Frontiers in Education: Digital Learning Innovations
4 days 3 hours ago
IntroductionThis study investigated the relationships among gifted behavior, Generative AI (GenAI) anxiety, and learning motivation among gifted EFL university students in Saudi Arabia, with an additional focus on the mediating role of GenAI anxiety and the moderating effect of gender.MethodsUsing a quantitative correlational design, data were collected from 304 purposively selected undergraduates classified as gifted based on institutional records and psychometric confirmation using Gifted Rating Scales. The participants answered the verified instruments of gifted behavior, GenAI anxiety, and academic motivation.ResultsAnalysis of structural equation modeling showed that gifted behavior was associated with lower GenAI anxiety and higher motivation, and that GenAI anxiety had a significant negative association with motivation. The mediation analysis indicated that the relationship between gifted behavior and motivation was partially mediated by GenAI anxiety. Gender was a significant moderator of the relationships between gifted behavior and motivation, as well as between GenAI anxiety and motivation, with both associations being stronger among females.DiscussionThe findings contribute to the growing body of research on the psychological impact of AI implementation in EFL learning, suggesting that gifted learners’ responses to GenAI technologies are characterized by distinct affective and motivational patterns. The research provides theoretical insights into giftedness and technology-related emotions, providing pedagogical implications for creating AI-based EFL learning environments that are sensitive to learners’ cognitive and affective profiles.
Amr Mahmoud Mohamed
1 week ago
Teaching Information and Communication Technologies (ICT) in higher education faces the challenge of engaging students accustomed to interactive and digital learning environments. Although gamification has emerged as a promising pedagogical strategy to enhance motivation, participation, and learning, there is still no consensus on which gamification elements and strategies should be prioritized in ICT courses. To address this gap, this study aimed to identify, through expert consensus, the most relevant gamification components for ICT teaching in higher education. A modified Delphi study with a mixed-methods design was conducted in two rounds: an open exploratory phase and a structured round using a five-point Likert scale. Twelve experts were selected based on a competence coefficient (K ≥ 0.75). Quantitative analyses included means, standard deviations, interquartile range (IQR), coefficient of variation (CV), and Kendall’s coefficient of concordance (W), complemented by qualitative thematic coding with an inter-coder reliability of κ = 0.82. Consensus thresholds followed current Delphi standards (≥ 80% agreement, IQR ≤ 1, CV ≤ 0.30, and W ≥ 0.60). The results indicate that experts prioritized challenges and quests (83% agreement; W = 0.66), followed by points and rewards (67%) and the complementary use of badges and leaderboards. Strong consensus was reached regarding the potential of gamification to strengthen problem-solving, critical thinking, and collaboration (100%; W = 0.90), and to increase active participation (100%) and promote deep understanding (83%). However, heterogeneity persisted in relation to the selection of technological platforms (W = 0.27) and specific strategies (W = 0.28), and the effects on academic performance were reported as inconsistent. Overall, the findings suggest that gamification is most effective when systematically integrated into ICT curricula, supported by teacher training and immediate feedback mechanisms. As no universal technological platform is recommended, the use of contextual selection criteria is essential. These results provide a conceptually validated reference framework for the design of gamified learning experiences in higher education and underscore the need for further empirical validation across diverse educational contexts.
Lorena Jaramillo-Mediavilla
1 week 1 day ago
This study introduces and empirically validates a comprehensive educational model designed to enhance digital competence and learning motivation among Master’s students in Kazakhstan. Using a quasi-experimental design with 236 participants from five pedagogical universities, the research examined how an integrated approach combining technology-enhanced pedagogy, microlearning, gamification, online assessment, and collaborative digital projects influenced students’ digital competence, learning motivation, and academic performance. Results demonstrated significant improvements in digital competence across all dimensions (effect size η2 = 0.46) for students in the experimental group, with particularly strong development in content creation and problem-solving competencies. The model also had a positive influence on learning motivation, self-efficacy, student engagement, and academic performance. Path analysis confirmed an integrated theoretical framework where technology-enhanced pedagogy influenced digital competence, which subsequently affected motivation, self-efficacy, engagement, and academic achievement. Students with elementary baseline digital skills showed the largest competence gains, indicating the model’s potential for addressing digital inequality in Kazakhstan’s higher education system. Follow-up assessments revealed durable effects, suggesting sustainable rather than transient changes. The research provides theoretical contributions to understanding the interrelationship between digital competence and motivation while offering practical strategies for modernizing Master’s programs in Kazakhstan and similar educational contexts.
