International Journal of Learning Technology (32 papers in press)

Regular Issues

• Citizen science co-constructed educational practices: a teacher training course  
  by Manuel Santos, Vania Carlos, António Moreira 
  Abstract: This paper presents the design of citizen science learning materials, emphasising the co-construction of knowledge. Using a design-based research methodology, we aimed to develop citizen science strategies that foster students' participatory citizenship. The study involved a teacher co-creation training course supported by a smart educational community and a network of community stakeholders, before and during the COVID-19 lockdown, in a secondary school of Aveiro, Portugal. A detailed description of the training course and its implementation is provided. Data collected by two surveys and a teacher self-awareness reflection is presented and discussed. During the study students did data gathering tasks, overcoming the formal/informal divide in learning, using participatory citizenship strategies, and learning guidelines. The study demonstrated the effectiveness of the co-construction process in developing citizen science learning materials, fostering citizenship engagement and collective awareness, creating a range of learning opportunities for students connected to their local context and promoting active citizenship.
  Keywords: learning guidelines; citizen science; teacher professional development; civic co-creation; participatory data collection; citizenship engagement; collective awareness; COVID-19.
  DOI: 10.1504/IJLT.2023.10061622
   
  
• Dynamic and Collaborative learning environments: their effect on Academic Performance and Students' Motivation  
  by Kanika Kanika, Neha Dutta, Krishan Dutt, Roop Lal, Prashant Ahlawat 
  Abstract: Teaching students in collaborative learning environments is a well-acknowledged pedagogical practice with numerous benefits. The paper presents the impact of a blend of dynamic and collaborative environments on students' academic performance and motivation in an engineering course. While the classroom environment is made collaborative using an automated grouping tool, the dynamic environment with immense possibilities for learning is also utilised to improve learning through visual cues. The study uses a quasi-experimental design where 253 students studying engineering were divided into four different groups. Qualitative and quantitative analysis of the results indicate that the approach generates significant differences in learning by influencing the academic performance and motivation of students positively. The results suggest that while using the dynamic environment improved learning outcomes significantly, using the collaborative learning function alone did not create a difference in factors affecting learning. It is noteworthy that merging the dynamic and collaborative environment also leads to significant improvements in academic performance.
  Keywords: collaborative learning; improving classroom teaching; lifelong learning.
  DOI: 10.1504/IJLT.2023.10061825
   
  
• A Systematic Review of the Use of Immersive Technologies in Young Children's Education  
  by Ridvan Ata, Kasim Yildirim 
  Abstract: Few studies have been conducted on the current state of immersive technologies in early childhood education despite the increase in scholarly attention paid to them. This paper identifies the focus and tendencies in the usage of immersive technologies, research contexts, sample sizes, methodological designs, immersive types, interventions, and benefits of such technologies in early childhood education. The results indicate that current focuses and topics are reading concentration and interest, story comprehension, understanding of visual shapes, motivation, interaction, attitude, attention, spatial skills, and cognitive attainment. In addition, the research designs and techniques included quantitative research methods and data were collected through pretests-posttests, performance, and recall tests. Besides, most research contexts are classroom settings and the most used immersion type is augmented reality while virtual reality is used at the rate of one in third less. Lastly, interventions are AR apps, picture books, games, VR environments, VR analogies, and manipulatives while benefits are mostly positive cognitive, affective, and behavioural outcomes.
  Keywords: immersive technology; augmented reality; virtual reality; early childhood; systematic review.
  DOI: 10.1504/IJLT.2023.10061836
   
  
• Design and Validation of a Multidimensional Scale for Assessing Teachers' Perceptions Towards Artificial Intelligence in Education  
  by Hector Galindo-Domínguez, Martin Sainz De La Maza, Lucía Campo, Daniel Losada 
  Abstract: Artificial intelligence (AI) is a technology that has gained popularity in the educational field. In this regard, understanding teachers’ attitudes toward this technology is crucial for more efficient future implementations. However, the instruments and studies analysing teachers' perceptions toward AI are excessively scarce. The aim of this study was to design and validate a scale to measure teachers’ perceptions toward AI. A total of 445 teachers from Primary, Secondary, and Higher Education participated in the study. The final scale consisted of a total of 25 items divided into 4 dimensions (Willingness to use AI, Attitude toward AI, Professional expectations toward AI, and Personal experiences with AI), demonstrating excellent validity and reliability indices. Likewise, it was observed that teachers scored moderately high in the Willingness to use AI dimension, but moderately low in the Personal experiences with AI dimension; and, that differences in the dimensions based on educational stage were scarce.
  Keywords: artificial intelligence; AI; teacher attitudes; teacher behaviour; assessment; questionnaire.
  DOI: 10.1504/IJLT.2023.10062094
   
