Search

In an authentic flight simulator, the instructor is traditionally located behind the learner and is thus unable to observe the pilot's visual attention (i.e. gaze behaviour). The focus of this article is visual attention in relation to pilots' professional learning in an Airbus A320 Full Flight Simulator. For this purpose, we measured and analysed pilots' visual scanning behaviour during flight simulation-based training. Eye-tracking data were collected from the participants (N = 15 pilots in training) to objectively and non-intrusively study their visual attention behaviour. First, we derived and compared the visual scanning patterns. The descriptive statistics revealed the pilots' visual scanning paths and whether they followed the expected flight protocol. Second, we developed a procedure to automate the analysis. Specifically, a Hidden Markov model (HMM) was used to automatically capture the actual phases of pilots' visual scanning. The advantage of this technique is that it is not bound to manual assessment based on graphs or descriptive data. In addition, different scanning patterns can be revealed in authentic learning situations where gaze behaviour is not known in advance. Our results illustrate that HMM can provide a complementary approach to descriptive statistics. Implications for future research are discussed, including how artificial intelligence in education could benefit from the HMM approach. [ABSTRACT FROM AUTHOR]

Emerging technologies such as augmented reality are impacting the field of education, it can be seen in the attention given to technology, specifically augmented reality. Systematic reviews on research related to learning through augmented reality aim to find gaps of augmented reality in learning. However, there is a limited number of systematic reviews that analyze current research articles that discuss learning experiences. Thus, this paper aims to analyze recent research articles on (1) the learning experience of augmented reality, (2) the usability of the applied method, (3) issues, and (4) the challenges of learning through augmented reality. Forty-eight articles in the recent five years, from 2018 to 2022, were selected, based on the designed query and PRISMA method. All articles were analyzed and the results show that the System Usability Scale (SUS) is the most popular usability questionnaire and qualitative method to evaluate learning experience. This scale was used in almost 70% of the research articles selected for this review. Several constructs to evaluate learning experience were identified including satisfaction, learning efficiency, assessment, and engagement. The limitations and challenges are summarized into three categories: respondent, data collection, and technical issues. [ABSTRACT FROM AUTHOR]

We designed a microbial science popularization product based on virtual reality technology, "Micro World – Exploring the Microbial Kingdom," and conducted usability tests. Participants used head-mounted VR glasses to experience virtual scenarios teaching microbiological knowledge. The product's user experience was evaluated through a User Experience Questionnaire (UEQ), and the results showed that our product provided both usefulness and enjoyment. In addition, the quality of participants' relevant knowledge acquisition was measured using the Student Education of Educational Quality (SEEQ). The SEEQ results show that "Micro World" is an effective tool for popularizing microbiology science and can actively promote students' independent learning and improve learning quality. [ABSTRACT FROM AUTHOR]

Although research has touted the value of making in educational settings, scant work has been done in formal school contexts utilizing quantitative methods. This could be attributed to the various challenges in integrating making in school settings. To fill in the gap, this study presents an approach to integrate making into science classes at the 3rd to 5th grade levels in a U.S. public school for four consecutive years (2015–2019). We examined the effect of the program on students' self-beliefs (self-efficacy, motivation, and self-concept) using a longitudinal quasi-experimental design. We also examined the effect of making on students' knowledge and skills using state testing data. Results suggest that when averaged across post school year surveys, students in maker classes (vs. control) reported higher self-efficacy beliefs in science and making as well as more interests in STEM-related careers. Moreover, over two school years, we observed that students in the control group experienced declines on some of our variables while our maker students did not. Data thereby speaks to the potential value and promise of integrating making into formal school settings. Practical implications are discussed. [ABSTRACT FROM AUTHOR]

The research aims to investigate the impact of augmented reality (AR) technologies developed within the framework of primary school students' on student achievement, attitudes towards the course, attitudes towards technology, and participation in classroom activities. The contents of AR-based learning materials have been developed by 4th-grade teachers and writers within the context of the existing curriculum. The study process was carried out based on the instructional design model. The research was performed in conjunction with the quasi-experimental design among the experimental designs of quantitative research methods. Using the cluster random sampling method, students in the experimental and control groups were selected among 11 primary schools. The findings indicate that contrary to the students in the control group, the students in the experimental group had higher academic achievement and participation in classroom activities, and also their attitudes to the course and applied technology were more positive. Moreover, concerning the experimental group students, a positive and significant correlation between their academic achievements, attitudes towards the course, attitudes towards technology, and their participation and participation in classroom activities have been observed. [ABSTRACT FROM AUTHOR]

Background: TPACK is a widely used framework for assessing teachers' competence in integrating technology in education. However, previous studies have shown varying interpretations of the relationship between TPACK elements. Qualitative studies that assess the manifestations of TPACK by examining the practices of pre‐service teachers are rare. Objectives: This study investigates technology integration in innovative physics teaching and learning materials designed by pre‐service teachers and the manifestation of technological pedagogical content knowledge (TPACK) in empirical cases. Methods: We qualitatively extracted the components of PCK, TPK, and TCK from the innovative physics teaching and learning materials developed by 22 pre‐service teachers in their fourth year at a teachers' college in South Korea. We scored them based on the new evaluation criteria established in this study. Results and Conclusions: Based on the materials, we identified three types of technology integration: Learning Materials Providing, Learning Activity Providing, and Virtual Experiments Creating. This study identifies teachers' level of TK and integrates it with TPACK expression. Results confirm the connection between TK and TCK and show that a strong PCK can serve as a basis for TPK. The TPACK expression pattern can help achieve balanced development of TPACK in teacher education. Lay Description: What is currently known about the subject matter: TPACK framework combines pedagogical, content, and technological knowledge in teachers' professional expertise.Despite TPACK's widespread use, studies showed varied interpretations of the relationships between its elements.TPACK measurement often relies on self‐assessment, lacking a total reflection of technology use in teaching.Few qualitative studies explore TPACK manifestations through pre‐service teachers' practices. What the paper adds to the currently known about: There are three types of technology integration: Learning Materials Providing, Learning Activity Providing, and Virtual Experiments Creating.The study found that pre‐service teachers in the virtual experiments creating type exhibit strong subject‐specific TPACK.In physics education, TK is essential and can be divided into the use of ICT and programming.The study correlates TK levels with TPACK expressions, resulting in five patterns based on PCK, TPK, TCK, and TK. The implications of study findings for practitioners: The study presents empirical evidence of TPACK manifestation in pre‐service physics teachers, focusing on TK.High programming TK has a significant impact on subject‐specific TPACK.The study confirms the TK‐TCK connection and highlights PCK's role in TPK.TPACK patterns can guide teacher education, fostering balanced development. [ABSTRACT FROM AUTHOR]

Studies have suggested that virtual reality (VR) as an ‘empathy-making machine’ has the potential to trigger historical empathy. Different VR technologies offer different levels of immersion with different educational implications. Higher immersive VR technology has shown promise in enhancing learners’ empathy levels. However, how highly immersive VR promotes learners’ historical empathy in real-life classroom settings has not been explored. Hence, this study focuses on comparing two levels of immersive VR-supported learning for historical empathy acquisition among secondary learners. A total of 49 students were recruited. A quasi-experimental design was employed and the quantitative and qualitative data were analyzed to explore participants’ historical knowledge and empathy. The quantitative data show no significant difference between immersive virtual reality (IVR) approach-supported learning and flatscreen VR-supported learning. However, the qualitative analysis suggests that the students from the IVR group showed stronger ‘physical empathy’. Intriguingly, even though the tests did not demonstrate that the students learned more in IVR-supported learning, they self-reported that they learned better in IVR-supported learning. The paper identifies implications for the connection between ‘physical empathy’ and the level of immersive technology.