Zakira Bakirova
1 week 1 day ago
IntroductionThis study examines the relationship between ultra-Orthodox teachers’ perceptions of non-formal education and their perceptions of 21st-century skills. These skills comprise a set of competencies essential for successful integration into today’s workforce and civic life. Teachers’ perceptions of these skills and their importance are critical for their successful implementation in the classroom. Several factors contribute to teachers’ positive perceptions of 21st-century skills, one of which is a positive view of non-formal education, which is a flexible, investigative, and creative educational method. This research explores this relationship by focusing on teachers from the ultra-Orthodox collectivist culture, a community that tends to show conflicting attitudes toward 21st-century skills and non-formal education.MethodsA group of 238 ultra-Orthodox teachers completed a questionnaire regarding perceptions of non-formal education, 21st-century skills and demographic data.ResultsThe findings indicate that positive perceptions of non-formal education are associated with all dimensions of 21st-century skills, with the strongest related to communication skills, which is aligned with cultural norms, while creativity showed the weakest association, which also reflects a broad cultural rejection of this skill.DiscussionThe study reinforces the positive connection between educational approaches and perceptions of 21st-century skills, including within a religious collectivist community.
Anat Barth
2 weeks ago
IntroductionThe use of large language models (LLMs) in education has rapidly expanded, generating interest in their potential to support teachers through task automation and instructional planning. This review synthesizes evidence on reported changes in time devoted to educational content generation and support for planning-related task automation.MethodsWe conducted a systematic review of peer-reviewed literature published between 2023 and 2025, focusing primarily on secondary and higher-education contexts. Study selection followed PRISMA 2020 guidelines. Risk of bias was assessed using ROBINS-I for non-randomized studies and CASP checklists for qualitative/mixed-methods studies and for secondary evidence syntheses.ResultsSixteen studies met inclusion criteria (13 primary empirical studies and 3 secondary syntheses). Across primary studies, LLM use was associated with reported time savings and perceived gains in clarity or usefulness of generated educational resources. However, outcomes and measures were heterogeneous and often self-reported, several risk-of-bias domains were rated as unclear, and evidence was concentrated in higher-education settings with small samples, limiting comparability and causal inference. Recurrent constraints included limited reproducibility, strong dependence on prompt design, and ethical or technical concerns.DiscussionLLMs may support educators, but conclusions should be interpreted cautiously. Effective integration requires clear pedagogical frameworks, human oversight, and standardized evaluation in real-world settings.Systematic review registrationOpen Science Framework (OSF). Unique identifier: v63nj. Public URL: https://osf.io/v63nj/
Giovanni Luna Chontal
2 weeks 4 days ago
IntroductionArtificial Intelligence (AI) is increasingly integrated into higher education to personalize instruction and support student engagement. However, the mediating role of teaching methods in this process remains underexplored.MethodsThis systematic review analyzed 73 peer-reviewed articles published between 2015 and early 2025, retrieved from Scopus and Web of Science, following PRISMA guidelines. Studies were screened based on predefined inclusion criteria and coded using a structured framework that examined AI types, engagement outcomes, and instructional strategies.ResultsFindings reveal that AI tools—such as chatbots, adaptive systems, and predictive analytics—enhance engagement most effectively when embedded within interactive pedagogies like flipped classrooms, project-based learning, and scaffolded feedback loops. To conceptualize this relationship, we introduce the PMAISE model (Pedagogical Mediation of AI for Student Engagement), which maps the alignment between AI technologies, pedagogical strategies, and the affective, behavioral, and cognitive dimensions of engagement. Concrete examples from recent studies demonstrate how teaching methods amplify or inhibit the effects of AI tools. The review also critically examines emerging concerns related to ethics, data privacy, and structural barriers to equitable AI adoption.DiscussionThis study offers a conceptual and practical framework for integrating AI into higher education in a context-sensitive, evidence-based, and pedagogically meaningful manner, highlighting the crucial role of thoughtful pedagogical mediation in maximizing AI’s educational benefits.
