Search

Highly cited articles have been revealed as being informative for research fields, topics, and trends. Through reading highly cited articles, researchers can gain fruitful results from previous studies and can identify essential clues and potential future research directions for their own research. Aiming at exploring the possibility of the application of and innovations in flipped learning, this study reviewed 100 highly cited articles related to flipped learning. By performing a literature review of the highly cited studies on flipped learning, we have discovered the proposed new learning strategies and flipped learning applied to the research topics that seldom draw attention, and the research fields that are less-frequently examined, including those research issues that are rarely discussed. We have also noticed that many studies have focused on comparing different flipped learning modes and identifying more effective flipped learning approaches. Only a minority of studies have compared the influences of flipped learning and traditional learning. Moreover, we found that researchers have tended to focus more on students' learning achievements and learning behaviors. Lastly, based on the reviews of the past flipped learning articles, this study provides suggestions from different perspectives. We hope to provide a reference for researchers and teachers to conduct flipped learning studies and design flipped learning activities in the future. [ABSTRACT FROM AUTHOR]

An editorial is presented on personalized learning evolving as the teaching and learning practices. Topics include emphasizing student-centered learning addressing individual learning strengths, interests, and needs; allowing flexibility in the learning mode and supporting students for taking ownership of the learning; and educational technology incorporating with other forms of innovative pedagogical practices such as blended learning.

Augmented reality (AR) has shown potential for aiding users in their assembly tasks. It provides a magic-lens view of the physical object. Thus, assembly tasks become less demanding. An assembly task using AR provides a pre-defined sequence of actions with a minimum amount of information to do the task. Thus, there is a need to exploit the advances in AR technology to provide assemblers with a more sophisticated learning experience. Using AR to turn the physical object into a smart object that communicates and interacts with a user can result in an assembler achieving a more knowledge and a greater awareness of the technology and provide insights and a deeper understanding of the software components inside the embedded computing instead of only learning the assembly hardware components. This study used a Pedagogical Virtual Machine (PVM) to evaluate the learning effectiveness with AR. We presented an experimental work based on assembling and exploring a modularized mobile robot task called Buzz-Boards. A total of 36 students participated in the study; 18 students participated in both experimental and control groups. Findings demonstrated that the PVM with AR approach was more effective in learning achievement, learning activity enjoyment, and usefulness than the paper-based approach. [ABSTRACT FROM AUTHOR]

Technology-Based Embodied Learning (TBEL) is a hotspot in learning science. By systematically reviewing 49 SSCI journal articles, this paper revealed the relationship between any two of sample group, sample size, duration, subject distribution, research design, and measurement instrument, etc. In general, the major results showed TBEL is helpful for students to enhance the knowledge comprehension and skills, improve long-term retention and transfer, et al. But sometimes, the effect of embodied learning may be limited by types of learning, age of learners, or redundant strategy. We also derive some limitations and future research directions from reviewed papers. ABSTRACT Technology-Based Embodied Learning (TBEL) has become a hotspot in learning science. This paper systematically reviewed 49 SSCI journal articles. The results mainly indicate that: (1) The learning phase is proportional to sample size; (2) The sample size of experiments is inversely proportional to the duration; (3) The experiment duration may be inversely proportional to the learning phase; (4) The integration between experiments and various subjects in middle and high school still needs to be improved; (5) A variety of measurement tools are used for almost every type of research design; (6) TBEL has been integrated with a variety of embodied learning theories in various disciplines, especially mathematics and language; and (7) Comparing with other interaction modes, tangible interaction is more conducive to achieve a higher degree of embodied learning, et al. In general, the major results showed TBEL is helpful for students to enhance the knowledge comprehension and skills, improve long-term retention and transfer, achieve high levels of engagement and attention, increase positive learning attitude, and decrease cognitive load. But sometimes, the effect of embodied learning may be limited by types of learning, age of learners, or redundant strategy. We also derive some future research directions from reviewed papers. [ABSTRACT FROM AUTHOR]

The paper investigates the level of development of a creative mindset in the training of music education professionals. The research is based on the experimental method which examines the level of creativity of students before and upon completion of the developed training program focusing on development of the creative thinking using cutting-edge technology. The Torrance Tests of Creative Thinking (TTCT) was used to measure the level of students' creativity. The study was conducted at the School of Music, Soochow University. A total of 95 students were involved in the experiment. According to the results of the pre-test, the majority of students (52%) have a low level of creativity development, while 35% have an average level and only 13% have a low level. The findings of the study show the high importance placed on developing creative thinking skills as part of music training programs in universities. [ABSTRACT FROM AUTHOR]

Learners' emotional states might change during the learning process, and unpredictable variations of a person's emotions raise the demand for regular assessment of feelings during learning. In this paper, an AI-based decision framework is proposed and implemented for e-learning systems that identify suitable micro-brake activities based on the learner's emotional state through an evolutionary genetic algorithm to change learner's mood and increase learning performance. This proposed framework was tested using a case study of English as a second language learner during one semester. The students were divided into two groups of participants (each group containing twenty students, forming a total of 40 students). The results of this study demonstrated the importance of learners' emotions in their learning performance and proved the effectiveness of our proposed framework and the success of the recommended micro-break activities chosen based on learners' emotions and preferences. The findings of this study have important practical implications in designing adaptive e-learning systems and learning management systems such as Moodle. They also contribute to theoretical implications in the field of AI and learner emotions by suggesting a novel approach to identifying, categorizing, and offering a learning path that can cater to the needs of individual learners. [ABSTRACT FROM AUTHOR]

