Frontiers in Education: Digital Learning Innovations

IntroductionIn recent years, virtual venue technology has been increasingly adopted in higher education. While existing studies indicate that feedback strategies can promote deep learning among college students in virtual environments, the specific mechanisms underlying this effect remain poorly understood. This study investigates how peer feedback strategies influence deep learning processes within virtual learning environments.MethodsThe study employed the ErgoLAB Environment Synchronous Cloud Platform V3.0 alongside questionnaire scales to collect multimodal data, including behavioral patterns, physiological responses (eye movements, EEG, and electrodermal activity), learning experience metrics, and deep learning outcomes.ResultsAnalysis revealed significant differences in deep learning outcomes across peer feedback strategies. The peer dialogue feedback group operating in a basic virtual interaction environment outperformed the other three experimental groups, suggesting that structured peer dialogue combined with foundational virtual interactions may most effectively support deep learning.DiscussionThe findings underscore the importance of deliberately designed peer feedback strategies to enhance deep learning in virtual educational contexts. This study addresses the need for targeted feedback interventions in virtual instruction and offers empirical evidence for the integration of virtual venues into academic curricula. It also provides practical insights for fostering innovative talent development in the context of digital transformation in higher education.

BackgroundImmersive virtual reality (IVR) is becoming increasingly important in medical education. In radiology, IVR as a tool for practicing image interpretation and diagnosis of pathologies has rarely been subject of research to date. This exploratory study investigated a self-programmed IVR application and its potential to improve radiology education for medical students.MethodsAn IVR learning environment was programmed which enables users to view 3D models of real patients and interact with them using various tools. Fourth- to sixth-year medical students (n = 26) participated in a 1 h IVR training session in small groups between November 2022 and January 2023. Subsequently, they completed an anonymous online survey comprising 37 items. Data were analyzed, with correlations examined using Spearman’s non-parametric rank correlation.ResultsThe IVR training increased students’ motivation (M = 3.6) and interest in radiology (M = 3.2) and fostered enjoyment (M = 3.7) as well as a more active (M = 3.6) and intensive (M = 3.3) engagement. IVR was considered a helpful tool to enhance the practical relevance of radiology education, to improve the immediate cognitive and psychomotor learning outcomes related to anatomy and radiology, such as interpreting cross-sectional images (M = 3.5) and identifying anatomical structures (M = 3.6) as well as pathological changes (M = 3.3) and to promote skill development (M = 3.2), learning transfer (M = 3.2) and long-term knowledge retention (M = 3.3). The usability, design, tools and didactic functions of the IVR application are strongly associated with learning process- and learning outcome-related variables.ConclusionIVR-based learning is a promising addition to traditional radiology education to enhance motivation, interest and learning. However, the success of IVR depends on its design, usability and integration into the curriculum. The study highlights the need for further research on the added value of IVR across the educational sector.

This article presents a qualitative investigation into the evolution of critical questioning that occurred in dialogic relationships between artificial intelligence (AI) and a group of higher education students. Drawing from students' class records, it attempts to understand the development of critical thinking within formal educational contexts, utilizing a five-level questioning framework: General and Defining, Specific, Applied, Integrative, and Critical Engagement. The results indicate the presence of questioning patterns centered on levels four and five—namely, the use of Integrative and Critical Engagement questions—emerging from contextualized discussions. Students' interactions with AI enabled them to observe: the diversity of questioning levels, the progression of critical thinking, areas for improvement within each working group, the encouragement of reflexivity and metacognition, engagement with complex concepts, visualization of practical concept applications, and the expansion of interdisciplinary thinking. This study contributes to the literature on education and technology by offering insights into how to structure effective dialogic interactions between students and AI systems.

The article presents a conceptual framework for the design, implementation, and analysis of multi-component summative assessment systems in an electronic educational environment. A universal model is proposed, based on a four-level hierarchy – meta-meta-model, meta-model, model, and actual assessment system. Various structures and assessment components are examined, including Bloom’s taxonomy, higher- and lower-order thinking skills, theory and practice, and the use of fuzzy logic and artificial intelligence. The processes of modeling, configuration, usage, and system analysis are described, along with the roles of the main participants—administrator, author and learner. The use of generative artificial intelligence for the automated creation of test questions is also explored. The system aims to enhance transparency, objectivity, and effectiveness of assessment in digital learning environments, offering practical solutions for modern higher education.