Dong Yu Long
2 weeks 6 days ago
Background and purpose of the studyThe rise of quantum technologies necessitates integrating foundational quantum mechanics (QM) concepts into secondary education. However, inherently abstract phenomena like quantum entanglement pose significant pedagogical challenges, as traditional formalism-based approaches are often inaccessible. This study introduces and delineates an innovative, scaffolded pedagogical model designed to foster robust conceptual understanding of entanglement in secondary STEM education, moving beyond reliance on mathematical formalism.The proposed pedagogical modelThe presented contribution is a detailed pedagogical sequence following a deliberate learning trajectory. It begins with a tangible analogy (magnetic interactions) as a conceptual anchor for correlation, then transitions to computational tools (Bloch sphere visualization, Qiskit simulations). These tools facilitate exploration of quantum concepts weakly addressed by the analogy (e.g., superposition) and allow more authentic engagement with quantum behavior. Underpinned by constructivism, cognitive load theory, and QM education research, the model strategically repurposes the analogy’s limitations as pedagogical opportunities to introduce and contrast key quantum features like non-locality and superposition with classical intuition. The sequence integrates exploration, guided use of representations, and critical comparative discussion.Conclusions and potential implicationsThis paper provides a theoretically grounded pedagogical model for introducing quantum entanglement in secondary STEM education, combining tangible and computational tools in a scaffolded manner. The approach offers potential advantages over traditional methods by providing concrete starting points and explicitly using classical limitations to illuminate quantum principles. While promising, rigorous empirical validation is the essential next step. Future research should investigate the model’s effectiveness in authentic classroom settings, informing curriculum design and teacher development for incorporating QM into secondary STEM.
David Castillo-Salazar
3 weeks 1 day ago
IntroductionPeer-learning recommendation remains an open challenge in e-learning systems, as most existing approaches—such as matrix factorization and neural collaborative filtering—rely on static interaction patterns. These methods often ignore contextual information including learner roles, content difficulty, and temporal engagement behavior. As a result, they struggle to form meaningful peer groups or provide adaptive learning paths that align with pedagogical needs.MethodsTo address these limitations, we propose a hybrid context-aware peer learning recommender that integrates collaborative filtering with interaction-based clustering. The framework incorporates adaptive peer group formation using multiple loss functions and multifactor BERT embeddings to capture content semantics. In addition, learner-specific characteristics such as difficulty level, job role, and software skills are explicitly modeled. These contextual and semantic features are dynamically used to cluster learners and generate personalized peer recommendations.Results and discussionExperiments conducted on an e-learning dataset demonstrate that the proposed model significantly outperforms sequential baseline approaches, as well as traditional matrix factorization and neural collaborative filtering models. The hybrid approach achieves an accuracy of 0.80, precision of 0.80, recall of 0.06, and an F1-score of 0.11. These results indicate improved personalization and contextual relevance in peer recommendations, enabling more adaptive and pedagogically suitable peer learning experiences.
Dazzle A. J.