The paper compares the effectiveness of the online and blended learning of music during COVID-19. The study involved 140 students from Nanjing Xiaozhuang University in China. The research design: a pre-test and post-test experiment with a control group. The following research findings were obtained: the combination of face-to-face and online learning resulted in significant increases in PK (from 205.72 to 303.40), TPK (from 258.75 to 271.50), PCK (from 271.00 to 295.00) and TPCK (from 261.00 to 293.00) among students in TPACK test, which was significant (p < 0.05). The experimental group's scores on the Piano Lesson Achievement Test were higher (293.00) than those of the control group (174.00), which was considered statistically significant (z = 2.67). The research suggests that personalized blended learning to play the piano is more effective than conventional online learning. The results can provide fundamental insights when designing and implementing online or blended piano courses. For example, a piano video tutorial can be created and applied in terms of personalized online instruction. Further on, it is important to explore alternative methods in online music learning (learning through apps, videos, etc.), to study their effectiveness in music education, to identify the advantages and disadvantages of each method. [ABSTRACT FROM AUTHOR]

The paper investigates the effect of introducing a course in Web Development for Chinese students on their academic achievements and the basic competencies, using traditional and online approaches. For the experimental learning purposes, 300 students were selected from three universities located in China's largest cities: Shanghai, Beijing, and Tianjin. A course in Web Development was designed and implemented to achieve the research objectives. The study results showed that the difference in the learning outcomes of the two groups was insignificant and did not depend on the training format. Online learners had more feedback and were able to take lectures and practical training more quickly. Further research requires quantifying and comparing the effects of online learning in programming instruction using the instrumental variable method and structural equation modeling to reveal the causal relationship between the two. The study can be useful to developers of training programs to create both traditional and online courses because the data obtained during this research can improve the effectiveness of the new course. [ABSTRACT FROM AUTHOR]

An editorial is presented on academic quality having an element of subjectivity in judgement. Topics include articles being used as a way of building academic credibility and ultimately career advancement; learning involves human interaction as well as programmable digital response; and articles offering for publication either to disseminate research being funded for new doctoral and post-doctoral research.

English for Specific Purposes (ESP) teacher development has become a crucial issue in ESP teaching and research. How to equip ESP teachers with necessary knowledge and skills in the digital era becomes a hot topic. A Personal Learning Environment (PLE) is a potential pedagogical approach to realize learning-centered in ESP teacher development. This paper is an exploratory research which attempts to integrate Learning Management System (LMS) with Personal Learning Environment for the training of ESP teachers at tertiary education in China. Based on the previous research on the seven-factor technology, pedagogy, and content knowledge (TPACK) framework and the five-factor skill Framework for ESP teachers in China, a PLE-ESP platform was built in the form of a website (). The platform was evaluated with 20 ESP participants within a two-month pilot study. A survey about the value and flexibility of the platform was carried out, the result of which indicated an improvement on the skills required in ESP teaching, learners' self-regulated learning competency and their ICT literacy. Recommendations were made for future research on the successful integration and maintenance of PLE and LMS. [ABSTRACT FROM AUTHOR]

This paper introduces the smart classroom learning model based on the concept of ambient intelligence. By analyzing a smart classroom, the ambient intelligence system detects a student and determines their level of fatigue based on the data about their previous daily academic activities. This information is then used to assign the student the appropriate learning strategy. The paper describes relevant factors for developing the model. The model was tested on a sample of 80 students. By analyzing the information available through ambient intelligence, it was possible to utilize the smart classroom to provide students with the adequate learning strategy in accordance with the criteria compatible with the expected leaning outcomes. The research results have shown positive effects of the application of the ambient intelligence-based smart classroom model on learning results. [ABSTRACT FROM AUTHOR]

This paper presents a competition-based active learning approach that prepares undergraduate students for careers in the drone industry. The competition-based learning (CBL) approach focuses on preparing students for three key drone industry requirements (1) drone assembly, testing, and validation using commercial off-the-shelf (COTS) parts, (2) simulation of drone flight missions and (3) manual and semi-autonomous drone piloting. The CBL curricular modules were developed using the Interactive-Constructive-Active-Passive (ICAP) framework of cognitive engagement. These modules immersed students in the technical challenges corresponding to the three essential drone industry requirements. The approach was implemented through fourteen (14) drone workshops that culminated in a final drone piloting competition at a STEM research university in the United States. Ninety-seven (97) students from various backgrounds with little to no prior experience in building drones participated in the competition as part of 22 teams in total. Multiple assessment methods were used to evaluate the students' progress and the perceived drone-related skills gained by the end of the workshops. Assessment methods included data from direct formative (weekly or biweekly curricular milestones), direct summative (drone piloting for multiple flight tests), indirect quantitative (Likert-style feedback survey about student perceptions), and indirect qualitative (descriptive feedback comments) tools. Direct quantitative assessments indicated that most students successfully reached the technical milestones of the workshop sessions and gained practical drone piloting skills. The indirect quantitative assessment revealed that students perceived the workshops to be a valuable experience in their drone industry skills and knowledge. Indirect qualitative analysis of the feedback comments revealed that students perceived CBL as an engaging and effective method of introducing drone technology. [ABSTRACT FROM AUTHOR]

