What drives Generation Z (Gen Z) university students in Vietnam to adopt and keep using Mobile English Learning Apps: content quality or something else? This study proposes a Social Override effect, that is, a pattern in which peer validation and hedonic engagement, rather than content quality, appear to drive actual use even when information quality is adequate. Using an explanatory sequential mixed-methods design, this study analysed survey data from 150 Vietnamese university students alongside 10 semi-structured interviews. Information Quality did not significantly predict actual use (β = 0.147, p = 0.103); Hedonic Motivation did (β = 0.401, p < 0.001). This pattern is consistent with a hygiene-factor interpretation of content quality: its absence may generate dissatisfaction, but its presence does not, on its own, increase usage. The interviews help explain why. In this setting, peer recommendation and group-based app use create a buffer that lets students overlook technical limitations and advertising friction. Among these Gen Z students, trust was expressed through interface aesthetics and social visibility more than through content accuracy. Whether the same pattern holds beyond Vietnamese university students is a question this single study cannot settle.
This study explores the impact of applying ChatGPT-4, a generative artificial intelligence (AI) model, in the teaching of Business Mathematics. The research had a dual aim: to generate diverse problem sets to support teachers, and to enhance students’ critical thinking by involving them in the verification of AI-generated solutions. Conducted with 342 undergraduate students at the University of Debrecen, the experiment focused on differentiation tasks. ChatGPT-4 solved these with 94% accuracy, and the majority of students (90%) also performed well. Student feedback indicated that the approach was both useful and motivating. Cluster analysis identified three distinct learner groups – Self-Determined Enthusiasts, Duty-Bound, and Drifters – who differed significantly in their engagement with AI-based learning. While most students positively evaluated the use of ChatGPT-4, many also recognised its limitations and the need for critical reflection. The findings suggest that the conscious and pedagogically grounded integration of AI into mathematics education holds considerable potential. However, the development of critical awareness and the continued presence of human oversight remain essential to ensure meaningful learning outcomes. However, its effectiveness depends on ethical use, ongoing critical reflection, and the sustained pedagogical involvement of educators.
This article critically examines the integration of digital resources (DR) in university foreign language teaching through a meta-aggregative systematic review of 60 peer-reviewed studies published between 2001 and 2025. Adopting a complex, situated, and posthuman epistemological perspective, the study combines a meta-aggregative synthesis conducted in accordance with the Joanna Briggs Institute guidelines with a complementary bibliometric analysis of 140 references. Seven thematic categories were operationalised, and the analytical procedures included frequency analysis, co-occurrence mapping, evolutionary analysis across 5-year periods, and Pearson’s chi-square test. The findings reveal the predominance of instrumental and technocratic orientations in the adoption of DR, characterised by limited pedagogical grounding and the increasing reduction of teaching agency to performance indicators, data-driven processes, and algorithmic governance. Although frameworks such as Technological Pedagogical Content Knowledge and the Unified Theory of Acceptance and Use of Technology provide operational value, they do not fully account for the contextual, relational, and subjective complexity of teaching practices. Critical and posthuman perspectives have gained visibility but remain secondary within the field. The analysis also identifies a significant geographical bias towards the Global North, restricting the development of situated and context-sensitive knowledge. In response, the article proposes reconceptualising DR as semiotic and techno-cultural environments that actively configure knowledge practices, professional identities, pedagogical decisions, and educational relationships. The complete list of the 60 studies constituting the analytical corpus is provided in Appendix A.
With the launch of Saudi Vision 2030, Information and Communication Technologies (ICTs) have been integrated into one of their realisation programmes, aiming to raise the quality of education resulting in a digitally literate citizenry for a vibrant community. Existing research has proven a direct and positive impact of ICTs on student engagement and satisfaction. However, studying the role of ICTs in Saudi Arabian Universities and their impact on student learning, Surface and Deep learning is an unexplored territory. To investigate the statistical significance of ICTs intervention on surface and deep learning performances, a case study approach was used between two terms of first year Art History students using the Mann–Whitney U test and a comparative analysis of three writing samples from the same groups. Contrary to current studies, the results showed that ICTs have an inconsistent impact on surface learning but a definite and significant impact on deep learning. The impact was also observed to be positive on overall withdrawal rates, failure rates, and the quality of writing. Further studies are recommended to validate the findings with a bigger sample size and involving different programmes.