  
• Technological-pedagogical knowledge in problem-solving teaching: an exploratory study of mathematics teachers  
  by Astri Wahyuni, Yaya S. Kusumah, Bambang Avip Priatna Martadiputra, Agus Hendriyanto 
  Abstract: The development of technology has brought about modern ideas in teaching and learning. This research study investigates how experienced Mathematics teachers use digital tools to solve non-routine mathematical problems and communicate their solutions. A qualitative study with a case study design found that effective technology integration in mathematics education requires a deep understanding of mathematical problem-solving, effective use of digital tools, and a strong TPACK framework. Teachers must be adept at selecting and creating mathematical problems, choosing problem-solving models, and facilitating students' problem-solving skills through appropriate tasks. Although technology can enhance traditional teaching methods, it should be used wisely and purposefully to support and enhance the teacher's role, rather than replace it. In addition, teachers need to consider their students' diverse learning needs and use various teaching strategies to ensure that technology is effectively integrated into their teaching practices.
  Keywords: mathematical teaching; problem-solving; technology in education; TPACK.
  DOI: 10.1504/IJLT.2023.10062134
   
  
• Strengthening Business English Skills: Investigating Student Perceptions of Creating Product Videos in an ESP Course  
  by Wen-Chi Hu 
  Abstract: This study investigated students' viewpoints on using product video creation to foster their Business English skills in an English for specific purposes (ESP) course. The study aimed to examine the extent to which students could enhance their conversational flow, language usage, and practical expression skills by creating videos to promote a product or service. The participants included 44 university students who enrolled in Business English. In this class, they received instruction on the Business English language and were tasked with creating promotional videos for a chosen product or service. Data were collected through questionnaires, interviews, and rubric-based assessments of the videos. The results revealed that the use of crowdfunding video creation as a learning framework contributed positively to the participants' English usage, persuasion skills, and creativity. The findings suggested that incorporating video production tasks in an ESP class can enhance video editing, collaboration of thoughts and ideas, contextual use of expression, objective evaluation, and logical flow of conversation, preparing students to communicate effectively in the dynamic global business environment.
  Keywords: constructivism; English for specific purposes; ESP; video creation; digital literacy.
  DOI: 10.1504/IJLT.2024.10063782
   
  
• A Hybrid Recommendation System for E-Learning Based on the Design Social Science Research Process Model  
  by Chandrakant Mallick, Syamalendu Pati, Dr. Bijay Paikaray, Jayanta Mondal 
  Abstract: Existing e-learning systems have the potential for improvement in terms of real-time scalability and personalised adaptation, which could improve the learning experiences of individual users. The study uses the design science research (DSR) process to explore potential enhancements to e-learning systems through collaborative filtering recommendation systems (CFRS). It expands on earlier theories and proposes a DSRP-based hybrid recommendation system to improve the user experience in e-learning. The proposed technique incorporates key prototype modelling approaches like collaborative filtering, machine learning, and clustering. Specialists seeking new approaches to improve online education, such as information system researchers and e-learning practitioners, are the intended audience for this method. It has practical applications in addition to its theoretical merits.
  Keywords: E-learning; Recommendation System; Social Science; Information System.
  DOI: 10.1504/IJLT.2024.10064258
   
  
• Exploring Digital Storytelling in Mathematics Education: A Systematic Review of Trends, Benefits, and Implementation Challenges  
  by Angga Hidayat, Tryanti Abdulrahman, Muhammad Zulqurnain Ul Haq Qazi 
  Abstract: The surge in technology, especially the prevalence of social media video platforms among the youth, underscores the need for incorporating digital tools in education. Despite its potential, a dearth of research exists on the merits and demerits of employing digital storytelling in math education. This study aims to scrutinise trends and delve into the advantages and challenges of this approach. Utilising PRISMA framework, the review initially identified 180 Scopus and 118 Web of Science documents, narrowing down to 64 and 67 English-language articles, respectively. A further review yielded 17 articles for systematic analysis, which were analysed using biblioshiny to examine the trends. Findings suggest that digital storytelling in mathematics education facilitates engagement, understanding, and meaningful learning experiences, fostering cognitive and emotional development, competency growth, collaboration, constructivist learning, and transferable skills. Implementation challenges encompass curriculum alignment, technological obstacles, low technological self-efficacy, and potential cultural and curriculum disparities impacting project effectiveness.
  Keywords: digital storytelling; mathematics education; technology integration; systematic review.
  DOI: 10.1504/IJLT.2024.10064272
   