Learning history is vital for students' intellectual, spiritual, emotional, and physical development. Students perceive history subject as difficult and boring because they must memorize facts and understandthose facts, concepts, time, and historical events. Interactive multimedia can increase students' enthusiasm and make the teaching and learning process more interesting to make the history "alive." Game-based learning uses game elements and principles to effectively deliver teaching and learning process in the classrooms. Yamashita's Treasure: A Quest to Find the Treasure is a game-based instructional material designed for grade 7 students of the Philippine K-12 curriculum that aims to teach significant lessons and events occurred in the Philippines over the last century. In this paper, we present findings from an assessment of an instructional material in teaching Philippine history. A System Usability Scale (SUS) was used to test the system's usability which generated a positive score. Respondents were highly satisfied with the game's usability scoring 87.5 on the SUS. Future work includes developing a programmed system, conducting quasi-experimental research design, and consultations with the experts for further enhancement. [ABSTRACT FROM AUTHOR]

The HyFlex learning model has gained popularity in recent years and, with the outbreak of COVID-19, the demand has increased. However, there are challenges associated with the model, especially related to equity and engagement. A HyFlex model known as Interactive Synchronous HyFlex is being developed and practised by the researchers in their introductory design thinking course. The purpose of the paper is to understand the experiences of students using the Interactive Synchronous HyFlex model. A qualitative method in the form of focus group interviews was followed in this study to better understand the student experiences. The focus group interviews were conducted during the beginning, mid and end of the semester. The resulting themes of the study are grouped into two categories: affordances and opportunities. The themes corresponding to affordances are (a) effective model, (b) flexibility, (c) sense of community, (d) ease of communication and (e) help prepare for future jobs. The themes corresponding to opportunities include (a) software learning curve, (b) online non-contributors and (c) inconsiderate face-to-face peers. The results of the study may help faculty and higher education institutions better prepare a version of the HyFlex model taking into consideration the affordances and finding better ways to incorporate opportunities. [ABSTRACT FROM AUTHOR]

An editorial is presented on Interactive Learning Environments. Topics include accelerating access to literature through the web, through academic databases, and online searching; describing the hermeneutic literature review approach as searching, clarifying, mapping and critically assessing evidence through a close and iterative study of sources.

With the advent of technological advancement in learning, such as context-awareness, ubiquity and personalisation, various innovations in teaching and learning have led to improved learning. This research paper aims to develop a system that supports personalised learning through adaptive content, adaptive learning path and context awareness to meet individual learner's requirements and promote the effectiveness and performance of the learning process. Furthermore, the study used an experimental control group to ascertain the significance of learners' learning styles and preferences in improving learning performance. The model considers different modules such as personalisation, location support, learning plan and context awareness while relying on the proper classification of learners' learning styles. The system was experimented using 127 learners of a Computer Science Course. The result obtained using 10-fold cross-validation on various algorithms shows better performance in ROC, Kappa and Accuracy, which were all used to evaluate the quality of classification outcome and compared with learners' performances in assessments. During classification, Naïve Bayes Model has the highest average ROC value of 0.979, TP Rate of 0.951 and FP Rate of 0.045. The results obtained show an improvement in learning. [ABSTRACT FROM AUTHOR]

This paper aims to study the features of vocal improvisation using interactive musical technologies. The survey method contributed to determining the level of vocal skills of 214 respondents auditioned before the experiment. The authors developed a training programme based on previously received information. It included breathing, technical, aesthetic, and vocal improvisation skills. The results showed that 93% of the experimental group believed that interactive technologies had advantages in the educational process, and 63% of the control group believed that they had no advantages. The survey of the students allowed identifying elements that required improvement or changes in the curriculum. The students of the experimental group showed that using national Chinese instruments for accompaniment was important for 32% of the respondents, 27% chose the answer "other", which included systematic and more frequent cross-sections of knowledge, the involvement of foreign approaches to learning. The calculation of the level of knowledge obtained showed that 88% of the students demonstrated a high level in the experimental group, a low one was only in 2%. Study prospects relate to studying technical and aesthetic elements to be applied during classical and folk vocal performance. [ABSTRACT FROM AUTHOR]

Owing to the predominant role of Machine Learning(ML) across domains, it is being introduced at multiple levels of education, including K-12. Researchers have leveraged games, augmented reality and other ways to make learning ML concepts interesting. However, most of the existing games to teach ML concepts either focus on use-cases and applications of ML instead of core concepts or directly introduce ML terminologies, which might be overwhelming to school students. Hence, in this paper, we propose ML-Quest, a game to incrementally present a conceptual overview of three ML concepts: Supervised Learning, Gradient Descent and K-Nearest Neighbor (KNN) Classification. The game has been evaluated through a controlled experiment, for its usefulness and player experience using the TAM model, with 41 higher-secondary school students. Results show that students in the experimental group perform better in the test than students in the control group, with 5% of students in the experimental group scoring full marks. However, none of the students in the control group could score full marks. The survey results indicate that around 77% of the participants who played the game either agree or strongly agree that ML-Quest has made their learning interactive and is helpful in introducing them to ML concepts. [ABSTRACT FROM AUTHOR]

An introduction is presented which discusses reports on learning achievement, role of experiential games in science education, and mobile learning.

