Frontiers in Education: Digital Learning Innovations

IntroductionMonitoring and controlling learning is often difficult for primary school students. This issue is partially resolved when Adaptive Learning Technologies (ALTs) take over part of these self-regulated learning (SRL) processes. Trace data in ALTs provides elaborate information on students' learning process, which can be translated into monitoring support. However, this data does not provide insight into students' goal-setting behavior, which is a crucial part of the monitoring loop. Therefore, we developed a form of co-regulation between the student and the ALT with goal-setting prompts and monitoring support.MethodThis experimental study compared an experimental condition in which primary school students worked with the co-regulation intervention while practicing mathematics problems in the ALT to a control condition where they only practiced with the ALT. Firstly, we examined the effects of co-regulation with ALTs on regulation of practice behavior and learning outcomes by comparing the experimental and control conditions. Secondly, to gain further insight into students' goal-setting behavior in co-regulation, we examined how the experimental condition set their goals and attained them.ResultsResults showed that students in the experimental condition were more effective in regulating their practice behavior, shown by more problems solved and higher accuracy than the control condition. Similar learning gain was found in both conditions on the easy and intermediate learning topics. For the hard learning topic, the control condition showed a higher learning gain. Higher week goals than day goals on all three learning topics and similar goals were set between the learning topics. Students' goal attainment was less for the easy compared to the hard learning topic.DiscussionCombined, these results indicate that co-regulation with an ALT positively affects students' regulation of practice behavior and goal- setting behavior but does not yet increase learning gain. A practical implication is that teachers could support students by explicitly providing students with goal-setting opportunities.

The most relevant intersections in society include the relationship between universities and companies for a projection toward the sustainable employability of future graduates. Among the possible intersections, Service-learning (SL) is an educational proposition that may help university students to develop their personal skills, offering them opportunities to learn and practice civic commitment, improving their sense of social and citizen responsibility, and combining academic and community-service learning in a constructed programme where participants train by working on real needs of the environment to optimize and transform the latter. The development of SL programmes in university departments related to technical areas is posing a challenge to faculty members and students, thus it is important to explore this lack of programmes. The main aim of the present study was to identify SL projects and their topics through a systematic review, following the guidelines of the «Preferred Reporting Items for Systematic Reviews and Meta-Analyses» (PRISMA) declaration in the knowledge areas of Architecture, Computer Science, Environmental Engineering, Software Engineering, Computer Engineering, Artificial Intelligence, and Computer Languages and Systems, from the year 2008 to the year 2023. This review includes 128 articles, which were analyzed with ATLAS. Ti 22. The categorical system employed in this work emerged from the topics of the programmes identified in the selected articles, which were verified by experts in the mentioned fields of knowledge. The agreed categories were: accessibility, learning, social groups, courses, devices, infrastructure, games, environment, landscaping, heritage, software and web. The most relevant conclusions highlight that most of the articles refer to theoretical aspects of SL, showing a lack of data on the practical development of SL programmes and their impact on employability. The largest number of SL programmes are developed in the areas of Architecture, Computer Science and Software Engineering. Regarding the topics that are addressed in research, most of the articles refer to social groups, software, learning and accessibility.

