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During the COVID-19 pandemic, many online lessons for emergency remote teaching (ERT) were recorded. However, little is known about how these recordings can be reused as resources for students' active learning. This study aimed to design a post-video learning approach that uses recorded videos of lessons to remediate students' learning losses associated with the pedagogical challenges of ERT. Two classes (54 students in total) with two teachers of general studies and mathematics in a Hong Kong primary school participated in a quasi-experimental study in which they used an approach integrating video selection, visualizations of classroom dialogues, a discussion forum, and quizzes for 10 weeks. After the intervention, the students' mathematics knowledge had improved significantly relative to a comparison group, while the general studies class did not show significant changes. Eight students and two teachers were interviewed about their experiences with the post-video learning approach. The approach appeared to be a pedagogically meaningful way of engaging students in active learning activities and addressing the challenges raised by ERT by recycling recorded lessons. The results of this study also suggest that recorded lessons can be useful learning materials beyond tertiary education as they cater to younger learners' needs in video-based learning by, for example, segmenting class videos, using visualization for easier viewing, and including discussion forums and quizzes for enhanced interaction. The design implications of using video segments and visualized representations of classroom interactions as learning materials and how to foster knowledge co-construction through forums and quizzes are also discussed.

The absence of instructional support during peer feedback prevents students from engaging with peer feedback. This study adopted regulated dialogic feedback as the instructional foundation and investigated its impact on students' engagement using an experimental research design. Students in the experimental group (n = 26) performed the feedback practice with a regulated dialogic feedback approach through three phases, each involving a different regulation type: 1. negotiation and coordination of feedback activities involving shared regulation of learning (SSRL); 2. feedback provision and discussion to support its uptake involving co-regulation of learning (CoRL); and 3. translation of feedback into task progress involving self-regulation of learning (SRL). Students in the control group (n = 25) performed the feedback practice without the regulated dialogic feedback approach in an online discussion forum. The study lasted for 10 weeks for both groups. The research data included students' responses to peer feedback engagement surveys, students' learning behaviors, and the transcripts of interviews with students. The survey results show that the regulated dialogic feedback led to a higher cognitive, emotional, and behavioral engagement with the feedback practice. Based on the feedbackrelated learning behaviors, this study found that the SSRL, SRL, and CoRL processes can potentially promote cognitive, emotional, and behavioral engagement. Extreme case analysis demonstrated how the support for SSRL, SRL, and CoRL promoted engagement in all three areas (cognitive, behavioral, and emotional). Pedagogical implications were provided for creating engaging dialogic feedback practices.

This study compares the interaction patterns of a novice and an experienced instructor using Social Network Analysis (SNA) and content analysis and explores how students' interactions, degrees of satisfaction, and cognitive presence differ according to the different interaction patterns of the two instructors. Results showed some differences in the interaction characteristics between the sections. First, the experienced instructor was the most powerful actor in the course, while some students in the novice instructor's section showed higher outdegree centrality than the instructor. In addition, the novice instructor's section was a more active network than the experienced instructor's section in which the instructor showed the highest outdegree and indegree and also seemed to have more reciprocal relations. In terms of satisfaction and cognitive presence levels, the students in the experienced instructor's section in which the instructor focused more on triggering events or exploration activities, reported higher satisfaction than the students in the novice instructor's section. However, there was no significant difference in students' cognitive presence levels. A key finding of research suggests that instructors need to balance their participation, stimulate students' curiosity, and encourage brainstorming--rather than directly offering solutions--to improve students' satisfaction in asynchronous discussion-based online learning. This research also indicates that well-designed discussion topics may contribute more to developing students' cognitive presence than the instructor's interaction patterns. Finally, this research highlights the effectiveness of SNA and content analysis to explore instructors' and student interactions on discussion boards.

The purposes of this study were to explore students' learning performance, knowledge construction, and behavioral patterns in computer-supported collaborative learning (CSCL) online discussions with/without using Form+Theme+Context (FTC) model guidance scaffolding in visual imagery education. In the online learning activities, the control group did not use the FTC model guidance scaffolding, while the experimental group did. This study employed quantitative content analysis and sequential analysis to investigate the discussion content and behavioral patterns of 63 students from a private university in Taiwan during online discussion learning activities. Results showed that the learning performance of the students in the experimental group outperformed that of students in the control group. Moreover, the study revealed that the two groups of students were primarily sharing or comparing information during discussion. More behaviors of exploring opinions and concepts and communicating or constructing knowledge among group members were observed in the experimental group. Secondly, students in the experimental group participated more in knowledge construction than did students in the control group, and their behavioral patterns were more diverse. Accordingly, this study shows that incorporating the FTC model into learning with sufficient guidance from the instructor could be useful for improving students' visual imagery analysis abilities.

This study investigated how English learners complete multimodal formative quizzes. Participants included 17,950 students enrolled in a mandatory English for Academic Purposes course at a university in Hong Kong. We retrieved data from Blackboard, a learning management system, and conducted a two-step cluster analysis to examine student self-regulated learning (SRL) profiles with the quizzes. We first identified five clusters of learners with distinctively different self-regulated learning patterns. Then, we performed a multivariate analysis of variance (MANOVA) to further explore their differences in SRL, in terms of start day, days started before deadline, differences in scores between first and last attempt, and scores in language learning activities. Our findings echoed those of previous studies on the relationship between self-regulated learning and academic success. This research enables us to better understand the needs of EAP students in Hong Kong.