The development of students' practical operation and their collaborative problem solving (CPS) ability are emphasized in higher education nowadays. Providing students a simulation learning tool and an social networking environment can improve the students' learning in CPS activities. This can be a potential learning environment for the students when the automatic scaffolding guidance tools are appropriately given to them. Therefore, the present study developed a scaffolding-based CPS learning environment. This empirical study explored learners' learning performance. The students' online discussion messages were also encoded for the later quantitative content analysis to explore their cognitive process in CPS activities. The study included 94 participants, who were divided into the study sheet group (use the simulation tool and paper study sheets for discussions) and the scaffolding mind tool group. The results showed that learning performance of the scaffolding mind tool group was significantly better than that of the study sheet group. Moreover, learners in the scaffolding mind tool group showed more diverse levels in the cognitive process. The researcher further conducted a Lag sequential analysis based on the coding results. The results also suggested that the scaffolding mind tool group showed more diverse cognitive process transitions in their behavioral patterns. [ABSTRACT FROM AUTHOR]

This scoping review examines studies using eye tracking technology to monitor learning and performance in virtual or mixed reality settings. The aim of this review is to describe the various ways in which eye tracking devices have been deployed in relation to key aspects of virtual reality and mixed reality environments, list the eye tracking measures most salient to such environments and identify emergent patterns in the findings that the eye tracking data in the studies reviewed have brought to light. Drawing on these findings, an analytical framework for attending to and analysing eye tracking data is proposed and recommendations for future research using eye tracking to optimise learning and performance within virtual reality and mixed reality environments are discussed. [ABSTRACT FROM AUTHOR]

This paper argues for conceptualizing the notion of personal learning environments in higher education from an explicit adult education perspective that emphasizes the realization, re-instrumentation, and integration of learning activity in the wider context of adult life. It discusses and re-interprets an existing proposal for modeling "the personal learner" on the basis of the Viable System Model in this context and provides an empirical illustration for the conceptual utility of such an approach for educational intervention work in higher education. The paper concludes that a careful redesign and reconfiguration of learning activity in formal educational settings is a necessary and important educational intervention goal in itself, allowing for expansive connections between specific forms of learning activity and the wider context of adult life. Such an approach treats participants as developing "adult learners" who gradually gain conscious control over their own modeling of learning activity, its flexible realization via personal learning projects, and their instrumentation via personal learning environments. [ABSTRACT FROM AUTHOR]

The paper proposes EXPLODE, a new model of exploratory learning environment for teaching and learning neural networks. The EXPLODE model is about pedagogically instrumenting a software development environment to transform it into an exploratory learning environment for neural networks. Such an environment is particularly aimed for students who are skilled in programming and meets typical challenges in teaching and learning neural networks, related to the lack of prerequisite knowledge in mathematics. By providing such students with a familiar learning environment and allowing them to programmatically experiment with neural networks, the EXPLODE model aims at improving the students' learning outcomes and learning experience. The effectiveness of the model was evaluated in an experimental study with 77 final-year IT students. The results have shown that the students from the experimental group, that is, those who were exposed to the EXPLODE model, scored higher on the knowledge test. Furthermore, the perceived learning experience of the experimental group was better than that of the control group. The results have also suggested that the proposed model helps students better understand learning topics that require practical experience and facilitates a deeper understanding of the internal operations of neural networks. [ABSTRACT FROM AUTHOR]

PS-I learning approaches with an initial problem-solving phase (PS) followed by an instruction phase (I) can be optimised by providing adaptive (individualised) instruction that builds on students' problem-solving products. A computer-based implementation of both phases offers the possibility of adaptivity at the transition from the problem-solving to the instruction phase. However, it also poses two challenges for the problem-solving phase, which should allow for (1) complex problem-solving processes (process validity) and (2) accurate diagnosis of problem-solving products. Increased openness of the learning environment can increase the process validity and decrease diagnostic accuracy and vice-versa (complexity-accuracy trade-off). Using two variants of a computer-based learning environment for fraction comparison with different extent of openness (O+ and O-), we investigate whether both requirements (complex problem-solving processes and accurate diagnosis of the problem-solving products) can be met simultaneously. To check process validity (complexity of problem-solving processes), we compare the problem-solving products with those from previous research on an analogous paper-based version. Our results show that valid and comparable problem-solving processes can be achieved in both computer-based learning environments (O+ and O-). Moreover, only the learning environment O- enables an accurate computer-based interpretation of students' products and thus resolving the complexity-accuracy trade-off. [ABSTRACT FROM AUTHOR]

In e-learning environments, several activities are offered to learners, including learning and assessment activities. During these activities, the learner may encounter difficulties, such as blocking situations or lack of motivation. This paper presents a new approach to detect these difficulties based on the learner's emotional states and recommends solutions to motivate him/her. Our first contribution is recognizing the learner's emotional state using two modules: facial expression recognition using a Gabor filter bank and vocal emotion recognition using MFCC features. Concerning the recommendations in these cases of difficulties, a psychological and/or pedagogical recommendation generator is proposed in this study; it is our second contribution. Three experiments to validate our approach were conducted on two groups of students: test and control. The results indicate that the proposed method improves the learner's emotional state, motivation, and engagement time in the system. [ABSTRACT FROM AUTHOR]