This article presents a structured protocol for contextualising digital teaching competence (DTC) in higher education through the co-creation of discipline-specific exemplars. Rooted in the national Spanish adaptation of the DigCompEdu framework (MCDDU), the protocol was implemented with 100 university lecturers, from 34 universities, across five broad disciplinary domains. Participants collaboratively generated over 4500 contextualised examples aligned to specific DTC indicators and levels of progression. The resulting open-access catalogues illustrate how abstract competences materialise differently across epistemic cultures, providing granular and authentic reference points for professional development, training, and assessment. We describe the methodology in detail, highlight patterns of variation, and reflect on the transferability of the process to other contexts. This study contributes both a reproducible protocol and a set of discipline-sensitive artefacts that may inform scalable DTC development strategies in higher education.
Considering the sensitive nature of the material, Islamic studies education is still provided with traditional pedagogies. In the current tech-driven era, the objective of the current study was to explore mainstream teachers’ perceptions of using ChatGPT as a pedagogical support in teaching Islamic Studies to Grade 8 students with learning disabilities in Pakistan. The study was guided by a phenomenological design. The participants were 10 elementary-level teachers with experience teaching Islamic Studies in inclusive classrooms. Data were collected using semi-structured interviews and analyzed using the thematic data analysis technique. The findings revealed that teachers believed that ChatGPT is a valuable tool for simplifying complex religious concepts, enhancing engagement, and generating relatable, real-life examples and stories that supported students with learning disabilities, contributing to the goals of inclusive education in line with Sustainable Development Goal 4. However, teachers also expressed concerns about inaccuracies, cultural mismatches, and the risk of misalignment with Islamic values. They emphasized the necessity of teacher supervision to validate and adapt ChatGPT’s outputs. The study concludes that ChatGPT has significant potential to support inclusive Islamic education but requires careful and human-supervised use. The study had significant implications for practice, policy, and research, highlighting the importance of ChatGPT-supported religious education.
Immersive virtual reality (VR) and interactive videos represent two forms of interactive multimedia utilized in education. Immersive VR, a relatively recent addition to educational technology, has gained attention with the advent of affordable commercial solutions and claims about its learning effectiveness. This study investigates and compares their impact on college students’ learning outcomes, motivation, and engagement. A total of 132 students participated in either immersive VR or interactive video learning experiences. Data were collected through pre- and post-knowledge assessments and self-report surveys measuring motivation and engagement. Findings revealed that participants in the immersive VR learning experience group exhibited significantly higher motivation and engagement than participants in the interactive video group. However, they achieved significantly lower learning outcomes than those in the interactive video group. Moreover, while motivation and engagement were positively correlated, neither factor showed a significant relationship with learning outcomes.
This study examines how Generative Artificial Intelligence Tools (GAIT) influence student learning performance (LP) through cognitive, affective and ethical pathways using Partial Least Squares Structural Equation Modeling (PLS-SEM). Data were collected from 292 Indonesian university students through a structured questionnaire. The results show that GAIT has a direct positive effect on LP (beta = 0.920, p < 0.001). Mediation analysis identifies AI Knowledge (AIK) as the most dominant mediator (beta = 0.715, p < 0.001), followed by AI Perception (AIP), Creativity (CRE), Fairness & Ethics (FE) and Cognitive Offloading (CO). Furthermore, AIK significantly moderates the GAIT-LP relationship (beta = 0.006, p = 0.048). The model demonstrates high predictive power (R-2 = 0.604) and good model fit (Standardized Root Mean Square Residual (SRMR) = 0.068). These findings highlight the central role of AI literacy and ethical awareness in maximising the benefits of GAIT for learning. This study contributes theoretically by integrating cognitive, affective and normative dimensions into a unified model of GAIT adoption and offers practical implications for designing AI literacy and ethics-oriented curricula in higher education.