  
• Exploring the influence of social media information quality, and perceived usefulness on academic achievement: the mediating role of usage of social media  
  by Badr Saleh, Abdallah M.M. Badr, Rozilah Kasim, FAISAL ALI 
  Abstract: Despite the embarking breakthrough of social medial in revolutionising communication and information access, the quality of information for students and scholars remain a concern. This paper investigates the effects of social media information quality and perceived usefulness on academic achievement. It also investigates the mediating role of usage of social media on the relationship between information quality, and academic achievement, as well as between perceived usefulness and academic achievement. Toward this end, data was collected from 445 students at King Khalid University in Saudi Arabia using a survey-based method. The findings of this study revealed a direct influence of the perceived usefulness, usage of social media and information quality on academic achievement, however, the perceived usefulness has a direct influence on social media. Additionally, the usage of social media has mediating effects on the relationships between the quality of information and academic achievement as well as perceived usefulness and academic achievement. These findings are of potential interest to Saudi higher education institutions, for improving student achievement.
  Keywords: social media; information quality; perceived usefulness; and academic achievement.
  DOI: 10.1504/IJLT.2023.10064325
   
  
• Pre-service science teachers' computational thinking skills and STEM self-efficacy  
  by Merve Lütfiye Şentürk, Uğur Sari 
  Abstract: This study aims to examine pre-service science teachers' CT skills and STEM self-efficacy in terms of different variables and to reveal the relationship between them. The participants of the study, in which the survey model was used, consist of 334 pre-service science teachers studying in state universities. CT skills and STEM self-efficacy scales were used as data collection tools. Single-factor MANOVA, correlation and linear regression analyses were used for the analysis of the data. In the study, it was determined that pre-service science teachers' grade level, level of technology interest, level of computer knowledge, activities/design/experiment/practice studies they carried out in undergraduate education and their STEM education were determinants of their CT skills and STEM self-efficacy. In addition, a positive relationship was determined between STEM self-efficacy and CT skills, and it was observed that creativity, collaboration, critical thinking, algorithmic thinking, and problem solving skills were predictors of CT and STEM self-efficacy.
  Keywords: Computational thinking; STEM; STEM self-efficacy; pre-service science teachers; teacher training.
  DOI: 10.1504/IJLT.2024.10064384
   
  
• Online Learning: Undergraduates Satisfaction and Roles of ICT infrastructure  
  by Pham Ngoc Thien Nguyen, Khanh-Trinh Tran 
  Abstract: During COVID-19, online learning proved crucial in ensuring continuous education. Post-pandemic, the necessity for online learning to align with learner satisfaction persists. This study investigated factors, including information communication technology (ICT) infrastructure (comprising learning support devices and Internet quality) and skill development, which impact online learning satisfaction. A convenient sample of 250 Vietnamese undergraduates, each of whom had completed at least one online course, participated in the survey. The results from the linear regression analysis revealed that both ICT infrastructure and skill development significantly contributed to the variance in students' online learning satisfaction. Furthermore, skill development partially mediated the relationship between learning support devices/Internet quality and online learning satisfaction. Situated within the technology acceptance model (TAM), these findings emphasise the critical roles played by both ICT infrastructure and skill development in achieving learning satisfaction. The study contributes theoretical insights and practical implications, offering valuable scientific evidence to advance online learning.
  Keywords: online learning; learning satisfaction; skill development; ICT infrastructure; undergraduates.
  DOI: 10.1504/IJLT.2024.10064727
   
  
• Recommender Systems in Education: Systematic Review and Future Outlook  
  by Feng Wang, Yitong Liu, Zhu Zou, Ze Liu 
  Abstract: Against the background of increasingly diversified educational contents and learners' demands, continuous growth in the number of users and the scale of educational resources, and diversified educational environments, recommender systems in the field of education face challenges such as cold start, poor scalability, and difficulty in integrating online and offline education. The purpose of this paper is to systematically sort out recommender systems using the systematic literature review method and PRISMA to analyse its different development characteristics in the last decade in terms of the types of recommendation items, recommendation algorithm applications, feature engineering methods, evaluation metrics diversity, system types, etc. and to focus on the latest research results in this field in the last five years. Meanwhile, the new challenges and characteristics it faces are elaborated. Finally, the critical future development directions of the field are inferred and foreseen.
  Keywords: recommender systems; e-learning; online learning; online education; review; LDA.
  DOI: 10.1504/IJLT.2024.10064826
   