3 weeks 4 days ago
Open Learner Models (OLMs) are increasingly positioned as pedagogical tools capable of enhancing self-regulated learning (SRL) within higher education. Despite considerable technological progress, the pedagogical mechanisms through which OLMs support students' regulatory behaviors, metacognitive processes and motivational engagement remain insufficiently theorized. This review synthesizes empirical studies exploring OLMs that intentionally integrate pedagogical strategies in order to deepen understanding of how these models influence SRL across its preparatory, performance and reflective phases. Drawing on thematic meta-synthesis of 26 studies, the review identifies a continuum of OLMs—Inspectable, Negotiable, Editable, and Persuasive/Adaptive—that reflects progressively greater levels of learner agency, transparency, and co-regulation. Across this continuum, the pedagogical design of OLMs emerges as a critical determinant of their educational value: inspectable models predominantly support monitoring and awareness; negotiable models foster active calibration and dialogic feedback; editable models strengthen autonomy and goal-setting; and adaptive models, frequently mediated by artificial intelligence, offer personalized scaffolding that sustains engagement and reflection. Together, these findings illuminate how pedagogically enriched OLMs can operate as metacognitive mediators rather than purely analytical systems, enabling students to interpret feedback, make informed learning decisions and assume increasing ownership of their learning trajectories. The review offers a theoretically grounded framework that informs the design of transparent, ethical, and learner-centered OLMs, with implications for instructional practice, digital pedagogy, and the broader field of educational research.Systematic review registrationCRD420251237223.
Jonathan L. Robles Mucho
4 weeks ago
IntroductionResearchers examined the effectiveness of a digital mapping project created in partnership with librarians for a history course. The project centered on the Israeli–Palestinian conflict and the 1948 war, aiming to improve students’ understanding of historical context while developing transferable skills such as critical thinking, research, and technological literacy. This initiative reflects broader trends in higher education that emphasize skill development and interdisciplinary collaboration.MethodsTo evaluate the project’s impact, a mixed-methods approach was used. Data collection involved pre- and post-surveys and analysis of course assignments. The sample included 17 undergraduate students enrolled in a history course, representing diverse majors such as History, Political Science, and Education. All enrolled students participated, with no exclusion criteria applied.ResultsFindings show that the digital mapping project greatly enhanced students’ understanding of the historical context, helped develop valuable skills, and boosted engagement compared to traditional assignments. Students’ responses were mainly positive, providing useful feedback for future projects and emphasizing the potential of digital tools in college education.DiscussionThe results indicate that integrating digital humanities into history courses can create engaging learning experiences and encourage deeper student involvement. These findings add to the growing evidence supporting the use of digital tools in humanities education. However, limitations include the small sample size and dependence on self-reported data, which may impact the ability to generalize the results.
Rami Zeedan
4 weeks ago
With the rapid advancement of artificial intelligence (AI) technology, its applications in medicine have grown increasingly widespread. In particular, AI has shown significant potential within residency education. This review examines current uses of AI in residency training, focusing on innovative educational models, curriculum design, outcome assessment, and existing challenges. By analyzing recent research across medical specialties, the discussion explores the role of AI in personalized learning, examination assistance, and clinical decision support. Furthermore, future strategies for integrating AI into residency education are proposed. This article aims to provide a comprehensive theoretical and practical reference for medical educators and policymakers, supporting the scientific application and continued development of AI in residency training.
Hongsen Zhang
4 weeks 1 day ago
AI, and especially generative AI, may have an effect on the number of gifted people in the world. But whether this effect will be positive or negative is up to us, collectively, and to each individual. This essay opens with a consideration of possible effects of AI on the giftedness of a society taken as a whole. Then it presents a philosophical conundrum, that of the Chinese Room, that is relevant to assessing the effects of AI. Next it reviews some recent empirical literature relevant to the question of AI’s effects on cognition and cognitive gifts. Then it discusses these effects. Finally, it draws some conclusions, in particular, that whether AI increases or decreases giftedness in a society is not preordained, but rather reflects a choice.