This study aims to design a comprehensive and theoretically grounded digital competence training program for middle school students, based on DigComp 2.1: The European Digital Competence Framework. An explanatory sequential mixed-methods design was employed. In the first phase, the Digital Competence Identification Survey (DCIS) was administered to 262 teachers to identify the most essential competencies for seventh-grade learners. Teachers’ evaluations focused on both the perceived importance of digital competencies and their suitability for the seventh-grade level. The quantitative findings were compared with the DigComp framework and the related literature, and the content development process was refined through expert review by three specialists. Rather than producing an assessment-oriented outcome, the study translated the identified competencies into a structured instructional design. The competencies selected through this process were organized into three instructional units: Information Literacy, Digital Content, and Ethics and Safety. The resulting program includes 10 themes, 22 instructional hours, and 45 learning outcomes structured according to Bloom’s Taxonomy and aligned with the basic, intermediate, and advanced proficiency levels of DigComp 2.1. Data analysis combined descriptive statistics and qualitative content analysis. Instrument reliability was confirmed through high internal consistency coefficients, and content validity was ensured via expert consensus and iterative refinement. The developed program demonstrates strong alignment with national and international policy documents, including the Turkish Qualifications Framework, the Digital Turkey Action Plan, the MoNE 2023 Education Vision, and the EU Digital Education Action Plan. The study demonstrates a replicable process for translating broad digital competence frameworks into localized, actionable curricula for underserved middle school student populations.
This article explores students' perspectives on how AI conversations can enhance brainstorming within the Learning Management System (LMS), specifically Blackboard (BB). By analysing students' feedback, the study investigates how students are familiar with AI conversation, benefits, challenges, and future possibilities of this approach. The sample was selected to reflect a variety of learning backgrounds, featuring brainstorming sessions with participants of different ages and academic disciplines. The research utilises both qualitative and quantitative techniques, including an electronic survey distributed to a group of 103 students (78 males and 25 females) enrolled in the Leadership, Entrepreneurship, and Innovation course as well as the University Success course. The average age of the participants is 29, with most being in their first or second year of study. The findings highlight the significant role of AI conversations in boosting brainstorming skills (60.19%). In addition, notable variations in the perceived advantages of AI conversation in brainstorming were (chi(2) = 11.4, P < 0.01). chi(2) = Correlation coefficient and P = Percentage. It is proposed to enhance e-learning systems by integrating AI. Universities should integrate AI conversational tools into their e-learning platforms to enhance student engagement. This can be achieved by developing AI platforms and providing comprehensive training for students and faculty on how to utilise these tools effectively. These platforms should also be integrated into assignments, group activities, and brainstorming sessions to encourage individual and group collaboration.
Graphical reasoning in rotational kinematics remains a persistent challenge for secondary students, largely due to difficulties in interpreting and connecting angular displacement, velocity, and acceleration graphs. Similarly, the integration of science process skills (SPS) in physics instruction is often underemphasized. This study examined the effectiveness of META Messenger-based AI tutoring in improving students' graphical reasoning and SPS in the context of rotational motion. A clustered quasi-experimental design was employed with 120 Grade 12 students from a public secondary school in the Philippines, assigned to an experimental group (artificial intelligence [AI] tutoring, n = 60) and a control group (traditional instruction, n = 60). Students completed validated assessments of graphical reasoning, basic SPS, and integrated SPS before and after the 4-week intervention. Results indicated statistically significant learning gains in both groups, with the experimental group demonstrating substantially greater improvements. Posttest scores for the experimental group were significantly higher than those of the control group across all measures, with large adjusted effect sizes and confidence intervals consistently excluding zero. These findings suggest that conversational AI tutoring delivered via accessible platforms can provide effective scaffolding for complex, graph-based physics concepts while simultaneously fostering scientific inquiry skills. The study contributes to emerging evidence on AI-enhanced science education and illustrates a practical model for integrating adaptive technologies in resource-constrained contexts.
This study proposes an artificial intelligence (AI)-enhanced framework that integrates AI with the Mechanics, Dynamics, and Aesthetics framework through theory synthesis and framework development. It explores how generative AI, adaptive learning algorithms, and procedural content generation enhance gameplay to advance educational game design. The framework aligns AI capabilities with constructivist learning principles, supporting personalized, engaging, and scalable game-based learning. While the framework offers theoretical and practical guidance for AI-integrated educational games, further research is needed to assess its empirical effectiveness across diverse learning settings.
