Research and Practice in Technology Enhanced Learning

A meta-analysis of technology usage in word problem solving interventions for elementary students: an application of the SAMR model

2024-08-06T03:29:15+00:00

This meta-analysis assessed the effect of the usage of technology in math interventions on the math achievement of students in kindergarten to the fifth grade. The SAMR (Substitution, Augmentation, Modification, Redefinition) (Puentedura, 2006) model was applied to evaluate the degree of technology integration within the math intervention. Twelve group studies met the criteria for inclusion in this meta-analysis. Overall, technology interventions yielded a significant positive effect on the math achievement of elementary-aged students with learning disabilities (LD) (ES = 1.34). While no significant differences in effect sizes were found by function of the SAMR model, the studies that utilize technology as substitutions yielded the highest effect sizes. These findings support the need for continued study into the effects of technology-mediated strategies in word problem solving interventions.

Zoom in the face-to-face classroom and its effects on the class performance of college students

2024-11-01T06:40:17+00:00

This study explored how Zoom, a popular videoconferencing and online collaboration tool, may influence college students’ class participation and learning in the traditional (face-to-face) classroom. Specifically, the study examined and tested the effects of using two main functions of Zoom, chat and quizzes, for in-person class participation on the overall class performance of students. The data from 240 undergraduate students participating in a face-to-face course of international business during the past three years provided evidence showing that the use of Zoom chat and quizzes was positively related to the students’ overall class performance. The pedagogical and research implications from this research are discussed.

Identity does matter: teacher disciplinary attitudes toward digital games

2024-09-23T23:27:11+00:00

Teacher gaming experience affects attitudes toward digital games and consequent instructional behaviors, yet the influences of gamer identity from the perspective of teacher-student relationships have received limited research attention. We recruited 683 junior high and elementary school teachers working in Miaoli County, Taiwan to investigate the influences of gaming experience and gamer identity on the ways they regulate student digital game play in terms of time (duration), location, game genre, and playing partners. A game experience questionnaire, gamer identity scale, and digital game discipline scale were used to collect data. Results indicate that respondents with more gaming experience or higher gamer identity scores were more likely to report hands-off attitudes regarding discipline, while teachers with less or no game experience held stricter disciplinary attitudes, especially in terms of game genre and playing partners. Our hope is that the findings support teacher training programs in their efforts to address teacher concerns and negative perceptions of digital games in classroom settings. Additional research is required to clarify how the connection between teacher gaming experience and identity affects classroom learning.

What’s more important when developing math recommender systems: accuracy, explainability, or both?

2024-11-04T07:19:11+00:00

To make accurate predictions, complex artificial intelligence techniques are being adopted in intelligent systems. It leads to the need for explanations, helping users understand how the model works. Beyond this original purpose, explanations in educational intelligent systems have been found to increase students’ awareness, perceived usefulness, and acceptance of the recommendations. Can we ensure a model makes accurate predictions and has effects of explanations at the same time? Though it is commonly considered that complex models are accurate but difficult to interpret, it remains debatable whether there is a trade-off between the accuracy and explainability of such models. In this study, we explore the relationships between accuracy and explainability of different models for recommending math quizzes in the context of formative assessment. Focusing on three recommender models—an inherently explainable model (Naïve CE), a black-box model (MF), and an integrated model (CE+MF), we compared the accuracy using a large-scale real-world dataset and evaluated the explanations in a semi-interactive questionnaire survey. We found that: 1) There was a trade-off between accuracy and explainability given the specific context. 2) The explainability did not demonstrate consistent trends among different aspects. Especially, perceived understandability did not indicate the perceived usefulness in math learning and the behavioral intention to use the system. 3) The integrated model displayed a balanced level of accuracy and explainability, which implies the feasibility to develop an explainable educational recommender system by improving the accuracy of an inherently explainable model.

Learning critical thinking skills with online bite-sized videos: a qualitative account of students’ perceptions

2024-09-26T10:16:37+00:00

Learning to think critically is a key educational goal for higher education that presents a significant challenge for many students. Surprisingly, few studies have reported students’ views and perceptions towards instructional methods in critical thinking. The current study explored university students’ experiences and perceptions towards an online intervention designed to improve critical thinking skills. The intervention employed video-based learning to introduce four common informal logical fallacies to students across two micro-learning episodes administered online. We conducted semi-structured interviews with 30 university students to gain insight into four key areas: i) the perceived usefulness of the intervention for critical thinking development, ii) the presentation of learning materials, iii) the factors impacting their engagement, iv) and the potential of this approach to support mainstream provisions. We identified four main themes using thematic analysis: 1) building understanding and awareness of critical thinking, 2) effective video design and presentation, 3) valuing technology-enhanced learning approach, and 4) divergent experiences derived from the practice phase. These themes encapsulate students’ experiences of learning critical thinking as a highly sophisticated skill within an online learning environment and their preferences towards an effective video design. We discuss the implications of these findings for future pedagogical research and training of critical thinking in higher education.

