Existing literature on blended learning in higher education predominantly relies on student surveys, offering a limited perspective on actual classroom dynamics. To address this gap, this study examines the mutual influence among teacher-student interaction, student engagement, and satisfaction within blended learning environments at a Chinese university. A mixed-methods approach was adopted, integrating three data sources: classroom observations, student perception surveys, and behavioral data from the Learning Management System (LMS), using a triangulation design to comprehensively explore the relationship between interaction quality and learning. The findings reveal that personalized feedback, especially the emotional support provided by teachers, is crucial for student satisfaction. While LMS data clearly reflect certain aspects of behavioral engagement, they show little correlation with students’ affective engagement or perceived instructor support. Importantly, affective support not only strongly predicts student satisfaction but also appears to compensate for lower levels of online activity. These results suggest that in blended learning contexts, emotional and personalized interaction from instructors plays a vital role in fostering satisfaction, potentially outweighing the influence of online activity metrics. In practice, institutions and instructors should prioritize meaningful interpersonal engagement and affective feedback, rather than relying primarily on digital activity indicators, to enhance students' learning experiences and outcomes.
This study examines changes in senior high school students’ critical thinking following the implementation of a mobile computer-based learning approach in Pancasila Education in Bali. Addressing the continued predominance of teacher-centered instruction, the study explores how an integrated Learning Management System (LMS), accessible via both mobile and desktop devices, supports learning activities that emphasize analysis, evaluation, and reflection within value-based contexts. A quasi-experimental pre-test–post-test design was employed involving 200 students from four public senior high schools in Bali. The intervention was implemented over four weeks as part of regular Pancasila Education lessons, during which students engaged in LMS-supported activities, including case-based discussions, formative digital assessments, and reflective assignments. Students’ critical thinking skills were measured using a validated scenario-based test aligned with Pancasila Education content. Data were analyzed using paired-sample t-tests and effect size calculations, while LMS log data were examined descriptively to contextualize student engagement. The results show consistent improvements in students’ critical thinking scores across all participating schools, with an average gain of approximately 13.5 points and large effect sizes (Cohen’s d > 1.6). Engagement data indicate stable participation across learning activities, suggesting adequate implementation conditions. Given the absence of a control group, the findings are interpreted as evidence of learning improvement under comparable instructional conditions rather than as causal effects.
In this study, researchers investigated the effect of nanolearning on developing digital skills among pre-service teachers, considering the cognitive theory of multimedia learning (CTML) and locus of control to assess the effect of nanolearning on digital skills. The researchers used a mixed methodology, a quasi-experimental approach with two experimental groups and pre- and post-tests. The 56 teachers in the sample study were split into two groups at random. Teachers' opinions on nanolearning were gathered through interviews, and the list of digital skills was determined qualitatively using the three-stage Delphi technique. Three instruments were used in the study. The findings of the study show: There was a statistically significant difference in the average scores of the post-test of digital skills in favor of the experimental group that used nanolearning (audio and image). The results also showed that teachers with an internal locus of control achieved higher scores on the post-test of digital skills compared to those with an external locus of control. Pre-service teachers expressed positive views toward the use of nanolearning to develop their digital skills. Based on the findings, the researcher recommends integrating nanolearning as an essential part of the curriculum in colleges of education at Jordanian universities.
Workplace situations Modern higher education relies heavily on English for Specific Purposes (ESP), especially for students majoring in Management-Business and Information Systems, who need to be able to adapt their language skills to work in more globalized environments. The purpose of this exploratory mixed-method study was to investigate the learning requirements of ESP among 150 undergraduates (75 from Management-Business and 75 from Information Systems). The study's empirical basis was to develop a pedagogical model based on Growth Mindset principles and the integration of Artificial Intelligence (AI). Information was collected by means of a structured questionnaire that probed the following areas: technology preparedness for AI-enhanced education, learning modalities preferences, language skill goals, and professional communication scenarios. According to descriptive statistics, the most highly regarded ESP skills are speaking (88%) and writing (82%), particularly for job presentations (76%), online communication platforms (72%), and formal report writing (69%). In addition, there was a strong emphasis on resilience and adaptability in dealing with language challenges, which is indicative of a growth mindset orientation, and 79% of respondents were very enthusiastic about AI-mediated learning environments that improve personalization and formative feedback mechanisms. On a 5-point scale, the average ESP learning readiness score was 4.21, showing high levels of motivation and readiness. In order to foster language competence, psychological agency, and global readiness in line with the needs of twenty-first-century professions, our results highlight the importance of developing an ESP instructional model that cohesively incorporates growth mindset principles and AI-driven innovation.