Given the importance of digital technology in daily life, computational thinking (CT) has become a necessary skill for everyone, not just for computer scientists. For CT development, students need to receive appropriate social learning support. However, instructors find it difficult to provide such support to many students in online courses. This study aimed to examine the effectiveness of e-mentoring via social network services (SNS) in developing students' CT during large-scale online courses. A total of 327 undergraduate students volunteered to participate in this study, which included 16 weeks of lectures aimed at developing CT. The effects of SNS-based e-mentoring on CT development, the influences of each e-mentoring activity on CT development, and gender differences were analyzed using data on participants' CT assistance scores and their utilization of e-mentoring activities. The findings indicated that SNS-based e-mentoring was effective in developing the CT of undergraduate students' engagement in a large-scale online course. The most influential ementoring activities for students' CT development were informational and technical support in a group and informational support in a private environment. Female students benefited more from SNS-based e-mentoring than male students, and they also engaged in more types of e-mentoring activities than male students. Participation in SNS-based e-mentoring was found to lower the gap in CT between students with and without prior learning experience. Our study findings can be used by educational institutions and instructors when designing courses for students' CT development in large-scale online courses or when developing strategies to close the gender gap in CT ability.

Although artificial Intelligence (AI) is prevalent and impacts facets of daily life, there is limited research on responsible and humanistic design, implementation, and evaluation of AI, especially in the field of education. Afterall, learning is inherently a social endeavor involving human interactions, rendering the need for AI designs to be approached from a humanistic perspective, or human-centered AI (HAI). This study focuses on the use of essays as a principal means for assessing learning outcomes, through students' writing in subjects that require arguments and justifications, such as ethics and moral reasoning. We considered AI with a human and student-centric design for formative assessment, using an automated essay scoring (AES) and feedback system to address issues of running an online course with large enrolment and to provide efficient feedback to students with substantial time savings for the instructor. The development of the AES system occurred over four phases as part of an iterative design cycle. A mixed-method approach was used, allowing instructors to qualitatively code subsets of data for training a machine learning model based on the Random Forest algorithm. This model was subsequently used to automatically score more essays at scale. Findings show substantial agreement on inter-rater reliability before model training was conducted with acceptable training accuracy. The AES system's performance was slightly less accurate than human raters but is improvable over multiple iterations of the iterative design cycle. This system has allowed instructors to provide formative feedback, which was not possible in previous runs of the course.

This study investigates the role of self-efficacy in an asynchronous online English course enriched with interactive features. Self-efficacy is a strong predictor of academic achievement in conventional classrooms. However, when learning happens in an online environment, the students' learning achievement is also affected by their psychological perceptions of online learning. In this study, the relationship between self-efficacy and affective factors (i.e., learner autonomy, learner-content interaction, and perceptions toward transactional distance) was investigated. The aims of this study were to identify the influence of different levels of self-efficacy on these factors and to explore their relationships in an online EFL course. In total, 286 students were administered the questionnaires before and after the curriculum to probe their self-perception of these affective variables. When asynchronous interactive learning materials came into play, learners with different levels of self-efficacy make statistically different learning achievements. The statistically significant differences were also found between the student's self-efficacy level, their learner autonomy, and their perception toward the interactive contents. However, the difference was not significant between self-efficacy and transactional distance. The cost of asynchronous learning is an increasing transactional distance due to the lack of instructor-learner interaction. This study suggests that interactive content triggered an opposite effect by making the instructor's role invisible rather than absent. A good online course must balance the student's self-determined learning and flexibility with the course structure. Interactive learning content can keep the balance between developing learner autonomy and fostering engagement by dissolving the teacher's role into interactive course material.

Due to the varied social inequities, the pandemic has prompted unprecedented attention to the social divides in learning gains via online/blended learning. It has been identified that approximately 27,000 Chinese cross-border students live on the Mainland but attend Hong Kong schools every day. The pandemic has restricted the passage of the Shenzhen-Hong Kong border, and these students suffer greatly as they may still be forced to attend online lessons at home for over two years, even if schools return to face-to-face teaching. This study is a 2-year longitudinal case study with a purposeful sampling of a primary school that has over 70% of Chinese cross-border students. A mixed-methods approach was adopted to examine students' online learning experiences via teachers' interviews. Regarding their learning challenges, 35 students were invited to complete a 5-point Online Self-regulated Learning Questionnaire (OSLQ) and an open-ended opinion survey, which was then triangulated with teachers' feedback. First, this study has identified three major challenges that cross-border students suffer the most in online learning: self-regulation strategies, technical challenges, and social interaction. Second, several teaching strategies have been found to offer additional support (e.g., after-school classes and learning centers in Shenzhen) for cross-border students to sustain their online learning and alleviate their learning challenges. Based on these findings, this study contributes to documenting the learning challenges for cross-border students during the pandemic, which provides insights for other schools to facilitate cross-border education and develop appropriate online learning strategies for cross-border students.

Help seeking is a self-regulated learning strategy, and peer help is an important form of interaction in online education. Yet, students often do not seek help even at the cost of lower performance. To understand the factors behind online students' commitment to peer help, this study implemented a peer-help discussion forum in an online course and investigated the relationship among students' help-seeking profiles, epistemic beliefs (EB), and their actual participation in peer help. The findings revealed a significant relationship between students' EB and the number of response posts in the peer-help forum. Moreover, EB moderated the relationship between students' help-seeking profiles and the number of response posts. Theoretical and practical implications are drawn from the findings.

In educational reform, people actively promote educational innovation by applying intelligent technology. As the main participants in education, people experience a series of psychological and cognitive changes in the teaching process. This autonomy and uncertainty will directly affect the effect of network teaching. Due to the variability in the characteristics of individuals, following the psychological perception and subjective value of people and optimizing the development of wisdom education with a reasonable technical cognitive attitude have become a focus. This study uses the grounded theory method to conduct in-depth interviews and questionnaire surveys on 330 e-learners and extracts 400 codes, 38 concepts, 9 categories and 4 core categories. This paper reconstructs the theoretical model of psychological distance in the network education process and identifies four new dimensions: cost distance, initiative distance, control distance and interaction distance. In addition, the four dimensions reflect four core value needs of learners for online education: convenience, self-efficacy, self-identity and binding force. The paper provides a good theoretical basis to improve the user experience and satisfaction in online education and optimize the level of intelligent education.