Investigating shared agency in student Knowledge Building discourse using epistemic network analysis

2024-09-30T07:42:38+00:00

In computer-supported collaborative learning, students engage in both synchronous online and face-to-face discussions to enhance engagement and learning from peers. Recent research highlights the potential of quantitative modelling techniques, such as those used in Epistemic Network Analysis, to deepen our understanding of student collaboration through discourse, including the concept of shared epistemic agency in Knowledge Building. However, these efforts are still in the early stages. This study aims to advance this research by analysing student contributions in synchronous discussions (online and verbal) within a Knowledge Building framework. Data was collected from a Grade 5 class during a 2.5-hour Social Studies lesson designed to foster real-world problem-solving and collaborative discussions. Students participated in discussions on Knowledge Forum (online) and in face-to-face small groups. Transcripts of group discussions and Knowledge Forum notes were coded for semantic types and analysed for weighted connections between coded contributions using Epistemic Network Analysis. The analysis of overall student contributions revealed distinct patterns of weighted connections between codes and varying degrees of idea development in online versus oral discussions. Additionally, the study identified different engagement patterns within groups based on their epistemic networks. The findings offer insights into student engagement during collaborative talk and have implications for future research and practice.

Pre-service teachers’ perceptions of integrating digital games into future teaching

2024-10-16T03:11:28+00:00

This study aimed to investigate pre-service teachers’ perceptions of using digital games for future teaching, with a focus on variables including beliefs, motivation to adopt digital games, self-efficacy of digital game integration, and intention to adopt digital games for future teaching. We examined the changes of pre-service teachers’ perceptions of adopting digital games over time as well as the relationships of beliefs, motivation, self-efficacy, and intention for the adoption of digital games. Participants included pre-service teachers from a university in the northeastern United States. Quantitative data were collected using online pre- and post-surveys. Quantitative approaches (e.g., t-tests, ANOVAs, etc.) were performed to analyze the data. Results indicated that there were significant changes in pre-service teachers’ belief, motivation, self-efficacy, and intention to adopt digital games before and after their participation in a digital game project. Beliefs and motivation were significant predictors of pre-service teachers’ intention for future adoption. Gender, iPad ownership, years of playing digital games, and thoughts of using digital games had an influence on pre-service teachers’ perceptions of using digital games in future teaching.

Synchronous online learning platforms and student engagement: Exploring high school learning experiences and environments in the Philippines using self-determination theory

2024-10-16T02:46:37+00:00

In the post-pandemic educational landscape, hybrid learning has become a crucial mode of instruction, prompting educators to assess its effectiveness. This study explores the relationship between classroom learning experience (CLE), environment, and engagement among high school students in selected international schools in the Philippines who engaged in online classes during the pandemic. The purpose of the study is to evaluate how these factors influence student engagement (SE) through the use of Structural Equation Modeling (SEM). A descriptive research design was employed, with data collected from 342 via survey questionnaires. The study is grounded in the Self-Determination Theory, which posits that learning is shaped by environmental and cognitive interactions. Key findings show that although students had 1–2 years of online learning experience, many preferred face-to-face learning due to challenges such as time management and connectivity. Despite these hurdles, students rated the classroom environment positively, particularly in areas like professorial concern over academic rigor (AR) and structure. Engagement was evident across affective, behavioral, and cognitive domains, with differences observed based on student profiles. The SEM analysis revealed a significant relationship between classroom experience (CE), environment, and engagement, with course delivery and assessment (DA) identified as critical predictors of enhanced engagement. Moreover, AR and structure emerged as essential components in shaping the classroom environment. In conclusion, improving course delivery and strengthening academic structure significantly enhance SE in hybrid learning environments. These findings provide actionable insights for educators aiming to optimize student experiences in post-pandemic education.

Scrutinizing the role of advanced robotics in educational processes: A qualitative study

2024-11-28T02:10:21+00:00

The study aimed to evaluate the acumens of educationists concerning the benefits of robotics technology in education, motivation, challenges in executing robotics autonomy, and future suggestions. The study included 10 educationist specialists and utilized open-ended questions to collect perceptions of the subject. A current investigation produced subjects: security concerns, job substitution issues, customization, flexibility, educational inspiration, and administrative needs related to robotics innovation. The collected responses were lensed through the instructive systems, including the Technological Pedagogical Content Knowledge (TPACK) system, constructivist learning speculations, and the Frankfurt Triangle demonstrated to collect broad suggestions. This conduct found that robotics technology offers benefits such as information, common sense, inspiration, and engagement. Despite that, challenges such as innovation, sociocultural components, adaptability, security concerns, and versatility were recognized. Additionally, the study backed the idea that future progressions and administrative systems are pivotal for overcoming these challenges and improving part of robotics in education. The consideration emphasizes the need for versatile mechanical autonomy arrangements, integration with existing advances, and energetic administrative systems. Tending to work substitution concerns, security issues, and information security is fundamental to guarantee the secure use of mechanical technology in instruction. The research recommends that policymakers and teachers contribute to reasonable robotics technology units, accomplices with innovation suppliers, and funding for underserved educational institutions. Future robotics technology improvement should prioritize user-friendliness and consistent integration with existing innovations.