IntroductionCreative thinking is essential for developing high-level innovative talents. However, its underlying neuroplastic mechanisms and effective educational interventions remain underexplored.MethodsThis meta-analysis synthesizes data from 35 experimental studies (N = 14,688) to examine the effects of brain science literacy on creative thinking and its potential moderators.ResultsThe results indicate that brain science literacy has a small but significant positive effect on creative thinking (g = 0.20, p = 0.003), with stronger effects observed in teaching strategy optimization (g = 0.32), student behavioral regulation (g = 0.37), and early childhood interventions (g = 0.70). The impact on originality (g = 0.53) was significantly stronger than on fluency (g = 0.20) and the overall creativity score (g = 0.26). The intervention effects varied across educational stages, with the most substantial benefits seen in early childhood (g = 0.70) and at the university level (g = 0.30).DiscussionThese findings suggest that improving brain science literacy can promote neuroplasticity and enhance creative thinking, with varying effects across developmental stages and creative components. The benefits observed in early childhood highlight the critical importance of brain science literacy-informed educational interventions during sensitive periods of cognitive development. This study provides solid empirical support for integrating neuroscience principles into educational practice, offering practical guidance for educational policy and curriculum design. Overall, brain science literacy appears to foster creativity through a dual pathway: neuroplasticity activation and developmental stage adaptation, presenting a focused framework for evidence-based neuroeducational interventions.

Problem based learning (PBL) is based on the idea that learning is “grounded by experience. ” PBL curriculums in medical school highlight the importance of engaging students and allowing students to be the driver of their education. This mimics their work in the hospital where answers are rarely suited to a multiple-choice question, but a myriad of complex clinical questions, ethical decisions, and cost barriers. Teaching medical students from the start of medical school to handle multiple variables is an important aspect of their learning. Studies indicate that PBL students consistently score at or above the national average on board exams compared to their peers. Furthermore, evaluations of competence during clinical rotations show statistically significant advantages for PBL students in areas such as critical thinking, social and cognitive interactions, and patient comfort. Studies highlight a notable advantage in interpersonal skills among PBL students. Additionally, geographical access plays a critical role in enrollment, and personal responsibilities can hinder potential applicants from pursuing medical school. PBL can be utilized to create an environment where location-based barriers are minimized to increase the number of individuals entering the medical profession. This approach could ultimately reduce the healthcare burden and enhance medical services in underserved areas of the country. Here, we present a concise review of resources and approaches including online and digital platforms to facilitate curriculum development and implementation of flipped classrooms and independent learning that are well-suited for PBL.

This perspective piece addresses the rapid integration of generative artificial intelligence (AI) in higher education and the imperative to move beyond a purely technical understanding towards fostering critical AI literacy among students. Despite the benefits of AI in enhancing learning experiences and preparing students for a tech-driven workforce, concerns exist regarding misinformation, diminished critical thinking, ethical dilemmas, and a lack of regulatory frameworks. This perspective piece proposes a circular pedagogical framework comprising contextual preparation, guided engagement, and collective critical reflection, drawing on Vygotsky’s sociocultural theory, Freire’s critical consciousness, and Mackey and Jacobson’s metaliteracies framework. The framework aims to address three critical competency gaps: AI tool assessment, critical AI evaluation skills, and AI information literacy. The paper highlights the importance of discipline-specific AI integration and scaffolded learning, supported by student reflection and metacognition, as demonstrated in the geography seminar courses discussed in the paper. Recognizing the need for instructor AI literacy, the paper concludes by emphasizing the necessity of institutional support through targeted training and interdisciplinary collaboration to ensure AI enhances learning effectively.