With the rapid increase of online learning and online degree programs, the need for a secure and fair scoring mechanisms in online learning becomes urgent. In this research, a secure scoring mechanism was designed and developed based on blockchain technology to build transparent and fair interactions among students and teachers. The proposed scoring mechanism was implemented by employing the Ethereum blockchain and its three autonomous smart contracts. The robustness and feasibility of the system was then verified with experiments. The resulting system is shown to be superior to existing online learning systems because it prevents answer tampering. In addition, fairness can be improved with blockchain protocols and a collaborative scoring policy. Lastly, this system helps manage interactions among students and teachers during the process of educational assessment, and encourages all on-chain members to trust the online learning process. These advantages improve peer evaluation and self-directed learning that are essential for a student-centered and collaborative learning environment.

In this paper, a multi-mode digital teaching approach is proposed based on the use of the VARK (Visual, Aural, Read/Write, Kinaesthetic) model where students have different styles (one or more) that improve their learning (face-to-face and online). Our research question is on the effectiveness of this approach in terms of learning efficacy and students' satisfaction. An experiment with 41 students has been carried out for five months to answer the research question and to provide a first validation of using VARK for multi-mode digital HCI teaching. During the experiment, the theoretical sessions were given through videoconference using Microsoft Teams and with the support of Moodle. In the practical sessions, students had to create a software prototype following a User-Centred Design with a real client. For this, they used Discord to collaborate in their groups, Teams to ask questions to teachers and PowerPoint and Genially to present their work online to the class through a Teams videoconference. A regression model has been provided to predict the VARK indicated by the questionnaire to each student with a prediction success of nearly 77%. Using the VARK multi-mode digital teaching approach has proved valid, and effective and beneficial in the teaching of HCI with a significant improvement in the learning scores and satisfaction levels of the students even with respect to pre-COVID-19 where the teaching was face-to-face.

A newly emerged micro learning service offers a flexible formal, informal, or non-formal online learning opportunity to worldwide users with different backgrounds in real-time. With the assist of big data technology and cloud computing service, online learners can access tremendous fine-grained learning resources through micro learning service. However, big data also causes serious information overload during online learning activities. Hence, an intelligent recommender system is required to filter out not-suitable learning resources and pick the one that matches the learner's learning requirement and academic background. From the perspective of natural language processing (NLP), this study proposed a novel recommender system that utilises machine translation and language modelling. The proposed model aims to overcome the defects of conventional recommender systems and further enhance distinguish ability of the recommender system for different learning resources.

This paper evaluates an international, online, content skills-based teacher education program sponsored by the U.S. State Department. The evaluation was designed using a RUFDATA framework (Saunders, 2000) to facilitate a complete, reflective assessment of the target program. Establishing causes-and-effects of the program's performance and data analysis involved adoption of a Contribution Analysis (Mayne, 2001; Mayne, 2008). Utilizing the six steps detailed in Mayne (2012), a credible contribution story emerged, highlighting strengths and weaknesses of transitioning teacher-training programs to virtual platforms. This evaluation has implications for teachers, teacher trainers, professionals planning similar programs particularly in developing regions, and individuals interested in how theory can be applied practically to impact continued teacher education processes. This paper contributes to knowledge as there are few formal evaluations of online international teacher education programs that facilitate observation of all aspects of a virtual course over an extended period of time and provide small-group engagement with course creators, especially with populations straddling the digital divide. It is also the first to conduct a theory-based evaluation of a U.S. English Language Specialist project despite the program's 1991 inception and current running rate of 150-200 projects annually worldwide (U.S. Department of State, 2021).

The study aimed to examine the readiness of faculty members in Arab universities for blended learning environments through an investigation of the attributes, skills, and knowledge in three roles of professional online teachers. Online teaching professionalism has been described as a set of required competencies, and behaviours for the effectiveness of educational online sessions. The authors have argued some requirements of teachers' roles as an instructional planner, an assessor, and as a mentor. A purposive sample of 24 experts from diverse disciplines contributed to the reference panel in a Delphi study through three rounds. Qualitative content analysis and some descriptive statistics e.g., the median and frequency distribution, have been used to reach a consensus among the panel of experts. A matrix of 30 requirements was shortlisted by experts in different roles. The panelists provided insight into the top 10 requirements for each role to measure the professionalism of faculty before, during, and after the online sessions. The readiness for online teaching was concluded by six main domains namely evaluating students' achievements and limitations, problem-solving skills, information technology and computer skills, monitoring and motivating techniques, communication, and class management skills. The study results can be used to plan faculty development programs based on performance gaps of faculty members at three levels: individual, departmental, and program or college. Moreover, the listed faculty attributes help higher education institutions to evaluate the perceptible skills and personal characteristics of faculty in enhancing the efficacy of online teaching in different academic disciplines.

Collaborative reflection (co-reflection) plays a vital role in collaborative knowledge construction and behavior shared regulation. Although the mixed effect of online co-reflection was reported in the literature, few studies have comprehensively examined both individual and group factors and their relationships that affect the co-reflection level. Therefore, this study explored the structural relationships between achievement goals (task-based, self-based, and other-based goals), online community identification, and co-reflection, which can consequently assist instructors in improving the related pedagogical strategies. To this end, 26813 posts on MOOC and college online learning platforms were gathered. Specifically, deep learning techniques were first used to train a classifier that classifies the large-scale co-reflection text automatically. The Bayesian method was then applied to disclose the structural relationships among achievement goals, community identification, and co-reflection. The results showed that the proposed classification algorithm achieved the best performance. Two best-fit models for characterizing the respective relationships between co-reflection and community identification as well as achievement goals were obtained using the Bayesian method. The results of the experiments on these two models demonstrated that both task-avoidance and other-avoidance goals were related directly to co-reflection, all task-approach, self-approach and other-approach goals were related indirectly to co-reflection, but self-avoidance goals had both a direct and an indirect relationship with co-reflection. The relationship between community identification and co-reflection was mediated by other-based goals. Some theoretical and practical implications were discussed for instructors and practitioners to build an online community.