This study was to review empirical studies on UAV usage in education. 43 papers were selected and reviewed with respect to the following dimensions: (1) publication time and source, (2) methodology in reviewed studies, and (3) main findings reported by researchers. The results showed that the highest number of published articles was between 2018 and 2020, and that most studies were published in journals and conference proceedings. Most participants were undergraduate students from Asia. Most studies were conducted for five days or less and the most frequent domain to which UAV was applied was STEM. Scholars often used questionnaires and tests as measurement instruments. We found that the most frequent learning activities were collecting data with UAV, learning how to fly UAV, introducing UAV, working in the field with UAV, and programming UAV. Research variables that scholars explored in reviewed studies often were learning performance, attitude and motivation. The main findings concerned skills, knowledge, motivation and responsibility. The advantages of UAV in education were accessing data from inaccessible or dangerous locations, collecting and delivering temporal and spatial resolution information quickly etc., disadvantages were availability issues, legal issues, logistical issues, and privacy and ethics issues. [ABSTRACT FROM AUTHOR]

Programming ability is the core ability of this era and can be obtained and improved through practice. In this paper, an Automated Programming Assessment system based on Mastery learning and Peer competition (APAMP) was proposed and developed. APAMP allows students to practice repeatedly by providing immediate feedback after their programs are submitted. It also presents an analytical dashboard as a competition mechanism for students to visualize their learning performance and compare their performance with peers. By incorporating APAMP into programming courses, students can master programming skills through repeated practice, and their enthusiasm for learning programming can also be encouraged by peer competition. To evaluate the effects of APAMP on the learning performance of students with programming language learning and novice students, a quasi-experiment was conducted in a high school. The experimental results showed that the learning achievement of the two groups of students improved significantly. Moreover, the learning attitude of students in the experienced group improved significantly, with the experienced students benefiting more from the system than the novice students. In fact, the novice students showed a significant decline in learning attitude and learning motivation, which was contrary to our intuition. [ABSTRACT FROM AUTHOR]

The prerequisite of developing countries' economic growth is to move along the technological development trajectory through technological learning, and large firms as hubs of technological knowledge, play an important role in this transition. In this paper, we tried to bridge two main taxonomies in the field of technological development, one of them referring to taxonomies of firms, and the other one referring to technological learning processes. We have identified technological learning processes in several post catch-up large firms through content analysis and then by employing a survey approach, we explore technological learning processes of Iranian large firms. The results indicate that as per scale-intensive firms in Iran, learning by doing, learning by using, learning by interacting and learning from spillovers are respectively the most important technological learning processes. Regarding large science-based firms, learning by searching, learning by interacting and learning from spillovers are the key learning processes. Finally, these results have been compared with those of post catch-up large firms. [ABSTRACT FROM AUTHOR]

The aim of this paper is to categorize and describe different types of learners in massive open online courses (MOOCs) by means of a subgroup discovery (SD) approach based on MapReduce. The proposed SD approach, which is an extension of the well-known FP-Growth algorithm, considers emerging parallel methodologies like MapReduce to be able to cope with extremely large datasets. As an additional feature, the proposal includes a threshold value to denote the number of courses that each discovered rule should satisfy. A post-processing step is also included so redundant subgroups can be removed. The experimental stage is carried out by considering de-identified data from the first year of 16 MITx and HarvardX courses on the edX platform. Experimental results demonstrate that the proposed MapReduce approach outperforms traditional sequential SD approaches, achieving a runtime that is almost constant for different courses. Additionally, thanks to the final post-processing step, only interesting and not-redundant rules are discovered, hence reducing the number of subgroups in one or two orders of magnitude. Finally, the discovered subgroups are easily used by courses' instructors not only for descriptive purposes but also for additional tasks such as recommendation or personalization. [ABSTRACT FROM AUTHOR]

The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for previous users or learners of such system and to use such analysis to guide and help the current user. New techniques are now available that rely on emergent or self-organising methods to analyse a large amount of interaction data being generated by large-scale online learning communities, interactions with learning resources or learning management mechanisms. One such technique is swarm intelligence, a set of computing algorithms in the form of multi-agent systems that simulate how swarms of insects or birds move or work. It has been applied to various intelligent functionalities such as adaptive content planning, computer-adaptive testing and assessment paper generation. In this article, we provide a survey of the various approaches in swarm intelligence that explores potential mechanisms to adapt and individualise learning and assessment. We hope that this article can inspire future studies in this exciting area. [ABSTRACT FROM AUTHOR]