This mixed-method quasi-experimental study investigated the effects of virtual reality immersion (VRI) in biology classes on East Jerusalem high school students' scientific habits of mind, specifically self-regulation, critical thinking, and creative thinking. The study was grounded in the Cognitive Affective Model of Immersive Learning (CAMIL), which emphasizes how immersive environments enhance cognitive and affective engagement. A random cluster sample of 207 male and female students from three East Jerusalem high schools (two male and one female) participated in the study. Over a four-month period, participants were exposed to VRI-based biology content designed according to CAMIL principles. Data were collected using pre- and post-tests to measure changes in students' self-regulation, critical thinking, and creative thinking. A mixed-method design was employed to capture both measurable outcomes and students' lived experiences, integrating quantitative results with qualitative insights to ensure methodological triangulation. Quantitative analysis using the non-parametric Wilcoxon Signed-Rank Test revealed statistically significant and substantial improvements in students' self-regulation, critical thinking, and creative thinking following the integration of VRI. Qualitative findings supported these outcomes, highlighting students' positive perceptions and experiences with immersive biology learning. The findings demonstrate that incorporating VRI into biology instruction can meaningfully enhance students' higher-order thinking skills and scientific habits of mind. These results suggest the potential of VRI to encourage greater student interest and enrollment in scientific tracks. However, further research is recommended across other science subjects (e.g., physics, chemistry, and mathematics) to validate the broader applicability of these results. Educators and researchers are encouraged to explore VRI integration to foster students' cognitive growth and promote pursuit of higher education in scientific domains.

Recently, various approaches have been adopted to cultivate environmental literacy, and prior studies have confirmed the value of digital games in this domain. Nonetheless, concrete discussions of specific elements such as environmental sensitivity and attitude remain limited. Accordingly, the present quasi-experimental study investigates whether Digital Game-Based Learning (DGBL) can enhance the environmental literacy of Taiwanese elementary school students. Thirty-four sixth-graders were assigned to a DGBL group (n = 17) and a Web group (n = 17). Quantitative data were collected with an Environmental Literacy Scale covering knowledge, sensitivity, and attitude, while qualitative insights were gathered through semi-structured interviews. Post-test scores were analyzed via ANCOVA with pre-test scores as covariates. Results indicate that the DGBL intervention significantly improved students’ environmental knowledge and attitude, whereas gains in environmental sensitivity, though evident, did not reach statistical significance. Qualitative responses echoed these findings, suggesting that immersive gameplay fosters deeper affective engagement with ecological issues even when measurable sensitivity improvements are modest.

The usefulness and ease of use of generative artificial intelligence (GAI) technology serve as the necessary technical foundation for its rapid proliferation. However, within the current educational landscape, students have raised growing concerns and apprehensions regarding the ethical governance of GAI technologies and their potential to disrupt employment opportunities through job displacement effects. This study investigated the relationship between perceptions of threats and hesitancy concerning the use of GAI technology among college students. A survey of 805 participants revealed a positive correlation between perceived technological threat and use hesitancy. Importantly, perceived avoidability and fear of GAI were found to serve as sequential mediators in this relationship. These findings elucidate the psychological mechanisms that underlie students’ reluctance to adopt emerging GAI technologies and suggest that interventions aimed at addressing threat perceptions, increasing avoidability, and reducing fear may promote greater acceptance of such techniques among students.

IntroductionThis study examines the integration of Artificial Intelligence (AI)-based tools into university-level accounting education in Medellín, Colombia. The objective was to identify the factors that influence students' intention to adopt these technologies, using theoretical frameworks such as the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM).MethodsAn experimental methodology was applied, which included the development of an educational video incorporating AI and an accounting simulator. A total of 105 students participated in the study and completed a Likert-type questionnaire designed to evaluate constructs including attitude, perceived usefulness, ease of use, subjective norm, and behavioral control.ResultsThe analysis revealed that perceived ease of use significantly influenced both perceived usefulness and behavioral control. Additionally, subjective norm had an impact on attitude and intention to use. However, perceived usefulness did not translate into favorable attitudes toward AI adoption, indicating a gap between the functionalities students recognized and their expectations of the technology.DiscussionThe findings highlight the importance of contextualizing AI functionalities within educational settings. They suggest the need for pedagogical strategies that align technological tools with students' expectations and foster a more receptive environment toward digital innovation in accounting education.