Evaluation of the effects of a hybrid laboratory for learning a hardware description language: Insights into student motivation and academic performance

2024-10-28T22:49:07+00:00

This research paper presents a study that investigates the effects of hybrid laboratories on learning Hardware Description Language (HDL) in digital electronics, focusing on student motivation and academic performance. With the advancement of telecommunications and computer applications in education, initiatives such as hybrid laboratories, which combine remote and on-site learning environments, have emerged. Despite this, the literature shows a lack of empirical evidence on the effect of these initiatives on students’ learning process in digital electronics. To address this gap, this study implemented a hybrid laboratory and a quasi-experimental design with two groups: an experimental group and a control group. The experimental group used the hybrid laboratory while the control group practiced in a traditional physical lab. Student motivation was assessed through the MSLQ-Colombia questionnaire and a perception survey, while academic performance was measured through laboratory report grades. Quantitative results showed no significant improvements in learning motivation or academic performance in the experimental group. However, qualitative analysis revealed improvements in students’ learning self-efficacy expectations, beliefs about control over learning, value of the task, autonomous learning, reduction of anxiety in the evaluation process, and confidence in experimentation among students in the experimental group. These qualitative findings provide insights for the design of new educational initiatives aimed at improving HDL learning environments.

Designing and developing a mobile teacher professional development course for digital game-enhanced language learning

2024-11-24T13:06:12+00:00

While digital games hold promise for language learning, teachers often lack the knowledge and confidence to integrate them into their curriculum. Existing professional development opportunities are scarce and not always accessible. In this study, a mobile teacher professional development course on Digital Game-Enhanced Language Learning was designed, developed, and evaluated through three iterative cycles. The research employed a Type 1 design and development research methodology. Three groups of language instructors teaching English at the tertiary level participated in the iterative cycles. Data collection included course evaluation questionnaires, achievement tests, lesson plan development, and participant interviews. The findings indicated that the mobile teacher professional development course was effective in improving teacher perceptions of the course content, usability, and self-efficacy in integrating digital games into their teaching. The course also led to a significant increase in participants’ knowledge of Digital Game-Enhanced Language Learning concepts. Overall, the mobile teacher professional development course has the potential to be a valuable tool for equipping language teachers with the skills and confidence needed to leverage digital games in their classrooms. This is particularly relevant considering the growing need for accessible and flexible professional development opportunities, such as during a global crisis.

Enhancing digital competency in EFL teacher education: Investigating graduate-level student teacher’s design and implementation of digital materials

2024-11-06T02:43:05+00:00

In modern educational technology, the digital competencies necessary for effective English language instruction remain relatively unexplored. This research addresses this knowledge gap by examining a graduate-level course designed to prepare prospective EFL student teachers with the essential skills to create digital teaching resources. Grounded in the SAMR framework, this investigation aims to introduce a new pedagogical design reflecting the progression of digital evolution. The primary goal is to determine the overall effectiveness of this structured approach in enhancing graduate students’ digital proficiency and instructional capabilities. By utilizing the SAMR model, the study hopes to establish a standard for assessing technology integration in pedagogical training, thereby improving the digital skills of upcoming EFL instructors across diverse technological platforms. The research narrative is presented across two interconnected academic settings: a graduate module emphasizing practical expertise in developing digital assets and a parallel online undergraduate English module for implementing these digital materials. The findings highlighted both the transformative potential of digital tools and the challenges in their adoption, emphasizing the necessity for training that integrates both technical aspects and pedagogical principles. This study provided strategic insights for curriculum developers in teacher education and offered guidance for future English instruction.

YouTube as a source of professional development for kindergarten teachers: A quantitative analysis of micro-videos

2024-09-09T06:17:37+00:00

YouTube has evolved into a global platform for formal and informal education. It has become one of the most important methods of digital transformation in educational and training institutions. The research aims to find out whether YouTube videos can be a useful source for the professional development (PD) of teachers, trainees and professionals in the field of kindergarten. 380 videos were selected; and sorted according to specific criteria. 94 videos were included finally. The video style, number of views, length, likes and comments are specified. The research used quantitative analysis of videos using the Instructional Design Quality Framework (IDQF). The beneficiary’s response was compared using the Keller Learning Motivation Model (ARCS model), and the relationships between the variables of the two frameworks were determined using the Pearson correlation coefficient at a significance level (0.05). Correlation results indicated a strong negative relationship between video length and the number of views and likes. While a weak negative relationship was found between video length and comments on the IDQF design and the dimensions of the ARCS model, a strong positive relationship was found between summed IDQF assessment scores and liking. There was a strong positive relationship between evaluation of instructional design quality and positive comments on the IDQF items and dimensions of the ARCS model. The talking head was the most commonly used style in producing video clips. Beneficiaries preferred short video clips.