  
• ChatGPT and Higher Education: Examining Early Public Opinions through Sentiment Analysis of Online News  
  by Areej Yousef, Yangsheng Zheng, Eunjae Park, Ahmad Abdel-Hafez 
  Abstract: The emergence of artificial intelligence (AI) chatbot ChatGPT has stirred interest in the higher education sector and the public. Public opinions, particularly those conveyed through online news, are likely to exert discursive influences on how society responds to AI innovations. The current study provides early insights into the public sentiment in online news articles around ChatGPT and higher education using a mixed methods approach. Through Python and SPSS, we compiled a dataset of 919 news articles, finding a positive sentiment in 856 articles (93.1%). Key trends concerning the prevalence of news published in English-speaking nations were also identified. By adopting Fairclough's critical discourse analysis approach to unpack negative sentiment, we unveiled public concerns around ChatGPT replacing the need for human empathy, increasing the risk of academic integrity/plagiarism, spreading misinformation and job losses. We emphasise the importance of understanding ChatGPT’s functionalities and imposing regulations to ensure ethical AI usage.
  Keywords: ChatGPT; artificial intelligence; AI; higher education; online news; sentiment analysis.
  DOI: 10.1504/IJLT.2024.10064945
   
  
• The Impact of Game-Based Learning (GBL) On Learners' Academic Performance, Social Skills and Academic Emotions in Computer Studies  
  by Ayaz Muhammad Hanif, Zohra Saleem, Yasir Javed, Abdel Karim Al Tamimi 
  Abstract: Educational game (EG) has emerged as a potent tool driving educational innovation. Investigating how educational emotions can bridge gaps in EG for computer science education is an emerging but insufficiently explored area. The research explores the relationship between academic performance, social skills, and academic emotions using experimental research based on Driver and Oldham model. It utilised techno-emotive learning environment model (TELEM), based on a web-based educational game (EG) to teach fifth, sixth, and seventh-grade students from five schools using a sequential explanatory design. Out of 170 participants, experimental group (n = 91) used the EG, and a control group (n = 79) received traditional classroom instructions. The EG users demonstrated higher social skills compared to the control group. The experimental group exhibited a noteworthy improvement in the social skills (optimism, zest and curiosity) compared to the control group. Additionally, the experimental group displayed a statistically significant, albeit moderate, enhancement in cognitive outcomes. The findings also revealed that hope' did not mediate the relationship, while enjoyment partially mediated the connection between learners declining performance and post-test scores. Anxiety partially mediated the relationship between declining performance and both pre-test and post-test scores.
  Keywords: game-based learning; academic performance; social skills; academic emotions; primary education; computer studies.
  DOI: 10.1504/IJLT.2024.10065083
   
  
• How QR Code is Reshaping Educational Technologies: A Multi-Method Exploratory Study from China  
  by Hasan Tinmaz, Jin Hwa Lee 
  Abstract: The study investigates user perceptions of QR code usage in education, focusing on participants' QR code familiarity, previous QR code experience, belief in QR code's positive effects, and defining QR code usage. The study includes 1,016 Chinese students and employs both quantitative (survey) and qualitative (interview) instruments. Exploratory factor analysis identifies three factors from the survey items: benefits of QR code for instruction, benefits of QR code for students and QR code integration earlier than higher education. Comparative tests reveal gender differences where male students scored higher in the first factor. School level significantly impacts all three factors, with secondary school students showing the most positive attitudes. QR code familiarity, previous QR code experience, and belief in QR codes positive effects induced positive user perceptions. Qualitative interviews support quantitative findings, emphasising QR codes role in accessing information, enriching learning, and improving efficiency.
  Keywords: QR code; education; educational technology; instructional technology; China.
  DOI: 10.1504/IJLT.2024.10065332
   
  
• Towards Technology-enhanced SRL Scaffolding: Alignment and Integration Framework Informing Design and Implementation  
  by Cheikh Boumediene, Abdelhafid Chadli, Benameur Ziani 
  Abstract: As a teaching-learning construct, self-regulated learning (SRL) scaffolding is bringing out potential ways for effective implementations of technology-enhanced learning, where learners have more autonomy and teaching-learning support is more mediated by technology. However, there is a clear lack in the explicit conceptualisation of SRL scaffolding as a systemic whole construct. Recognising that teaching-learning systems are complex meaning-making environments with multiple perspectives and roles, this paper proposes a framework called SRL-SF, a two-level framework approaching the explicit conceptualisation and informing the systemic implementation of SRL scaffolding. To elaborate this framework, we extensively reviewed foundational literature and meticulously refined various alignment and integration issues. Our major concern is to provide a groundwork for designing SRL scaffolds that enhances capabilities of both teachers and learners as well as technologies.
  Keywords: Technology-enhanced learning; socio-constructivism; self-regulated learning; scaffolding; learning design.
  DOI: 10.1504/IJLT.2024.10065427
   