This article examines the transformative impact of Artificial Intelligence (AI) on the teacher's role in contemporary learning environments, focusing on a shift from knowledge transmission to the orchestration of cognitive ecosystems through pedagogical prompt design. The study adopts an exploratory mixed-methods design conducted in three ninth-grade classrooms at a public secondary school in Colombia, where an educational escape room generated using generative AI and a structured pedagogical prompt was implemented to stimulate emergent learning processes. Quantitative analysis focused on the frequency of “insight moments,” defined as audibly articulated ideas that restructured the collective cognitive field, and the complexity of students’ final creative responses. The intervention identified 32 insight moments and revealed two divergent pathways of cognitive emergence: one characterized by frequent individual insights and another by slower collaborative synthesis leading to high-complexity outcomes. These findings indicate that high frequencies of insight do not consistently predict deeper conceptual integration at the group level. Qualitative observations suggest that the teacher’s role evolved into a “Higgs-like” configurator, an invisible architect who shapes the learning field through prompt design rather than direct instruction. The study concludes that pedagogical prompting constitutes a sophisticated form of instructional planning that enables spontaneous idea generation and transdisciplinary cognition in AI-mediated classrooms.
Digital competence is becoming a fundamental skill for 21st-century learners, especially in vocational education, where practical and technical skills are crucial. The study focuses on developing learner-centered online competence among students involved in work-based chemistry learning in vocational settings. It considers the contributions of leaders, teachers, and learners in supporting a digitally competent learning environment. The research sample included 80 vocational students. Data collection involved pre- and post-intervention assessments, surveys, observations, and semi-structured interviews. The learning intervention consisted of student-focused tasks such as virtual lab sessions, group online experiments, and self-guided data analysis tasks, with teachers guiding and instructing students. Quantitative analysis using paired t-tests and ANCOVA revealed significant improvements in students’ digital competence scores (p < 0.001) and enhanced practical laboratory performance. The most notable improvement was in Teacher Facilitation (TF) (Pre: 3.60; Post: 4.30). The highest paired t-test value was in Software Proficiency (SP) (t = 9.76, p < 0.001). Qualitative findings indicated increased motivation, autonomy, and engagement, with students reporting higher confidence in digital chemistry experiments. The research emphasizes institutional support for teacher training and digital tools, demonstrating that a competency-based, learner-centered approach effectively develops digital and practical skills essential for modern vocational chemistry education.
Measuring students’ attitudes towards mathematics is important because students’ attitudes influence their mathematical progress. In this study, we administered the Motivation and Attitude (MAT) questionnaire to 4,742 fourth-grade students, aged 10–11 years, from 114 Danish primary schools. The questionnaire was based on the Attitudes Towards Mathematics Inventory (ATMI), but in this study, it was adapted to suit a younger age group than what the ATMI has previously been used. In this process, the questionnaire was reduced from 40 to 32 questions. The questionnaire was designed to measure students’ attitudes towards mathematics in a Danish context. The structural validity and internal consistency reliability of the MAT questionnaire were satisfactory based on confirmatory factor analysis (CFA) and Cronbach’s alpha analysis, and the scores indicate that the MAT questionnaire has adequate internal consistency reliability. The CFA supported the use of a four-factor model; each factor was directly associated with a specific subscale. Correlations between the motivation and enjoyment, and between motivation and self-confidence, were high (0.8), indicating a close connection between the subscales. This may be due to the theoretical background of the concepts, and a continued effort to define attitude may help develop the questionnaire further.
The rapid rise of Artificial Intelligence (AI), particularly Generative AI, presents unique challenges and opportunities for higher education in emerging economies. This study quantifies AI’s impact on lecturers’ pedagogical innovation and students’ learning experiences within Vietnam's digital transformation. Grounded in an extended Technology Acceptance Model (TAM), the research employs Structural Equation Modeling (SEM) to analyze data from 710 respondents (270 lecturers and 440 students) at leading universities. Empirical results indicate that digital competence is a critical prerequisite for AI adoption, which subsequently exerts a strong positive effect on teaching performance through the full mediating role of pedagogical innovation. For students, the capacity for content personalization emerges as the primary driver of enhanced learning experiences; however, perceived ethical risks significantly undermine trust in these technologies. Furthermore, multi-group analysis reveals notable differences in adoption levels between STEM and Social Sciences students. Based on these findings, the study offers key policy implications for data-driven university governance and underscores the urgent need to establish a comprehensive ethical and legal framework. This research contributes vital empirical evidence to the discourse on sustainable, human-centered AI integration in developing educational systems.