Massive open online courses (MOOCs) provide numerous open-access learning resources and allow for self-directed learning. The application of big data and artificial intelligence (AI) in MOOCs help comprehend raw educational data and enrich the learning process for students and instructors. Thus, we created two deep neural network models. The first model predicts learning outcomes on the basis of learning behaviors observed when students watch videos. The second is a novel exercise-based model that predicts if a student will correctly answer examination questions on relevant concepts. The study data were collected from two courses conducted on the National Tsing Hua University's MOOCs platform. The first model accurately evaluated student performance on the basis of their learning behaviors, and the second model efficiently predicted student performance according to how they answered the exercise questions. In conclusion, our AI system remedies the present-day inability of MOOCs to evaluate student performance. Instructors can use the systems to identify poor-performing students and offer them more assistance on a timely basis.

Online discourse is widely used in diverse contexts of learning and professional training, but superficial interactions and digression often occur. In the face of these problems and the large-scale unstructured text data, the traditional way of learning analytics has been challenged in terms of providing timely intervention and feedback. In this paper, a workflow for automatically detecting in-service teachers' cognitive engagement in an online professional learning community is described. Discourse data of 1834 in-service teachers involved in a teacher professional development program was collected and processed using the Word2vec toolkit to generate lexical vectors. The method of vector space projection was used to calculate the new information contained in each post, cosine similarity was used to calculate topic relevance, and cluster analysis was used to explore in-service teachers' discourse characteristics. Results showed that in-service teachers' average contribution was 4.59 posts and the average length of each post was 39.47 characters in Chinese. In the mathematics online professional learning community, the average amount of new information contained in each post was 0.221 and in-service teachers' posts contained much new information in the early stages of online discourse. Most in-service teachers' posts were relevant to the discussion topic. Cluster analysis showed three different groups of posts with unique characteristics: high topic relevance with much new information, high topic relevance with little new information, and low topic relevance with little new information. Finally, limitations are discussed and future research directions are proposed.

Although online learning systems (OLSs) are widely discussed with regard to most forms of higher education, they are still immature in terms of their development and compared to mainstream teaching and learning activities, and their implementation remains a challenge. Few studies have investigated the factors that contribute to students' learning performance in the context of the adoption of OLSs in higher educational institutions. Additionally, among the handful of studies that focus on this research issue, investigating the influences of environmental factors and personal innovativeness on students' learning performance and adoption of OLSs has received very little attention. Consequently, by integrating social cognitive theory and innovation diffusion theory, this study developed a theoretical model of OLS adoption. It empirically validated the model using data collected from 151 undergraduate students who used OLSs. The results showed that key compatibility (as an environmental factor) and personal innovativeness (as a personal factor) had significant direct and/or indirect influences on students' learning performance and continued intentions to use OLSs. Theoretical and practical implications are also discussed.

The question of how to best design an online course that promotes student-centred learning is an area of ongoing research. This mixed-methods study focused on a section of advanced high school students, in college-level mathematics courses, that used a synchronous online environment mediated over web-conferencing software, and whether the affordance of multiple communication channels and student-centred activities affected involvement, cohesion, and satisfaction. Study participants reported that anonymous input and group work activities encouraged their involvement in learning activities, increased their satisfaction, and fostered social cohesion. Although the on-going management of technical issues limited student involvement and satisfaction, there were no differences in final grades obtained by students participating in this delivery format and their peers participating in an alternate learning environment facilitated by video-teleconferencing. This study offers supporting evidence that a student-centred learning environment mediated over web conferencing software can foster social cohesion, student involvement, and student satisfaction.

Personalized language learning (PLL), a popular approach to precision language education, plays an increasingly essential role in effective language education to meet diverse learner needs and expectations. Research on PLL has become an active sub-field of research on technology-enhanced language learning and artificial intelligence applications in education. Based on the PLL literature from the Web of Science and Scopus databases, this study identified trends and prominent research issues within the field from 2000 to 2019 using structural topic modeling and bibliometrics. Trend analysis of articles demonstrated increasing interest in PLL research. Journals such as "Educational Technology & Society" and "Computers & Education" had contributed much to PLL research. PLL associated closely with mobile learning, game-based learning, and online/web-based learning. Moreover, personalized feedback and recommendations were important issues in PLL. Additionally, there was an increasing interest in adopting learning analytics and artificial intelligence in PLL research. Results obtained could help practitioners and scholars better understand the trends and status of PLL research and become aware of the hot topics and future directions.

The rapid and impressive development of Massive Open Online Courses (MOOCs) in less than half a decade has generated contrasting arguments about their social dimension. This paper investigates how the socio-economic background of learners affects their own experience and chances of course completion. The analyses test whether learners with a low socio-economic status (SES) have fewer chances of completing the online course and whether participation in online discussion forums moderates the role of SES. The data comes from two MOOCs provided by Stanford University. We find a negative association between low SES, course completion and course engagement. Moreover, we find that forum participation plays an ambiguous role, reinforcing the advantage of well-educated learners enrolled in one course, while it has no significant effect on the other course. The article concludes with some policy implications on social stratification in MOOCs and with some design suggestions for creators of MOOCs.