Evaluating AI adoption among university students in Indonesia: A case study at the Department of Office Administration Education at the Universitas Sebelas Maret

2025-01-24T00:08:27+00:00

The integration of artificial intelligence (AI) in education has gained global attention, yet significant gaps exist in the understanding of how AI adoption varies across academic disciplines and geographical regions. In Indonesia, particularly in office administration education, limited empirical evidence exists regarding the intersection of AI adoption patterns, user preferences, and educational outcomes. This study examines AI tool adoption among office administration students at Universitas Sebelas Maret (UNS), Indonesia, via an integrated framework that combines the technology acceptance model (TAM) and the information system (IS) success model. Structural equation modeling (SEM) analysis of data from 61 undergraduate students revealed that ChatGPT was the predominant AI tool among students. The analysis identified key relationships between information quality, system quality, and user acceptance factors. The findings support experiential learning theory principles and demonstrate that successful AI integration in education depends on user-friendly interfaces, quality content delivery, and robust support systems. These insights enhance our understanding of AI tool adoption in Indonesian higher education and provide practical strategies for effective AI integration in academic curricula.

Technology integration levels and related beliefs of Mathematics Teacher Educators in Chile

2025-02-02T13:40:16+00:00

Digital technology integration is a fundamental component of Mathematics Initial Teacher Education. Mathematics Teacher Educators (MTEs) are responsible for providing future teachers with equitable and high-quality technology experiences, given their pervasive role. Technology-related Beliefs of MTEs may influence the frequency and quality of these experiences, although we still lack enough understanding about this influence. To understand the relationship between levels of technology integration reported by Chilean MTEs and their technology-related beliefs, we distributed an online questionnaire to 450 MTEs, obtaining 85 complete responses. We analyzed the data utilizing structural equation modeling (SEM). Results suggest that beliefs explain 49% of MTE’s reported levels of technology integration, where “time-consuming” and “multiple representations” beliefs show the strongest link to MTEs´ levels of technology integration. These findings confirm that beliefs are a highly determining factor for MTEs’ technology integration, are coherent with the local incipient integration of technology, and signal digital technology uses rooted in the mathematical domain. These local findings can also contribute to the broader international context.

Promoting higher-order thinking through online collaborative concept map recomposition

2024-11-18T01:48:53+00:00

This study evaluated the effectiveness of online collaborative kit-build concept mapping (CKB) in promoting higher-order thinking (HOT). Online collaborative kit-build concept mapping is a method of synchronous collaborative learning that applies the kit-build concept map framework, which proposes the recomposing method. Using a quasi-experimental procedure, sixty-nine undergraduate students were divided into an experimental group performing a CKB activity (n=33) and a control group conducting an online collaborative scratch-build concept mapping (CSM) activity (n=36). All students were assessed on their ability to answer HOT questions about specific learning content before and after collaborative mapping. The results showed that individuals in the CKB group performed better in solving HOT questions than those in the CSM group.

Unveiling the landscape: A systematic review of personalized learning facilitated by learning management system

2025-01-23T11:31:34+00:00

Personalized learning (PL) initiatives represent a powerful instructional strategy that prioritizes a learner-centered approach, allowing educators to tailor content to meet individual students’ characteristics and needs. Various technologies have been developed to support PL, the integration of Learning Management Systems (LMS) has emerged as a particularly effective to deliver adaptive materials and strategies in classroom settings. This study presents a systematic literature review on the application of LMS in facilitating PL, guided by PRISMA protocols to ensure rigorous screening and inclusion of relevant studies. Out of an initial 1,069 publications from 2014 to 2024, a total of 61 studies met the inclusion criteria. Findings highlight promising opportunities to enhance standard LMS features with data-driven tools that support personalized learning. Additionally, this study highlights the need for further research into learner attributes extending knowledge levels and learning styles. It also encourages exploring learning outcomes that transcend cognitive achievements.

Empirical analysis of teacher-student interaction patterns in synchronous online learning: Teaching English as a Foreign Language in Vietnam

2025-01-20T02:08:21+00:00

Synchronous online learning (SOL) is becoming a common learning modality among students in higher education. However, concerns remain about student loneliness, stress, anxiety, and social isolation arising from reduced face-to-face interaction. Students’ language learning often depends on teacher-student interaction, an important element of language acquisition. While studies examine interaction types and their frequencies, how these occur in SOL needs more focus. This exploratory study explored various interaction patterns between a university teacher and students in an online English class delivered through Microsoft Teams. Interaction transcript data were extracted from fourteen SOL sessions and analyzed using Content and Thematic Analyses. The findings reveal five interaction patterns: Moving along, Coaxing, Degrading, Demanding, and Polling. Data were further analyzed for prevalence and frequencies. Moving along was the most prominent pattern observed in the data. In this pattern, the teacher tends to progress the learning activities after observing students performing satisfactorily on a given task. Coaxing was the second frequently observed pattern. It entails the teacher encouraging interaction among students when they sense students are delaying their response to particular activities, stimulating in-depth discussion. Degrading and Demanding were the least common patterns to students’ unsatisfactory responses. Polling interaction patterns occurred fairly often when students were given time and space to respond to the teacher’s query, intended to improve engagement. The study provides a generic and practical view of interaction patterns in SOL and implications for teaching and learning in SOL environments.