IntroductionArtificial intelligence tools like ChatGPT and DeepSeek are increasingly shaping higher education. However, their integration into student learning remains underexplored. This study investigates how university students in South Africa use AI-based tools in their academic practices and the specific tasks these tools support. It also examines the ethical challenges and considerations arising from their use, highlighting the need for structured institutional guidelines.MethodsA qualitative approach was employed, involving in-depth semi-structured interviews with 50 students from four South African universities.ResultsFindings reveal that students widely but informally use AI tools for tasks such as essay writing and assignment preparation. The absence of formal institutional guidance has led to ethical ambiguities and inconsistent usage practices.DiscussionThe study accentuates the urgency for universities to develop institutional AI frameworks. These frameworks should promote the responsible and effective use of AI tools while addressing academic support needs and ethical considerations in higher education.

ChatGPT empowers instructors to provide interactive, individualized attention and enhance student engagement. It is used to understand the learners so that the teaching materials and assessments can be contextualized. ChatGPT can enrich the learning experience, motivate the learners, and improve academic performance. No study in Saudi Arabia surveyed law educators on the intention to use ChatGPT. To fill the gap in this area, this research investigated the intention of law educators to use ChatGPT. To achieve the research objective, the researcher used a survey method to collect information from law educators in Saudi Arabia. The research revealed that law educators will use ChatGPT in legal education as the constructs of the performance expectancy, effort expectancy, social influence, facilitating conditions, and behavioral intention are found to be significant. The finding has policy, practical, and theoretical implications. The finding can be used to understand the factors that influence ChatGPT adoption by law educators. Accordingly, teaching and learning policies can be strengthened, and the learning institutions can introduce training for the proper and acceptable use of ChatGPT in legal education. The research also expanded the technology adoption model to understand the intention to use ChatGPT among law educators in a developing country.

Despite the increasing integration of technology in education, digital inequities persist among ESL students, particularly in under-resourced academic settings. This explanatory mixed-methods study examined digital equity among undergraduate ESL students in the English Department of an Afghan public university, drawing on data from 78 questionnaires and six in-depth interviews. Thematic and statistical analyses revealed that while students reported high access to personal technological devices for language learning, they faced significant constraints in accessing computer laboratories and developing digital English learning materials. Additionally, limitations were observed in their engagement with technology-enhanced educational research. The findings indicated no statistically significant correlations between digital equity and gender, academic year, or socioeconomic status. Both students and instructors encountered these challenges, underscoring the urgent need for institutional strategies to mitigate digital disparities in higher education. Ultimately, the study concluded with several pedagogical implications.

IntroductionRemote teaching often feels unnatural and restricted compared to on-site lectures, as traditional teaching aids are reduced to a 2D interface. The increasing adoption of VR expands online teaching platforms by offering new possibilities for educational content and enables teachers to teach more intuitively. While the potential of virtual reality (VR) for learners is well-investigated in the academic literature, VR tools for educators have hardly been explored. In this paper, we introduce the tool VRTeaching, a platform designed for presenters to enable immersive lectures using VR glasses and integrated tools such as an interactive whiteboard that can display slides, built-in chat integration to enable communication, and interactivity features such as polling tools or audience questions.MethodsThe presented study includes an expert evaluation assessing the usability and the potential of the teaching and learning platform and an investigation of the mental demand and psychophysiological responses on teachers and students giving presentations depending on the teaching environment.ResultsThe results indicate a significantly higher mental demand for the VR environment than the online environment, with no significant effects on the psychophysiological measures.DiscussionDespite the increased perceived mental demand, participants recognized the VR lecture room as having strong potential for enhancing teaching and learning experiences. These findings highlight the potential of VR-based platforms for remote education while underlining the importance of considering cognitive load aspects in their design.