The increasing use of hybrid learning in language education has not been fully matched by the development of models that are sensitive to local social and cultural contexts. This study aims to develop and evaluate the Hybrid Mode Indonesian Language Learning (PBIMH) model through a formative research approach that positions teachers as co-designers throughout all stages of development. A total of 28 teachers from professional education programs in Banda Aceh and Aceh Besar were actively involved in the design process, limited trials, and iterative reflection. Data collection was carried out through expert validation, questionnaires, and reflective feedback to assess the validity and practicality of the model. The analysis results showed a high level of content and construct validity with an average of 4.51 (SD = 0.53), with expert construct assessments ranging from 87.5–95, which is classified as very acceptable. The practicality test showed a positive response from teachers, with an average score of 4.51 (SD = 0.58). The novelty of the research lies in the systematic integration of local wisdom into a hybrid learning structure through collaborative and formative mechanisms. PBIMH was deemed valid, practical, and provided a conceptual contribution to the development of context-based language learning.
This study examined the level of mathematics self-efficacy among ninth-grade girls, with particular emphasis on geometry self-efficacy, and explored instructional practices that may enhance their confidence. A quantitative survey design was employed using a validated self-efficacy scale grounded in Bandura’s theory, focusing on the geometry unit in the ninth-grade mathematics curriculum. The instrument measured key dimensions of self-efficacy, including magnitude (task difficulty) and generality (transfer of confidence across tasks). The sample consisted of 105 ninth-grade girls selected from four randomly chosen classes in a private school during the first semester of the 2022/2023 academic year. Findings indicated a moderate overall level of mathematics self-efficacy. While participants demonstrated confidence in solving routine mathematical problems, their self-efficacy declined when addressing complex or unfamiliar geometry tasks. The results highlight the need to strengthen sources of self-efficacy, mastery experiences, vicarious experiences, verbal persuasion, and emotional regulation to support female students’ engagement in mathematics. Practical implications include implementing differentiated instruction, reinforcement strategies, hands-on geometry activities, and modeling practices. Additionally, curriculum developers and policymakers should integrate structured self-efficacy enhancing strategies within mathematics programs to foster sustained motivation and achievement among female learners.
The rapid penetration of Generative AI is reshaping the global higher education ecosystem; however, its integration in developing countries like Vietnam faces significant institutional and cultural constraints. This study utilizes an explanatory sequential mixed-methods design to examine how AI influences pedagogical innovation and student learning outcomes. During the quantitative phase, survey data from 970 participants (students, lecturers, and administrators) were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The qualitative phase integrated insights from 30 semi-structured interviews. PLS-SEM results indicate that perceived usefulness strongly promotes teaching integration intentions (β = 0.525) and learning outcomes (β = 0.315). Furthermore, pedagogical integration directly enhances academic performance (β = 0.468). However, academic integrity risks pose a substantial barrier to pedagogical innovation (β = -0.215). Qualitative findings reveal a critical paradox: while AI optimizes short-term efficiency, it threatens critical thinking and fosters algorithmic dependency. Crucially, institutional responsibility emerges as a decisive factor in mitigating these integrity risks (β = -0.385). The study concludes that the principal obstacle to AI integration is the absence of comprehensive digital ethics frameworks, not technological limitations. Consequently, universities must shift toward transparent governance policies and systematically restructure assessment practices to ensure responsible AI integration.
Reading difficulties (RDs) present significant challenges for inclusive education, underscoring the need for professional development programs that equip teachers with evidence-based literacy instruction strategies. This study examined the effectiveness of the MindPlay Comprehensive Reading Course for Educators, an online professional development program combined with in-person training and coaching, used to enhance the knowledge and instructional skills of 48 in-service early childhood teachers in the United Arab Emirates working in inclusive classrooms. Using a mixed-methods design, the intervention included ten asynchronous online modules, a two-day face-to-face workshop, and ongoing coaching support. Quantitative findings revealed substantial gains in participants’ reading-related knowledge, with post-intervention scores more than doubling pre-intervention scores across key domains, including phonological awareness, phonics, fluency, grammar, vocabulary, and reading comprehension. Results from the comprehensive reading test demonstrated statistically significant improvement with a large effect size, indicating a strong program impact. Qualitative findings indicated high participant satisfaction, highlighting the program’s practical applicability, flexibility, and alignment with evidence-based reading instruction. Participants reported increased confidence in implementing explicit, structured literacy strategies in inclusive classrooms while recommending extended training time and practicum-based experiences. Overall, the findings support blended professional development as an effective and scalable model for strengthening teacher competencies and advancing inclusive literacy practices.
