were further examined and interpreted through a combined use of conventional statistical methods and psychological networks analysis. Results and Conclusions: The inclusion of psychological networks in the analysis of learners' self-reports collected before the start of the MOOC offers better understanding of trace-based learner profiles, compared to the conventional statistical analysis only. Likewise, the combined use of conventional statistical methods and psychological networks in the analysis of learners' self-reports before and after the MOOC provided more comprehensive insights about changes in the constructs measured in each learner profile. Major Takeaways: The combined use of conventional statistical methods and psychological networks presented in this paper sets a path for a comprehensive analysis of survey data. The insights it offers complement the information about learner profiles derived from trace data, thus allowing for a more thorough understanding of learners' course engagement than any individual method or data source would allow.

Motivation Objectives Methods Results and Conclusions This research investigates the transformative impact of integrating AI into mathematics education, aiming to enhance students' conceptual understanding and self‐efficacy. It addresses the crucial need for innovative teaching methods in response to contemporary challenges in education and aims to fill gaps in understanding the potential drawbacks and benefits of AI implementation.The primary goal of this study is to investigate the effects of AI tools, such as GeoGebra and ChatGPT, on students' conceptual understanding and self‐efficacy in a mathematics classroom setting, with a focus on collaborative learning, teacher‐led discussions, and problem‐solving.Employing a mixed‐methods approach, the research involves pre‐ and post‐implementation surveys, supplemented by qualitative data from interviews, focus groups, and classroom observations. The study emphasises the utilisation of AI in collaborative learning environments and explores the challenges and opportunities associated with its integration.The study reveals a noteworthy enhancement in students' conceptual understanding and self‐efficacy belief when AI tools are incorporated into mathematics education. However, it highlights concerns such as technological challenges, potential teacher replacement fears, biases in AI systems, and difficulties related to pacing and social interaction. To optimise the use of AI, the paper suggests strategies like adaptive learning platforms, real‐world simulations, intelligent tutoring systems, and data‐driven instruction, positioning AI as a complement rather than a substitute for traditional teaching methods. The study recommends addressing challenges through additional support resources and transparent communication, emphasising the need for a thoughtful integration of AI in education. [ABSTRACT FROM AUTHOR]

Background Paper Objectives Methods Results and Conclusions Takeaways Personalised and timely feedback in massive open online courses (MOOCs) is hindered due to the large scale and diverse needs of learners. Learning analytics (LA) can support scalable interventions, however they often lack pedagogical and contextual grounding. Previous research claimed that a human‐centred approach in the design of LA solutions can be beneficial. Yet, there is a scarcity of empirical studies discussing participatory approaches addressing LA for feedback in MOOCs.We report a human‐centred design, where an instructor and a tool developer employed a conceptual framework, named FeeD4Mi, to shape personalised LA‐informed feedback in a MOOC.The current study follows a qualitative interpretative approach to understand how the proposed conceptual framework FeeD4Mi served the MOOC instructor and the tool developer to design feedback interventions and re‐design an existing LA tool, respectively.The results showed that FeeD4Mi helped the tool developer to create a contextualised LA tool, named edX‐LIMS+. edX‐LIMS+ allowed the instructor to monitor and assist struggling MOOC learners in a timely manner. Additionally, FeeD4Mi successfully guided the course instructor in designing and delivering personalised interventions. Yet, the feedback design process was perceived as time‐demanding, an issue we plan to address in our future work.The current study extends the existing empirical research about employing human‐centred approaches for the design of LA‐driven interventions. Moreover, this study advances the theory of scalable feedback tactics, through a conceptual framework that aims to guide MOOC instructors during the definition of feedback interventions. We envision that this research contributes to promoting participatory approaches for designing, delivering, and evaluating LA‐informed feedback interventions in authentic contexts. [ABSTRACT FROM AUTHOR]

Background Objectives Methods Results and Conclusions The adoption of virtual laboratories (VLs) has experienced a significant surge, catalysed by the global changes in the educational landscape, notably influenced by the COVID‐19 pandemic. Originally supplementary to traditional in‐person laboratory experiments, VLs swiftly transitioned into a primary source of hands‐on laboratory activities for educational institutions worldwide during the pandemic. As restrictions have eased, virtual, computer‐assisted learning platforms continue to be used, though now as a complement to, rather than a substitute for, hands‐on experimentation opportunities. However, their adoption presents both opportunities and challenges that require thorough investigation to maximize their effectiveness and equity.This paper aims to provide a comprehensive overview of VL resources utilized across various scientific disciplines. It evaluates their potential to enhance traditional hands‐on laboratory activities and examines the efficacy of computer‐assisted learning platforms from a constructivist learning perspective. By doing so, the study seeks to identify best practices, challenges, and strategies for the effective integration of VLs in science education.A content analysis was conducted on literature published from 2013 to 2023, focusing on VLs in educational settings. Thematic analysis was employed to categorize the findings into three primary pillars: Merits, Challenges, and Implementation Strategies. Multiple researchers participated in the analysis to ensure reliability and consistency. To further enhance reliability, regular cross‐checks and consensus meetings were held to resolve any discrepancies and maintain the integrity of the thematic categorization. A constructivist learning perspective was used to analyse the instructional implications, focusing on active learning to evaluate alignment with educational goals, adapted teaching methods, and assessments.The analysis revealed that VLs offer significant benefits, including enhanced accessibility, flexibility, and opportunities for active learning. Virtual labs provide scalable, safe opportunities for inquiry‐based science learning by replicating experiments in an accessible digital environment, enhancing understanding of scientific concepts based on research demonstrations of improved learning outcomes. However, challenges such as high initial setup costs, technological barriers, and the need for effective integration with traditional curricula were also identified. Despite these challenges, VLs have the potential to complement and enhance hands‐on laboratory experiences, provided they are implemented thoughtfully and equitably. Future research should focus on improving the efficacy, accessibility, collaboration among stakeholders, and economic feasibility of VLs to maximize their educational impact. [ABSTRACT FROM AUTHOR]

