E-learning Research Articles

Developing an integrated model for remote teaching amelioration with artificial intelligence (AI) awareness

Purpose This research aims to propose a high-performance-based model of remote teaching where trained teachers (those who deliver lectures by using different tools i.e. Microsoft Team, Zoom, etc.) can get the desired results through artificial intelligence (AI) awareness, knowledge sharing and transformational leadership in the future. Design/methodology/approach This research is quantitative in nature and convenience sampling is followed to gather data from 307 trained faculty (those who deliver lectures by using different tools i.e. Microsoft Team, Zoom, learning management systems, etc.) from various universities of the federal capital territory (FCT) Islamabad and district Rawalpindi of Punjab province, Pakistan who worked online from home during novel corona lockdown. SmartPLS is used for data analysis and structural equation modeling is performed to test the suggested model. Findings Results revealed that AI awareness has a significant positive influence on knowledge sharing but exhibited a negative significant impact on teacher performance. Likewise, knowledge sharing acts as a partial mediator; however, transformational leadership moderates between remote working and knowledge sharing. Originality/value During the pandemic, the mode of instruction shifted from physical to online, generating several barriers for teachers who were used to on-campus teaching. This research presented an effective model for knowing the mechanism of possible and reliable implications at educational institutions of developing countries to get the desired outcomes of effective online teaching in calamity situations.

The application of the SPOC teaching model in college elective basketball courses: integrating biomechanical principles for enhanced performance

The SPOC (Small Private Online Course) model is a new teaching model derived from Massive Open Online Courses (MOOC) and is an important direction for the reform and innovation of future higher education. In the practical application of SPOC teaching, subjectivity issues may arise, namely the influence of individual opinions and judgment criteria. The evaluation may focus on certain aspects and neglect others, resulting in incomplete overall assessment results. This paper applies the SPOC teaching model in three time periods: before class, during class, and after class, with a focus on integrating biomechanical principles into the evaluation of student performance in basketball. The study employs various research methods such as literature review, Analytic Hierarchy Process (AHP) analysis, and fuzzy comprehensive evaluation to construct a comprehensive evaluation index system for student ability improvement in SPOC teaching in higher education. This system incorporates biomechanical factors such as movement efficiency, force production, and body mechanics, which are essential for enhancing basketball skills. Based on this, an evaluation method for student ability improvement in college SPOC elective basketball courses is proposed using the AHP-fuzzy evaluation model. This model not only assesses traditional skill metrics but also integrates biomechanical assessments, such as shooting mechanics, dribbling efficiency, and defensive posture. The application of the AHP-fuzzy evaluation model, enhanced with biomechanical insights, demonstrates that his method can effectively improve students basketball abilities. The incorporation of biomechanical principles allows for a more holistic evaluation of student performance, emphasizing the importance of physical mechanics in skill development. The integration of the SPOC teaching model with biomechanical principles in elective basketball courses provides a comprehensive framework for evaluating and improving student performance. By focusing on both skill acquisition and biomechanical efficiency, this approach not only enhances basketball abilities but also fosters a deeper understanding of the physical demands of the sport.

“I Wish There Was a Way to Share”: The Changing Campus Ecologies Around Community College Life Science Courses

ABSTRACT We present a case study of changing campus ecologies for students in life science courses at an urban community college. Through analysis of six surveys (n = 583) over a three-year period, we note how changes in students’ coursework affect their virtual and physical developmental ecologies. Students’ abilities to access peers for academic and social support declined and rose relative to social distancing activities, but upon return even when students could identify accessible peers, they expressed a lack of knowledge for how to form social and academic relationships on campus. Changes in social-distancing policy shaped students’ access to socio-academic integrative moments. Students expressed appreciation for their instructors during the transition to online learning, but encountered a number of social and technical roadblocks to participating effectively. Competing demands on their time, lack of access to the internet and digital tools, constraints produced by digital tools like proctoring software, and a general frustration with the amount of “screen time” that the transition required all undermined students’ formation of learning communities. The lack of third spaces – publicly accessible space that is neither home nor work – created a challenge for students who could not demarcate academic space in their homes. Among life science students were a considerable number who worked in health sciences, a field where pandemic-related burnout was considerably higher. Many of these students expressed plans to slow down their education or leave community college entirely. We identify implications for practice including strategies for instructors to foster community in their classroom.