  
• The Potentials of Virtualisation Readiness in Language Laboratories: the Case of Iranian Context  
  by Sayed Hadi Sadeghi  
  Abstract: Human-machine interactions are increasingly important in monitoring and modifying virtual practices in learning laboratories. This study scrutinises the virtualisation readiness in an Iranian language learning laboratories (ILLLs) vis--
  Keywords: virtualisation; virtualisation readiness; v-practice; virtualisation practice; digital transformation; language labs; Iranian language learning laboratory; ILLL; Iran.
  DOI: 10.1504/IJLT.2024.10066142
   
  
• A Systematic Review of the Impact of Distance Learning Technologies in Language Classes on Students' Motivation (2020-2023)  
  by Ekaterina Voronina, Anne Yates, Linda Hogg 
  Abstract: Distance learning (DL) technologies in education proliferated worldwide with the onset of COVID-19, contributing to a need for knowledge about how to effectively use them. Because motivation has a key role in learning, this systematic literature review investigated how DL technologies currently used for language teaching influenced students’ motivation. Research papers selected for review were published between 2020 and 2023. Mixed findings pointed to the influence of student and environmental factors as well as DL design features, including teacher actions. Half of the studies reported that studying online led to decreased motivation for language learners, which was linked to the nature of teacher-student interaction in asynchronous classes. We provide recommendations for future research, including reporting on how motivation is conceptualised and details of DL technologies, to enable analysis of intrinsic and extrinsic motivation, and so that new knowledge can better inform how language teachers integrate and use modern DL technologies.
  Keywords: distance learning; DL; distance learning technology; language learners; motivation; world language learners; teacher-student interaction; feedback.
  DOI: 10.1504/IJLT.2024.10066394
   
  
• Lost in Transition: A Mixed-Methods Study on Students' Experiences and Challenges Migrating Between Learning Management Systems in Higher Education  
  by Lan Nguyen, Jared Walters 
  Abstract: With the increasing reliance on learning management systems (LMSs) to support online and blended-learning in higher education, the adoption/switch to a new system can disrupt student learning. This mixed-methods study explored 128 students’ reflections of an institution-wide transition from blackboard to canvas, and whether individual characteristics (self-efficacy, technology anxiety, personality) predicted positive experiences. Positive LMS transition experiences were predicted by higher online-learning self-efficacy and lower technology anxiety, but not personality. Overall ratings of the transition were moderately negative due to lack of awareness and understanding of why the transition occurred, lack of staff confidence and knowledge about the new system, and lack of consistency across courses and systems. Interestingly, these concerns were consistent among students regardless of their level of online-learning self-efficacy and technology anxiety. This study contributes to the academic discourse on technological transitions for online and blended-learning in higher education and provides guidance for institutions planning system changes.
  Keywords: learning management system; LMSs; transition; migration; students; higher education; mixed-methods.
  DOI: 10.1504/IJLT.2024.10066553
   
  
• The Influence of Digital Literacy Training on Self-Efficacy, Digital Literacy Skills, and Internet Outcomes  
  by Heena Choudhary, Nidhi Bansal 
  Abstract: Digital literacy training (DLT) is paramount in equipping individuals with knowledge and skills necessary to navigate the online landscape. While existing literature has extensively explored the roles of self-efficacy (SE) and digital literacy skills (DLS) in influencing digital engagements and, subsequently, internet outcome (IO) achievement, there is a notable gap in understanding how DLT directly affects IO achievement. This study addresses this gap by comprehensively examining the relationship between DLT and IO, explicitly focusing on the parallel mediating mechanisms of SE and DLS. Drawing from social cognitive theory (SCT) and the digital inclusion perspective, a conceptual framework was developed and tested involving 450 participants. Results reveal that DLT not only directly impacts IO but also exerts an indirect influence through the mediating effects of SE and DLS. Individuals undergoing DLT enhance their SE and DLS and experience positive IO achievement. These findings contribute to designing effective training programs and policies, offering actionable knowledge to bridge the digital divide and cultivate a digitally empowered society.
  Keywords: digital divide; digital skills; digital literacy; self-efficacy; SE; internet use; internet outcomes; training; marginalised; rural.
  DOI: 10.1504/IJLT.2024.10066967
   