Web enhanced active learning has been demonstrated to be an effective approach in Engineering Higher Education, as it provides students with more flexibility in dealing with the development of skills related to professional knowledge. However, students require a sufficient level of self-efficacy and control over their own learning, which might impact negatively on their effort and academic performance. Therefore, promoting self-regulated learning among students would help them to develop effective strategies they could adopt in planning, monitoring and evaluating their learning process. In this paper, a web-enhanced active learning approach is proposed which integrates a self-regulated learning strategy that supports Control Engineering students in managing their learning process. In order to evaluate the effectiveness of the proposed approach, a three-year quasi-experimental study was performed in the context of an undergraduate Automatic Control course at the Università Politecnica delle Marche, Italy. This involved 418 students and 4 teachers. Both quantitative and qualitative measurement tools were used for the evaluation. The results of the study confirmed the effectiveness of a learning design specifically tailored to implement self-regulated learning features in a web-enhanced active learning approach for undergraduate engineering students. Moreover, the qualitative-quantitative evaluation model proved to be effective in capturing and gauging a more comprehensive and detailed picture of the triggered self-regulated learning dynamics.

The practice and application of education data mining and learning analytics has become the focus of educational researchers. However, it is still a difficult task to explore the law of group learning and the characteristics of individual learning. In this study, the online learning logs of 1,088 students from 22 classes were analyzed from the aspects of their login behaviors, resource utilization, quizzes, interactive behaviors, and academic achievement. To address these issues, multiple methods, including statistical analysis, visualization social network analysis and correlation analysis, were used to analyze the process and results of online learning. The results reveal the characteristics of group behavior of online learners and highlight the key factors that influence the learning process and outcomes of individual learners. From the view of students, these factors include the length and allocation of online time, the effective utilization of resources, social interaction, online learning support and services, etc. From the perspective of teachers, the factors include the management of online teaching, the appropriateness of learning resources, the effectiveness of online intervention strategies, the accurate feedback for online learners, etc. Therefore, learning analysis technology can not only standardize the assessment of learning outcomes, but can also focus more attention on the standardization of learning process assessment. It also identifies the main factors that affect the online learning outcomes and the group characteristics of online learners. At the same time, it provides the learners with personalized learning diagnosis reports which can both help learners understand their own learning status and promote instructors' accurate teaching and reasonable evaluation.

Massive Open Online Courses (MOOCs) and Open Educational Resources (OER) are rapidly growing, but are not usually offered in multiple languages due to the lack of cost-effective solutions to translate the different objects comprising them and particularly videos. However, current state-of-the-art automatic speech recognition (ASR) and machine translation (MT) techniques have reached a level of maturity which opens the possibility of producing multilingual video subtitles of publishable quality at low cost. This work summarizes authors' experience in exploring this possibility in two real-life case studies: a MOOC platform and a large video lecture repository. Apart from describing the systems, tools and integration components employed for such purpose, a comprehensive evaluation of the results achieved is provided in terms of quality and efficiency. More precisely, it is shown that draft multilingual subtitles produced by domain-adapted ASR/MT systems reach a level of accuracy that make them worth post-editing, instead of generating them ex novo, saving approximately 25%-75% of the time. Finally, the results reported on user multilingual data consumption reflect that multilingual subtitles have had a very positive impact in our case studies boosting student enrolment, in the case of the MOOC platform, by 70% relative.

This study investigates the impact of students' motivation and personality traits on their academic performance in online and blended learning environments. It was conducted with students attending a mandatory introductory information technology course given in a university in Turkey. The Big Five Inventory and Motivated Strategies for Learning Questionnaire were completed by a total of 316 students. A learning management system (LMS) was used for online collaboration and accessing course materials. At the end of the course, information on the accessibility of LMS and students' academic performance including their exam results was obtained. The Bayesian Structural Equation Modeling was used to examine academic performance in terms of its relationship with motivation and personality. In the online learning environment, the results showed that the conscientiousness trait was significantly related to LMS use whereas in blended learning, there were no significant relations between personality traits and LMS use. Self-efficacy was found to be the predictor of LMS use in the online environment while task value and test anxiety were the predictors in the blended learning environment. Conscientiousness and LMS use were significantly related to course grades in both learning environments. Finally, self-efficacy for learning performance was also associated with course grades in the online learning environment.

Software developers rely on the abundance of online resources to meet their informal learning needs. Designing systems to effectively support this relies on a sound understanding of the informal learning process. In this paper, we show how the development and implementation of an ontological model can be used to increase understanding of informal learning needs and enhance system design. We interviewed developers about their informal online learning behaviors, and created a novel ontological model, LILO (Learning Informally Online), to represent user interaction with online learning resources by incorporating the resulting concepts, typologies, and relationships. From this ontology, we derive five main design requirements for an informal learning system for developers: keyword support, search support, resource genre utilization, reliability cues, and objective support. We then demonstrate how the ontology can be applied to advance system design using as an example CAN (Composable Accessibility Infrastructure), a system capable of supporting web developers' informal online learning.

Computer-graders have been in regular use in the context of MOOCs (Massive Open Online Courses). The automatic grading of programs presents an opportunity to assess and provide tailored feedback to large classes, while featuring at the same time a number of benefits like: immediate feedback, unlimited submissions, as well as low cost of feedback. The present paper compares Algo+, an automatic assessment tool for computer programs, to an automatic grader used in a MOOC course at EPFL (Ecole Polytechnique Fédérale de Lausanne, Switzerland). This empirical study explores the practicability and behavior of Algo+ and analyzes whether it can be used to evaluate a large scale of programs. Algo+ is a prototype based on a static analysis approach for automated assessment of algorithms where programs are not executed but analyzed by looking at their instructions. The second tool, EPFL grader, is used to grade programs submitted by students in MOOCs of Introductory programming with C++ at EPFL and is based on a compiler approach (Dynamic Analysis approach). In this technique submissions are assessed via a battery of unit tests where the student programs are run with standard input and assessed on whether they produced the correct output. In this study results showed the advantages and limits of each approach and pointed out how the two tools can be used to get a benefit assessment of students' learning in MOOCs of computer programming. This study led to the proposition of a model for the relationship between the number of submissions and the appearance of the most frequent submitted programs. This technique is used by Algo+ for giving feedback and it is based only on the "n" most redundant submissions that have been annotated by the instructor.