Aligning and comparing values of ChatGPT and human as learning facilitators: A value‐sensitive design approach

Ethical considerations have become a central topic in education since artificial intelligence (AI) brought both great innovation and challenges to educational practices and systems. Values influence what we believe is morally right and guide how we behave ethically in different situations. However, there is limited empirical research on improving the alignment between the values embedded in technology and the values prioritised by learners. Using the approach of value‐sensitive design (VSD), this study conducted an empirical investigation to explore: (1) how ethical values of learners regarding facilitators were characterised in the online learning environment, (2) how specific features of ChatGPT and human experts as online learning facilitators embody these values and (3) what value tensions occur in the online learning environment. In order to address the research questions, we designed a comparative experiment about online writing and revision facilitated by ChatGPT‐4 and a human expert. We conducted semi‐structured interviews with 59 learners about their learning experiences and feelings after completing the experiment. The results showed that learners prioritised the value of responsiveness, social comfort, autonomy, freedom from bias and privacy during online learning. Compared with the human expert, ChatGPT as a facilitator presented features of tirelessness, friendliness and support for independent decision‐making in embodying the value of social comfort and autonomy. However, ChatGPT struggled to interpret learners' intentions and emotions and posed risks of information leakage, thereby presenting a deficiency in embodying the value of responsiveness and privacy. Value tensions arose both within learners' groups and between learners and other stakeholders, including developers and researchers. These tensions emerged from conflicting ethical values and pragmatic considerations in the online learning environment. Our findings highlight the importance of enhancing value alignment in online learning environments. The strategies for achieving this include developing value‐sensitive AI, leveraging the strengths of AI tools in embodying specific values, and expanding VSD methodology in AI's entire life cycle. Practitioner notesWhat is already known about this topic Using ChatGPT as an online learning facilitator has been demonstrated to have various advantages, but its use also brings ethical challenges, particularly in aligning its features with the values of learners. Value‐sensitive design (VSD) helps improve value alignment by embedding the values of stakeholders into the technology design. However, the values of learners regarding facilitators in online learning environments remain under investigation. What this paper adds We conducted a comparative experiment to investigate the value characteristics of learners, compare embodied features of AI and human experts, and identify the potential tension of values. We found that learners prioritised the value of responsiveness, social comfort, autonomy, freedom from bias and privacy in the online learning environment. We found that ChatGPT has shown advantages in embodying specific values compared with the human expert, but value tensions and misalignment still emerged during online learning. We found that value tensions not only arose within learner groups but also between learners and other stakeholders, such as developers and researchers. Implications for practice and/or policy Educational technology developers should embed stakeholders' values in AI tools to enhance value alignment and seek a balance between their values and the values of the learners. Educators should actively utilise AI as a powerful tool and maximise its advantages in embodying specific values. Researchers should consider expanding VSD methods to the entire life cycle of AI tools to accommodate value dynamism.

Personalized learning path based on graph attention mechanism deep reinforcement learning research on recommender systems

In e-learning, the rapid expansion of learning resources poses challenges for learners in finding suitable materials due to their diverse preferences and cognitive abilities. Consequently, personalized learning path recommendation has emerged as a pivotal research area, especially for advancing e-learning systems. This paper introduces an algorithmic framework that integrates deep reinforcement learning with a graph attention mechanism to tailor learning paths to individual learners. The online course dataset is selected and a series of controlled experiments are conducted on the common recommendation models proposed in the past, and the experimental results are analyzed using a combination of two evaluation indices, such as data evaluation results and model variance. The experimental results show that adding the attention mechanism can significantly improve the accuracy of the model recommendation, compared with the deep reinforcement learning model without adding the graph attention mechanism, the comprehensive scores of the students in the test set were improved by 5.8 and 12.8 points, respectively, and the accuracy was improved by 5.3% compared with the previous deep learning model; the deep reinforcement model used in this paper with the addition of the labeling feedback mechanism was improved by 5.3% compared with the deep learning with feedback mechanism. In the recommendation model, the final scores of the students were improved by 3.7 and 8.2 points, respectively. In addition, the Advanced test set in the recommendation model of the learning path recommended by the student score improvement is more than two times of the Middle test set’s scores improvement, indicating that more learning recommended object knowledge points the richer, the model recommendation accuracy rate is higher. By merging graph attention mechanisms with deep reinforcement learning, our system provides precise recommendations, offering insights into the development of efficient personalized learning path systems and accelerating their educational applications.