Artificial intelligence in higher education: Opportunities and concerns

2024-10-14T03:56:23+00:00

This qualitative study investigates the opportunities and concerns regarding the integration of artificial intelligence (AI) in higher education. Through in-depth interviews with students, faculty, parents, administrators, policymakers, and employers, the research explores the complex landscape of AI adoption in colleges and universities. Thematic analysis reveals shared anxieties about equity and inclusion, the preservation of human interaction in teaching, potential job displacement, the ethical implications of AI, technical capabilities and resource requirements, the impact on educational quality and student outcomes, and the alignment of AI education with workforce demands. The findings underscore the need for a collaborative and transparent approach to AI integration that addresses stakeholder concerns and prioritizes ethical considerations, pedagogical effectiveness, and societal values.

Causal discovery for automated real-world educational evidence extraction

2025-01-22T06:46:03+00:00

There is increasing demand to shift from intuition- and experience-based practices to evidence-based education. However, extracting meaningful evidence from real-world educational data poses significant challenges. Traditional approaches to evidence generation, such as randomized controlled trials and systematic reviews, face limitations in both the medical and educational domains due to high costs and ethical constraints. In response, the concept of real-world evidence has emerged as a promising alternative, particularly in medicine and, more recently, in education. Although this approach may be less robust than traditional methods, it offers the potential to uncover broad and practical insights from naturally occurring data. This study explores the use of deep learning for causal discovery in real-world educational data. Specifically, we apply Structural Agnostic Modeling, a method previously validated in biological datasets, to identify underlying causal relationships. In Study 1, we compare this data-driven approach to a traditional hypothesis-driven method. The results demonstrate that this technique can generate both interpretable and novel causal hypotheses, although it occasionally produces plausible relationships in the reverse direction. To address this limitation, we propose an enhanced model, SAM+, in Study 2. Our findings indicate that SAM+ effectively mitigates the identified shortcomings. This research contributes a new methodology for leveraging large-scale educational data and opens new possibilities for advancing evidence-based education.

From learner-built to expert concept maps: An evaluation of the effects of closed concept map recomposition on learning

2024-11-18T04:37:56+00:00

Kit-Build concept map framework offers a unique approach to enhancing learning through concept mapping. It involves decomposing an expert map into components, which are then used by learners to construct their own concept maps. Kit-Build concept map can accurately detect differences between the learner’s map and the original expert map at a propositional level. In this study, we developed an activity that guides learners to complete the same map as the expert map by presenting the detected proposition-level differences and encouraging learners to correct them. We report on the learning effects of this activity by comparing it to a Kit-Build concept map activity conducted without the feedback or expert map completion task. Our findings reveal that engaging in Kit-Build concept mapping with expert map completion task significantly enhances reading comprehension compared to the Kit-Build concept mapping control group. Importantly, this improvement persists even after a two-week interval. Although the activity requires more time than Kit-Build concept mapping control group, the time-on-task does not predict learning improvement, underscoring the value of the proposed guidance. Further analysis demonstrates that this process not only helps learners acquire new knowledge but also consolidates their understanding of previously learned information.

Impact of reusing question banks on test integrity and student learning

2024-12-30T08:26:54+00:00

Instructors are increasingly utilizing the convenience of computer-based testing to produce randomized versions of examinations to maintain assessment integrity. As preparing a sufficiently large bank of questions for examinations can be very demanding, instructors may be tempted to utilize the same question bank for both practice quizzes and examinations. However, as some of the questions could be exposed during practice, sharing banks would raise concerns about the integrity of the examination. This study developed a formula for calculating the expected integrity of an examination’s question bank and then used non-parametric statistical tests to analyze the benefits and risks of sharing question banks between assessments. The study found that sharing banks can still provide learning benefits without significantly impairing the authenticity of an examination. The study also showed that a bank’s integrity was not correlated with student performance, question exposure alone did not lead to improved performance, and learning from practice questions improved students’ examination performance.

Use of Medium platform in teaching EFL writing, academic self-efficacy, and undergraduate students’ perceptions

2024-12-30T08:16:17+00:00

In an era where digital platforms have become ubiquitous, it is necessary to integrate digital teaching tools in education to help students learn. There have been many digital teaching tools reported in research on the teaching of English; however, the use of Medium platform to teach students write an argumentative essay in English is scarcely reported. This study investigates the application of Medium platform in the teaching of argumentative writing to undergraduate EFL students, the contribution of academic self-efficacy, and the students’ perception of Medium platform application. In the treatment, the students were asked to use Medium platform to learn how to write argumentative essays. Following the completion of the teaching, the students’ writing achievement was tested and compared across academic self-efficacy. Finally, the students were asked to respond to a 5-point Likert-scale questionnaire. The students’ scores of the posttest were compared to their scores before the treatment. Analysis of t-test indicated that there was a significant difference between the students’ argumentative writing achievement before and after the treatment (p < 0.05). Comparisons of students’ scores across academic self-efficacy levels showed that there was no significant difference between the argumentative writing achievement of the students with high and low levels of academic self-efficacy. Analysis of the students’ perceptions revealed that the students had positive responses to the use of Medium platform in the teaching of argumentative writing. The findings imply that Medium platform is a versatile tool that can accommodate diverse learners in terms of academic self-efficacy in writing instruction.