  
• How do Teachers' Emotions Affect Student Sentiment in MOOCs? A Study using Facial Emotion Recognition and Sentiment Analysis  
  by Vishnu Lal, Avuduri Venkata Amarnadh Reddy, G. Varaprasad 
  Abstract: This study investigates the impact of teachers’ emotions on student sentiment in MOOCs, exploring the potential relationship between emotional expressions conveyed by instructors and the emotional experiences of learners. The study uses the bidirectional encoder representations from transformers (BERT) model for sentiment analysis and the convolutional neural network (CNN) model for facial emotion recognition to analyse the emotions of teachers using instructional videos, discussion forums, and written communication. The findings demonstrate a significant correlation between teachers' emotions and student sentiment in MOOCs. Instructors displaying positive emotions elicited higher levels of student engagement and satisfaction. Conversely, negative emotional expressions were associated with decreased student sentiment and reduced motivation. The study makes a significant contribution to the emerging area of emotional dynamics in e-learning by providing vital insights for developing instructional strategies, course design and development of emotionally responsive educational technologies.
  Keywords: deep learning; emotional intelligence; sentiment analysis; facial emotion recognition; FER; convolutional neural network; CNN.
  DOI: 10.1504/IJLT.2024.10067023
   
  
• Web 2.0 Activities in Web-Based Courses: Metacognitive Learning Strategies and Metacognitive Skills of Teacher Candidates  
  by Cengiz Gündüzalp 
  Abstract: This study aimed to assess the effects of Web 2.0 technologies-based activities used in web-based courses on metacognitive learning strategies and metacognitive skills of the preservice teachers and reveal student opinions on this subject. Accordingly, the study findings revealed a significant difference between the evaluation and affective strategies and metacognitive skills-related scores among the students of the experimental and control groups. It also identified a significant difference between the scores of the students in the experimental group on evaluation and affective strategies and metacognitive skills, whereas there was no substantial difference between their scores on planning and monitoring strategies. Considering the Web 2.0 technologies-based activities, students in the experimental group mostly expressed favourable opinions on its effect on evaluation and affective strategies and metacognitive skills. As a result, this study concluded that Web 2.0-based activities were productive and essential in developing students’ evaluation and affective strategies, and metacognitive skills.
  Keywords: Web 2.0; metacognition; learning; strategy; skill.
  DOI: 10.1504/IJLT.2024.10067594
   
  
• Predicting Teachers' Attitudes towards Technology Integration  
  by Joseph Njiku 
  Abstract: Attitudes have been reported to have significant influences on teachers’ technology integration. Conversely, attitude is a predisposition that needs to be addressed to attain its desired level. This study examines contextual factors: training, access, use, and experience that influence teachers' attitudes toward technology integration in teaching using a survey research design where 125 teachers selected from 38 schools. The standard regression analysis shows that contextual factors, when put together, significantly predict attitude, although none of them was a significant predictor on its own. This suggests that multiple factors influence the level of teachers' attitude towards technology integration and implies that addressing teachers' attitudes toward technology integration needs to harness multiple factors that might be operating concomitantly. The study contributes to our understanding of the complexity of the relationship between attitudes and potential predictors and that attitudes can be attributed to multiple factors.
  Keywords: attitudes; technology integration; technology access; experience; teacher education.
  DOI: 10.1504/IJLT.2024.10067595
   
  
• Artificial Intelligence Influence on E Learning Instructional Design: a Systematic Literature Review  
  by Hicham Boustane, Razane Chroqui, Abdelkader Sabil 
  Abstract: The integration of Artificial Intelligence (AI) into educational practices has transformed Instructional Design (ID), introducing novel approaches. This systematic literature review evaluates AI's role in reshaping e learning ID and its implication for educational technology. Following PRISMA guidelines, we conducted a thorough search across Scopus and Web of Science, focusing on peer-reviewed articles between 2003 and 2023. Our methodology involved rigorous data extraction and both bibliometric and thematic analyses. The findings reveal that AI enhances the development of personalised learning paths, collaborative interactive platforms, and intelligent tutoring systems, resulting in improved learner engagement and knowledge retention. While AI application aligns with constructivist and connectivist theories by enabling learner-centred networked systems, ethical concerns remain regarding algorithmic bias, data privacy, and the digital divide. Implications embrace the need for design-based research to bridge the gap between theory and practice, helping make informed decisions to leverage AI's full potential while preserving educational values.
  Keywords: AI; artificial intelligence; e-learning; instructional design; curriculum development; educational technology; natural language processing; machine learning; personalized learning; adaptive learning.
  DOI: 10.1504/IJLT.2024.10068456
   