While learning can happen anywhere and everywhere, most educational practices in K-12 are confined within the walls of a classroom and the school; such practices narrowly define learning and exclude the opportunities that an expanded and digitally mediated definition of learning can offer. Augmented reality (AR) technologies offer exciting new opportunities for supporting ubiquitous learning, by superimposing layers of digital information on the real world. The digital augmentation can provide enriched learning experiences, through situating the learning content in authentic contexts and fostering inquiry-based learning. Nonetheless, learning can often be sidestepped as the use of AR technologies becomes a mere fun activity, akin to a treasure hunt. Such challenges indicate the need to provide scaffolded AR environments to support deep learning. These ideas are reflected in the design of the TraceReaders, a platform for enabling location-based mobile learning using augmented reality (AR) technologies. TraceReaders supports the authoring of inquiry-based AR apps, to engage students in evidence-driven reflective inquiry in situ. This paper first describes the theoretical commitments which guided the development of the TraceReaders platform, followed by a description of its design rationale. Two case studies of informal inquiry learning using TraceReaders are then presented: the first one reports on the use of the "Young Archaeologists" TraceReaders app to support primary school students' historical reasoning, while the second one reports on the "Mystery at the Lake" app to support high school students' environmental science inquiry. These cases offer the opportunity to discuss the affordances and challenges in using such a scaffolded tool to support location-based AR learning in situ. The discussion concludes with lessons learned from empirical studies about the design and effectiveness of tools like the TraceReaders platform and future steps. [ABSTRACT FROM AUTHOR]

The emotional participation of online learning is a process-oriented emotional indicator that measures learners' learning effects. Existing studies have shown there is little research on online-learning emotional participation, and even fewer have studied the online learning participation of ethnic college students. In order to study the online learning participation of ethnic college students, this paper tried to build the online-learning emotional participation theory model, which included four dimensions: learning interest, self-efficacy, self-worth and the sense of belonging. Based on the survey of 723 students from Yunnan Minzu University in China, we analysed the structural and quantitative relationships among the four dimensions of online-learning emotional participation of ethnic and Han college students respectively. The results show that there are significant differences in the online-learning emotional participation between ethnic and Han college students, especially their sense of belonging. Furthermore, in order to build a better online learning environment for ethnic college students and enhance their sense of belonging, an online learning community model is proposed. [ABSTRACT FROM AUTHOR]

With the recent development of internet and mobile technology, a new kind of e-text communication is emerging. From messenger chatting, mobile texting, to social networking through Twitter or Facebook, e-text communication is becoming a main communication channel, especially for the younger generation. However, there has not been sufficient investigation into how this new kind of e-text communication can be applied in interactive learning environments, and which attributes of communicative e-text might influence learning. This paper, therefore, integrates a theoretical framework for understanding the essentials of e-text communication and explores the implications for its appropriate application in learning practice. After reviewing the historical background of orality and literacy as the basis of communication, this paper presents the core attributes of e-text communication. Finally, a theoretical framework for evolving e-text communication is elaborated with learning implications. [ABSTRACT FROM PUBLISHER]

This paper presents a new algorithm called competency-based guided-learning algorithm (CBGLA), which can be applied on adaptively guiding e-learning. Computational process analysis and mathematical derivation of competency-based learning (CBL) were used to develop the CBGLA. The proposed algorithm could generate an effective adaptively guiding learning path in order that it would guide the learners to study adaptively without requiring teacher involvement. In order to verify the effectiveness for the CBGLA, a system is implemented. Using statistical methods, the data of which are collected from the students' learning activities on the system, we have verified the efficiency of the CBGLA by the comparison of the pre-test and post-test scores of students. While the learning materials possess fixed scope and could be classified into several categories, students could even learn more effective under the guidance of CBGLA system than a teacher. Analyzing the questionnaire, it also has been shown that learners were very satisfied with the design of the system user interface and the guided-learning mechanism. [ABSTRACT FROM PUBLISHER]

Choosing a career is one of the most important decisions that youth has to take but many young people find this a hard issue to engage with. Current career counselling practice does not appear very compelling or motivating to young people. Professional games could provide a more engaging and motivating way of acquiring professional awareness and competence for career decision making and learning. We present the design and effects of playing a game that aims to increase career awareness and adaptabilities in youth (13-19 years). In a Randomized Controlled Trial, 93 high school students from Iceland and Romania were asked to carry out career-oriented activities, with half playing an interactive game and the other half performing a paper-and-pencil version of the same activities. The students were compared on career adaptability, career learning and career awareness scores before and after these interventions. Main results show that engaging players in these career-oriented activities has short term effects on outcome scores for career adaptabilities and for perceptions of career learning competences. Students who played the game report significantly faster growth on career adaptabilities that deal with “concern”, “control” and “confidence”. It can therefore be concluded that introducing game-based learning in career decision support for youth is a promising endeavour. [ABSTRACT FROM AUTHOR]

This paper presents a computational model for simulating how people learn from serious games. While avoiding the combinatorial explosion of a games micro-states, the model offers a meso-level pathfinding approach, which is guided by cognitive flow theory and various concepts from learning sciences. It extends a basic, existing model by exposing discrete-time evolution, allowing for failure, drop-out, and revisiting of activities, and accounting for efforts made and time spent on tasks, all of which are indispensable elements of gaming. Three extensive simulation studies are presented involving over 10,000 iterations across a wide range of game instances and player profiles for demonstrating model stability and empirical admissibility. The model can be used for investigating quantitative dependences between relevant game variables, gain deeper understanding of how people learn from games, and develop approaches to improving serious game design. [ABSTRACT FROM AUTHOR]

An editorial is presented on focussing on end-users of information systems. Topics include model being widely embraced in education as the foundation theory for many papers on the adoption of learning technology; and incorporating the variables hedonic motivation, price value, and habit while using the model in relation to consumer acceptance of new technology.