In recent times, science education has turned its attention toward computational modeling (CM). While there exists a substantial body of research on CM case design and practical applications, a notable gap exists in systematic reviews of these studies. Although systematic reviews of computational thinking in science classrooms exist, they diverge from the definition of CM, often omitting pertinent articles. This study adhered to the standardized process of systematic literature review, selecting Web of Science (WOS) and Scopus as the databases. It established search keywords and criteria for the inclusion and exclusion of literature. After multiple rounds of screening, this study ultimately obtained 70 works related to CM. For the results, this study begins with an analysis of publication distribution, research popularity trends, research types, and methodologies. Subsequently, it delves into participant profiles, encompassing their geographical distribution, educational levels, and sample sizes. Furthermore, it scrutinizes case types, modeling tools, and the fundamental functionalities within case design. Lastly, it explores the scientific disciplines and student competencies that researchers prioritize in CM’s practical application, along with the evaluation methods, collected data, and core empirical findings. The findings of this study offer valuable insights for future research directions, catalyzing deeper exploration within the field. [ABSTRACT FROM AUTHOR]

Families with disabled children in the Kingdom of Saudi Arabia (KSA) face unique challenges that impact their quality of life (QoL). Saudi Vision 2030 aims to empower all citizens, including those with disabilities. This research is a review that explores how the Semantic Web (SW), a technology enabling intelligent data interoperability, can be utilized to enhance the QoL for families with disabled children within the framework of Vision 2030. Two instruments were developed and administered by the researcher for data collection in addition to a review of the literature and related studies. First, needs assessment open interviews aimed to analyze the challenges and needs of the Saudi family caregivers. Second, an SW-QoL questionnaire was conducted to explore the key features and functionalities of SW that could fulfill those needs and improve the caregivers’ QoL accordingly within the context of Saudi Vision 2030. The findings of the study propose that SW has got the promising potentials, if applied, to improve the QoL among Saudi family caregivers of disabled children. The study pinpoints that SW’s ability to empower families, improve resource access, and promote social inclusion directly aligns with Saudi Vision 2030’s vision for a more inclusive and equitable society. Applying SW applications in QoL programs remains a suggested area of experimentation in KSA as this research is a call to action. To improve the QoL among Saudi family caregivers of disabled children, further research is recommended to examine the SW functions on the improvement of their QoL. The SW power of linked data could be designed for promoting powerful informed decision-making, as well as SW reasoning engines could be developed for personalizing resources among family caregivers. In addition, SW virtual communities of practice could be built for enhancing resource sharing and social inclusion among those families. Studies are also needed in alignment with the aspirations of KSA Vision 2030 for determining the effect of the information accessibility function of SW on enhancing caregiver families’ access to the target information and support services. Above all, the impact of coordinated care via SW could be investigated to reduce the administrative burdens among caregiver families via data connection from different government agencies. [ABSTRACT FROM AUTHOR]

Writing proficiency is an essential skill for upper secondary students that can be enhanced through effective feedback. Creating feedback on writing tasks, however, is time-intensive and presents a challenge for educators, often resulting in students receiving insufficient or no feedback. The advent of text-generating large language models (LLMs) offers a promising solution, namely, automated evidence-based feedback generation. Yet, empirical evidence from randomized controlled studies about the effectiveness of LLM-generated feedback is missing. To address this issue, the current study compared the effectiveness of LLM-generated feedback to no feedback. A sample of N = 459 upper secondary students of English as a foreign language wrote an argumentative essay. Students in the experimental group were asked to revise their text according to feedback that was generated using the LLM GPT-3.5-turbo. The control group revised their essays without receiving feedback. We assessed improvement in the revision using automated essay scoring. The results showed that LLM-generated feedback increased revision performance (d = .19) and task motivation (d = 0.36). Moreover, it increased positive emotions (d = 0.34) compared to revising without feedback. The findings highlight that using LLMs allows to create timely feedback that can positively relate to students’ cognitive and affective-motivational outcomes. Future perspectives and the implications for research and practice of using LLM-generated feedback in intelligent tutoring systems are discussed.

Previous studies reported that acquiring computer programming skills is challenging and might result in high dropout rates. A quasi-experimental design was used to examine the role of different factors in dropping out of an e-based computer programming course. This study applied a knowledge in programming assessment test (20 multiple-choice questions covering the following topics: variables, loops, conditionals, functions, and general knowledge of Python), The Learning Motivating Factors Questionnaire, The Big Five-2, and The Basic Psychological Need Satisfaction & Frustration Scale. Ninety-four participants (38 males and 56 females) completed the course, while 305 participants started it. The mean age of e-learners was 29.96 years (SD 8.27), age range = 18 to 54. The results showed that e-learners who completed the course had higher initial knowledge assessment scores than those who dropped out after the first assessment. Reward and recognition as a motivator were significantly higher in males who completed the course than those who dropped out after the second knowledge assessment. Extraversion was significantly lower in females who completed the course than those who dropped after the first or second knowledge assessment test. Relatedness frustration was significantly higher in those who dropped out after the first knowledge assessment. Due to significant limitations of the sample size, cultural context, measures applied, and research design, the findings would preferably be regarded with caution.

Digital media are widely used among Higher Education (HE) students; however, it is not clear yet how students from different disciplines apply learning technology. When differences in technology use were found among disciplines, they were identified broadly, for example, between soft and hard sciences, that is, social sciences/humanities vs. natural sciences. Beyond this, disciplines may also differ according to their traditions, norms and values that form their discipline-specific cultures. Thus, based on the theoretical perspectives of social cognitive theory and organisational culture, this present study aimed to examine students’ technology use in different HE disciplines. In a multilevel analysis, data from four German universities were analyzed, including more than 1,200 students from 105 disciplines. The findings suggest that students in different disciplines vary substantially in their average use of study-related technology. Furthermore, on the individual level, study-related technology use depends on individual factors, e.g., perceived usefulness. This present study's results contribute to further extending our knowledge about student technology use in HE. Above all, the conceptual and methodical models can serve as a theoretical and empirical basis for future studies. To analyze disciplinary differences, the study shows that a rough classification, for example hard versus soft disciplines, is not sufficient. Instead, the different disciplines need to be distinguished.