Exploring EFL students’ digital well-being through scenario-based assessment: A vignette study in Vietnamese universities

2025-03-18T07:25:33+00:00

This mixed-methods study investigates Vietnamese EFL university students’ digital well-being and emotion regulation in technology-mediated learning environments. Through quantitative surveys (N=342) and qualitative interviews (n=40), the research examined students’ emotional experiences across different educational technology scenarios and their regulation strategies for maintaining digital well-being. Findings revealed complex patterns of co-existing anxiety and enjoyment, with significant variations across synchronous and asynchronous activities. Technical proficiency emerged as a key predictor of positive emotional experiences, while gender differences indicated higher anxiety levels among female students. The study identified three main categories of emotion regulation strategies: proactive preparation, real-time adjustment, and post-session reflection, with strategy effectiveness significantly predicting digital well-being outcomes. Results demonstrate the critical role of institutional support systems and peer networks in successful emotion regulation. This research contributes to digital well-being theory by illuminating the intricate relationship between emotional experiences, technical competence, and cultural factors in online language learning contexts.

Automatic generation of introductory programming exercises with large language models

2025-03-06T03:13:38+00:00

Despite recent advances in code generation made possible by large language models (LLMs), programming is still an essential skill that computing students need to master now and in the foreseeable future. In learning programming, frequent practices with exercises set at an appropriate difficulty and knowledge level is of crucial importance for students. However, it’s not a trivial task for instructors to create many good quality exercises customized for each student. Programming problems found on Internet sources such as LeetCode are mostly too challenging for novice programmers with no prior coding knowledge. Recent work in AI-enabled education has been leveraging LLMs for adaptive feedback generation on code submitted by students. Not much work has been done in generating customized exercises for students to have more practice. In this work, we propose ExGen, an automatic exercise generation system which uses LLMs such as OpenAI’s GPT models to generate on-demand, customized, and ready-to-use programming exercises for individual students. ExGen is designed as a plugin to Visual Studio Code. It incorporates a set of prompting strategies for candidate exercise generation, and a novel chain of automatic filtering mechanisms to select ready-to-use exercises. ExGen is convenient to use as compared to chatbots such as ChatGPT. We have conducted an extensive performance evaluation using more than 1400 generated Python exercises. We considered several prompting strategies with various keyword and seed exercise types, filtering techniques, difficulty levels, and LLMs with different generative performance and cost. The results demonstrated the effectiveness of ExGen’s design and implementation.

Trends in educational technology research: Examining seamless learning, metaverse and educational robotics

2025-04-26T01:26:16+00:00

Technology in education offers significant opportunities for innovation, particularly in the design of transformative and engaging learning activities. Prominent approaches in the field of technology-enhanced learning (TEL) include seamless learning, metaverse education and educational robotics, which together have potential to drive advances in education. This study employs bibliometric literature review to explore the potential of metaverse technologies and educational robotics in supporting seamless flow of learning across various contexts. Through keyword co-occurrence analysis, key themes, emerging trends and connections between these areas are identified. The findings highlight the central role of virtuality and artificial intelligence in enabling metaverse-based education and educational robotics. The research and development in digital twins, hybrid extended reality, immersive human-computer and human-robot interfaces, emerge as key topics in supporting seamless learning and personalized learning scenarios. This study highlights an underexplored area of aligning these technologies with pedagogical approaches, and identifies the need for the development of systems and data management approaches for seamless learning with the metaverse and robotics at a more general learner population level.

Generative AI in educational processes: ChatGPT-4 in providing feedback to students’ written responses

2025-04-17T15:45:49+00:00

This article examined the use of ChatGPT-4 in offering written feedback to students regarding their open-ended responses in written exams. Proper feedback is crucial for learning, helping students to understand their strengths, identify areas for improvement, and devise strategies and practices for future learning. However, crafting detailed and systematic feedback is a time-intensive task for teachers. Consequently, there is growing interest in educational circles to leverage generative AI and Large Language Models (LLMs) like ChatGPT for facilitating feedback provision as part of adaptive learning environments. For this article, ChatGPT-4 was employed to generate feedback for university students’ written exams. It familiarized itself with evaluation guidelines, three short articles as learning materials in English and related 54 student responses, which varied in length from 24 to 256 words in English. Then it evaluated these responses and provided each student with personalized feedback that was on average 64 words long. The findings suggest that ChatGPT-4 has the potential for providing systematic and constructive feedback on students’ written exam responses. ChatGPT-4 need to be instructed with precisely crafted prompts to ensure the feedback is precise and consistent and aligns with teacher’s and educational institution’s objectives to support students in learning.