Lecture capture (LC) has become a standard feature in higher education, yet its impact on student performance and attendance remains contested. This study used a within-course availability comparison across four in-person undergraduate biology courses (N = 277, 352 enrollments), in which half of lecture blocks were recorded (LC-ON) and half were not (LC-OFF). Each block culminated in an independent exam, enabling within-student comparisons of performance under LC-ON versus LC-OFF conditions. Attendance was tracked electronically, and LC use was quantified from Zoom analytics.Students who accessed at least one LC video scored 4.7% higher on exams than non-viewers, consistent with self-selection differences between viewers and non-viewers. Within LC-ON blocks, greater viewing predicted higher performance (+1.3% per hour). In contrast, in adjusted mixed-effects models, exam grades were 6.0% lower in LC-ON blocks. Attendance did not significantly decline in LC-ON blocks, but higher attendance consistently predicted better outcomes. An interaction model indicated that attendance mitigated LC’s negative association with exam performance.Together, LC viewers outscored non-viewers overall; within viewers, more LC view time in LC-ON blocks is associated with higher exam %, whereas lower performance in LC-ON blocks by all may reflect behavioural changes that coincide with recording availability.
Identified as the single most predominant curriculum delivery vehicle in schools, textbooks not only play a crucial role in disseminating knowledge and organising learning objectives but also reflect learning approaches and curricular orientations. In Morocco, as in many developing countries, the process of updating textbooks is often slow and struggles to keep pace with rapid technological advancements, resulting in significant gaps in students’ learning experiences, especially for physics and chemistry, which require experimental material and contemporary examples. The rise of digital educational resources, such as Open Educational Resources (OERs) and open textbooks, presents an opportunity to address these challenges by offering a more accessible, dynamic and regularly updated version of this indispensable teaching material. This study investigates the impact of adopting an open textbook dedicated to the physics and chemistry course at the scientific common core level in the secondary cycle (K–12) in Morocco on student learning outcomes by providing a qualitative and quantitative analysis involving a sample of 160 students over two academic years 2022/2023 and 2023/2024. Data were collected using a questionnaire developed around the four components of the COUP (Cost, Outcomes, Usage and Perceptions) framework. Results have shown positive feedback from students praising the accessibility, affordability and interactive features of the open textbook, enriching their learning experiences and helping to improve their academic performance.
This study explores how Artificial Intelligence (AI)-enhanced adaptive learning supports technical competencies and emotional intelligence (EI) development in project management education. Using a mixed-methods design, it integrates Partial Least Squares Structural Equation Modeling (PLS-SEM) with thematic analysis to examine how intelligent learning systems influence conceptual mastery, engagement, and interpersonal skills. Findings show that AI-enhanced features, such as real-time feedback, simulations, and reflective prompts, enhance understanding of project management concepts while fostering EI capacities such as empathy, collaboration, and conflict resolution. Participants emphasised the importance of prompt engineering for personalisation, alongside concerns about bias, transparency, and ethical data use. Grounded in constructivist, experiential, and connectivism theories, the study proposes an illustrative framework for adaptive systems integrating cognitive and socio-emotional learning. The findings highlight AI’s potential to develop the hybrid skill sets essential for project leadership while calling for responsible, inclusive, and ethically governed implementation in higher education.
This study examines how generative artificial intelligence (AI) can assist secondary school teachers in Tanzania to create personalised learning paths more efficiently and effectively. Many educators face overcrowded classrooms and limited resources, making it challenging to meet the diverse needs of their students. To address this, 120 Dar es Salaam and Dodoma teachers tested AI-driven tools like ChatGPT and Grok for lesson planning, assessments and adaptive content delivery. The results indicated significant improvements in student engagement and academic performance while reducing teacher workload. Teachers found these AI tools intuitive and beneficial, especially for customising instruction and saving time. However, challenges such as inadequate training and infrastructure continue to pose significant obstacles, particularly in rural areas. The study concludes that generative AI offers a scalable and inclusive solution for enhancing teaching and learning when paired with proper support. It recommends strategic investments in professional development and digital infrastructure to fully realise generative AI’s educational potential and address existing equity gaps across Tanzanian schools.