The aim of this study is to use augmented reality and hands-on activity with phonics cubes to create an augmented reality English learning system named the Rolling Alphabet-AR System to investigate its impact on English learning, flow experience, and English self-efficacy for sixth graders. This study adopted quasi-experimental research on 114 sixth graders from Taiwan, which comprised experimental and control groups. The experimental group used the Rolling Alphabet-AR System to learn, and the control group used flash cards and picture cards. Before and after the experiments, these two groups took the Phonics vocabulary, flow experience, and English self-efficacy scales as pre- and posttests. The study was conducted 7 times in 7 weeks for a total of 280 minutes. The pre- and posttest results were analysed by independent sample t tests in SPSS 20.0. Using the Rolling Alphabet-AR System in English learning positively impacts English learning effectiveness and flow experience for sixth graders. This study combined AR learning with manual operations to prove that this combination can effectively improve students' English learning results. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the effect of augmented reality (AR) using a 3D app in a smartphone on students' learning outcomes and satisfaction in teaching angle measurement error to vocational high school students with different spatial ability. A quasi-experimental pretest/posttest was employed. There were 197 students from three vocational high schools in the southern, northern, and eastern part of Taiwan participated in this study. To minimize the biased result, we established one control group and one experimental group in each school. The experimental group used multimedia teaching tools and AR technology as a supplement, while the control group was taught by multimedia teaching tools only. We assessed some factors that possibly affect the learning outcomes and learning satisfaction, including different spatial abilities and different digital materials as teaching tools. Our finding highlights that different teaching materials influence students' learning outcomes and satisfaction, whereas spatial ability does not affect. Further discussion and implementation are also identified in this study. [ABSTRACT FROM AUTHOR]

Around the world, the number of English speakers and the significance of the English language are constantly increasing. Among various technology-supported instructional styles, Mobile Learning (M-Learning) has been recognized as a promising approach to enhance students' competencies and skills in the English language. By examining previous literature, a number of reviews have been performed to investigate the role of M-learning in the English language. However, none of these studies has highlighted the trends, opportunities, and challenges identified in the most cited articles that focused solely on the English language. Therefore, to address these limitations, this study performed a review of the top 100 most cited articles, published between 2007 and 2020, indexed by the Web of Science, and addressing the English language only. The results revealed that most research in Mobile English Language Learning (M-ELL) followed an experimental design and employed a single mobile learning implementation. Additionally, the current study identified a number of research areas that require additional research attention. For example, further research is needed among students learning from home, more qualitative research is needed, and additional research is required to improve students' higher-order thinking skills. The outcomes of this study provide a reference to researchers and educators who intend to use mobile technologies in the area of language education, especially in the context of the English language. [ABSTRACT FROM AUTHOR]

With the continuous progress of society, tests, and exams appear more and more frequently in people's lives. Faced with the ever-increasing demand for test papers, efficient test paper generation algorithms have become more important. In this paper, we improved and proposed a Diseased Enhanced Genetic Algorithm (DEGA) based on the Genetic Algorithm (GA), and applied it to the test paper generation algorithm. I the crossover operator, the crossover probability that will change in different situations of the population is adopted. According to the characteristics of the test paper generation algorithm, we use the method based on the hamming distance to calculate the distance between individuals in the population. Aiming at the shortcoming that the mutation operator is too random, we designed and used a disease operator that includes three modules: natural disease, infection, and mutation. It effectively guarantees the distance between individuals in the population and improves the shortcoming that GA is easy to fall into a locally optimal solution. Finally, using the College English Test Band 4 (CET-4) questions from 2014 to 2021 as the data set, comparative experiments were carried out on the test paper generation algorithm based on Random Sampling Algorithm (RSA), GA, Enhanced Genetic Algorithm (EGA) and DEGA. The results show that when using the test paper generation algorithm based on DEGA, the generation of test papers is faster, the number of iterations is less, and the algorithm results are significantly better than other algorithms.

The recent pandemic brought on considerable changes in terms of learning activities, which were moved from in-person classroom-based lessons to virtual work performed at home in most world regions. One of the most considerable challenges faced by educators was keeping students motivated toward learning activities. Interactive learning environments in general, and augmented reality (AR)-based learning environments in particular, are thought to foster emotional and cognitive engagement when used in the classroom. This study aims to compare the motivation and learning outcomes of middle school students in two educational settings: in the classroom and at home. The study involved 55 middle school students using the AR application to practice basic chemistry concepts. The results suggested that students' general motivation towards the activity was similar in both settings. However, students who worked at home reported better satisfaction and attention levels compared with those who worked in the classroom. Additionally, students who worked at home made fewer mistakes and achieved better grades compared with those who worked in the classroom. Overall, the study suggests that AR can be exploited as an effective learning environment for learning the basic principles of chemistry in home settings. [ABSTRACT FROM AUTHOR]

Writing an English research article for novice English as an additional language (EAL) writers is a challenging task that requires experience and training at both the sentence and meaning levels. One strategy that EAL writers employ when writing a research article is the use of formulaic sequences (FSs). However, available FS corpora are general purpose and are very limited in size. Previous studies have reported the effectiveness of FS usage in writing using a small set of FSs. The present work proposes an assistive environment for academic writing improvement through the use of domain-specific FSs. FSs are extracted from published articles and are classified under rhetoric categories using a machine learning technique. The user can then search for and add new FSs of his/her choice from any research article using proposed prototypes. The effectiveness of the proposed approach was evaluated in a real environment. The results show a positive impact of the proposal in terms of academic writing improvement. Novice writers who worked with the proposed prototype reported a significantly higher degree of perceived usefulness than those who worked with the traditional phrasebank approach. [ABSTRACT FROM AUTHOR]