Use of AI in Japanese Language Education

The way we learn languages is continuously changing. Traditionally, languages were learned in classrooms. However, as the Internet has become more widespread, more and more learners are learning languages through online courses. For example, about 500,000 learners from around the world have registered to study Japanese “Minato” on (https://minato-jf.jp), an online Japanese language learning platform provided by the Japan Foundation (JF).

Pandemic, pressure and pedagogy: a digital transformation of French business schools?

Purpose The purpose of this study is to investigate how French business schools managed the change to Emergency Remote Teaching (ERT) during the COVID-19 lockdown and to propose a rudimentary framework based on the Technology Acceptance Model. Design/methodology/approach This paper uses exploratory in-depth case studies in four French business schools to analyze the influence of the COVID-19 pandemic on the transition to Emergency Remote Teaching and whether it may lead to long-term Online Learning. Findings Results of this study show that, despite several constraints, French business schools efficiently managed the transition to Emergency Remote Teaching. The findings also suggest that schools may provide Online Learning as way to increase their course offerings. Originality/value This paper contributes to the extant literature on COVID-19 and organizational management by being one of the first studies to explore how French business schools made the transition to Emergency Remote Teaching and its potential long-term impact. To the best of the authors’ knowledge, this is the first paper to apply the Technology Acceptance Model to the digital transformation of the French business schools during COVID-19.

Analysis of Self-Regulated Learning and Learning Style Preference of First-Year Medical Students for E-Learning Optimization

First-year medical students adapt to hybrid education, combining online and offline learning in the new standard era. The various features of e-learning need to accommodate students' skills in self-regulated learning and their preferences, such as learning style preference. Therefore, this research aims to analyze first-year medical students' self-regulated learning skills and learning style preferences in online learning to identify e-learning optimization needs that can facilitate their adaptation to medical education. A descriptive quantitative and qualitative narrative method was conducted through document analysis. The Online Self-Regulated Learning Questions (OSRLQs) were used to obtain quantitative descriptive data on students' self-regulated learning skills, and the learning style preference questionnaire was used to obtain data on first-year medical students. The results showed that first-year medical students require optimization in four domains of the self-regulated learning skills in online learning, including task strategies, time management, help-seeking, and self-evaluation. The analysis yielded 19 categories with three main learning style preferences: a combination of visual and auditory and a combination of visual, auditory, and kinesthetic. This analysis recommends optimizing several e-learning features to improve first-year medical students' self-regulated learning skills and learning style preferences.

Behavior changes to promote preconception health: a systematic review

BackgroundPreconception care is expected to prevent diseases, promote health, and improve pregnancy outcomes. Although a consensus exists on the efficacy of folic acid supplementation and preconception vaccination, evidence regarding comprehensive approaches to preconception care targeting the general population remains lacking. We aimed to identify and examine preconception care programs delivered to reproductive-aged women and men to promote behavioral change.MethodsWe searched the MEDLINE, EMBASE, and CENTRAL databases on November 30, 2023. We included randomized controlled trials (RCTs) and cluster RCTs assessing preconception care programs provided to the general population. We included behavioral change interventions, including screening, counseling, and education, to encourage preconception health. We performed a narrative synthesis of the characteristics and a summary of the intervention effects of the included studies.ResultsWe identified 26 trials (from 29 reports). Most of the studies recruited women. The most common study setting was healthcare services, and various types of behavioral change interventions were noted. All types of interventions, including individual education, group education, online education, and information campaigns, exhibited certain effects of improvement regarding behavioral change, knowledge, health outcomes, and other health-related outcomes in preconception health.ConclusionsIn this systematic review, only three studies recruited men. Further research on preconception care in men is needed. The topics typically addressed in preconception care are folic acid supplementation and nutrition. Additionally, further research is needed for a comprehensive approach, including physical, mental, and social health. Future research addressing the broad determinants of preconception health for both women and men could provide more effective preconception care.