IntroductionThe field of poetry learning is currently facing significant challenges, primarily due to a lack of motivation and interest among students. This has resulted in educators encountering difficulties in identifying suitable educational alternatives. To address the latter issue, immersive learning has emerged as a potential solution, as it has been demonstrated to enhance motivation and learning outcomes in a multitude of fields.MethodsIn light of the aforementioned considerations, this field study seeks to examine the potential of virtual reality (VR) tools in enhancing the memorization of poetry by increasing the engagement of the participants. The study concentrated on the acquisition of a French poem by a group of middle school students. A virtual environment has been developed for this purpose, tailored to the poem in question. The experimental design included a pretest, segmented learning sessions, a posttest, and a retention test. To evaluate student engagement, both motivation and sense of presence were measured using Likert-scale questionnaires, while memorization performance was assessed through a scoring system based on recall accuracy.ResultsThe findings reveal that the VR group demonstrated significantly higher motivation than the control group, with a mean difference of 12.626 on a 7-point Likert scale (six items), indicating that VR is a notably more effective tool for enhancing motivation in poetry learning than traditional methods. Additionally, the VR group reported a significantly stronger sense of presence, with a mean difference of 6.111 on the same questionnaire scale, further suggesting that VR enhances students’ sense of immersion in the learning experience. These results indicate that students using VR exhibited higher levels of overall engagement than those in the control group.DiscussionHowever, this increased engagement did not lead to improved memorization outcomes, as there was no significant difference in recall accuracy between the two groups. A potential explanation for this discrepancy is the “novelty effect” of VR, which may have distracted students from focusing fully on the memorization task. The implications of integrating VR in educational settings are thus discussed.

The rapid evolution of knowledge requires constantly acquiring and updating skills, making lifelong learning crucial. Despite decades of artificial intelligence, recent advances promote new solutions to personalize learning in this context. The purpose of this article is to explore the current state of research on the development of artificial intelligence-mediated solutions for the design of personalized learning paths. To achieve this, a systematic literature review (SRL) of 78 articles published between 2019 and 2024 from the Scopus and Web or Science databases was conducted, answering seven questions grouped into three themes: characteristics of the published research, context of the research, and type of solution analyzed. This study identified that: (a) the greatest production of scientific research on the topic is developed in China, India and the United States, (b) the focus is mainly directed towards the educational context at the higher education level with areas of opportunity for application in the work context, and (c) the development of adaptive learning technologies predominates; however, there is a growing interest in the application of generative language models. This article contributes to the growing interest and literature related to personalized learning under artificial intelligence mediated solutions that will serve as a basis for academic institutions and organizations to design programs under this model.

This study examines the efficacy of using a digital gamed platform in acquiring phoneme-grapheme correspondences of closed syllables with short vowels. Fifty-five fourth-grade English as a Foreign Language (EFL) learners navigated through five digital escape rooms where they learned, practiced, and produced target graphemes. Mixed methods analyses found that spelling competence in the intervention group as opposed to the control group improved in the post-test and continued to improve significantly in the delayed post-test. Following analysis of the participant interviews four themes emerged. Autonomous learning and self-monitoring were the dominant themes followed by engagement and motivation, self-confidence and self-esteem, and peer learning and social interaction in decreasing order of prevalence. Combining learning with play while participants navigated within the digital learning environment proved to be an effective method of teaching young EFL learners to spell. The results of this intervention contribute to recent research in the post-COVID-19 era and mirror OECD goals for the 21st century which have highlighted the need for effective digital platforms that promote independent learning while maximizing student engagement.

IntroductionThe study investigates the integration of artificial intelligence (AI) in higher education (HE) and its impact on pre-service teachers at the University of Latvia (UL) by exploring pre-service teachers' perceptions of the benefits and challenges of AI in both their academic learning and their future professional roles as educators, particularly regarding the promotion of inclusive education.MethodsData was collected via an online survey of 240 pre-service teachers across various disciplines at the UL. The survey included demographic details, AI usage patterns, and perceived benefits and challenges. Responses were analyzed using descriptive statistics, Kruskal-Wallis H tests, Spearman's correlation, and thematic analysis.ResultsLess than half of the participants used AI in their studies, with many expressing ambivalence or opposition toward AI. Benefits included language assistance and accessibility to global knowledge, while challenges involved reduced critical thinking and concerns over plagiarism. Despite recognizing AI's potential to promote inclusivity, most pre-service teachers have not applied it in practice. No significant differences in AI perceptions were found based on age, gender, or study level.DiscussionThe findings highlight a low adoption rate of AI among pre-service teachers and a gap between theoretical recognition of AI's potential and its practical application, particularly for inclusion. The study emphasizes the need for HE institutions to enhance AI literacy and readiness among future teachers.ConclusionAI is underutilized by pre-service teachers in both HE learning and teaching environments, which has implications for teacher preparation programs that better integrate AI literacy and inclusive practices.