In the age of generative AI, can teaching videos be efficiently and effectively generated by large language models? In this study, the authors used generative AI tools to develop four short teaching videos for a management course and then compared them with human-generated videos on the same subjects in an online experiment. In an across-subject experimental design, 447 participants completed two treatment conditions presenting different mixes of AI-generated and human-made videos. The participants were asked to rate their learning experiences after each video and had their learning outcomes tested in a multiple-choice exam at the end of the session (N = 1788 video treatments). The findings show that human-generated videos provided a statistically significant but small advantage to participants in terms of learning experience, indicating that the participants still prefer to be taught by human teachers. However, a comparison of exam results between the experimental groups implies that the participants eventually acquired knowledge about the content to a similar degree. Given these findings and the ease with which AI-generated teaching videos can be created, this study concludes that AI-generated teaching videos will likely proliferate. • This study compares the learning effects of AI-generated versus human-made teaching videos. • In an online experiment, 447 participants watched four teaching videos, filled out a survey, and took an exam. • Participants prefer human-made teaching videos in terms of learning experience. • When watching AI-generated videos, participants achieved equally high learning outcomes. • Teaching videos can quickly be made using generative AI tools and can be expected to proliferate. [ABSTRACT FROM AUTHOR]

Using computational methods to produce and interpret multiple scientific representations is now a common practice in many science disciplines. Research has shown students have difficulty in moving across, connecting, and sensemaking from multiple representations. There is a need to develop task-specific representational competencies for students to reason and conduct scientific investigations using multiple representations. In this study, we focus on three representational competencies: 1) linking between representations, 2) disciplinary sensemaking from multiple representations, and 3) conceptualizing domain-relevant content derived from multiple representations. We developed a block code-based computational modeling environment with three different representations and embedded it within an online activity for students to carry out investigations around the earthquake cycle. The three representations include a procedural representation of block codes, a geometric representation of land deformation build-up, and a graphical representation of deformation build-up over time. We examined the extent of students' representational competencies and which competencies are most correlated with students' future performance in a computationally supported geoscience investigation. Results indicate that a majority of the 431 students showed at least some form of representational competence. However, a relatively small number of students showed sophisticated levels of linking, sensemaking, and conceptualizing from the representations. Five of seven representational competencies, the most prominent being code sensemaking (η2 = 0.053, p < 0.001), were significantly correlated to student performance on a summative geoscience investigation. • Representational competencies (RCs) enable students to build domain knowledge. • Students developed knowledge of the earthquake cycle using the three representations. • Students can link, make sense of, and understand dynamically-linked representations. • RCs are significant indicators of performance on real-world investigation tasks. [ABSTRACT FROM AUTHOR]

The internet provides up-to-date, multi-dimensional and spatial information on geographical conflicts worldwide. Internet searches can therefore be used in geography education for students to learn about geographical conflicts and to form their own opinions on them. However, previous research indicates that students lack competences in searching and evaluating digital information on geographical conflicts and also in processing the information found argumentatively. Therefore, we developed a digital learning unit, available as Open Educational Resource, to train upper secondary and university students in targeted strategies for conducting internet searches on geographical conflicts and developing subsequent argumentations. In this study, we investigated whether geographic internet searches and argumentation skills can be promoted using the learning unit. For this purpose, we analysed the work products of 39 students that they produced within the learning unit, consisting of an internet search on a geographical conflict and a subsequent argumentation. In addition, the students evaluated the learning unit using digitally provided questionnaires. A comparison of the students’ work results with previous research shows that the learning unit does not seem to affect the amount of information students find on the internet, but students seemed to engage more intensively with the information found. Using the information from the internet, students were able to create multi-perspective argumentations in which they could defend their opinions with justifications, counter-arguments and rebuttals. The results of our study thus show that internet searches on geographical conflicts and the development of subsequent argumentation can be promoted with the digital learning unit.

Although a large variety of methodologies, contexts and perspectives have been used to examine educational application of technology, there is a paucity of instruments that are designed to comprehensively evaluate the use of technology in education. This paper presents a Confirmatory Factor Analysis (CFA) of an instrument that incorporates eight key dimensions: learning, affective, behavioral, technology, design, pedagogy, presence/community, and institutional environment. These dimensions were derived from rigorous systematic literature review and field specialist validation processes. The model was then refined and empirically confirmed in this study by 1,352 participants undertaking a Coursera open online course. The results of applying the instrument, as well as qualitative feedback from participants, are shared to illustrate its breadth and utility. The final 28 item "Comprehensive Evaluation of Use of Technology in Education" instrument is provided in full to support consistent, holistic and robust evaluation and comparison of technology use across educational contexts. [ABSTRACT FROM AUTHOR]

In the field of environmental education, it is crucial to obtain a profound understanding of students' learning about ecosystem concepts, particularly with regard to the intricate processes of material cycling. Material cycling involves the movement and transformation of elements and compounds within ecosystems and serves as a cornerstone for effective instructional techniques aimed at improving learning outcomes. This study examines the synergistic potential of merging inquiry-based instruction with information literacy within the context of the "mini ecosystem" theme to increase seventh-grade students' comprehension of ecosystem concepts, material cycling, modeling design, and visual literacy. Utilizing a quasiexperimental design, the student cohort was divided into an experimental group that was exposed to inquiry-based instruction and information literacy and a control group that utilized integrated audiovisual media. Assessment tools included standardized tests, open-ended inquiries, design drawings, and evaluations of visual literacy. This study sheds light on students' comprehension of concepts related to ecosystems and material cycling and highlights the effectiveness of integrating inquiry-based instruction and information literacy. Notably, the experimental group surpassed the control group in several aspects, including understanding and higher-order thinking of ecosystem concepts, overall model design with material selection, and overall visual literacy, including aesthetic techniques and creative imagination. However, no significant differences were found in conceptual design or material cycling of model design or in theme composition in visual literacy. In both groups, students with higher pretest scores did not exhibit improvement in the understanding of ecosystem concepts. Despite the identified limitations, the results underscore the potential benefits of each individual component (i.e., inquiry-based instruction and information literacy) as well as their combined synergistic effect in bolstering students' grasp of ecosystem concepts. The study concludes by discussing its limitations and providing suggestions for future research. • Examine impact of integrating 5E inquiry with information literacy into ecosystem understanding. • Analyze grasp of ecosystem and material cycling, modeling design, and visual literacy. • Experimental group outperformed control group in various ecosystem concepts. • Low-scoring students notably improve in the ecosystem and material cycling concepts. [ABSTRACT FROM AUTHOR]