Through profiling and matching processes, technology provides individuals with information that becomes redundant to their previous beliefs, attitudes and preferences. The emergence of informational redundancies encouraged by some technologies is likely to influence the way knowledge is constructed by individuals in these settings. In this paper, we present a theoretical basis, rooted in cognitivist and socio-constructivist educational psychology, to characterize such knowledge-construction processes in informal settings. Learning processes in these environments are defined as cumulative: on the individual level, the most likely form of learning is through accretion of knowledge into previous schemata; on the social level, these environments foster learning through cumulative talk. We highlight the challenges that this might pose to education systems and suggest possible educational responses. [ABSTRACT FROM PUBLISHER]

This study examined the role of self-monitoring (SM) support for writing skill improvement in a reciprocal peer review of writing system called scaffolded writing and revision in the disciplines (SWoRD). Based on previous literature on the key role of SM in self-regulated learning, students were provided with opportunities to self-monitor their writing through self-evaluations and peer evaluations on both their own and peer writing. With 601 graduate and undergraduate students from 16 courses in three US universities, we found that the students who developed successful SM dramatically improved their writing compared with those who did not. Finally, we discuss future research in SM of writing. [ABSTRACT FROM AUTHOR]

This paper reflects on the current position of virtual learning environments (VLEs) in universities and speculates about likely future directions for e-learning. Using accepted models of technology innovation and looking at current Web trends, it considers the extent to which e-learning is truly embedded in institutions, how Web 2.0 is being used by the upcoming generation and what this might mean for teachers, learners and higher education institutions. The paper concludes that optimism about the impact of e-learning on higher education based on the market penetration of VLEs is misplaced and suggests that Ivan Illich's concept of learning webs may be a more reliable guide to future developments. [ABSTRACT FROM AUTHOR]

Interactive learning environments (ILEs) are increasingly used to support and enhance instruction and learning experiences. ILEs maintain and display information, allowing learners to interact with this information. One important method of interacting with information is navigation. Often, learners are required to navigate through the information space of an ILE, a process which can be quite difficult and cognitively exacting as the information space becomes very large and complex. Proper design can make this process less exacting and, at the same time, facilitate better learning of the information space. However, this is not easy to do, especially for ILEs. Frameworks can assist in the effective analysis and design of interactive environments. However, there is lack of conceptual frameworks for guiding the analysis and design of navigation in ILEs. This paper tries to address this issue by presenting a framework which can be used to characterize navigation within ILEs. To create this framework, this paper brings together research from various disciplines, such as human-computer interaction design, educational multimedia design, cognitive technologies and learning sciences. This framework prescribes a three-stage process for designing and analyzing navigation: 1. content structuring; 2. information navigation modeling; 3. interface presentation structuring. By bringing these three stages together, it is intended to provide a conceptual framework to assist and guide designers in the proper analysis and design of navigation in ILEs. [ABSTRACT FROM AUTHOR]

This paper presents findings from a two-year qualitative study examining integration of computer science (CS) and computational thinking (CT) into elementary mathematics instruction. Integrated units were developed by elementary teachers and CS/CT coaches with support from university faculty with expertise in CS/CT and elementary mathematics. CS/CT instruction primarily relied on the Scratch environment, although some lessons made use of Code.org materials. This research primarily relied on two theories of integration (i.e. Kiray, 2012. A new model for the integration of science and mathematics: The balance model. Energy Education Science and Technology Part B: Social and Educational Studies, 4(3), 1181–1196) that provided insight into the level of interconnection between the disciplines and the relative amount of instructional time spent within each discipline. Findings revealed that cross-grade CS/CT concepts included sequencing, looping, and conditional logic. Within each category: (a) concepts were taught with increasing complexity across the grades, (b) the mathematics was dominant and CS/CT was important but secondary, and (c) three types of lessons emerged: No integration, partial integration, and full integration. Lastly, lessons generally included a transition from less integrated to more integrated activities with an initial focus on discipline-specific conceptual understanding prior to integrated activities. [ABSTRACT FROM AUTHOR]

A positive emotional state of students has proved to be essential for favouring student learning, so this paper explores the possibility of obtaining student feedback about the emotions they feel in class in order to discover emotion patterns that anticipate learning failures. From previous studies about emotions relating to learning processes, we compiled a Twelve Emotions in Academia Model, which is composed of six positive and six negative emotions. Using this model as a base we built the EmotionsModule in the PresenceClick system, allowing students to identify their emotions and follow their evolution by means of visualizations. Instructors can also view an anonymized version of these data to increase their knowledge about the emotional state of the group and propose new learning strategies to improve the group's overall state. Information about attendance in face-to-face sessions has been also considered due to the fact that it is positively related to students' progress. Over the course of two academic years, we carried out an experiment in a single subject in the Computer Science degree in which students' emotional data and attendance were collected through PresenceClick. Then, we analyzed the compiled data through a correlation study and a principal component analysis whose results demonstrate the consistency of the data, allowing the prediction models to be fed each academic year. Once the correctness and stability of data were verified, data mining techniques were applied and two models based on probability tables and decision trees were obtained. These models enable instructors and students to detect problems early and avoid failure. [ABSTRACT FROM AUTHOR]