Background: In scientific inquiry learning, students often have difficulties conducting hypothetical reasoning with multiple intertwined variables. Concept maps have a potential to facilitate complex thinking and reasoning. However, there is little investigation into the content of student‐constructed concept maps and its association with inquiry task performance. Objectives: This study explored students' concept mapping style and its association with task performance in computer‐based inquiry learning. Methods: An exploratory study was conducted with 80 Grade 11 students, who collaboratively constructed concept maps in a free style to support inquiry learning with a virtual ecosystem. Student‐constructed concept maps was analysed by firstly identifying different types of propositions formed in the maps and then determining the style of each concept map based on the dominant type of propositions in the map. Finally, the association between the concept map style and inquiry task performance was explored. Results and Conclusions: Two major concept map styles were identified: (1) knowledge‐oriented concept maps (KCMs) mainly representing problem‐related subject knowledge as a set of concepts and their relationships, and (2) problem‐oriented concept maps (PCMs) mainly representing problem situation as a sequence of changes and their causal relationships. Compared with those constructing KCMs, the students constructing PCMs formed higher‐quality propositions in their maps and performed better in hypothesising, reasoning, and drawing conclusions in the inquiry task. Implications: Besides KCMs, students in inquiry learning can be encouraged to construct PCMs to foster effective thinking and reasoning; that is, constructing a concept map to represent the problem situation as a sequence of changes and the causal relationships between the changes. Lay Description: What is currently known about the subject matter: Concept maps (CMs) can facilitate complex thinking and reasoning in inquiry learning.There is little investigation into the content of student‐constructed CMs.It is unknown how CM content might associate with inquiry task performance. What this paper adds: Students constructed two major styles of CMs in computer‐based inquiry learning.The two styles of CMs are problem‐oriented and knowledge‐oriented CMs.Students constructing problem‐oriented CMs performed better in the inquiry task. Implications for practitioners: Analysing student‐constructed CMs helps understand student thinking in inquiry.Students are encouraged to build problem‐oriented CMs in inquiry learning. [ABSTRACT FROM AUTHOR]

Background: Effective learning in computer programming courses has been a constant challenge for university teachers and has become a relevant competence for current professionals. The literature on gamification in learning presents mixed results, mainly due to problems in instructional design and inconsistency in gamification. Studies with positive empirical results on computer programming formative activities and showing under what conditions gamification is effective still need to be included. Objectives: This study aimed to quantify the effects of gamification techniques in software tools that support computer programming learning applied to data‐structures university students. The study focused on determining whether there are differences in learning when using gamification techniques in online exercising formative activities. The effects of gamification on learning objectives with diverse complexity are studied. Methods: The study was conducted on computer engineering university students following a pretest‐intervention‐posttest design. They were divided into control and experimental groups, where both used a bank of exercises in Moodle to support learning. The experimental group considered gamification techniques, including points, leaderboards, and badges. Results and Conclusions: Gamification techniques significantly outperformed in learning gains in exercising activities without gamification. Regarding learning complexity, increasing taxonomic complexity did not negatively affect gamification learning effects. Lay Description: What is currently known about the subject matter?: Gamification has been explored as a strategy to enhance learning motivation in various educational contexts, including computer programmingLiterature shows mixed quantitative results on learning improvements under gamification.Few studies cover formative exercises, deal with computer programming tasks, or use a LMS like Moodle.Lack of literature exploring the conditions for effective gamification use, and involving learning objective complexity. What does this paper add to the existing body of research?: Quantifies the impact of gamification techniques on learning outcomes, specifically focusing on computer‐programming in university.Provides empirical evidence on gamification significantly improving learning gains compared to non‐gamified data‐structures exercisesGamification is effective in tasks of diverse levels of taxonomic complexity, with consistent effectiveness regardless of learning difficulty. Implications of study findings for practitioners: Gamification techniques, can be used in higher education to enhance student engagement and learning outcomes in computer programmingThe gamification information (e.g. points and ranking) do not require an automatic update, can be processed manually and published daily.It is effective to use gamification for learning tasks of medium‐high difficulty in Moodle on computer programming topics.It is key a thoughtful instructional design when applying gamification, ensuring alignment with learning objectives and task complexity. [ABSTRACT FROM AUTHOR]