In the Massive Online Open Course (MOOC) forum, learning engagement encompasses three fundamental dimensions—cognitive, emotional, and behavioral engagement—that intricately interact to jointly influence students' learning achievements. However, the interplay between multiple engagement dimensions and their correlations with learning achievement remain understudied, particularly across different academic disciplines. This study adopts an automated configurational approach that integrates bidirectional encoder representation from transformers (BERT) and fuzzy set qualitative comparative analysis (fsQCA) to explore the configurations of learning engagement, their connections with learning achievement, and variations across disciplines. Our analysis reveals a nuanced profile of learners' learning engagement, indicating the high-achieving individuals demonstrated more frequent posting and commenting behaviors and the high-level cognitive engagement than low-achieving individuals. Second, our analysis revealed multiple configurations where the coexistence or absence of factors at different levels of the cognitive, behavioral, and emotional dimensions significantly impacted learning achievement. Learners who conducted posting and replying behaviors, expressed positive emotions, and engaged in deep cognitive engagement tended to achieve superior learning outcomes. Third, there were significant differences in behavioral and emotional engagement among learners across different academic disciplines. Specifically, pure discipline learners were more inclined to engage in postin g behaviors than the applied discipline learners. Across academic disciplines, positive emotions correlated strongly with higher achievement. These findings deepen our understanding of the multifaceted characteristics of learning engagement in MOOCs and highlight the importance of disciplinary distinctions, providing a foundation for educators and designers to optimize learners' MOOC effects and tailor learning experiences in diverse disciplinary contexts. • Using automated configurational approach for analyzing learning engagement. • Building multiple configurations of learning engagement to identify achievement. • Revealing differences in configurations of learning engagement between disciplines. • Replying behavior, positive emotion and higher-order cognition linked to higher achievement. • Revealing behavioral differences between pure and applied subject learners. [ABSTRACT FROM AUTHOR]

The main drive for this study is to look into potential predictors of educational achievement using OECD's original Pisa 2018 dataset. This paper explores (i) access to ICT, (ii) physical characteristics of learning environment at school, (iii) quality of teaching staff and educational material, (iv) student characteristics and learning climate, and (v) political and economic structure of the country as potential true predictors of academic achievement. Our sample covers 41 countries and data used in our analysis are collected from 282,461 students distributed in 9,317 schools worldwide. Multiple linear regressions are developed and analyzed using stepwise estimation techniques. The results indicate that (i) availability of internet connection and enjoyable pastime activity at home have positive impacts on student's success, (ii) a strong correlation exists between high test scores and student characteristics & learning climate, i.e. students' sense of belonging at school, students' fear of failure and disciplinary climate, (iii) there is a negative relationship between academic performance and teacher enthusiasm & support, (iv) student success is negatively correlated with income level and political and economic freedoms but positively associated with economic competitiveness of a country, and (v) the students in lightly populated classes are more successful than those in overloaded ones and inadequate or poor educational material deteriorates educational outcomes. [ABSTRACT FROM AUTHOR]

Augmented reality (AR)-based learning environments are argued to foster cognitive and emotional involvement. Immersion has been identified as one of the driving forces that promote learning in technology-based learning environments. This study evaluated the learning effectiveness and immersion appeal of an AR-marker-based learning activity targeted at practicing basic chemistry concepts. Data were collected from a cohort of 124 middle school students in Mexico and analyzed using pretest–posttest comparisons and cluster analysis. The results suggest that students with higher immersive learning profiles achieve better learning outcomes compared with those with lower immersive profiles. [ABSTRACT FROM AUTHOR]

This study aims to integrate video games into classrooms not as a replacement for regular lessons but as supplementary materials under the teacher's supervision. To this extent, the researcher created an educational English learning video game specifically modeled on the students' real lives. Ninety-six middle school students, 48 in the control group and 48 in the experimental group, participated in the study. While follow-up activities were used in the control group and the regular classroom teaching, students in the experimental group played the educational game under the teacher's supervision with no follow-up activities. Pre, post, and retention achievement tests were applied to the students. Semi-structured interviews were also conducted with 18 students from the experimental group. The results showed that the experimental group's vocabulary learning and retention were significantly higher than the control group. Also, the views of the students on English lessons and games based on their lives were promising. By considering the achievement test and students' views on the game developed, it can be said that the game in the study includes educational features as well as the basic features of the games. [ABSTRACT FROM AUTHOR]

The recent pandemic brought on considerable changes in terms of learning activities, which were moved from in-person classroom-based lessons to virtual work performed at home in most world regions. One of the most considerable challenges faced by educators was keeping students motivated toward learning activities. Interactive learning environments in general, and augmented reality (AR)-based learning environments in particular, are thought to foster emotional and cognitive engagement when used in the classroom. This study aims to compare the motivation and learning outcomes of middle school students in two educational settings: in the classroom and at home. The study involved 55 middle school students using the AR application to practice basic chemistry concepts. The results suggested that students’ general motivation towards the activity was similar in both settings. However, students who worked at home reported better satisfaction and attention levels compared with those who worked in the classroom. Additionally, students who worked at home made fewer mistakes and achieved better grades compared with those who worked in the classroom. Overall, the study suggests that AR can be exploited as an effective learning environment for learning the basic principles of chemistry in home settings.

Educators seek to develop accurate and timely prediction models to forecast student retention and attrition. Although prior studies have generated single point estimates to quantify predictive efficacy, much less education research has examined variability in student performance predictions using nonparametric bootstrap algorithms in data pipelines. In this study, bootstrapping was applied to examine performance variability among five data mining methods (DMMs) and four filter preprocessing feature selection techniques for forecasting course grades for 3225 students enrolled in an undergraduate biology class. While the median area under the curve (AUC) values obtained from bootstrapping were significantly lower than the AUC point estimates obtained without resampling, DMMs and feature selection techniques impacted variability in different ways. The ensemble technique elastic net regression (GLMNET) significantly outperformed all other DMMs and exhibited the least amount of variability in the AUC. However, all filter feature selection techniques significantly increased variability in student success predictions, compared to when this step was omitted from the data pipeline. We discuss the potential benefits and drawbacks of incorporating bootstrapping into prediction pipelines to track, monitor, and forecast classroom performance, as well as highlight the risks of only examining point estimates.

This study explores the pedagogical use of adaptive learning to foster learner-content interaction, and its subsequent impact on student performance in a large first year Macroeconomics course in an Irish University. To increase student-content interaction, an adaptive learning tool (LearnSmart) is employed to create five weekly adaptive reading assignments, over a six-week period. We include two separate indicators of learner-content interaction (the amount of time spent and number of completed adaptive assignments) in our analysis. Results indicate that student performance is enhanced by the number of completed adaptive assignments, which captures learner-content interaction and adaptive learning. However, the amount of time spent studying was negatively associated with performance. This surprising result comes as a novel contribution, which extends our knowledge of how adaptive learning technology can be potentially used to drive learner-content interaction and student performance. Pedagogically, our findings suggest the need for more intentional design and personalisation of learning activities to enhance student-content interaction and subsequent performance. • Adaptive learning enhances learner-content interaction and performance. • The number of completed adaptive assignments increases student performance. • The amount of time spent studying is negatively associated with performance. • A certain time investment is required to realise benefits from adaptive learning. [ABSTRACT FROM AUTHOR]