  
• Analysing the Impact of E-Learning Practices in Higher Education  
  by Ram Kumar Dwivedi, Neetika Arora Bajaj, Razia Nagina, Kanagala Anusha 
  Abstract: This study explores the relationship between relationship marketing and customer satisfaction in the context of e-learning within higher education. With an increasing shift toward flexible academic options, understanding how marketing strategies influence student satisfaction becomes crucial. The research uses a two-step process: first, data is gathered from 365 students across selected higher education institutions in India using a questionnaire designed around the proposed hypothesis. In the second step, structural equation modelling (SEM) is applied to analyse the data. The studys findings indicate a positive relationship between relationship marketing and customer satisfaction in e-learning environments. These results highlight the importance of tailored marketing strategies in enhancing student experiences and satisfaction with e-learning platforms. Future research is recommended to further expand the data pool to gain deeper insights into students perceptions of e-learning and refine marketing strategies for better engagement and retention in higher education.
  Keywords: E-learning; Higher Education; Internet; Relationship Marketing; Customer Satisfaction.
  DOI: 10.1504/IJLT.2024.10068747
   
  
• Enhancing Elementary C Code Comprehension Assessment: a Weighted Fusion Approach based on AI Models  
  by Yasmine Chachoui, Nabiha Azizi, Imene Labiod, Tahar Bensebaa 
  Abstract: The advent of artificial intelligence (AI) has opened up new perspectives for semantic understanding as well as new ways of assessing learners comprehension. This study investigated the effectiveness of AI pre-trained language models, specifically BERT, RoBERTa, and CodeBERT, in a multi-label classification aimed at capturing students code comprehension. The dataset comprises four introductory C programming exercises focusing on basic input/output commands (scanf, printf) and conditional statements. The research explores different models for chain classification and introduces a weighted fusion method based on the accuracy of each label, combining the strengths of different models in a best-model ensemble approach. The approach weights the global performance of the model with the individual performance of each label to improve accuracy. CodeBERT, in particular, showed superior performance for different labels, underlining the importance of specialised models for code analysis. The experimental results showed that the weighted fusion proved to be effective for challenging labels, leading to an overall improvement in accuracy with values of 0.90 for BERT, 0.88 for RoBERTa, and 0.96 for CodeBERT.
  Keywords: AI in Education; Semantic Understanding; Code Comprehension; Multi-label Classification; CodeBERT; RoBERTA; BERT.
  DOI: 10.1504/IJLT.2024.10069032
   
  
• A Comprehensive Analysis of Digital Traces Categorisation in Online Learning Environments and its Implications in the Dropout  
  by Karima Hamdane, Abderrahim El Mhouti, Mohammed Massar 
  Abstract: The progression of technology has transformed learning analytics, enabling educators to leverage real-time data to comprehend learner behaviour and enhance personalized learning experiences. Learning Analytics field plays a pivotal role in monitoring and predicting student performance, facilitating timely interventions to support at-risk students and inform decision-making processes. This article aims to contribute to evidence-based practices that foster student retention and success through two main objectives: (1) to compile and classify various digital traces identified in previous literature concerning Learning Analytics, and (2) to elucidate the utilization of these traces in addressing the issue of student dropout. By providing a comprehensive classification of digital traces, the study offers a nuanced understanding of learner behaviour in digital learning environments. The findings highlight the transformative potential of advanced data analytics, including machine learning and predictive modelling, in enhancing student success and retention by enabling timely and effective interventions for at-risk students.
  Keywords: Digital traces data; learning analytics; student’s dropout; predictive modelling; real-time data analytics.
  DOI: 10.1504/IJLT.2025.10069438
   
  
• Effects of Collaborative 3D Printing Problem-Based Learning on Preservice Elementary Teachers' Socially Shared Metacognition and Science Fascination: a Mixed Methods Study  
  by Elena Novak, Shannon L. Navy, Megan Alicea 
  Abstract: Teacher collaboration develops teachers’ abilities to discuss ideas, analyse teaching strategies, and promote student learning. However, the metacognitive processes supporting group learning, or socially shared metacognition (SSM), are less understood. This pre-/post-test mixed-methods study investigated the effect of collaborative 3D printing problem-based learning (PBL) on preservice elementary teachers' SSM and fascination in science as well as differences in groups' shared regulation of collaborative learning processes. Thirty-one preservice teachers worked in small groups on a 3D printing design challenge. After participating in collaborative 3D printing PBL, participants' fascination in science as well as shared knowledge of cognition and planning strategies significantly increased from pre- to post-test. The group with the highest pre-/post-test loss in shared regulation of cognition had more difficulties co-creating a 3D model than a group with the highest gain in shared cognition. Implications for collaborative making activities for shared regulation of group learning experiences are discussed.
  Keywords: socially shared metacognition; problem-based learning; 3D printing technology; preservice elementary teachers; science education.
  DOI: 10.1504/IJLT.2025.10070158
   