Robert J. Sternberg
4 weeks 2 days ago
Samar A. Ahmed
4 weeks 2 days ago
Technological development is reshaping teaching and learning environments, particularly through the integration of artificial intelligence (AI) tools such as ChatGPT in higher education. The objective of this study was to analyze university students’ intention to use ChatGPT, considering the gender variable. A quantitative methodology was employed, using an ad hoc questionnaire administered to a sample of 368 students from the Faculty of Education Sciences at the University of Málaga. Data analysis was conducted using the Jamovi software v2.3.26.0, applying techniques such as descriptive statistics, hypothesis testing, exploratory and confirmatory factor analysis, and ANOVA. The results showed widespread acceptance of ChatGPT, with no significant gender differences, suggesting a homogeneous adoption of this technology. These findings contrast with previous research indicating a gender gap in technology use. The importance of integrating AI into educational processes in a critical and pedagogically sound manner is emphasized, as well as the need to ensure equitable access. This study contributes to the understanding of how ChatGPT is perceived and used in academic contexts at the university level. It is recommended that the study be replicated in other contexts to validate the findings and broaden their applicability.
Enrique Sánchez-Rivas
1 month ago
IntroductionTraditional teaching methods have been central to education systems worldwide. Still, digital innovation in higher education has transformed how education is delivered, introducing new teaching models and enhancing school management processes. However, most Higher Education Institutions (HEIs) face numerous limitations in effectively adopting digital systems, although these challenges are often context-specific.MethodsTo gain a deeper understanding of the scope and limitations of digitalization in higher education institutions, we conducted a comparative analysis of existing digital ecosystems across developed and developing countries.ResultsWe introduced a three-layer framework for digitalization comprising institutional strategies, technological tools, and pedagogical methods. These layers are further divided into several components that support innovation. Using data from multiple sources, we identified several current drivers of the adoption of digital innovation in universities, including student expectations and needs, technological advances, strategic leadership, and the rise of hybrid learning models. Additionally, we compared the rate of digitalization in HEIs between developed and developing countries; our findings indicated that innovation proceeds more smoothly and is easier to manage in developed nations. We highlighted strategies for scalable and sustainable innovation through successful case studies from well-known universities. To tackle systemic challenges in digitalization, their impacts, potential solutions, and levels of implementation, we employed a priority matrix approach. This approach showed that most challenges are quick wins when addressed and have a substantial impact on digitalization.DiscussionThis study emphasizes the importance of adaptive, inclusive, and strategic approaches that promote equity and encourage the adoption of global learning ecosystems by comparing digital innovation in developed and developing countries.
Taojing Wang
1 month ago
The COVID-19 pandemic forced higher education institutions in resource-constrained contexts to rapidly adopt online learning, yet little is known about how students in Sub-Saharan Africa experience and evaluate these platforms, particularly when facing severe infrastructure barriers. Understanding student satisfaction in these contexts is critical for ensuring educational equity and informing evidence-based policy. This study investigates student satisfaction with Google Classroom at the Faculty of Engineering—Lúrio University in Mozambique, where 220 students participated in a mixed-methods study during the 2020–2021 academic year. Using the Technology Acceptance Model (TAM) as a theoretical basis, the research examined overall satisfaction, demographic differences, challenges faced, and valued features of the platform. Results showed moderate satisfaction levels (M = 3.18, SD = 1.12 on a 5-point scale), with 35% of students expressing satisfaction and 28% expressing dissatisfaction. Internet connectivity quality was identified as the most significant factor affecting satisfaction (p < 0.001), while device type also influenced results (p < 0.05). Qualitative data identified six main challenges: connectivity issues, mobile data costs, social isolation, technical difficulties, limited interaction, and workload concerns. Students valued the platform’s flexibility, accessibility of materials, organization, and ease of use. The study emphasizes the need for infrastructure investment and targeted support systems for effective online learning, especially in resource-limited settings, providing useful insights for improving higher education quality during and after the pandemic.