As higher education continues to embrace diverse learning needs, the effective integration of assistive technology (AT) into instructional practices has become increasingly important. Despite its potential to promote accessibility and inclusivity, many faculty members lack a clear understanding of what constitutes AT and how to implement it effectively in the classroom. This study explored the challenges higher education faculty face in adopting AT, identifies knowledge gaps that hinder its use and proposes strategies for improving faculty preparedness through targeted professional development. Findings indicated that whilst faculty generally recognise the value of AT in creating inclusive education, its practical application is often limited by insufficient awareness, inadequate training and lack of institutional support. This study highlighted the need for a coordinated, campus-wide approach to AT implementation that includes faculty training, accessible support structures and the promotion of a culture that normalises the use of AT in higher education.
This research investigates the design and application of a culturally appropriate, modular Internet of Things (IoT) learning module for undergraduate business students, responding to the demand for interdisciplinary education merging technology and business expertise. By blending modular biomedical circuits, IoT power management and a blended learning approach, this course sought to promote student engagement, technological confidence and relevant innovation. Students assembled biomedical sensor circuits, like heart-rate and temperature monitors, which connected to IoT dashboards for data visualisation, to experience tangible links between physical computing and business. The course included 128 students from two groups, ending with individual projects and team contests. Data for this qualitative study came from student journals, focus groups and project artefacts. Four major results were found by the thematic analysis: learner motivation increased via modular practice, comprehension improved through contextualised applications, interdisciplinary collaboration skills grew and competitive innovation outcomes benefited from successful knowledge transfer. Five student teams’ projects earned national recognition; they involved smart poultry farming and energy-efficient hospitality systems. These findings emphasise how IoT education can enable non–Science, Technology, Engineering, and Mathematics (non- STEM) learners.
Augmented reality (AR) integration in learning aims to improve overall educational experiences through multiple pathways, with cognitive processing enhancement serving as a fundamental mechanism. Whilst AR’s benefits encompass motivation, engagement and satisfaction, understanding how AR influences cognitive processing provides crucial insights into the underlying mechanisms that drive these broader improvements. Despite broad recognition of this goal, it remains underexplored. Drawing on cognitive absorption theory, this study examines how key cognitive absorption factors influence cognitive processing benefits. Data were collected from 184 university students and analysed using partial least square-structural equation modelling and importance-performance map analysis (IPMA). Findings reveal that enjoyment, control and curiosity significantly influence perceived usefulness (PU) (R2 = 62.4%) and ease of use (R2 = 65.4%). These factors, in turn, mediate immersive experiences (R2 = 63.7%), which significantly affect cognitive processing benefits (R2 = 55.3%). The results suggest that within AR-based learning, traditional technology acceptance models should be reconsidered. Notably, whilst perceived ease of use and enjoyment are important (as shown by IPMA), they do not significantly impact PU. Additionally, multi-group analysis indicates that AR-supported learning results in consistent cognitive processing outcomes for students from both natural and social sciences, suggesting AR’s broad applicability across academic disciplines.
Following the 2022 invasion of Ukraine, thousands of Ukrainian children enrolled in schools across Europe. In Spain, most lacked prior knowledge of Spanish. This study examines whether real-time speech-to-text translation technology (STTT) can reduce classroom language barriers. Two activities – a fable reading and a neuroscience lecture – were conducted with 12–15-year-old Spanish-speaking students (n = 23) and Ukrainian students unfamiliar with Spanish but bilingual in Ukrainian and Russian. Using PowerPoint 365, the teacher’s speech was transcribed and translated into Russian – which at the time was far more reliably supported by automatic translation tools than Ukrainian – and projected onto a shared classroom display. Although this choice was based on technical and pedagogical criteria, it later drew some resistance, reflecting the sociopolitical sensitivities surrounding language use in wartime contexts. Comprehension was assessed using content-specific questionnaires. Ukrainian students scored lower than their Spanish peers but significantly higher than a control group (n = 22; p < 0.001; Cliff’s delta indicated large effect sizes). Qualitative analysis of teacher interviews highlighted improvements in comprehension and inclusion, along with implementation challenges. Taken together, these findings indicate that STTT has the potential to support newly arrived refugee students and help address multilingual education challenges.