The popularity of mobile technology has significantly impacted language education, especially in vocabulary acquisition. However, MAVL outcomes vary considerably, suggesting that access alone is insufficient. The present study contends that, as an essential skill in technology usage, metacognitive self-regulation acts as a crucial moderator. Quantitative in nature, the study collected data from 223 Thai university EFL students and used structural equation modeling for analysis. The study found that MAVL significantly predicted vocabulary acquisition. More importantly, it identified a significant moderator effect of self-regulation, whereby the positive correlation between MAVL and learning outcomes was notably stronger among learners high in self-regulation than those low in self-regulation, implying synergy. The study contributes to existing knowledge in several ways. First, it provides empirical evidence of self-regulation as an essential moderator in Mobile-Assisted Language Learning, shifting focus from technology-centric models to more holistic models of technology use. The study emphasizes the importance of moving beyond access to mobile technology and instead cultivating self-regulation skills in learners to bridge the “strategic divide” and reach maximum potential.
Learning continuity advocates the uninterrupted advancement of knowledge, enabling students to consistently build on their learning abilities in pursuit of their academic objectives. The research proposed the newly developed D&S Matrix and D&S Scale of Learning Continuity, along with their validation, as a groundbreaking effort to visually monitor learners' progress in higher education. Prospective cohort research, EFA, box-and-whisker plots, and data analytics were used in this study to monitor the cyclical development of students. Data were collected from Higher Educational Institutions across different parts of the globe. An experimental study was conducted to observe how a group of higher education students transferred from one cohort to another and to evaluate their learning gains. The findings demonstrate encouraging results in monitoring the incremental development of learners, both at the individual and group levels, across dimensions such as maturity, rote, traditional, and induced characteristics. Acquiring deep understanding, expertise, and lasting memory of scholarly material is a crucial component of research in the technology-mediated learning space. The advent of remote learning and disruptions to conventional classroom instruction necessitate preserving learning continuity to avert adverse effects on students' academic achievements. This will have a substantial influence on the future undertakings of educational policymakers.
This quantitative study investigates Saudi early childhood teachers’ usage of digital storytelling to support children’s academic and social development. A quantitative approach was adopted to collect data from 200 early childhood teachers working in public and private schools over nine weeks. The scales explored teachers’ usage of DST as a pedagogical tool to support children’s academic and social development and learning, the benefits and challenges teachers face when integrating DST into their teaching practices, and the impact of DST on children’s engagement, creativity, narrative skills, and media literacy. The findings indicated that the majority of respondents held positive attitudes toward DST as a pedagogical tool. They also indicated a positive influence on children’s academic learning and social development. The respondents revealed some challenges related to lack of training, managing children, and costs associated with equipment and software tools. Test results showed statistically significant associations between teachers’ attitudes towards using DST and years of teaching experience. No statistically significant associations were found between teachers’ attitudes and school type. This study offers valuable insights into educational technology, especially media literacy for childhood education, to integrate DST into weekly lesson plans to maximize its impact on children’s academic and social development.
This study aims to develop and evaluate the effectiveness of E-Archives Learning 2.0 as an integrated, intuitive, and adaptable instructional medium for digital archiving. Using a Research and Development (R&D) design, the study was conducted through stages of needs analysis, prototype development, expert validation, and multi-stage field trials. A mixed-methods approach was applied, combining qualitative data from interviews and focus groups with quantitative data from surveys and assessments. Results show a significant improvement in participants’ proficiency, with mean scores increasing from 86 to 94 (p < 0.05) and a large effect size (Cohen’s d = 1.39). The learning media achieved a success index of 95%, with digital archiving comprehension at 81.97%, user competency at 82.87%, and technology use effectiveness at 87.75%. Challenges include technological infrastructure (77.10%) and the need for advanced technical training (70.11%). Overall, findings indicate E-Archives Learning 2.0 effectively enhances digital archiving competencies and has potential as a sustainable platform-based learning model, supported by infrastructure improvements and systematic human resource development. The study contributes empirical evidence on developing and evaluating an integrated digital archiving learning system, linking media effectiveness, user competency, infrastructure readiness, and training needs within vocational education, extending research by connecting instructional design outcomes with institutional capacity.