Online learning and teaching during the COVID-19 pandemic had mixed impacts on students’ accessibility and performance. It benefited the concerned stakeholders, including management, teachers, and the students, to retain in the system, but it reinforced pre-existing discrimination among students from various disadvantaged groups. Studies reveal that the online learning system created an environment that facilitated students’ motive and interest in learning who disengaged themselves from classrooms due to various socioeconomic reasons during the pandemic. The present study explored students’ experience and perception of online learning in Nepal and analyzed the predictors of their interest in participating in the new learning environments. More specifically, it studied how the online modes of learning were associated with the interests of disadvantaged higher education students in their academic pursuits during the COVID-19 pandemic and how online learning impacted the pre-existing discrimination among them. The study generated concepts and variables drawing from the technology acceptance model (TAM) and a review of existing literature. A survey among 324 higher education students and a follow-up interview among nine selected respondents were conducted in Nepal between April and June 2021. The sample represented students from all social classes, genders, financial status, and geographies. Using a logistic regression model of the survey data and thematic analysis of interviews, this study found that compared to others, students from disadvantaged groups were significantly motivated by the online learning system. Their perception of online learning was positive despite the shortcomings of the system, such as the lack of internet infrastructure and the continuous flow of electricity. Students’ motivation toward the online learning system was triggered by their perception, which helped them to retain and continue in the higher education system. Based on the findings, this study concludes that in a developing country like Nepal, where students face social, economic, and geographical challenges in accessing higher education, the online learning system could be an effective alternative to traditional face-to-face learning to minimize pre-existing discrimination.

Collaborative online learning became a necessity for universities during the COVID-19 pandemic. Even though it is known from research that online collaboration is an effective way of learning, digital interaction can be challenging for learners. Group members have to create a high-quality interaction to ensure the success of the collaborative learning process. Based on a theoretical model of collaborative learning, high-quality interaction can be determined with regard to cognitive group activities (prior knowledge activation, transactivity), meta-cognitive group activities (organization of the work process), and relational group activities (group climate, participation and task-related communication). Our study aims to examine how students manage a self-directed collaborative learning setting, how they perceive the process quality of digital interaction and how the interaction quality is related to self-reported outcomes (learning gain and satisfaction). We use a newly developed questionnaire to assess the quality of digital interaction in terms of the aforementioned dimensions. Furthermore, we focus on associations with the beliefs about web-based learning and the ability of perspective-taking at the individual level as well as the sense of community at the group level. We conducted a quantitative study within online university courses that were implemented asynchronously due to the COVID-19 pandemic. N = 298 undergraduate students in teacher education rated the quality of a digital collaborative learning settings (response rate of 72%). The students worked on collaborative tasks autonomously without any guidance from the teacher. We find differences between (meta-)cognitive and relational factors of interaction quality, and differences in the strength of the associations with outcomes and individual and group-related factors. Our study provides insights into students´ collaborative online learning and examines the relationships between different dimensions of group interaction quality and the input and outcome variables. Limitations and areas for further research are discussed.

The widespread use of generative AI tools like ChatGPT has seen significant growth. This rise prompted discussions on integrating these technologies into school education. However, the practical implementation, testing, and assessment of generative AI in primary and secondary education remained largely unexplored. This article examines the application of ChatGPT-3.5 and 4 in primary school education. A study involving 110 students aged 8–14 across grades 4–6 in two Uruguayan schools was conducted. The focus was on using generative AI for dynamic personalization of educational content during classroom lessons. In these sessions, instructional content followed the curriculum goals, and text, illustrations, and exercises were generated and dynamically adjusted based on generative AI. The findings indicate that generative AI effectively tailors school materials to match varying pupil knowledge levels. Real-time adjustments during lessons cater to individual learning needs, enhancing cognitive ergonomics. This approach not only boosts pupil motivation but also improves their performance, facilitating more effective achievement of the curriculum’s learning objectives. These results suggest a promising avenue for leveraging generative AI to personalize and optimize primary school education.