Heráclito Rodrigues Comia
1 month ago
Despite growing interest in educational digital leadership and supervision, validated instruments measuring supervisors’ digital competencies for their performance excellence (SDC-PE) remain scarce, particularly in developing nations. This study developed and validated the SDC-PE scale through stakeholder perceptions of 318 principals and teachers across 78 senior high schools in 17 districts of South Sulawesi, Indonesia. The SDC-PE integrates classical supervision theories (Cogan, Goldhammer, Glickman) with ISTE Standards and DigCompEdu 2.2, yielding four dimensions: Strategic digital leadership (SDL), digital culture promotion (DGC), teacher digital development (TDD), and digital learning facilitation (DGL). Confirmatory composite analysis (CCA) using PLS-SEM demonstrated excellent psychometric properties: factor loadings (0.839–0.936), composite reliability (0.933–0.955), AVE (0.776–0.811), and model fit indices exceeding thresholds (CFI = 0.968, TLI = 0.960, RMSEA = 0.072). Discriminant validity was confirmed through Fornell-Larcker criterion and HTMT ratios (<0.85). The SDC-PE provides educational institutions with an empirically validated assessment tool for evaluating supervisor digital competencies, designing targeted professional development.
Ansar Ansar
1 month 1 week ago
Within the global movement of cultural revival, the modern translation of poetic imagery (defined as the process of transmuting classical poetic symbols along with their emotional and cultural connotations into modern design elements) has emerged as a critical concern in Chinese design education, presenting a central tension between AI-driven efficiency and cultural depth. This study addresses three structural faults in current translation practices: fragmented symbolic extraction, weakened nostalgic drive, and over-reliance on AI tools. It establishes a tripartite efficacy evaluation framework encompassing emotion, cognition, and market dimensions, as well as a dual-cycle educational model featuring critical and iterative phases. A controlled experiment with 22 second-year product design majors (divided into an AI-assisted group and a traditional group) was conducted over a 4-weeks design psychology course, focusing on war, boudoir, and pastoral poetry themes. Results show that the AI-assisted group outperformed in emotional resonance (4.22 ± 0.38 vs. 3.54 ± 0.47) and market responsiveness (81.3% ± 8.2% vs. 64.1% ± 10.7%), while the traditional group maintained an advantage in cognitive completeness (83.7% ± 5.9% vs. 80.3% ± 5.1%). The dual-cycle model effectively reduced cultural misinterpretation rates in the AI group from 33% to 12%. Meanwhile, this study proposes the “Nostalgia-Congruent AI Guidelines (NCAI-G),” which regulates AI application from three aspects: symbolic fidelity, nostalgia coherence, and user safety. This study provides a reusable educational framework for balancing AI instrumental rationality and cultural value rationality, advancing traditional cultural design education toward quantitative evaluation-driven iteration.
Shijiang Hou
1 month 1 week ago
Student feedback literacy is vital for effective use of feedback. While traditional peer review activities provide opportunities for students to practice giving and receiving feedback, their effectiveness is sometimes undermined because of interpersonal factors, such as friendship and psychological safety. Generative artificial intelligence (GenAI) offers a promising new avenue by providing adaptive and instant feedback; however, its effectiveness compared to traditional peer interaction and the underlying mechanisms remain underexplored and warrant further investigation. This study used a mixed-methods design with first-year undergraduates to explore the effect of GenAI and human peer feedback on student feedback literacy development. The study also analyzed the role of students’ self-regulated learning (SRL) as a mechanism explaining how these two feedback sources contribute to enhancing feedback literacy. The results revealed that GenAI yielded a small but significant improvement in developing feedback literacy compared to human peers. Qualitative analysis clarified this finding by uncovering behavioral differences between the two groups, highlighting GenAI’s specific support for the SRL process, especially in goal setting, planning, critical evaluation, and immediate self-reflection. These findings suggest that GenAI is powerful in fostering feedback literacy because it facilitates self-regulatory behaviors essential for effective interaction with feedback. Educators can strategically integrate GenAI in classroom activities to scaffold self-regulatory behaviors, fostering student feedback literacy development.
Jiahe Gu
1 month 1 week ago
Maka Eradze