An empirical study on the impact of generative artificial intelligence-based learning activities on college students’ deep learning

2025-05-15T06:34:42+00:00

Deep learning, emphasizing the comprehensive understanding and transfer of knowledge, is a critical indicator of learning quality among college students. Generative artificial intelligence (AI), through its support for efficient feedback and personalized learning, offers a new technological approach to fostering deep learning. This paper, grounded in Activity Theory, presents a deep learning activity model enhanced by generative AI technology. A quasi-experimental study was conducted over a semester, using the “Modern Educational Technology and Informatization Practice” course as a case study to validate the model’s effectiveness. The study found that the model positively contributes to learners’ learning process performance, knowledge acquisition, cognitive development, and emotional experience. This paper provides empirical evidence supporting the practical application of generative AI in promoting deep learning among college students, highlighting the need for continuous evaluation and refinement to fully harness its potential in advancing the technological transformation of higher education.

Beyond reality: Empowering autistic learners in communication

2025-04-30T04:58:14+00:00

Autistic learners encounter a range of communication challenges in social-emotional communication, non-verbal communication, and building and sustaining relationships. This conceptual paper explores the impact of technology, particularly extended reality (XR), in aiding individuals with autism spectrum disorder (ASD) in enhancing their communication skills. It begins by providing a concise summary of the three main communication obstacles faced by individuals with ASD, and then proceeds to examine various technologies used for ASD education. The primary objective of this paper is to explore the relationship between XR and ASD education through the introduction of a five-component model. It concludes by offering practical recommendations for integrating XR into communication training for individuals with ASD.

Technology-enriched learning through the lens of Bloom’s Taxonomy: A practice-based framework from classroom observations

2025-04-16T03:30:37+00:00

The benefits of incorporating technology into education are promising; however, there are limited suggestions on how to transform traditional classrooms into technology-enriched learning environments. To address this gap, this project adopts the grounded theory approach, framed within Bloom’s Revised Taxonomy and outcome-based education principles. It involved observing sixty-six real-life classes across academic levels to gather teaching practices that involve the use of technology. The collected teaching practices were classified into five major categories based on their intended purpose and the alignment with cognitive learning levels from Bloom’s Taxonomy: interactive learning activities (Remember/Understand), experiential learning activities (Apply), mutual learning activities (Analyze), innovative learning activities (Evaluate), and performance-based learning activities (Create). This categorization allows for a comprehensive understanding of how technology can be effectively integrated to achieve different cognitive learning outcomes. A panel of experienced teachers with doctoral degrees and at least five years of professional teaching experience evaluated these practices’ desirability and transferability across educational contexts. Such an evaluation provides incremental insight into the essential factors underlying effective transformation while considering the transfer of learning principles central to outcome-based education. This project provides theoretical, practical, and methodological implications for the field and teaching practitioners.

Exploring the role of peer review in computational thinking development among pre-service teachers

2024-11-08T02:59:11+00:00

Computational thinking can be interpreted as a cognitive process that provides a new paradigm for higher-order thinking about successfully solving problems posed in a technology-mediated teaching and learning context. Peer review has been employed as an effective learning strategy to enhance cognitive practices such as critical thinking, reflection practices and collaborative experiences. A qualitative case study was conducted to explore the role of peer review as a learning strategy of computational thinking among pre-service teachers. The peer comments were coded by adopting a coding scheme of comments, and the interview transcripts were analysed to investigate the significance of the peer-review process and student perceptions of what is most beneficial. Each student was required to design a lesson by integrating the computational thinking facets into their lesson plan. Upon submitting the lesson plan, they were engaged in a blind review process. Individual student reviews the lesson designed by their peers and provides their comments. By adapting a peer-review cognitive process model, this article provides evidence that the peer-review process played a critical role in facilitating pre-service teachers’ computational thinking, particularly problem-solving competencies. The findings indicate that peer review strategy can facilitate computational thinking by enhancing pre-service teachers’ higher-order thinking through constructing and providing critical feedback to their peers. The students perceived the peer-review process was beneficial in improving their computational thinking-integrated lesson design. However, it was suggested that the students be informed about the purposes and learning benefits of the peer-review process to improve their learning experience.

The evaluation of concept map recomposition order and its effect on learning outcomes

2025-06-10T03:59:12+00:00

Concept map serves as a visual tool in education, facilitating the organization and representation of knowledge. Concept map recomposition activity, which is a kind of concept map building activity, has been shown to promote meaningful learning and enhance reading comprehension. In this process, the teacher creates an expert map from a text material, decomposes it into individual concepts and links, and the learners then recompose these components. During the recomposition activity, learners connect concepts and links to form propositions, using information acquired from teacher’s explanation and/or by reading the text material. However, since the information in the text is generally presented in a specific sequence, it is important to evaluate whether following this sequence during the recomposition affects their learning outcomes. Understanding this is beneficial for teachers in providing support in concept map recomposition activities. This research evaluated the similarity between the recomposition order and the text’s information order, and how it relates to learning outcomes. The results revealed that various recomposition orders led to equal learning outcomes. However, the recomposition order was related to the aspects of the activity, which are time on task, time required to perform each action and map quality. This finding suggests that teachers should provide support that adapts to differing recomposition order, recognizing that learners may approach the recomposition activity in different ways.