Student physical education teaching achievement test incorporating biomechanics analysis via decision tree algorithm

In the context of China’s economic growth, building a “sports power” is crucial. With the Internet’s development, the nation focuses on physical education curriculum and students’ test results. Currently, Chinese students’ physical education achievements are mainly evaluated by storage, inquiry, and basic statistics. Digital mining is under - utilized, leaving much data unexplored. But digital education’s progress has brought educational data to the fore, enabling schools to find value and patterns for better teaching decisions. In this case, this paper delves into the integration of biomechanics analysis into the assessment of student physical education teaching achievements. Biomechanics offers invaluable insights into the mechanical aspects of human movement during physical activities. By examining biomechanical factors such as joint angles, muscle forces, and movement velocities during various sports, a more profound understanding of students’ physical capabilities and performance can be achieved. Taking the physical test results of students in a specific school as a case study, this research employs data mining technology to explore the rich dataset. The optimized decision tree algorithm is then utilized to analyze the biomechanics - related data. This algorithm enables the identification of key factors that influence students’ physical test outcomes. For instance, it can pinpoint how a student’s running gait mechanics, including stride length, frequency, and leg - muscle activation patterns, affect their performance in track - and - field events. Through this comprehensive approach, the paper not only aims to uncover hidden information within the physical test data but also to elucidate the intricate interplay between biomechanics and students’ overall physical education performance. By dissecting the factors that influence physical test results from a biomechanical perspective, this study provides actionable insights for enhancing physical education teaching methods. Educators can leverage these findings to design personalized teaching programs that cater to the unique biomechanical characteristics of each student, thereby optimizing the effectiveness of physical education and promoting students’ physical development and athletic performance.

Effects of COVID-19 on Dental Surgery Teaching Methods among Final Year Students in Nigeria: A Cross-Sectional Post-Pandemic Study

Background: The COVID-19 Pandemic which took the world by a storm in the year 2020 has had a far-reaching effect on all segments of human development, and especially on education and dental surgery, through the social distancing measures and the phases of lockdowns it imposed, infection prevention measures, among other things. Objectives: To assess the impact COVID-19 has had on dental surgery teaching methods and skill acquisition among final year students of dentistry and dental surgery in a developing country like Nigeria. Methodology: A cross-sectional study of final-year dental students across four (4) dental schools in Nigeria using a structured online Google form. Data was collected from fifty-four (54) respondents and the data was analyzed using Statistical Package for Social Sciences (SPSS) version 26. Results: The respondents agreed that COVID-19 reduced metrics such as physical practical sessions (83.3% of the respondents), contact times with patients (85.2%), physical classes’ reduction (31.5%), theatre experiences (61.1%), ability to meet up with training requirements (72.2%), flow chart affectation (79.6%), and availability of equipment for dental surgery training (53.7%). The cost of training increased according to 70.4% of the respondents while dental skills acquisition further reduced according to 61.1% of the respondents. There was an association between the institution of study and the effect of the pandemic on dental skills acquisition, however, the association wasn’t significant (Fischer’s exact value – 15.326. Degrees of significance p = 0.06. There was also no significant correlation between age and the effect of the pandemic on dental skills acquisition. (Pearson’s correlate = -0.030, Significance (2-tailed) = 0.892) Conclusion: The effect of COVID-19 on dental surgery teaching methods have been largely negative, reducing amount of practical sessions, reducing student’s interaction with patients, increasing cost and length of training among other negative effects, with a minor increase in access to journal groups and website links. Recommendation: Despite the reduction in overall teaching experience, there is a need to inculcate training in infection prevention and control to arm dental trainees with the wherewithal to protect themselves from infection. In addition, to further improve access to the online classes, the government can channel a part of the budget on education towards subsidizing the cost of data access to online learning platforms like Zoom and Google meet, by liaising with internet service providers and making provision for WiFi in the different campuses.