IntroductionStudents pursuing science, technology, engineering, and math (STEM) majors often struggle with essential skills critical to their academic success and future careers. Traditional self-regulated learning (SRL) training programs, while effective, require significant time investments from both students and instructors, limiting their feasibility in large lecture-based STEM courses.MethodsThis study investigates whether completion of three AI-powered virtual-human training modules—focused on planning, self-monitoring, and reflection—leads to increased use of corresponding MS Planner tools among STEM majors compared to a control group.ResultsResults indicate that students who did not complete the first two training modules were less likely to use MS Planner features for planning and self-monitoring; however, the reflection module did not yield comparable results.DiscussionThese findings highlight the potential of AI-powered virtual-human training as a scalable solution to enhance desirable learning behaviors among STEM majors, particularly in large and diverse classrooms. This research contributes to the understanding of effective interventions for fostering SRL behaviors in STEM education and suggests avenues for future refinement and implementation of digital training tools.

Advancements in the generative AI field have enabled the development of powerful educational avatars. These avatars embody a human and can, for instance, listen to users’ spoken input, generate an answer utilizing a large-language model, and reply by speaking with a synthetic voice. A theoretical introduction summarizes essential steps in developing AI-based educational avatars and explains how they differ from previously available educational technologies. Moreover, we introduce GPTAvatar, an open-source, state-of-the-art AI-based avatar. We then discuss the benefits of using AI-based educational avatars, which include, among other things, individualized and contextualized instruction. Afterward, we highlight the challenges of using AI-based educational avatars. Major problems concern incorrect and inaccurate information provided, as well as insufficient data protection. In the discussion, we provide an outlook by addressing advances in educational content and educational technology and identifying three crucial open questions for research and practice.

This mini review provides a concise overview of recent developments in mobile-assisted vocabulary learning (MAVL) and compares its effectiveness to traditional methods in English as a Foreign Language (EFL) settings. The review synthesizes findings from recent empirical studies, highlighting how MAVL, particularly digital flashcards, promotes learner autonomy, engagement, and long-term vocabulary retention through features like spaced repetition and gamification. Traditional methods such as paper flashcards, while effective in structured classroom settings, lack the interactive and personalized benefits of MAVL. The review also discusses existing research gaps, including the need for further investigation into productive vocabulary use and long-term retention. Future developments in the field may include hybrid approaches that combine the strengths of both traditional and digital methods. This review aims to provide language teachers and researchers with an up-to-date understanding of MAVL and its potential to enhance EFL vocabulary acquisition.

In the ever-evolving landscape of educational technology, it is vital to understand the empirical relationships of teachers' Technological Pedagogical and Content Knowledge (TPACK) and its interplay with explanatory factors such as cyber wellness, school climate, and digital nativity. This study employs Covariance-Based Structural Equation Modeling (CB-SEM) to analyze self-reported data from 311 basic education teachers in Central Visayas, Philippines. The model demonstrates robust validity and reliability, showing diverse direct impacts on the antecedent variables to the seven constructs of TPACK. The findings reveal 16 significant hypothesized paths, with digital nativity has a significant effect on all three core knowledge domains of TPACK while school climate and cyber wellness have a significant effect on two knowledge domains. Another significant finding shows that content knowledge emerged with the highest significant effect on technological content knowledge (β = 0.621). This connection highlights the fundamental role of content knowledge in successfully integrating technological competencies among teachers, especially from a developing economy. The study provides policy insights tailored to post-pandemic educational management.