Numerous computer-based collaborative learning environments have been developed to support collaborative problem-solving. Yet, understanding the complexity and dynamic nature of the collaboration process remains a challenge. This is particularly true in open-ended immersive learning environments, where students navigate both physical and virtual spaces, pursuing diverse paths to solve problems. In response, we aimed to unpack these complex collaborative learning processes by investigating 16 groups of college students (n = 77) who utilized an immersive astronomy simulation in their introductory astronomy course. Our specific focus is on joint attention as a multi-level indicator to index collaboration. To examine the interplay between joint attention and other multimodal traces (conceptual discussions and gestures) in students' interactions with peers and the simulation, we employed a multi-granular approach. This approach encompasses macro-level correlations, meso-level network trends, and micro-level qualitative insights from vignettes to capture nuances at different levels. Distinct multimodal engagement patterns emerged between low- and high-achieving groups, evolving over time across a series of tasks. Our findings contribute to the understanding of the notion of timely joint attention and emphasize the importance of individual exploration during the early stages of collaborative problem-solving, demonstrating its contribution to productive knowledge co-construction. This research overall provides valuable insights into the complexities of collaboration dynamics within and beyond digital space. The empirical evidence we present in our study lays a strong foundation for developing instructional designs aimed at fostering productive collaboration in immersive learning environments. • Capturing joint attention dynamics through multimodal engagement using ONA. • Attention coordination behavior differences between students with varying performance. • Role of timely joint attention engagement during critical moments in CPS processes. • Analyzing data at various temporal granularities for unique insights. • Highlighting the interpretative loop for a deeper comprehension of joint attention. [ABSTRACT FROM AUTHOR]

Augmented reality (AR)-based learning environments are argued to foster cognitive and emotional involvement. Immersion has been identified as one of the driving forces that promote learning in technology-based learning environments. This study evaluated the learning effectiveness and immersion appeal of an AR-marker-based learning activity targeted at practicing basic chemistry concepts. Data were collected from a cohort of 124 middle school students in Mexico and analyzed using pretest–posttest comparisons and cluster analysis. The results suggest that students with higher immersive learning profiles achieve better learning outcomes compared with those with lower immersive profiles.

Exergaming enables players to engage in real-life games and sports by allowing them to move from one place to another. To investigate the effects of students' performance of sit-up exercises during an exergame, this study utilized the Fit-Fun exergame. In this game, the agent (a rabbit) is triggered to jump every time it receives a signal from the sensory detector embedded in the exercise belt. The game also enables players to compete against each other by performing sit-up exercises. This study focused on the relationship between emotions and performance in the exergame. It examined the connections between beliefs about exercise health, gameplay interest, competition anxiety, practicing attitude, and exergaming performance. Elementary school students aged 11–12 years old participated in this single-group quasi-experimental study. A total of 228 valid questionnaires were collected over a period of 6 weeks during a series of 6 practice sessions. The research hypotheses were tested using structural equation modeling. The results revealed that exercise health belief was positively correlated with gameplay interest, but negatively correlated with competition anxiety. Additionally, practicing attitude was found to have a positive association with exergaming performance. Based on these findings, it is suggested that teachers can incorporate this exergame into synchronized competitions to motivate students to maintain their exercise routine by competing with their friends. [ABSTRACT FROM AUTHOR]

Existing studies on MOOCs examine learners' engagement processes but have not explored links between them and motivations to enroll. In our previous work, we identified three motivation groups in a MOOC for educators: intrinsic, professional, and prosocial. In the current study, we used process mining to compare the course engagement patterns of these three groups. We found that throughout the course, the intrinsic group was the most engaged, but the prosocial group became the most engaged by the end of the course. We also identified rarely visited pages and page sequences that do not follow the intended course structure. Our findings enhance existing research on motivation and engagement in MOOCs by showing how motivation relates to fine-grained engagement metrics. They suggest that MOOC developers may want to consider why some groups are less engaged and why some pages appear less engaging and change the course structure accordingly. • We explored the engagement patterns of learners in a massive open online course • Learners with intrinsic, professional, and prosocial motivations were compared • Intrinsic motivation was associated with higher engagement overall • Prosocial learners were more engaged at the end of the course • We identified sequences of page visits that do not follow the intended structure [ABSTRACT FROM AUTHOR]

In today's digital age, incorporating technology in teaching has become increasingly important. To prepare future teachers, understanding the factors that influence the development of teachers' corresponding knowledge base is crucial. However, not only is there a small number of studies investigating the development of pre-service teachers' professional knowledge, but these studies also predominantly rely on cross-sectional and/or self-reported data. This pre-post study investigated the factors associated with the development of digital media Pedagogical Content Knowledge (PCK) in physics teacher education through a seminar-based approach with N = 66 pre-service teachers (PSTs). Investigated factors include PSTs' PCK about students' conceptions (PCK-SC), general motivation to use digital media, interest in digital media, and previous experience with digital media. The findings suggest that a strong foundation in various aspects of PCK is essential for the development of digital media PCK, as PSTs' PCK-SC has proven to be a positive predictor for the development of PTSs' digital media PCK. Surprisingly, the study found that higher motivation to use digital media negatively affects the development of digital media PCK, suggesting that excessive motivation may hinder the acquisition of digital media PCK. Additionally, the study found that PSTs' interest in digital media positively influenced the development of digital media PCK, while previous experience with digital media had a negative impact on its development. The study suggests that future research should focus on investigating the general professional knowledge of PSTs and identifying the proficiency levels of PCK needed for the development of digital media PCK. It also emphasizes the importance of considering both, cognitive and affective aspects of teacher preparation, as seminars that solely focus on motivation may not be adequate in fostering effective technology integration. The study recommends that seminars on digital media integration should be situated at later stages of teacher education or after introductory courses that cover other facets of PCK. Furthermore, integrated seminars addressing multiple facets of PCK alongside digital media PCK could be explored in future research. Overall, this study provides insights into the factors influencing PSTs' development of digital media PCK and suggests avenues for further research to improve the integration of digital media in teaching practices for enhanced student learning outcomes. • Pre-post study investigating the development of digital media PCK in seminars. • Digital media PCK was measured using an established, validated test. • Analysis was conducted in a Bayesian framework using Bayesian multiple regression. • PCK about student's conceptions and interest positively predicted digital media PCK. • Motivation to use digital media and previous experience with digital media negatively predicted digital media PCK. [ABSTRACT FROM AUTHOR]