Examining Master’s Students’ Success at a Hispanic-Serving Institution

This work examines the indicators of master’s students’ persistence from 2014 to 2021 at a Hispanic-Serving Institution (HSI) in the southern United States. Demographic and academic variables were used in a logistic regression model to predict students’ successful completion across sixteen master’s programs. In this two-fold study, first, we examined the impact of COVID-19 on students enrolled in twelve face-to-face (F2F) programs and evaluated their performance against a pre-pandemic baseline period. Second, we compared student performance in four accelerated online programs against a pre-accelerated baseline. Most demographic variables were insignificant, while all academic variables were significant across program types. However, GPA became an insignificant variable when the F2F programs were forced to move online during the COVID-19 pandemic. During this period, GPA also increased for students who had discontinued their studies. The accelerated online programs recorded a significant decrease in terms enrolled (Term Count) compared to the pre-accelerated baseline. These results add to the limited literature on student success at the master’s level in HSIs, thus filling a vital knowledge gap. This study provides two case studies focusing on how the pandemic and the accelerated online learning model impacted academic persistence at the master’s level at an HSI.

Strategy for Successful Use of E-learning at the Islamic University of Nusantara Bandung

The use of e-learning in higher education has become a basic need, especially since the drastic changes in learning methods due to the pandemic. Islamic University of Nusantara Bandung faces challenges in optimizing the implementation of e-learning to maintain the quality of learning. This study aims to analyze the strategy for the success of implementing e-learning by considering aspects of digital infrastructure readiness, lecturer competence, and student adaptability. Using a qualitative-descriptive approach, the study was conducted through in-depth interviews with 25 lecturers and 150 students, direct observation of the online learning process, and documentation analysis for two academic semesters. The results of the study indicate that the success of e-learning at Islamic University of Nusantara Bandung is supported by three main pillars: continuous training for lecturers in the use of digital learning technology, development of interactive learning content tailored to student characteristics, and responsive technical support. Another interesting finding was the significant increase in student participation through online discussion forums which reached 85%, compared to conventional methods which were only 60%. This study also revealed that the integration of Islamic values ??in e-learning content has a positive impact on student learning motivation. These strategies have proven effective in increasing learning satisfaction by up to 78% based on student feedback surveys.

Learning behaviour prediction and multi-task recommendation based on a knowledge graph in MOOCs

ABSTRACT One challenging issue in improving the teaching and learning methods in MOOCs is to construct potential knowledge graphs from massive learning resources. Therefore, this study proposes knowledge graphs driving online learning behaviour prediction and multi-learning task recommendation in MOOCs. Based on the knowledge graphs supported by multi-entities and features, the authors designed a novel deep learning model to fully calculate and optimise iterative learning processes, explore key semantics and potential values of learning behaviours, integrate multi-task items and flexibly analyse learners’ multi-entities and related features. Assisted by knowledge concept semantics and the formation of knowledge graphs, multi-entities of learning behaviours are fused and associated, which might be the leading trend of knowledge graphs. Sufficient experiments have proved that the whole work might ensure learning behaviour prediction and multi-task selection that can enable the knowledge graph to improve learning behaviours in MOOCs.

Exploring Therapists’ Experiences of an Educational Website to Support Telehealth Delivery of Constraint-Induced Movement Therapy

Purpose: Constraint-induced movement therapy (CIMT) is an evidence-based intervention for arm recovery after acquired brain injury. Clinician knowledge, time and confidence in delivering CIMT are established barriers to the routine use of CIMT in practice. CIMT delivery via telehealth is one option to help overcome these barriers. This study aimed to understand clinician experiences of using an educational website and if the education and online resources contributed to their self-reported use of constraint-induced movement therapy via telehealth (TeleCIMT) in practice. Materials and Methods: Data were collected from a purposive sample of therapists registered to use the TeleCIMT website and website analytics. An online survey explored participants’ experience with CIMT delivery (both face to face and via telehealth), their perceptions of the website, and barriers and enablers to TeleCIMT implementation using the Capability, Opportunity, Motivation—Behaviour model. Website analytics were used to evaluate website traffic and resource use. Data were analysed using descriptive statistics (quantitative data) and content analysis (qualitative data). Results: Forty therapists responded to the survey; 72.5% (n = 29) of the respondents were occupational therapists, and 37.5% (n = 15) had delivered TeleCIMT. Most of the participants agreed that the website was easy to navigate (n = 26, 90%) and felt that they had the knowledge (n = 28, 96.6%) and skills (n = 24, 82.7%) to deliver TeleCIMT. The enablers to TeleCIMT included motivation to implement learnings from the website, confidence in delivering the programme, and the convenience of remote delivery. The perceived barriers to TeleCIMT use included limited access to technology and the availability of a client supporter to enable engagement in TeleCIMT. The resources used most frequently by the respondents were the participant preparation pack and participant programme pack. Shorter video learning modules (<11 min in duration) had greater engagement than longer video learning modules. Conclusions: Whilst online education and resources may enhance clinician knowledge of constraint-induced movement therapy and telehealth delivery, other barriers such as lack of technology access, may need to be addressed through additional learning and implementation strategies to support the routine use of TeleCIMT in practice.