The increased access to artificial intelligence (AI) applications has made it possible to develop more engaging and complex educational activities for students in different disciplines. This research explored expanding university students’ knowledge of scientific entrepreneurship skills using an Artificial Intelligence application. The students participated in a training experience using the conversational ChatGPT language model to generate narrative scripts for various topics on scientific discoveries and technological advances to create new products or services that offer cost-effective solutions based on science. The experience was designed employing the i4C model (identify, ideate, invent, inform). The study used a two-sample design with repeated measurements based on a pre-test and post-test. One hundred five graduate students from two master’s degree programs at the Bolivarian University of Ecuador participated during the 2022–2023 academic period. The results indicate that the students notably improved in acquiring the knowledge necessary for scientific entrepreneurial skills. The study concluded that applying AI ChatGPT with a narrative scripting strategy can create new learning opportunities for students.

Online education has become an integral part of everyday life. As one form of online education, traditional Massive Open Online Courses mostly rely on video-based learning materials. To enhance accessibility and provide more variety of the learning content, we studied how podcasts can be integrated into online courses. Throughout three studies, we investigated the acceptance and impact of podcasts made available to learners on the online education platform openHPI. Throughout the studies we applied different methodologies, such as a Posttest-Only Control Group study, and a Static-Group Comparison. In the initial two studies, we identified that podcasts can serve as reasonable addition to MOOCs, enabling additional learning just as well as videos, and investigated the optimal podcast design for our learners. In one of our six-week courses on cybersecurity with more than 1,500 learners, alongside the third study, we identified that consuming an additional podcast can increase learning outcomes by up to 7.9%. In this manuscript, we discuss the applied methodologies and provide reasoning behind design decisions concerning, e.g., the podcast structure or presentation to be taken as inspiration for other educators.

IntroductionStudents in U.S. rural schools experience lower educational outcomes than their urban peers related to social determinants of health such as under resourced schools, shortages of qualified teachers and staff, and high poverty levels. Geographic, social, or professional isolation in rural communities can compound these disparities by contributing to high turnover of educators and staff. Virtual communities of practice (VCoPs) can address the needs of individuals in remote and rural communities. However, it is critical to understand if VCoPs meet rural school staff needs to support their students. Wenger’s Community of Practice (CoP) framework and the Project ECHO model for VCoPs guided this descriptive, qualitative arm of our study to explore experiences of school staff participating in VCoPs through Project ECHO.MethodsThirteen ECHO for Education participants joined virtual focus groups to discuss their experiences and perspectives of VCoPs. Interview transcripts were inductively coded using the CoP framework with enhanced rigor through audit trails and member checking.ResultsFour predominant themes emerged from the interviews: 1) belonging/connected with others; 2) reduced sense of isolation; 3) exchange of new ideas/knowledge; and 4) sense of collaboration. Participants described how the VCoP they participated in resulted in positive professional and personal experiences including the support offered in context of working in rural schools during the COVID 19 pandemic.DiscussionVCoPs can establish supportive professional networks for rural school staff working with students in under-resourced settings. Our theoretically-grounded results substantiate VCoP development as a systems-level approach to facilitate professional collaboration, mitigate staff turnover, diminish professional isolation, and support students in rural communities.

In the next 5 years, artificial intelligence (AI) tools are expected to become commonplace in people’s lives, especially in their work processes. Therefore, educational institutions feel intrinsically responsible for ensuring that their students acquire and develop competences associated with the appropriate use of this technology in their educational programs. However, what are the perceptions of students regarding the inclusion of artificial intelligence tools in their educational process and future careers, and what competencies can influence a greater adoption of this technology in the classroom? The objective of this article presents the results of an exploratory study in a sample population of students from a technological university in Mexico, in which their perception and openness toward the training and use of artificial intelligence tools for their professions was examined. Their perception of the development of complex thinking and its sub-competencies was evaluated, recognizing that complex thinking is a valuable cognitive skill to face changes in uncertain environments. The methodology of the study consisted of a multivariate descriptive statistical analysis using R software. The results determined a positive correlation between students’ perceived improvement in the achievement of complex thinking competence and their perception of the use of AI tools. In conclusion, participants perceived the use of these tools as a feature of their profession, although they questioned whether this knowledge is included in their professional training. This article presents several findings that offer ample opportunities for future research.