Previous studies reported that acquiring computer programming skills is challenging and might result in high dropout rates. A quasi-experimental design was used to examine the role of different factors in dropping out of an e-based computer programming course. This study applied a knowledge in programming assessment test (20 multiple-choice questions covering the following topics: variables, loops, conditionals, functions, and general knowledge of Python), The Learning Motivating Factors Questionnaire, The Big Five-2, and The Basic Psychological Need Satisfaction & Frustration Scale. Ninety-four participants (38 males and 56 females) completed the course, while 305 participants started it. The mean age of e-learners was 29.96 years (SD 8.27), age range = 18 to 54. The results showed that e-learners who completed the course had higher initial knowledge assessment scores than those who dropped out after the first assessment. Reward and recognition as a motivator were significantly higher in males who completed the course than those who dropped out after the second knowledge assessment. Extraversion was significantly lower in females who completed the course than those who dropped after the first or second knowledge assessment test. Relatedness frustration was significantly higher in those who dropped out after the first knowledge assessment. Due to significant limitations of the sample size, cultural context, measures applied, and research design, the findings would preferably be regarded with caution., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Dirzyte Aiste, Perminas Aidas, Kaminskis Lukas, Zebrauskas Giedrius, Sedereviciute - Paciauskiene Zivile, Sliogeriene Jolita, Suchanova Jelena reports financial support was provided by Public Institution Lithuanian Business Support Agency. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Based on Festinger's theory of cognitive dissonance, this study aimed to explore whether arousing cognitive dissonance among game players can alter their attitudes and behavioral tendencies towards their favorite games. Sixty-six college students (Study 1) and 108 primary school students (Study 2) were randomly divided into a game-related dissonance group and a snack-related dissonance group to perform a short-term counter-attitudinal self-persuasion intervention task. The results suggested that college and primary school students in the game-related dissonance group experienced a significantly higher decrease in positive attitudes towards games and behavioral tendencies to continue playing games than those in the snack-related dissonance group. The participants' attitudinal change toward the games played a mediating role in the effects of the counter-attitudinal intervention on their changes in the behavioral tendency to continue playing the games. In addition, there was a significantly higher game-related dissonance-based intervention effect in the sample of college students than in the sample of primary students. The findings expanded the application of cognitive dissonance in the gaming field and provided implications for educational computer systems to change the attitudes and behaviors of students with excessive gaming behaviors. • Game-related dissonance led to higher internal changes towards games. • Snack-related dissonance led to smaller internal changes towards games. • Dissonance affected behavioral tendency changes by affected attitudinal changes. • Game-related dissonance intervention led to a better effect on internal changes among college students. [ABSTRACT FROM AUTHOR]

This paper reports on a study aiming at examining the effect of the digital storytelling approach on the aggregate reasoning of high school students. A pretest-posttest quasi-experimental design was implemented on 50 10th-grade students for five weeks to reveal the effectiveness of digital storytelling in mathematics courses regarding aggregate reasoning. Results of statistical analysis showed a significant improvement in aggregate reasoning in favor of the students in the digital storytelling group. It was also noted that aggregate reasoning was specifically enhanced to analyze data and interpret results rather than the other two components (formulate question and collect data) in the experimental group. The results support the idea that the use of digital storytelling can be an effective instructional tool for statistics education and provide implications for course designers to provide better teaching of aggregate reasoning. • Aggregate reasoning is an essential skill at the core of statistical reasoning. • Aggregate reasoning is involved in every component of the statistical process. • DST, effective to construct context is essential in statistics education. • DST improves aggregate reasoning, especially data analyze, and interpret results. [ABSTRACT FROM AUTHOR]

The modality effect occurs when people learn better from a combination of pictures and narration than from a combination of pictures and written text. Despite the strong empirical results in earlier studies, the modality effect has been less prominent in later studies of children in learner-paced settings. However, the generalizability of these results in practice may be limited because the studies included notable differences compared to a classroom context. The present study examined the modality effect in a learner-paced classroom context. In a within-subjects experiment, fifth graders learned from illustrated texts and videos and completed pre-, post-, and delayed tests on two science topics. The video group outperformed the illustrated text group in retention, delayed retention, cognitive load, and efficiency measures but there were no statistical differences in transfer. In both learning conditions, the cognitive load was moderate and did not correlate with any learning outcomes. The results suggest that while the modality effect can occur in a learner-paced classroom context, it may not be based on the avoidance of cognitive overload. Alternative explanations concerning the differences in settings and materials between classroom contexts and modality effect research are discussed. [Display omitted] • Modality effect (ME) has not been evident in learner-paced (LP) settings and children. • Fifth graders studied videos (V) and illustrated texts (IT) in a LP classroom context. • V led to better learning and less cognitive load than IT. • Unexpectedly, cognitive load did not affect learning outcomes in either condition. • The influences of the research settings and materials on ME are discussed. [ABSTRACT FROM AUTHOR]

While computer-mediated feedback (CMF) for vocabulary learning has been a focus of considerable attention among both practitioners and researchers, synthesized research to quantitively understand its pedagogical effect is still lacking, and the accumulation of abundant experimental studies also necessitates a meta-analysis. To fill the gap, this study aims to meta-analyze the effect of CMF on second language (L2) learners' vocabulary learning performance and which moderators may underline such effect. More specifically, drawing on the comprehensive categories of Activity Theory (AT), this paper reported meta-analysis results based on 28 valid effect sizes from 25 experimental studies published during 2000–2022. The results showed that the overall effect size was significantly large for vocabulary learning, suggesting that CMF for vocabulary learning is more effective than traditional methods. The moderating effects of a series of AT-related moderators were reported. Based on the results obtained, implications have been proposed for future studies. • Effects of CMF for vocabulary learning are largely inconclusive. • This meta-analysis reports results on CMF for EFL vocabulary learning. • The overall effect size was significantly large. • The moderating effects of a series of AT-related moderators were reported. [ABSTRACT FROM AUTHOR]

While virtual reality (VR) provides a great potential for musical instrument learning, little attention has been paid to the instructional design in creating a VR musical instrument. Previous research has suggested that high embodied interaction or added visual cues (e.g., distinctive colors, flashing areas) on VR-based musical instrument may aid students' learning. In this study, we investigated the feasibility and efficacy of the embodied design (low and high level of embodiment; LoEmb and HiEmb) and visual cues (low and high level of visual cues; LoViz and HiViz) on students' musical instrument learning. Four corresponding virtual Chinese dulcimers (Yangqin) were thereby designed. A sample of 112 university students participated in our study, and they were randomly assigned into the four conditions (LoEmb & LoViz, LoEmb & HiViz, HiEmb & LoViz, and HiEmb & HiViz). Results showed that the LoEmb design benefited students' completion rate, the HiViz improved students' playing rhythmic accuracy. Both LoEmb and HiViz decreased students' playing errors and improved their overall performance. Moreover, we found that the HiViz and HiEmb designs had a combined effect on reducing students' cognitive load and improving the instructional efficiency of learning material. These findings collectively reveal that the design of VR learning materials should carefully consider the trade-off between the level of embodiment and visual cues. • The effect of embodiment and visual cues was investigated in musical instrument learning. • The LoEmb design benefited students' musical playing completion rate, and the HiViz facilitated students' playing rhythm. • Both LoEmb and HiViz decreased students' playing errors and improved their overall performance. • HiViz and HiEmb design can reduce students' cognitive load and improve the instructional efficiency of learning material. • Designing a VR learning material should carefully consider the trade-off between the level of embodiment and visual cues. [ABSTRACT FROM AUTHOR]