Generative artificial intelligence (GenAI) is transforming educational practice, yet limited research has examined how pre-service teachers in non-STEM disciplines are prepared to use it critically and pedagogically. This study investigated the level of GenAI literacy among pre-service teachers majoring in physical education in South Korea, where AI literacy is emphasized in national policy but unevenly implemented across disciplines. Using a descriptive survey design, students at a four-year university completed an online questionnaire during the fall semester of 2025. The survey, adapted from the Generative AI Literacy for Learning Scale, measured four dimensions: needs analysis, prompt and language skills, autonomous learning, and critical thinking. The results showed that participants demonstrated relatively strong competence in selecting appropriate AI tools and using GenAI for autonomous and collaborative learning. However, their perceived ability to critically evaluate AI-generated content, particularly in identifying bias and verifying information, was comparatively weaker. These findings suggest a gap between functional GenAI use and the evaluative and ethical reasoning required for responsible classroom integration. The study offers baseline evidence for developing discipline-sensitive GenAI literacy frameworks and highlights the need for teacher education programs to strengthen critical verification, bias awareness, and ethical decision-making.
Ensuring equitable vocational education in remote areas remains challenging due to limited infrastructure, unstable connectivity, and shortages of qualified teachers. This study examines the implementation of a Progressive Web App (PWA)–based learning ecosystem to enhance learning access, competency development, and employability outcomes in seven vocational schools across Pulau Sumba, one of Indonesia’s least developed regions. A proprietary platform (https://www.pwa-smk.id/) integrating an Academic Information System, e-learning, and internship (Prakerin) management was developed with offline-first caching, low-bandwidth microlearning, and cross-device accessibility. Using an explanatory sequential mixed-methods design, the quantitative phase involved 214 students, followed by qualitative data from 32 purposively selected teachers and school managers, complemented by system-generated engagement logs. Ethical approval was obtained from Universitas Negeri Yogyakarta (No. B/2795/UN34.21.LS.17/LT/2025). The results demonstrate substantial improvements in learning access, vocational and digital skills, and user engagement. Online learning access increased from 46.2% to 87.9%, with 68.1% of materials accessed offline. Pre- and post-assessments showed gains in hard skills (31.1%), soft skills (31.6%), digital literacy (46.7%), and certification readiness (47.0%). The intervention contributed to multiple SDGs, including quality education, youth employability, reduced inequalities, and sustainable practices. Community spillover effects included increased parental involvement, MSME engagement, and digital literacy uptake. Overall, the findings provide strong empirical evidence that context-adapted PWA solutions offer a cost-effective and inclusive approach to accelerating vocational education and community transformation in remote areas.
Digital transformations in higher education have highlighted the need for further use of educational analytics as a separate mechanism to support adaptive management of academic processes. The purpose of the proposed article is to analyze the patterns in the application of analytical data to improve the effectiveness of management decisions in universities (using the example of Ukraine). The study was carried out within the framework of a mixed design, which combined quantitative data analysis of more than 15,000 students and semi-structured interviews (25 participants from among teachers and administrators). The proposed results demonstrate the existence of a steady growth in the digital activity of students (up to +59% in three years) and close links between behavioral and academic transformations (r = 0.55–0.71). The regression model made it possible to establish that separate, integrated analytical panels, regular reporting, and early warning systems have become the main factors for increasing the adaptability of management in modern universities. Qualitative analysis showed an increase in managerial reflexivity, ethical awareness, and staff readiness to further use analytics. The conclusions indicate that educational analytics has now become an effective mechanism for universities to transition to an adaptive model of effective management of educational processes.
Kazakhstan officially recognizes the early learning of a foreign language. Young students must still adjust to their new language environment when they begin studying a new school subject in the second grade as a foreign language. The use of modern technologies will provide favorable conditions for successfully mastering the necessary knowledge in the classroom and overcoming obstacles. In this regard, it is critical to identify key teaching strategies that promote English language learning. The study aims to evaluate modern foreign language teaching technologies and their effects on developing young students' positive attitudes and motivation towards learning English. For this purpose, EG (n = 110) and CG (n = 100) were identified in which pre-experimental and post-experimental activities were carried out. The study revealed that some of the children in the group lack motivation to learn English. The teacher only uses foreign-language texts from textbooks. Other texts are not used in the classroom that students might find interesting. Students' vocabulary in monologues and dialogic speech is monotonous and does not correspond to their age or accepted speech norms. The traditional approach to teaching English in primary school does not fully address many existing issues. The study's findings demonstrated that the integration of modern teaching technology and training methods into classrooms increases young students' positive attitudes and motivation to learn English.