Background: Many instructors transitioned their courses from face‐to‐face environments to computer‐mediated learning environments (CMLEs) following the onset of the coronavirus disease 2019 (COVID‐19) pandemic. However, little was known about how teleconferencing platforms and their corresponding functions affect student learning when the COVID‐19 pandemic began. Objectives: The aim of this study was to provide more clarity on the conditions through which online teleconferencing platforms influence student achievement. More specifically, this study investigated how displaying lecture‐relevant and lecture‐irrelevant messages in a chat box during a video lecture delivered via the Zoom teleconferencing platform affected student learning and note taking. Methods: Participants viewed the video lecture either with (relevant or irrelevant) or without messages appearing in the chat box of the Zoom window. Participants completed a learning test immediately following the lecture. Results and Conclusions: No difference regarding student achievement was observed between the three groups. However, results revealed that students in the relevant‐lecture messages group reported a higher extraneous cognitive load than the other groups even if they reported positive attitudes about the messages appearing on the chat box. Students in the lecture‐relevant group also recorded more notes during the lecture compared to the two other groups, but this result did not reach significance. This study extends previous research that investigated how messaging influences learning in classroom settings. Findings suggest that allowing relevant discussions is not the best strategy to promote learning in CMLEs as this information seems to compete with the other relevant information being presented during the ongoing lecture. Lay Description: What is already known about this topic: In video lectures, the chat box has been identified as the function most often used to support students' learning.Responding to lecture‐relevant messages can enhance students' learning.However, it remains unknown how simply reading, but not responding to, lecture‐relevant and lecture‐irrelevant messages can affect learning and note taking. What this paper adds: In previous studies, researchers examined how messaging affects learning in a classroom setting, but not within a computer‐mediated lecture environment.The present study extends previous research that investigated how messaging influences learning in classroom settings.This study provides more clarity on the conditions through which online teleconferencing platforms affect student learning and note taking.Findings suggest that allowing relevant discussions is not the best strategy to promote learning in CMLEs as this information seems to compete with the other relevant information being presented during the ongoing lecture. Implications for practitioners: The features of video lectures are critical factors, as they influence students' learning and should therefore be taken into account when designing educational materials.Instructors should not allow students to engage in lecture‐relevant and irrelevant messaging and discussion during video lectures as it competes with the other relevant information being presented. [ABSTRACT FROM AUTHOR]

Background: Higher vocational education is an essential part of the higher education system that complements conventional education. In the context of information and communication technology (ICT) development and academic competition, more and more literature has proved the importance of ICT use in educational development (academic achievement and mental health) and the relationship between information literacy and the educational development of higher vocational students. Objectives: Based on one of the most extensive surveys of higher vocational students, the study combined the Opportunity‐Propensity (O‐P) framework and ecological model to explore the direct effects of different types of ICT use on educational development and the indirect effects from psychological and social factors. Methods: The data involved 28,956 students from seven higher vocational colleges. The class fixed effect and causal mediation analysis models verified the results. Results and Conclusion: The results found differential effects of different types of ICT use on academic achievement and mental health. Information literacy ability can improve the academic achievement of higher vocational students, but at the cost of mental health. ICT use not only directly impacts the academic achievement and mental health, but also has an indirect impact through psychological factors represented by self‐efficacy and technostress and social factors represented by social support. Implications: This study promotes integrating and expanding the O‐P framework and ecological model, enriching the relevant research in ICT use and educational development. Meanwhile, it also provides practical suggestions for realizing rational interventions in ICT use and improving the educational development level of higher vocational students. Lay Description: What is already known about this topic: Information and communication technology (ICT) use is closely related to the educational development of higher vocational students.The trend of ICT use in higher vocational education has become increasingly apparent.The effects of ICT use are heterogeneous among groups with different information literacy. What this paper adds: O‐P framework and ecological model provide the perspective of theoretical integration.The impact of different types of ICT use on educational development varies.Information literacy can improve academic achievement at the cost of mental health.Psychological and social factors play a mediating role in educational development. Implications for practice and/or policy: The research is helpful to guide students to allocate their time reasonably for different ICT uses.Mental health counselling should be strengthened while cultivating information literacy ability.Develop appropriate ICT usage strategies for students with different information literacy.It is helpful to develop appropriate interventions from a psychological and social perspective. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence–generated content (AIGC) has stepped into the spotlight with the emergence of ChatGPT, making effective use of AIGC for education a hot topic. Objectives: This study seeks to explore the effectiveness of integrating AIGC into programming learning through debugging. First, the study presents three levels of AIGC integration based on varying levels of abstraction. Then, drawing on extended effective use theory, the study proposes the underlying mechanism of how AIGC integration impacts programming learning performance and computational thinking. Methods: Three debugging interfaces integrated with AIGC by ChatGPT were developed for this study according to three levels of AIGC integration design. The study conducts a between‐subject experiment with one control group and three experimental groups. Analysis of covariance and a structural equation model are employed to examine the effects. Results and Conclusions: The results show that the second and third levels of abstraction in AIGC integration yield better learning performance and computational thinking, but the first level shows no difference compared to traditional debugging. The underlying mechanism suggests that the second and third levels of abstraction promote transparent interaction, which enhances representational fidelity and consequently impacts learning performance and computational thinking, as evidenced in test of the mechanism. Moreover, the study finds that learning fidelity weakens the effect of transparent interaction on representational fidelity. Our research offers valuable theoretical and practical insights. Lay Description: What is currently known about the subject matter?: In the present information era, programming and computational thinking are important.AIGC has attracted remarkable attention from both academics and managers.If it is appropriately utilised, AIGC can facilitate education. What this paper adds: Three forms of AIGC integration based on the level of abstraction, which enhance programming learning and computational thinking.Application of extended effective use theory to propose an underlying mechanism for how AIGC integration affects learning performance and computational thinking.Concrete information on the utilisation of AIGC in the education domain.Evidence that shows the importance of interaction transparency and representational fidelity for leveraging information technologies in education. Implications of the study findings for practitioners: AIGC can be an effective tool for teachers, learners, and institutions.Platform designers and teachers should carefully design AICG integration.Platform designers and teachers could make use of various methods and other forms of AIGC integration to promote interaction transparency. [ABSTRACT FROM AUTHOR]