This paper presents the eight Learning Events Model (8LEM), a pedagogical reference framework which was used, in more than 100 online courses, as a starting point for instructional planning. Besides supporting teachers in early stages of the learning design continuum, the paper shows how this learning/teaching model, as a professional development tool, prompts them to diversify the learning methods experienced by students in their courses. A three-pronged rationale about the importance of this diversification with respect to "mathetic" competence development, epistemology and personalization is also submitted to discussion. [ABSTRACT FROM AUTHOR]

A considerable amount of the effort and enthusiasm that goes into the development and implementation of technology-mediated learning environments often fails to create effective settings for learning. Too often the opportunities and advantages of the use of technology in the learning process are poorly exploited. This paper explores ways in which contemporary pedagogical principles can inform and guide the design of technology-mediated learning environments. The paper argues the need to plan learning settings based on meaningful and relevant activities and tasks which are supported in deliberate and proactive ways by the tutor. The paper presents and describes a framework which supports a design process comprising three critical strategies: the selection of learning tasks; the selection of learning supports; and the selection of learning supports as a strategy for the development of online learning settings that promote knowledge construction. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue including the integration of mobile learning in education, the proliferation of online courses and the importance of mobile learning as a tool for teachers.

This paper presents a design for a cutting-edge English program in which elementary school learners of English as a foreign language in Taiwan had lively interactions with a teaching assistant robot. Three dimensions involved in the design included (1) a pleasant and interactive classroom environment as the learning context, (2) a teaching assistant robot designed and built by the researchers as instructional technology (instructional tool/medium), and (3) the need for improved motivation and learning outcomes and positive learning experiences of the students as the core research problem. This Human–Robot Interaction (HRI) led to better pedagogical effects on learning and teaching by (1) employing a vivid, enjoyable teaching approach; (2) adopting practical, interesting learning materials; and (3) creating a natural, enjoyable learning context. Both quantitative and qualitative findings of this study indicate that the students' English learning experiences were enhanced, as were their motivation and learning outcomes as a result of this HRI. This paper, instead of merely suggesting design criteria for robots, provides a set of instructional design guidelines that other researchers can follow to create an innovative and enjoyable English classroom that employs an interactive robot as an assistant for enhancing English acquisition while simultaneously reducing the pressure and teaching load of the English instructors. [ABSTRACT FROM PUBLISHER]

Process mining methodologies are designed to uncover underlying business processes, deviations from them, and in general, usage patterns. One of the key limitations of these methodologies is that they struggle in cases in which there is no structured process, or when a process can be performed in many ways. Learning Management Systems are a classic case of unstructured processes since each learner follows a different learning process. In this paper, we address this limitation by proposing and validating the user behavior pattern detection (UBPD) methodology which is based on detecting very short user activities and clustering them based on shared variance to construct a more meaningful behavior. We develop and validate this methodology by using two datasets of unstructured processes from different implementations of a learning management system. The first dataset uses a gamified course where users have the freedom to choose how to use the system, and the second dataset uses data from a massive online open course, where again, system usage is based on personal learning preferences. The key contribution of the methodology is its ability to discover user-specific usage patterns and cluster users based on them, even in noisy systems with no clear process. It provides great value to course designers and teachers trying to understand how learner interact with their system and sets the foundation for additional research in this class of systems. [ABSTRACT FROM AUTHOR]

This paper presents the findings of a mixed-methods research that explored the potentials emerging from aligning learning design (LD) and learning analytics (LA) during the design of a predictive analytics solution and from involving the instructors in the design process. The context was a past massive open online course, where the learner data and the instructors were accessible for posterior analysis and additional data collection. Through a close collaboration with the instructors, the details of the prediction task were identified, such as the target variable to predict and the practical constraints to consider. Two predictive models were built: LD-specific model (with features based on the LD and pedagogical intentions), and a generic model (with cumulative features, not informed by the LD). Although the LD-specific predictive model did not outperform the generic one, some LD-driven features were powerful. The quantity and the power of such features were associated with the degree to which the students acted as guided by the LD and pedagogical intentions. The leading instructor's opinion about the importance of the learning activities in the LD was compared with the results of the feature importance analysis. This comparison helped identify the problems in the LD. The implications for improving the LD are discussed. [ABSTRACT FROM AUTHOR]

Textual data, as a key carrier of learning feedback, is continuously produced by many students within course forums. The temporal nature of discussion requires students' emotions and concerned aspects (e.g. teaching styles, learning activities, etc.) to be dynamically tracked for understanding learning requirements. To characterize dynamics of emotion-aspects, this paper presents an unsupervised model, namely temporal emotion-aspect model (TEAM), modeling time jointly with emotions and aspects to capture emotion-aspect evolutions over time. Especially, the primary output of TEAM is two-fold: emotion-specific aspect probabilistic distributions and their evolutions over time. With the discussion data from two online course forums, we validated the performance of TEAM and utilized this model to discover most concerned emotion-aspects as well as their evolutionary trends for the whole learning group and different achievement levels of groups, respectively. The results indicated that, (1) content-related aspects were the main focus with higher probabilities to negative and confused emotions; (2) there were higher probabilities of emotional expressions in the initial and final stages of a semester; (3) compared with high- and medium-achieving students, low-achieving students were less active in emotional engagement on the whole, and tended to express more confusion in the final stage of a semester. [ABSTRACT FROM AUTHOR]