Enhancing personalised learning with artificial intelligence - Implementation challenges from educators’ perspective in vocational education and training

2025-05-12T07:27:11+00:00

With the recent uptrend of personalised learning (PL) coinciding with the advancement of artificial intelligence (AI) technologies, Singapore has been encouraging the mainstream education to adopt PL by tapping on the AI’s capabilities and potential. Although a Singapore’s vocational education and training (VET) institution had planned to pluralise PL with AI, they recognised that staff might face potential challenges hindering its implementation. A qualitative case study was conducted to explore the feasibility of implementing PL across the institution from the perspective of VET staff. Semi-structured interviews were carried out on six experienced VET staff members from four different faculties to gain insight into their prior knowledge, existing experience and future perspective of PL with AI. Adopting Cultural-Historical Activity Theory (CHAT), the data were sorted based on themes that contradict the notion of pluralising PL with AI. Through abductive reasoning approach, the findings indicated that the division of labour, community and rules contradicted the mass consumption of PL due to the lack of PL pedagogical knowledge from VET staff and the complex setup of various diploma courses in the institution. Additionally, the usage of AI to support or enhance PL and the VET institution’s direction to pluralise PL without thorough research and guidelines was further contradicted by the community and the division of labour. Therefore, this study recommends VET institutions not to pluralise AI PL too early. Instead, VET institutions are recommended to conduct small-scale AI PL to build up use cases and staff confidence prior to institutional wide adoption.

Generative artificial intelligence in K-12 education: A systematic review

2025-03-29T22:10:52+00:00

With the continuous innovation of deep learning algorithms, Generative Artificial Intelligence (GenAI) technology is rapidly developing globally and gradually expanding its application scenarios in multiple fields, especially in education. Considering the novelty of this field, there is currently a scarcity of comprehensive research on GenAI in K-12 education. Therefore, this systematic review aims to reveal the application trends, teaching themes, tool adoption, research methods, challenges, and advantages of generative artificial intelligence in K-12 education through the in-depth analysis of 45 studies between 2020 and 2024, providing theoretical and empirical support for future research and practice in this field. Our thematic analysis results indicate that GenAI tools can significantly improve students’ academic performance and cognitive abilities, enhance their learning motivation, and thus promote the development of personalized learning. However, using these tools also brings a series of challenges, including misleading or erroneous content generation, difficulty in understanding technology, students’ dependence on technology, and privacy infringement. In addition, the shortcomings demonstrated by educators in terms of AI literacy emphasize the necessity for relevant educational institutions to organize targeted AI literacy training. Finally, given that we are currently in the early stages of developing generative artificial intelligence, most existing empirical research has focused on the short-term impact of GenAI tools on K-12 education. Future research will incorporate more longitudinal studies to systematically evaluate the long-term and deep implications of GenAI in education.

Hybrid learning environments in higher education: A systematic review of emerging learning and teaching modalities

2025-05-14T07:42:39+00:00

Since the onset of the pandemic, hybrid learning environments have seen significant expansion to cater to diverse learning preferences across different domains. As educators become more familiar with these settings, they encounter challenges and opportunities. Hybrid learning must meet the needs of both in-person and remote students, ensuring fair access to educational outcomes. Our review reveals varied experiences among teachers adapting to these technologies and methods. From students’ perspective, hybrid learning enhances autonomy and self-directed learning as they navigate in-person and online modalities. It suggests that personal dispositions significantly impact student engagement more than peer interactions. Educators also need additional academic development opportunities to adapt curricula for hybrid delivery. Future research should continue to explore how to better support educators and students in these settings, focusing on optimising design principles for hybrid learning, enhancing digital tool integration, and developing personalised learning paths to accommodate diverse students and improve learning outcomes.

Students’ perceptions of challenges in online reading and their affective responses: A focus group study

2025-06-11T21:26:35+00:00

In the present-day digital landscape, the internet serves as an essential medium for learning and acquiring information. As reliance on internet-based reading increases, it is necessary to address and resolve the difficulties encountered by the readers in this medium. Keeping this objective in mind, this study investigates the challenges faced by students and the affective responses they evoke while reading on the websites for educational purposes. Three focus group discussions were conducted with six participants each to explore the students’ perceptions and experiences while reading through websites. Four themes emerged related to the challenges of website reading such as: (i) distractions and interruptions, (ii) information overload, (iii) difficulty in using active reading strategies like highlighting and annotating, and (iv) difficulties while using hyperlinks. The results further show that these challenges evoked various unfavorable affective responses in the readers depending on the challenge they faced. The study concludes that these challenges and the ensuing emotional responses are likely to detract from the seamless reading experience and diminish the enjoyment derived from learning. Understanding such challenges faced by students while reading through websites is important for educators in making necessary interventions to enhance the effectiveness of online reading and learning.