  
• Teaching in Online Classrooms: an Analysis of Time, Space, and Embodiment in Human-Technology Interactions in Online Teacher Practices  
  by Andreas Lagerlöf 
  Abstract: Online instruction in adult education is a reality for many teachers. Teacher practices employed in digital classrooms depend on inherent materiality. This article analyzes online teaching and the materiality of the digital classroom. The article focuses on teaching in synchronous online classrooms, and the study’s data consists of semi-structured interviews and observations of teachers in Swedish Municipal Adult Education (MAE). While this study provides insights into teacher practices, it does not include student perspectives, which presents a notable limitation in fully capturing the dynamics of online education. The analysis is based on actor-network theory. The findings show that time enacted in digital classrooms is elastic in form and becomes open to negotiation. Space shifts from teaching being located in one physical location to multiple places, often governed by students through the doings of technology. The body takes on multiple forms, leading to feelings of both closeness and distance.
  Keywords: online instruction; teacher practices; adult education; materiality; actor-network theory.
  DOI: 10.1504/IJLT.2025.10070858
   
  
• Exploring the Existing Project-Based Learning for Tea Art Courses To Develop and Modify PjBL Framework: a Study on Higher Vocational Education in Henan, China  
  by Jing Xu, Nur Husna Abd. Wahid 
  Abstract: Tea art courses (TAC) in higher vocational education call for an effective learning model to increase students’ engagement. Thus, the objectives of the study are to identify the major elements of PjBL for TAC, to distinguish between important and unimportant elements, and to modify and develop an effective framework for PjBL for TAC. For that purpose, the study has used a mixed-methods research design involving a semi-structured interview with eminent professors (n=7) and a survey of TAC students (n=512). Purposive and snowball sampling were used. The thematic analysis of qualitative data identified twelve major elements of PjBL and five expected TAC outcomes. By using exploratory and confirmatory factorial analysis and structured equation modelling, the study has eliminated unimportant elements to develop, modify, and propose a PjBL framework for TAC.
  Keywords: Tea Art Course; Structural Equation Modelling; Exploratory Factor Analysis; Project Based Learning Framework; Higher Vocational Education; Students’ Engagement; Semi-Structured Interview.
  DOI: 10.1504/IJLT.2025.10070864
   
  
• Designing a Behaviour Pattern Analytics Model for Learning and Action Recommendation in Children using Improved Nature-Inspired-assisted Deep Adaptive Reinforcement Learning  
  by E. Samatha Sree Chaturvedi, L. Mary Gladence 
  Abstract: This paper explains an Artificial Intelligence-based recommendation system for the student to improve their performance. Initially, the multi-modal input data like language, image, speech signal, and EEG signal for recommendation of learning and action of children is collected from the available data resource and subjected to feature extraction process. The Term Frequency-Inverse Document Frequency based feature from language, CNN based feature from the image, Cepstral & spectral features from the speech signal, and EEG signal features from EEG signal are extracted in this process. The extracted feature is combined and sent to the Deep Adaptive Reinforcement Learning technique for action and learning recommendation. Here the parameters from the developed DARL are tuned using an Improved Walrus Optimisation Algorithm for performance enhancement. The effectiveness of the model was validated by the simulation result. The outcome revealed that the proposed learning recommendation model based on AI outperformed the traditional routing method.
  Keywords: Learning and Action Recommendation System; Term Frequency-Inverse Document Frequency; Convolutional Neural Network; Improved Walrus Optimization Algorithm; Deep Adaptive Reinforcement learning.
  DOI: 10.1504/IJLT.2025.10071069
   
  
• Generative AI in Higher Education: Investigating how Perceived Usefulness and Usage Patterns Influence Student Engagement and Academic Performance  
  by Olutoyin Olaitan, Isaac O. Ajao 
  Abstract: This study examines the influence of generative Artificial Intelligence (AI) tools on student learning outcomes in South African higher education. Using surveys from 208 participants across four institutions, analysed via Partial Least Squares Structural Equation Modeling (PLS-SEM), the research highlights AI's ability to enhance engagement, intellectual curiosity, and personalised learning experiences. Key findings include the high perceived usefulness of AI in understanding complex topics and connecting coursework to real-world applications. Challenges such as limited technical training for academics and data privacy concerns are also identified. The study emphasizes AI's potential to support active knowledge construction and cognitive development, offering actionable insights for educators and policymakers. Recommendations include strategic interventions like enhanced training, adaptive AI tools, robust ethical frameworks, and longitudinal studies to assess sustained impacts and inform solutions tailored to diverse educational contexts.
  Keywords: Generative AI; Higher Education; Technology Integration; AI Privacy and Ethics; Cognition and Learning Outcomes; Perceived Usefulness.
  DOI: 10.1504/IJLT.2025.10071161