Due to their perceived scope and openness to socially underprivileged groups, Massive Open Online Courses (MOOCs) have been presented as tools to enhance social mobility. However, there has also been evidence to suggest that MOOCs are mainly beneficial for privileged groups and could even contribute to an increasing gap in educational opportunities between privileged and underprivileged populations. This systematic review has evaluated 31 empirical studies to examine how MOOCs benefit the socially privileged in comparison to underprivileged groups. The literature has pointed out specific formal barriers that might make MOOCs less accessible for underprivileged learners. In addition, enrollment demographics displayed that the majority of MOOC learners is well educated, employed and from developed countries. Finally, the literature suggested that privileged learners could be more likely to complete a MOOC. Nevertheless, the literature indicated a notable share of underprivileged learners that would otherwise not enjoy higher education. Moreover, it is suggested that certain MOOCs might serve underprivileged learners more than other MOOCs. The implications of these findings and recommendations for future research will be discussed.

Educators seek to develop students' mathematical knowledge retention to increase student efficacy in follow-on classwork, improvement of test scores, attainment of standards, and preparation for careers. Interactive visuals, feedback during problem solving, and incorporation of higher-order thinking skills are known to increase retention, but a comparison of online and face-to-face learning regarding knowledge retention has not been fully explored. The current study tested 38 Caucasian eighth grade students for knowledge retention on ten mathematical topics they had learned in sixth grade during either online or faceto-face conditions. After two years, students were given the same posttest as in 6th grade over the 10 units of which five had been learned online and five face-to-face. Scores for long-term gain scores showed no significant differences between online or face-to-face learning conditions. A TOST calculation was used to show equivalence of middle school student long-term learning across online and face-to-face conditions in mathematics in this study within the limits of the test. The interactive nature of each condition contributed to strong mathematical understanding, which led to the retention being equivalent for both conditions.

Physical design projects are a way to motivate and engage students in authentic science and engineering practices. Web-based tools can support design projects to ensure that students address and reflect upon critical science concepts during the course of the project. In addition, by specifying challenging design goals that require students to consider potential trade-offs between features, web-based tools may promote more deliberative scientific inquiry than open-ended or feature maximization goals. To study the role of web-supported projects, we developed an online curriculum that guides students through the planning, building, and analysis of self-propelled vehicles. To address content related to energy transformation we incorporated virtual models that display dynamic graphs of energy levels as a virtual scooter travels along a path. We compared two design goals for the project with different constraints. In the "target" version students are prompted to build virtual and physical scooters to reach a specific position. In the "distance" version students are prompted to maximize the distance the scooter travels. Our results indicate that students learned energy concepts from both versions; however, students with the "target" version did refer to the virtual model in their posttest responses to a greater degree than those with the "distance" version.

This study investigated the characteristics of deep and surface approaches to learning in online students' responses to instructor's qualitative feedback given to a multi-stage, ill-structured design project. Further, the study examined the relationships between approaches to learning and two learner characteristics: epistemic beliefs (EB) and need for closure (NFC). Four emerging themes were identified where the students' approaches to learning spread along a spectrum of deep to surface learning: "number of feedback items addressed," "understanding of feedback," "quality in addressing feedback," and "holistic thinking." In addition, the maturity of EB was likely to be associated with students' understanding of feedback and the systematic and relational thinking demonstrated in their responses to feedback. The relationship was unclear between NFC and deep/surface learning characteristics. The findings provide implications for the design of feedback to scaffold deep learning in ill-structured problem solving.

Online participation in collaborative online learning environments is instrumental in motivating students to learn and promoting their learning satisfaction, but there has been little research on the technical supports for motivating students' online participation. The purpose of this study was to develop a visualization tool to motivate learners to participate actively in collaborative online learning communities and examine its effects on online participation, perceived learning, perceived satisfaction, team project performance, and usability. Two types of visualization tool were developed: the A-type for representing group participation and interaction between groups, and the B-type for representing group participation and individual participation. Undergraduate students (N = 118) were assigned randomly to one of three groups (A and B: experimental group, C: control group). The results showed that two types of visualization tools have significant effects on the perceived satisfaction, perceived learning, and team project performance. Regarding online participation, the B-type of visualization tool was found to be effective. The usability of the A and B groups was similar and many learners in both groups reported that the visualization tool motivated them to participate in online learning. Theoretical, empirical and practical discussions are provided based on the results.

The study presented here is interested in understanding the ways in which social interaction in technology-mediated institutional settings is constrained and afforded by what Pennycook defines as "critical moments" in the educational experience. Drawing on Social Learning Analytics and on the concepts of heteroglossia, contingency and chaining, this paper critically discusses a methodology that allows the analysts, and ultimately learners and educators, to follow and visually represent the mobility of the learners-in-concert-with-tools across space, time and language varieties and modalities in technology-mediated communication. The empirical data focused on here is drawn from a large project which includes 40 hours of naturally occurring interactional materials, generated through screen recordings of online sessions of an Italian for Beginners course offered by a Swedish university in the videoconferencing platform Adobe Connect. Preliminary findings suggest that the environment, both in terms of what happens inside and outside the virtual learning site, is of primary importance when it comes to the organization of the interaction among individuals in terms of what becomes the participants' focus during the encounters. A visual representation through a multivocal approach of this mobility of learners, topics and tools will, it is suggested, support learners, educators and designers in locating where and when in the interaction "critical moments" have occurred, in order to understand how such shifts in focus support or hinder the learning experience.