Background: Delivering effective feedback to large groups of students represents a challenge for the academic staff at universities. Research suggests that undergraduate students often ignore the Elaborated Feedback (EF) received via digital learning environments. This may be because instructors provide feedback in written format instead of using more engaging channels (e.g., audiovisual). Objectives: This quasi‐experimental study examines the extent to which feedback format (video vs. written) influences students' perceptions of feedback, their decision to access EF messages related to high‐stakes assignments in digital environments, and its impact on academic performance, while considering the effect of their academic engagement. Methods: A total of 171 undergraduate students received generic EF messages through a learning platform the day after submitting each course assignment. 78 students received EF in written format and 93 in video format. Results and Conclusions: Our results showed that feedback format influenced students' decision to access EF and their academic performance, but not their feedback perceptions. Students in the written‐feedback group accessed EF messages more often, but students who received video‐feedback performed better than their counterparts in the written‐feedback group. Moderation analysis showed that the relationship between the feedback format and students' academic performance was moderated by their academic engagement, suggesting that students with lower levels of academic engagement may benefit from video‐feedback. Takeaways: The results reveal that using video feedback in digital environments may influence students' decisions to process EF and their academic achievement, especially when it comes to students with lower levels of academic engagement. Lay Description: What is currently known about the subject matter: Delivering Elaborated Feedback (EF) to large groups of students represents a challenge for instructors.Undergraduate students often ignore the EF received via digital learning environments.Students usually prefer audiovisual formats to receive feedback compared to the written format.Results in regard to whether video‐feedback is best for learning are inconclusive. What this paper adds: A quasi‐experimental study to compare two feedback formats (video and written) in an ecologically valid setup.Data of students' voluntary decisions to process EF related to high‐stakes assignments.The moderating effect of students' academic engagement on the relationship between feedback format and academic performance. The implications of study findings for practitioners: Students positively value the EF received in both video and written formats.Students may not engage with EF as expected even when provided in audiovisual formats.Students may access written‐EF more frequently than video‐EF.Video‐EF may positively influence academic performance when students have low levels of academic engagement. [ABSTRACT FROM AUTHOR]

Background: Science history is a discipline that teaches the development of scientific thought and the discoveries of scientists. However, these topics can sometimes be abstract and difficult to understand. The use of technology can make the teaching of the history of science more effective, engaging, and accessible. By providing students with visual and interactive experiences, it allows them to better understand abstract concepts and closely follow the discoveries of scientists. In this way, history of science lessons can become more appealing and conducive to learning for students. Objectives: This research aims to design and develop a Mobile Augmented Reality (MAR) environment that can be used for teaching science history. Methods: The research was conducted using a design‐based research method consisting of four stages: Analysis, design, development‐implementation‐evaluation, and reporting. The research involved 10 science teachers and five secondary school students. Data were collected through focus group interviews, individual interviews, notes, audio recordings, and images, and then analysed using content analysis. Results and Conclusions: As a result of the research, a MAR application named TISAR‐3D was developed, which allows students to interactively and visually explore scientists and enrich their learning experience. Implications: The widespread use of the TISAR‐3D application in science history education is recommended, as well as the development of similar MAR applications for other topics. Lay Description: What is known about this topic: AR technology is an increasingly used technology in education.AR technology is effective in teaching the history of science.AR makes abstract concepts concrete and provides interactive experiences for students. What this paper adds: The research focuses on the development of a MAR application called TISAR‐3D.The application supports Turkish and English languages and offers voice narration.The role of scientists in the history of science is not sufficiently known.Scientists are not adequately represented in textbooks. Implications of the study findings for practitioners: Include more scientists in the app for a broader learning experience.Include more interactive activities in the app for a fun learning experience.Teachers should extend more time to accommodate the app's use in class. [ABSTRACT FROM AUTHOR]