Situating learners in a context relevant to scientific phenomena enables them to acquire knowledge through experience, reflection, conceptualization, and practice, which is an important learning mode in science education. However, learners generally do not have opportunities to experience many scientific phenomena in the real world. Therefore, virtual learning environments (VLE) are becoming a frequently adopted technology to provide authentic learning contexts. In particular, spherical video-based learning environments (SVLE), which are a low-tech form of VLE, have attracted the attention of school teachers and educational technology researchers. Additionally, effective assessment methods, such as the two-tier-test, have been adopted to examine learners' performance during the virtual learning process. On the other hand, researchers have pointed out that lack of effective learning strategies may decrease the learning effects in a virtual learning context. Hence, this study integrated a graphic organizer into a two-tier test-based learning mode, in which the first-tier questions were declarative items with a short answer (e.g., the questions of where, what, and when), whereas the second-tier questions were more in-depth, deeper causal-type questions (e.g., the questions of why and how), in the contexts of SVLE. To verify the effectiveness of this learning approach, a graphic organizer-based two-tier test SVLE was developed; moreover, a quasi-experimental design was conducted in the "Mysteries of the Earth" unit of the sixth graders' natural science course. A total of 41 sixth graders from two classes, with an average age of 12, were recruited in this experiment. One class was assigned to be the experimental group adopting the graphic organizer-based two-tier test SVLE (GT-SVLE), while the other was the control group adopting the conventional two-tier test-based SVLE (CT-SVLE). All of the students learned with the SVLE using tablet computers. Based on the results, the GT-SVLE could better improve students' learning achievement than the CT-SVLE. Besides, according to behavioral analysis and interviews, the control group had significantly more learning behaviors of repeated reading of supplementary materials and repeated wrong answers, indicating that the proposed approach facilitated students' positive behaviors through observation and knowledge construction in SVLE, which helped them achieve the learning objectives. • A spherical video-based learning environments (SVLE) learning approach is proposed. • The approach advanced students' positive behaviors through observation and knowledge. • The approach was conducted with two-tier test strategy. • The study was conducted in the unit of the sixth graders' natural science course. • The study used concept map as a tool for researching. [ABSTRACT FROM AUTHOR]

This systematic review study synthesizes research findings pertaining to the use of eye-tracking technology in immersive virtual reality (IVR) learning environments created by using head mounted displays. Research published between January 2012 and May 2022 has been explored and specific inclusion and exclusion criteria have been applied to select articles. Fifty articles were selected and then reviewed with respect to (1) devices employed in research; (2) learning domains; (3) the number and academic level of participants, data collection methods, and duration of IVR activities; and (4) indicators and themes of visual attention. The main findings from this review demonstrate Tobii and HTC Vive are the most popular tools in research on eye-tracking technology usage in IVR learning environments. What's more, cognitive science and educational technology were found to be the most frequent domains in research on eye-tracking technology usage in IVR. The number of participants varied across reviewed articles but tertiary education was the most common academic level of participating students. Scholars used questionnaires and tests frequently to collect their research data. Fixation duration was the most frequently used indicator. The most frequent themes in reviewed research were task performance, teaching and learning strategies, and learning tools. The study concludes with suggestions for future research. • We reviewed thirty-six articles on eye-tracking technology in IVR. • Our focus was on devices, domains, methods, indicators and themes in research. • Future research directions were also provided. [ABSTRACT FROM AUTHOR]

This study investigates how students interact with artificial intelligence (AI) for English as a Foreign Language (EFL) learning and what matters in AI-supported EFL learning. It was conducted in naturalistic learning settings, involving sixteen primary school students and lasting approximately three months. The students' usage data of an AI agent and their reflection essays about the interactions with the AI agent were analyzed using cluster analysis and epistemic network analysis based on the frameworks of community of inquiry and students' approaches to learning. The results suggest four clusters of students, each with its distinct way of interacting with AI for language learning. More importantly, the comparisons of the four clusters of students reveal that even in AI-supported learning, not everyone can benefit from the potential promised by AI. The deep approach to AI-supported learning may amplify the benefits of AI's personalized guidance and strengthen the sense of the human-AI learning community. Passively or mechanically following AI's instruction, albeit with high levels of participation, may decrease the sense of the human-AI learning community and eventually lead to low performance. This study contributes to and has implications for the educational implementation of AI, as well as the facilitation and graphical representation of learner-AI interactions in educational settings. • Community of inquiry and students' approaches to learning are used to analyze human-AI interactions. • Four clusters of students are identified with distinct ways of interacting with AI. • Not everyone can benefit from the potential promised by AI. • The deep learning approach may enhance the human-AI learning community, leading to high performance. • Passively or mechanically following AI's instruction may weaken the human-AI learning community. [ABSTRACT FROM AUTHOR]

The main purpose of the study was to explore how different augmented 3D visualizations may affect the learning of complex science concepts using the eye tracking method. An Augmented Reality (AR) learning system incorporated with different 3D visualizations was developed to assist conceptual learning in the topic of "molecular shapes." Learners' visual attention during the AR learning was recorded using a mobile eye tracking system. Participants were 32 10th grade students. Pre- and post-tests were used to assess students' learning achievements. Learners were grouped into low and high achievers according to the posttest result. To analyze the associations between learners' visual attentions and learning achievements, correlation, t -test, correlation, and regression analyses were applied. Additionally, we conducted lag sequential analysis (LSA) to compare the visual transitions of different groups of achievers. The results showed that learners' conceptual understanding was improved after the AR learning activity. Among the different 3D visualizations, learners attended more to the static and dynamic types in the basic learning stage and to the static and interactive types in the advanced learning stage. Attention to the 3D static model was found to associate more to the attention to the interactive type. The correlation and regression analyses found that the cognitive effort to integrate information about the static 3D model was the key predictor for the learning achievement. LSA showed that high achievers displayed a higher chance of looking back to the static 3D model from other AOIs. The visual pattern analysis suggested that a guidance to connect information delivered by the static and the animated visual representations is necessary for complex conceptual learning. • Visual attention to the augmented 3D static objects predicted learning achievement. • Visual attentions to the 3D static and interactive models were highly correlated. • Low achievers attended more to the interactive 3D objects. • High achievers looked back to the static 3D object from other AOIs more frequently. • High achievers made more sequential transitions between text and 3D objects. [ABSTRACT FROM AUTHOR]