This paper is based on the deliberations of the Assessment Working Group at EDUsummIT 2015 in Bangkok, Thailand. All of the members of Thematic Working Group 5 (TWG5) have contributed to this synthesis of potentials, concerns and issues with regard to the role of technology in assessment as, for and of learning in the 21st century. The group decided to focus primarily on formative assessment rather than summative assessment and high stakes testing. Formative assessments and feedback provide an important opportunity to support and enhance student learning. Recognizing shifts in education towards blended and online learning with problem-based and inquiry-based approaches led to considerations of technologies that could effectively support formative assessment and informative feedback to 21st century learners. The paper concludes with a summary of conclusions and recommendations of the working group to be taken up in subsequent efforts.

As education has turned towards technology to provide academic support, the incidence of e-tutoring has grown due to decreasing educational budgets and as a potential remedy for the generational digital divide. However, many service-learning e-tutoring studies have focused on tutees' academic achievement and tutors' cognitive development rather than tutors' moral development. The purpose of this study is to develop a literature-based instrument related to service-learning e-tutoring in order to explore college students' development of moral reasoning competencies as a result of their service as online tutors for rural primary students. By reviewing the literature on service-learning and conducting interviews, content analysis is applied to identify the moral reasoning factors; then factor analysis is conducted to assess the reliability and validity of the moral reasoning questionnaire for e-tutoring. Five competencies, including moral character, problem solving, caring, empathy, and social interaction,--are recognized. Further study is needed to better ascertain the range of educational and personal gains in both tutor and tutee that result from service-learning e-tutoring.

Education is a basic human right. In pursuit of this right, governments in developing countries and their donors often invest scarce resources in educational initiatives that are sometimes not sustainable. This paper addresses the problem of selecting a sustainable learning technology intervention (LTI) for a typical developing country. By solving this problem, more sustainable LTIs can be selected for implementation; this will in turn improve the efficiency with which limited resources are utilised, thereby allowing greater access to education for all. The paper introduces a unique decision framework for project selection by combining "soft" and "hard" decision analysis techniques. The selection problem is modelled as a multi-criteria decision-making (MCDM) problem and a combination of the Future Search Conference technique and the Analytic Network Process (ANP) is used to develop a decision tool for selecting the most sustainable LTI for a developing country. Our analysis revealed that of the nine LTIs considered, "school on wheels" was the most sustainable LTI in the collective opinion of all the experts involved in this study.

Due to the increasingly multicultural nature of e-learning environments, it is critical that instructors and instructional designers be aware of the importance of cultural factors in education and that they deliver culturally adaptive instruction. The main challenge of this paper is identifying the critical success factors for multicultural online learning from learners' perceptions and their relationships with the six-dimensional Hofstede cultural model. Specifically, a categorization of the students' perceptions is proposed by combining multiple correspondence and clustering analyses. To that end, two surveys were conducted in four e-learning universities in four different countries: Spain, the USA, China, and Mexico. Findings from clustering analysis show that learners are categorized according to their autonomy levels at the beginning of the educational process, and they are classified according to their satisfaction levels at the end of the instruction.

The purpose of this qualitative study was to understand activities and behaviors of learners and instructor in an online programming course. Adobe Connect web conferencing system was used as a delivery platform. A total of fifty-six sophomore students attending a computer education and instructional technology program (online) participated in this study. Data were collected through observations of twenty-two online course recordings and semi-structured interviews. The findings were discussed through Mwanza's Activity notations based on Activity Theory. The results indicated that, by using web conferencing tools, students could develop programming knowledge through the learning tasks by interacting each other. The instructor acted as a key role in constructing the online learning community. Opportunities of getting instant feedback, acting in online collaborative activities and sharing features of the system contributed to students' learning. Also, it is suggested that; both conceptual and strategic structures of the programming courses should be taken into consideration while using web conferencing.

In this study, we assessed the communication structure in an educational online learning environment using social network analysis (SNA). The communication structure was examined with respect to time, and instructor's participation. The course was implemented using ELGG, a network learning environment, blended with face-to-face sessions over a 14-week period. Data were collected from 114 undergraduate students who were enrolled in Instructional Technology and Material Design course. The program functions on the basis of a matrix; in this case a square matrix with rows and columns being the students' ID numbers. Density and centrality measures were visualized and interpreted. In terms of the density of the groups, it was found that the lowest density occurred during the first week. The highest density, on the other hand, occurred during the week when the instructor participated, in all the groups except for the third and sixth groups. The students placed in the center and those on the edges of the network differed on the basis of time as well as the instructor's participation. Other online learning environments could be assessed in a similar fashion using SNA in order to understand levels of participation and changes in interaction over time.

Massive open online courses (MOOCs) have developed rapidly and become tremendously popular because of their plentiful gamification designs, such as reputation points, rewards, and goal setting. Although previous studies have mentioned a broad range of gamification designs that might influence MOOC learner engagement, most gamified MOOCs fail to meet learning objectives because of a lack of research regarding suitable game design, as well as poor rationale for or design of gamification mechanics. This study aims to explore and identify engaging gamification mechanics for MOOC learners. We conducted a focus group interview with 25 MOOC frequent users to identify 40 gamification mechanics. This study then determined the relative engagingness of these gamification mechanics by administering an online survey to 5,020 MOOC learners. The results indicated that the 10 most engaging gamification mechanics accounted for more than 50% of the engagingness. The mechanics of the Where's Wally game is extremely engaging for MOOC learners; however, it has not been demonstrated in previous relevant studies. Finally, we discuss the top five engaging gamification mechanics and their implications.