Background: Education is often the primary arena for exploring and integrating new technologies. AI and human‐machine communication (HMC) are prevalent in the classroom, yet we are still learning how student perceptions of these tools will impact education. Objectives: We sought to understand student perceptions of credibility related to written feedback attributed to a human or an AI grader (Study One). We also investigated how corrective messages containing verbal immediacy and social support influenced student perceptions of an AI grader's credibility based on feedback in an evaluated essay (Study Two). Methods: We used an online experimental design to assess the perceived credibility of a grader. In Study One, we randomly assigned students (N = 155) to a condition that contained a paragraph they were told was evaluated by a human or an AI grader. In Study Two (N = 222), we investigated ways of increasing perceptions of an AI grader's credibility by writing messages with higher/lower levels of immediacy and social support. Results: In Study One, the students rated both the human and AI grader as credible (yet rated the AI grader lower on goodwill). The data suggest that students in Study Two attributed more goodwill (i.e., caring) to the AI grader when the feedback included more verbal immediacy. Conclusions: Our results highlight the importance of student perceptions and communication styles when integrating technology into education. The two studies imply that students viewed the human and AI graders as competent, caring, and trustworthy, specifically when feedback included more immediacy cues. Lay Description: What is currently known about this topic: An instructor's use of verbal and non‐verbal behaviours is a crucial component of establishing credibility within a student‐instructor relationship.Non‐human actors (artificial intelligence and social robots) are perceived as credible when they use appropriate verbal and non‐verbal messages.Education plays a central role in exploring and integrating new technologies, but initial impressions and perceived utility impact acceptance and adoption. What does this paper add: Students perceived both human and machine graders as credible based on measures of competence, goodwill, and trustworthiness.This is the first study that sought to alter perceptions of a machine grader's credibility by manipulating verbal and non‐verbal immediacy cues.Results suggest that a machine grader's communication style, especially verbal immediacy, would influence student engagement. Implications for practice/or policy: This study offers initial insights into using machine grading as a supplementary engagement tool.Communication style is a key factor to consider when designing courses that include automated scoring systems or AI graders. [ABSTRACT FROM AUTHOR]

Background: Despite the significant emphasis on self‐determination in special education and the crucial role of mobile learning, there is a notable absence of path modelling studies that explore the effect of self‐determination on the usage of mobile learning by students with special needs. Objectives: This study sought to investigate the intentions of mobile learning usage among students with special needs by proposing a model rooted in the technology acceptance model, complemented by extraneous constructs from self‐determination theory (competence, autonomy and relatedness). Methods: The data of the study was obtained online from 1298 special needs university students with eight different types of disabilities. Data were analysed with descriptive statistics, confirmatory factor analysis, structural equation modelling and bootstrapping. Results and Conclusions: The proposed model explained 78.4% of ease of use, 85.2% of usefulness, and 76.5% of intention. 11 of the 12 hypotheses tested within the scope of the model were supported. All hypotheses examining the impacts of self‐determination theory constructs on ease of use, usefulness, and intention were validated (8 hypotheses), with the exception of the autonomy → intention relationship. Substantial empirical evidence has been acquired to support the role of the self‐determination theory in exploring the intention toward mobile learning among university students with special needs. Concurrently, a robust theoretical framework has been introduced to the field of special education to elucidate the acceptance and utilization of technology by university students with special needs. Lay Description: What is already known about this topic: Numerous studies have demonstrated the significance of mobile tools and mobile learning in the realm of special education.Self‐determination holds immense importance in fostering independence and social engagement by empowering individuals with special needs to gain confidence, assume control and accountability for their own choices and actions.Self‐determination theory underscores the importance of providing individuals with support for three fundamental psychological needs—autonomy, competence, and relatedness—to foster healthy development. What this paper adds: To the best of the authors' knowledge, this study stands as a unique contribution within its field due to its distinctive characteristics. The model, supported by exceptionally successful outcomes and its ability to elucidate technology acceptance constructs at remarkably high levels, offers a robust theoretical framework for enabling students with special needs to engage effectively with mobile learning in both special and inclusive educational settings.Investigating how self‐determination theory enhances the explanatory power of the technology acceptance model in special education.Illuminating the significance of basic psychological needs in the adoption of mobile learning, employing advanced statistical methods with a substantial participant base, and delivering valuable insights to advance the utilization of mobile learning in special education. Implications for practice and/or policy: Special education settings should encourage students to take initiative, make choices, and exercise autonomy, and curriculum design should include opportunities for students to make choices.Making students part of the design processes and emphasizing usability through the prioritization of customizable, user‐friendly designs should be an inherent aspect of educational technology.Educators and support staff must have training and professional development opportunities to effectively use mobile learning tools and create inclusive learning environments. [ABSTRACT FROM AUTHOR]