The Future Transformations: The Role of Artificial Intelligence in Shaping Advanced Online Education"

The Future Transformations: The Role of Artificial Intelligence in Shaping Advanced Online Education"

Leveraging opportunities for self-regulated learning in smart learning environments

Abstract Smart learning environments provide students with opportunities to engage in self-regulated learning (SRL). However, little research has examined how teachers leverage these opportunities. We employed a multiple-case study methodology to examine the SRL supporting instructional practices of five third-grade teachers as they implemented a science unit embedded within a smart learning environment which enabled student engagement in SRL processes. The identified set of instructional practices was used to formulate the teachers’ SRL support profiles, which indicates the extent to which teachers provided students with opportunities to regulate the cognitive aspect of SRL. Our findings indicated that teachers’ interactions with the smart learning environment varied from teacher-focused use, restricting opportunities for SRL engagement, to student-focused use, leveraging opportunities for student engagement in SRL. These results demonstrate that, while smart learning environments potentially provide rich contexts for students’ engagement in SRL, how teachers use this environment through their SRL-supporting instructional practices determines students’ actual engagement in SRL.

Naming Māori Learning Spaces

Abstract Following up on our recent article in this journal, this research note discusses the range of names used in Māori school settings for flexible learning spaces (FLS) and innovative learning environments (ILE), There are various existing Māori names for FLS/ILE, which fall into two types: individual names and category names. We consider several of these names as a way to explore this concept and provide a background for positing ‘he wāhi ako’ as a generic name for Māori FLS/ILE, which translates into English as ‘Māori learning space(s).’

Qingdao Regional Economic Development of High Quality of Port and Shipping Logistics Talent Science and Education Integration Training Mode

Starting from the adaptive context of the port and shipping logistics professional training of higher vocational education to the port and shipping industry, we study experts at home and abroad.The relevant results, combined with the empirical research of the subject, proved the laws and characteristics of the development of the port and shipping logistics industry under the new quality productivity, corresponding to the higher vocational port and shipping logistics.The new requirements of talent training supply, further investigate the Marine development of shipping trade and the corresponding demand changes of talent training supply, analysis Ming new quality productivity enables the connotation mechanism of digital education of higher vocational education, analyzes its internal constraint factors, and concludes it through practical empirical research. The training model of high-quality economic development of port and aviation logistics talents promotes the quality of Qingdao port and aviation talent trainingRising, to provide a reference for the government's decision-making.

Surveillance Digitisation, Performativity, and Teacher-Student Relationships in a Blended Learning Setting

Abstract This study investigates how digitized surveillance technologies impact teacher-student relationships in a blended learning environment at a UAE university. Using semi-structured faculty interviews, it examines the effects of tools such as plagiarism detection, class recordings, and learning analytics on trust and engagement. The findings reveal tensions between institutional goals of academic integrity and active participation and the unintended consequences of fostering performative behaviours and eroding relational trust. Teachers report that surveillance mechanisms promote compliance over genuine learning, reshaping their roles and interactions with students. Despite these challenges, educators employ strategies of resistance, prioritising human connection and relational pedagogy to counteract the dehumanising effects of constant monitoring. This study contributes to postdigital scholarship by exploring the complex entanglements of technology, pedagogy, and trust, emphasising the need for critical and human-centred approaches to digital education.