This study sought to establish a baseline for understanding the epidemiology of online K-12 students with special health care needs, determine the prevalence in K-12 online schooling of students from certain racial/ethnic backgrounds, those with socioeconomic disadvantages, and determine how these students perform in online classes compared to their prior experiences in traditional, face-to-face programs. Data from two different studies was used to address these questions with the goal to support virtual K-12 schools, blended programs, and teachers as they continue to implement best practices for all students. Students with special health care needs attending virtual school are underrepresented in the literature. A possible explanation is that these students are not identified. However, current research suggests that high-risk students, with or without a disability, are choosing virtual school as a viable option (Cavanaugh, Repetto, & Wayer, 2011). The Children with Special Health Care Needs screener can be used to identify these students in order to provide support beyond their Individualized Education Program (IEP). Students who need extra support, self-pacing, or cannot attend school physically can potentially benefit from virtual schooling.

In the twenty-first century, online learning has evolved as a worldwide platform to connect, collaborate and engage users in the learning process. Online learning today is integrated with social network connectivity, which builds an ecosystem for interaction between students, teachers, and professors from every corner of the world, providing them with free and accessible online resources. However, in order to promote active engagement of the learners and delivery of meaningful learning in the online learning settings, it is also necessary to determine students' perceptions towards online learning. The aim of this study was to develop a scale for determining students' perceptions of online learning (POSTOL). This scale consists of four dimensions: instructor characteristics, social presence, instructional design, and trust. Research data was collected from 208 Taiwan university students. In order to determine the validity of the scale, exploratory factor analysis, and confirmatory factor analysis and item discrimination was used. Results showed that the POSTOL is a valid and reliable instrument. The implications of the present study are important for instructional designers, educators, and institutions that are planning to offer, or are currently offering, online courses.

As cyberschooling options expand, it is vital that we understand the nuances of these particular learning opportunities. Because little research exists on leaders of K-12 cyberschools, this exploratory case study had two purposes. We first examined how 18 cyberschool leaders in the United States obtained their position. Second, we explored the perceptions of cyberschool leaders regarding the differences between their job and that of a traditional brick-and-mortar school leader. We found that cyberschool leaders tend to be predominantly new, technology savvy administrators who have some background in online learning. Main differences between cyberschool leadership and brick-and-mortar school leadership included interactions with students, teacher supervision, provision of professional development, and management of the day-to-day operations.

E-learning systems have witnessed a usage and research increase in the past decade. This article presents the e-learning concepts ecosystem. It summarizes the various scopes on e-learning studies. Here we propose an e-learning theoretical framework. This theory framework is based upon three principal dimensions: users, technology, and services related to e-learning. This article presents an in-depth literature review on those dimensions. The article first presents the related concepts of computer use in learning across time, revealing the emergence of new trends on e-learning. The theoretical framework is a contribution for guiding e-learning studies. The article classifies the stakeholder groups and their relationship with e-learning systems. The framework shows a typology of e-learning systems' services. This theoretical approach integrates learning strategies, technologies and stakeholders.

Currently there is an increasing trend to implement functionalities that allow for the development of applications based on Cloud computing. In education there are high expectations for Learning Management Systems since they can be powerful tools to foster more effective collaboration within a virtual classroom. Tools can also be integrated with these systems that can provide assistance to students on any topic covered in class through the proliferation and popularity of publicly available Web APIs. However, generally most students and teachers still face technological barriers to access these resources and integrate them into their educational systems. This paper discusses an effort to overcome this problem by proposing a method of resource access through linked data, which is explicitly defined with semantic annotations related to the learning environment. Doing so, we are able to decorate the Cloud providers API's, thus providing easy integration into learning applications and important benefits for learning. The effectiveness of our approach has been measured and evaluated through usability methods and cognitive load theory principles.

With the increased use of social media there is a growing interest in using social interaction and social presence in education. Despite this phenomenon, no appropriate methodology was found on effective integrating of both concepts into online learning. In this study, we propose integrating two different kinds of learning tools to provide social interaction and social presence in Personal Learning Environments. We have evaluated the proposed concept in a classroom setting, using a specific social interaction tool and a specific social presence tool. The findings revealed that although the use of the social interaction tool was positively associated with students' academic success, the perceived ease of using the social presence tool was negatively related to students' success.

In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we refer to its structural, position and relationship attributes. Analysis of data collected from an elearning environment shows that rather than performance, social learning correlates with properties of social networks: (i) structure (density, inter-group and intra-network communication) and (ii) position (efficiency), and (iii) relationship (tie strength). In particular, individuals who communicate with internal group members rather than external members express higher tendencies of "content richness" in social learning. The contribution of this study is three-fold: (i) a theoretical development of a social network based model for understanding learning and performance, which addresses the lack of empirical validation of current models in social learning; (ii) the construction of a novel metric called "content richness" as a surrogate indicator of social learning; and (iii) demonstration of how the use of social network analysis and computational text-mining approaches can be used to operationalize the model for studying learning and performance. In conclusion, a useful implication of the study is that the model fosters understanding social factors that influence learning and performance in project management. The study concludes that associations between social network properties and the extent to which interactions are "content-rich" in eLearning domains cannot be discounted in the learning process and must therefore be accounted for in the organizational learning design.

Learning English is an important and challenging task for English as Foreign Language (EFL) students. Educators had indicated that, without proper learning support, most EFL students might feel frustrated while learning English, which could significantly affect their learning performance. In the past research, learning usually utilized grouping, but few studies have considered the difference in group members' learning styles. In this study, a learning style-based collaborative learning approach is proposed to cope with this problem. To evaluate the effectiveness of the proposed approach, an learning style-based online collaborative learning platform has been developed. Moreover, an experiment has been conducted on a university English course to compare the learning performance and learning interest of the students who learn with the proposed approach and those who learn with the conventional collaborative learning approach. It was found that the homogeneous learning style groups outperformed the heterogeneous groups. Besides, those students who used the online English collaborative learning approach outperformed those who used the traditional paper-based English collaborative learning approach. Sequence analysis was also carried out to analyze the students' online discussion.