Background: A resurgence in teaching coding in primary school classrooms has led to a pedagogical swing towards using physical computing and coding to develop students' use of algorithms, computational thinking, and problem‐solving skills. Two obstacles impede the optimal development of these objectives: the availability of a suitable pedagogy and an instructional sequencing model for primary school teachers to effectively present coding and computational thinking concepts and skills to students in alignment with their developmental stage. Objective: This study aims to address both obstacles by introducing the 3C Model, a newly developed instructional sequence grounded in established pedagogies and designed to effectively teach coding and computational thinking skills to primary school students based on their developmental stage. Methods: The qualitative study employed two data sources to triangulate findings, using: (1) semi‐structured interviews and thematic analysis to investigate 11 primary school students' perceptions of their learning experiences with the 3C Model, and (2) researcher observations along with reflections of the students' developed and demonstrated learning through the method of knowing‐in‐action, reflection‐in‐action, and reflection‐on‐action. Results and Conclusions: The findings of this study fill a gap in the existing literature by demonstrating that the pedagogical and sequential approach embedded in the 3C Model not only enhanced students' engagement levels but also resulted in improved curriculum learning outcomes. The 3C Model provides teachers with a coherent and age‐appropriate instructional structure. It uses physical computing devices and digital coding platforms to introduce coding concepts, furthering the development of computational thinking skills in primary school students beyond mere procedural and rote learning. Implications: The study holds important implications for practical applications, as it addresses an absence in the literature of an established pedagogy and instructional sequencing model for effectively teaching coding and computational thinking concepts and skills to primary school students. Drawing on established pedagogical and developmental learning theories, the 3C Model provides primary school teachers with an engaging, age‐appropriate instructional method that avoids decontextualised teaching and surface‐based learning. Instead, it encourages collaborative student work and contextualised learning, steering away from isolated and generic approaches. Lay Description: What is currently known about this topic: Teaching coding and computational thinking concepts and skills is complex due to their abstract nature.Teaching resources such as work samples, curriculum connections and tools are available to primary school teachers.There is no consensus on the most effective methods to teach these abstract concepts and skills.Primary school teachers default to applying general teaching strategies due to the lack of an age‐appropriate, specific activity sequencing model to use during coding instruction. What does this paper add: The study fills the existing gap by presenting a newly conceptualised instructional model, which considers the students' developmental stage of learning and pedagogical best practices.The study trialled the 3C Model with primary school students in a classroom setting.The study found that employing the pedagogical approach of the 3C Model increased students' engagement levels and resulted in enhanced curriculum learning outcomes. Implications for practitioners: Without an age‐appropriate instructional sequencing model students may not be grasping the underlying concepts.Simply focusing on the code without emphasising concepts such as decomposition and algorithmic thinking will result in shallow learning.Key considerations in using the 3C Model are ensuring that conceptual development occurs using physical computing devices and language students are familiar with prior to introducing coding language and its symbolic representations.Primary school teachers should consider incorporating physical interactive digital devices, physical movement, staged language development and subsequent coding procedures within the context of an engaging and authentic problem. This approach enables students to effectively grasp and represent coding and computational thinking concepts and skills, surpassing mere procedural and rote learning. [ABSTRACT FROM AUTHOR]

Background: Some studies have researched the correlation between flipped learning and cognitive learning outcomes; however, there is a paucity of research elaborating on the effects of flipped language learning on cognitive load (CL). Objectives: This study investigates the effects of using flipped learning designs (student‐led, teacher‐led and collaboration‐led) on learning outcomes and CL management during out‐of‐class activities versus during‐class activities. Methods: A mixed methods research was used to concurrently triangulate different strands of data on the effects of flipped learning designs on English as foreign language (EFL) learners' learning outcomes and CL. A total of 122 EFL learners were randomly assigned to either the control or experimental group and participated in the study. The interpretations were made based on running one‐way analysis of variance between four groups. Results and Conclusion: This study evidenced the efficacy of the interactive use of collaboration‐led flipped learning design over student‐led and teacher‐led designs for improving learning outcomes and lowering CL during computer‐assisted language learning (CALL) course. Pedagogically, CALL practitioners need to develop and integrate a well‐organized combination of student‐led and teacher‐led flipped learning activities for during‐class and out‐of‐class phases with respect to the CL and learning material complexity, while also considering the specific contexts and goals of their instructional settings. Theoretically, the results indicate the necessity of merging active learning and sociocultural theories into an instructional design to take advantage of the identified affordances of flipped language learning approach in terms of psychological effects (CL management) and learning effects (CALL outcomes). Lay Description: What is already known about this topic: The flipped language learning approach involves receiving online instruction outside the classroom and is a learner‐centered pedagogy. What this paper adds: This study contributes by triangulating different strands of data on the effects of flipped learning designs on learning outcomes and cognitive load.The findings highlight the effectiveness of collaboration‐led design for flipped language learning, facilitating engagement in both out‐of‐class and during‐class activities. Implications for practice: The findings emphasize the importance of designing and implementing instructional designs that align with emerging educational technologies.Teachers should consider the flexibility, fluency and novelty of the learning material when designing flipped learning activities. [ABSTRACT FROM AUTHOR]

Background: Investigating emotion sequence patterns in the posts of discussion forums in massive open online courses (MOOCs) holds a vital role in shaping online interactions and impacting learning achievement. While the majority of research focuses on the relationship between emotions and interactions in MOOC forum discussions, research on identifying the crucial difference in emotion sequence patterns among different interaction groups remains in its infancy. Objectives: This research utilizes deep learning and sequential pattern mining to investigate whether there are differences in emotion sequence patterns across different groups of learners who exhibit various types of interactions in online discussion forums. Methods: Data from a comprehensive array of sources, including log files, discussion texts and scores from 498 learners in online discussion forums, were collected for this study. The agglomerative hierarchical algorithm is used to classify learners into groups with different levels of interactions. Additionally, we implement and evaluate multiple deep learning models for detecting different emotions from online discussions. Relevant emotion sequence patterns were identified using sequence pattern analysis and the identified emotion sequence patterns were compared across different groups with different levels of interactions. Results and Conclusions: Using an agglomerative hierarchical algorithm, we classified learners into three distinct groups characterized by different levels of interactions: high, average and low level. Leveraging the bi‐directional long short‐term memory model for emotion detection yielded the highest predictive performance, with an impressive F‐measure of 94.01%, a recall rate of 93.83% and an accuracy score of 95.01%. The results also revealed that learners in the low‐level interaction group experienced more emotion transition from boredom to frustration than the other two groups. Therefore, the aggregation of students into groups and the utilization of their MOOC log data offer educators the capability to provide adaptive emotional feedback, customize assessments and offer more personalized attention as needed. Lay Description: What is currently known about the subject matter: Emotions are dynamic over time when learners experience cognitive disequilibrium/equilibrium.Online interactions are critical components, which influence learners' emotional state, cognitive processes and learning achievement.It is not clear what are differences in emotion sequence patterns across the groups with different interaction types. What the paper adds: An agglomerative hierarchical algorithm was implemented to cluster learners into three groups by analysing behavioural data.We explore possibilities for automated classification of emotions using deep learning approaches.Learners in the low‐level interaction group experienced more emotion transition from boredom to frustration. Implications for practitioners: A considerable amount of effort should be expended to identify and respond to learners who experience boredom and frustration emotions.Designing interventions or scaffolding to facilitate learners' interaction and promote favourable emotions.Educators could provide more personalized support based on learners' online interaction cluster. [ABSTRACT FROM AUTHOR]