IntroductionVirtual learning systems (VLS) have become increasingly significant in agricultural education, especially for enhancing accessibility and flexibility. However, their effectiveness in improving learners’ engagement, satisfaction, retention, and overall outcomes remains uncertain, particularly within the Indian agricultural education context.MethodologyA cross-sectional study was conducted among 400 students from Undergraduate (UG), Postgraduate (PG), and PhD programs across randomly selected agricultural universities. Effectiveness Index was constructed using entropy method. Multiple linear regression analysis was employed to identify key predictors.ResultsThe findings indicate that 50.5% of students perceived a medium level of VLS effectiveness. Postgraduate and PhD students reported higher engagement and satisfaction than UG students. Self-regulation was the most significant predictor of learning effectiveness, followed by learners’ attitudes and e-learning design. Gender differences were also observed, with female students performing better in virtual learning environments.Discussion and conclusionThe study highlights the critical role of self-regulation, positive learners’ attitudes, and well-structured e-learning design in enhancing the effectiveness of virtual learning. These insights can inform the development of strategies aimed at optimizing virtual platforms for agricultural education.

BackgroundDeep learning (DL), a subset of machine learning and artificial intelligence (AI), is transforming engineering by addressing complex problems with innovative solutions. Despite its growing influence, a comprehensive review of current trends, applications, and research gaps in engineering disciplines is essential to understand its full potential, limitations, and potential educational implications.PurposeThis study systematically explores the state, trends, and future directions of deep learning applications in engineering, and potential educational implications. The primary research question is: “What are the current applications, trends, and research gaps in the use of deep learning across engineering disciplines, and how can these insights guide future innovations in engineering practice?”MethodA systematic literature review (SLR) was conducted in three phases: identification, screening, and synthesis. Articles were retrieved using the search term “deep learning + engineering” from databases like IEEE Xplore, Web of Science, and Google Scholar. After removing duplicates from an initial pool of 346 articles, abstracts and full texts were screened based on predefined exclusion criteria, narrowing the selection to 101 relevant studies. The synthesis categorized data into four themes: strategic methodologies, practical implementation, system optimization, and emerging applications.ResultsThe analysis revealed DL's significant impact on engineering disciplines, especially mechanical and electrical engineering, with applications such as predictive maintenance and automated grid management. Key trends include strategic deep learning model development, practical evaluation frameworks, and the optimization of efficiency. However, research gaps remain in scalability, model interpretability, and real-world implementation.ConclusionsThis study underscores DL's transformative potential in engineering while identifying critical research gaps and opportunities. It provides a framework for future research and industry applications, emphasizing the importance of strategic innovation and interdisciplinary collaboration to advance deep learning in engineering.

This research contributes to the growing field of technology-enhanced learning by demonstrating how gamification and connected technologies can address gaps in bilingual education and language therapy. It investigates the design, development, and evaluation of Olly’s Adventures: The City of Two Languages, a novel, gamified language intervention tool for bilingual Maltese-English-speaking children aged five to eight. The tool merges a physical board game with a companion mobile application, creating an engaging phygital experience that supports language acquisition across clinical, educational, and home settings. Developed by a multidisciplinary team, the tool was iteratively refined through a user-experience-driven process involving speech and language pathologists, caregivers, educators, design engineers, and children. Mixed-methods data were gathered via focus groups, observations, surveys, and a case study. Findings highlight the tool’s potential to foster language development and increase motivation, with users reporting high levels of engagement, satisfaction, and relevance. Despite limitations related to sample size and the need for clinical validation, the study demonstrates the promise of user-centered connected tools in delivering inclusive, motivating, and linguistically responsive interventions.

IntroductionThis study explores how the synergy between Artificial Intelligence (AI) and Experiential Learning enhances students’ creativity through motivation.MethodsA quantitative survey with 200 purposively selected students was conducted. A structured questionnaire was used to collect data on AI usage, motivation, and creativity.ResultsAI integrated with experiential learning significantly boosts motivation, which in turn increases creativity.DiscussionThe findings support incorporating AI-based experiential practices in education to foster student innovation and engagement.