Background: Science teachers' understanding of the roles of computing practices in science frame how they enact scientific computational practices in their teaching and how their students perceive the relationship between computational practices and scientific endeavours. Objectives: This critical, integrative review synthesizes teacher learning literature about the role of computational literacy and computing practices in K‐12 science teaching. Methods: We examined 54 peer‐reviewed articles and analysed the ways the researchers and teacher participants describe the affordances of integrating computational thinking (CT) and other computational practices in science. We characterize how CT and computational practices are framed in relation to scientific learning goals. We identify six primary affordances for integrating computational practices with science that are conveyed to teachers and by teachers, as represented in these studies of teacher learning. Results and Conclusions: These six perspectives include (1) learning computer science principles, (2) developing CT dispositions, (3) engagement and inclusion in science, (4) taking ownership of science, (5) supporting learning science content, and (6) participating in computational practice as a form of scientific epistemic practice. Our analysis indicates that computational thinking and computational practices are often integrated in science in order to teach something about computing (e.g., Perspective 1), rather than to support learners' scientific work. Only the 29 articles coded for the sixth perspective—that is, in service of epistemic aims in science—demonstrate commitment to students' uses of computational ideas and practices as epistemic tools to participate in the sensemaking work of science. Takeaways: Comparison of Perspectives 5 and 6 illustrates the nuance between computational practices in science that reify something students have already "figured out," rather than those that serve epistemic goals. Perspective 6 encapsulates the deep synergy among (1) the reflexive nature of computing with scientific ideas and (2) computing as a central practice in science and engineering. We contend that a more focused message of computational practices in service of scientific sensemaking goals is necessary if we expect teachers to enact CT and related computational practices in their classrooms. Lay Description: What is already known about this topic?: Science teachers' understanding of the roles of computing practices in science frame how they enact scientific computational practices in their teaching. What this paper adds?: We analysed 54 peer‐reviewed articles regarding teacher learning about the role of computational literacy and computing practices in K‐12 science teaching.We characterized the ways the researchers and teacher participants describe the affordances of integrating computational thinking (CT) and other computational practices in science.We present six primary affordances for integrating computational practices with science that are conveyed to teachers and by teachers, as represented in these studies of teacher learning. These six perspectives include (1) learning computer science principles, (2) developing CT dispositions, (3) engagement and inclusion in science, (4) taking ownership of science, (5) supporting learning science content, and (6) computational practices in service of epistemic aims in science. Implications for practice and/or policy: We find that computational thinking and computational practices are often integrated in science in order to teach introductory computer science principles, but not to support the original science learning aims.Only the 29 of 54 articles demonstrate commitment to students' uses of computational ideas and practices as epistemic tools to participate in the sensemaking work of science.We contend that a more focused message of computational practices in service of scientific sensemaking goals is necessary if we expect teachers to enact CT and related computational practices in their classrooms. [ABSTRACT FROM AUTHOR]

Background study: Computer‐assisted pronunciation training (CAPT) has emerged as an important resource for second language (L2) pronunciation learning. CAPT offers diverse opportunities for learners to master L2 pronunciation with the help of authentic learning activities in multiple contexts. Objectives: This study presents a comprehensive overview to examine the overall effect of using a computer in learning pronunciation in multiple settings and diverse educational levels with the assistance of different tools. Methods: The meta‐analysis consisted of 31 primary studies that reported results obtained from experimental vs. control group designs. These studies reported 42 effect sizes in the results. Results: The findings of the meta‐analysis indicated that using CAPT in learning pronunciation had an overall medium effect size. Similarly, the results showed that using CAPT inside the classrooms had a large effect size. The results also showed that CAPT had a large effect size when used in schools and other formal learning contexts, such as language institutes. CAPT had a medium effect when it was used in universities. The results also showed that using videos for learning pronunciation had a large effect size while other tools had a medium effect size. Conclusions: The study findings contribute to understanding the overall effect of CAPT and offer implications for educators and practitioners involved in designing effective instructional strategies for enhancing L2 pronunciation skills. Lay Description: What is already known about this topic: Computer‐Assisted Pronunciation Training has emerged as a valuable tool for L2 pronunciation learning.The variables that may affect the using of Computer‐Assisted Pronunciation Training include settings, educational level and CAPT tools. What this paper adds: The study drew on a meta‐analytic framework to examine the overall effect of using a computer in learning pronunciation in different settings and in different educational levels with the help of different tools.The meta‐analysis consisted of 31 primary studies reported results obtained from experimental vs. control group design. Implications for practice and/or policy: Language instructors are requested to incorporate CAPT in their teaching of L2 pronunciation.The integration of CAPT can be to any educational stage (i.e., schools, colleges, etc.).To optimize the benefits of CAPT, instructors should consider integrating videos, games, and other multimedia elements into their teaching practices. [ABSTRACT FROM AUTHOR]

Introduction: Media comparison studies examining the effectiveness of immersive virtual reality in education have yielded inconclusive findings, leaving the question of its impact on learning compared to conventional media unanswered. To address this issue, our study employs a novel approach that combines media comparison with an investigation on the influence of broader educational context. Methods: In the experiment, 262 students from two distinct types of lower secondary schools—comprehensive school and multi‐year gymnasium (a selective academic school)—participated. The students received a lesson on topography and contour line interpretation, using either an immersive virtual environment or a PowerPoint slideshow. A transfer test was carried out before, immediately after, and 1 month after the lesson to measure knowledge application. Results: The impact of the media (immersive virtual reality vs. PowerPoint slideshow) on learning outcomes was found to be minimal, with no clear advantage of one over the other in any experimental condition. In contrast, a significant influence on learning gains was observed due to school type. Multi‐year gymnasium students consistently outperformed comprehensive school students in the pre‐test and demonstrated greater learning gains, regardless of the learning media. Conclusion: The present study employs an innovative approach by integrating a comparative analysis of different media types with an investigation into the impact of learner characteristics. By including students from distinct types of schools, the study provides insights into the differential effects of immersive virtual reality in varied educational contexts. Lay Description: What is already known about this topic: Media comparison studies typically assess the effectiveness of immersive virtual reality as a learning medium in comparison to other instructional methods in education.The findings of these studies differ markedly.Numerous factors impact learning outcomes in an immersive virtual environment. What this paper adds: Recommendation that research in the field should explore not only if but also when and how IVR learning is effective.Evidence that learning achievements may not be affected by the medium used.Evidence that the type of school can significantly influence learning gains.Evidence that cognitive dispositions, such as spatial abilities, can be another factor that influence learning outcomes. Implications for practice: A technology‐centred approach alone does not allow for a proper evaluation of the learning gain potential of IVR, learner characteristics and broader educational context should also be taken into account.IVR as a learning medium may not be appropriate for all students and every educational setting.To ensure reliable evaluation of learning gains, it is necessary to align the content and format of the intervention in both learning mediums as closely as possible.Measuring learning gains not only immediately after the intervention but also with a significant time delay can contribute to a more comprehensive understanding. [ABSTRACT FROM AUTHOR]

Background: Peer assessment has played an important role in large‐scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop an effective automated grading model to analyse the data and predict learners' learning results. Objectives: The present study aimed to propose an automated grading model with reliability detection. Methods: A total of 109,327 instances of peer assessment from a large‐scale teacher online learning program were tested in the experiments. The reliability detection approach included three steps: recurrent convolutional neural networks (RCNN) was used to detect grade consistency, bidirectional encoder representations from transformers (BERT) was used to detect text originality, and long short‐term memory (LSTM) was used to detect grade‐text consistency. Furthermore, the automated grading was designed with the BERT‐RCNN model. Results and Conclusions: The effectiveness of the automated grading model with reliability detection was shown. For reliability detection, RCNN performed best in detecting grade consistency with an accuracy rate of 0.889, BERT performed best in detecting text originality with an improvement of 4.47% compared to the benchmark model, and LSTM performed best with an accuracy rate of 0.883. Moreover, the automated grading model with reliability detection achieved good performance, with an accuracy rate of 0.89. Compared to the absence of reliability detection, it increased by 12.1%. Implications: The results strongly suggest that the automated grading model with reliability detection for large‐scale peer assessment is effective, with the following implications: (1) The introduction of reliability detection is necessary to help filter out low reliability data in peer assessment, thus promoting effective automated grading results. (2) This solution could assist assessors in adjusting the exclusion threshold of peer assessment reliability, providing a controllable automated grading tool to reducing manual workload with high quality. (3) This solution could shift educational institutions from labour‐intensive grading procedures to a more efficient educational assessment pattern, allowing for more investment in supporting instructors and learners to improve the quality of peer feedback. Lay Description: What is already known about this topic: Peer assessment has played an important role in large‐scale online learning, as it helps promote the effectiveness of learners' online learning.Issues such as disagreement between peer assessors, rough assessment, and plagiarism in large‐scale online learning can decrease peer assessment reliabilityIncorporating extensive data into a training model may result in grading uncertainties. What this paper adds: Detecting the peer assessment reliability before grading is essential in the context of large‐scale online learning.This study aimed to propose and validate an automated grading model with reliability detection for the large‐scale online peer assessment, which will help improve the effectiveness of automated grading, combining the advantages of computer technology and human expertise. Implications for practice and/or policy: The introduction of reliability detection is necessary to help filter out low reliability data in peer assessment, thus promoting effective automated grading results.This solution could assist assessors in adjusting the exclusion threshold of peer assessment reliability, providing a controllable automated grading tool to reducing manual workload with high quality. [ABSTRACT FROM AUTHOR]