Online tutoring is crucial for pre-university students, as it provides academic support and helps them develop the essential skills needed for a successful transition to higher education. With the widespread shift to remote learning, online tutoring has emerged as both an intervention and an alternative to traditional instruction. Despite its relevance, existing studies have emphasized factors influencing adoption and effectiveness, while paying limited attention to systematically exploring the barriers to its successful implementation. To address this gap, this work aims to identify and analyze the barriers to online tutoring in the context of pre-university education in the Philippines. The study design comprises two sequential components. First, a systematic literature review guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework is conducted to determine a comprehensive initial list of barriers. The initial list was validated by a group of experts tasked with evaluating the relevance of barriers in the pre-university context. Second, to analyze these barriers, the DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach was used to identify critical barriers and map their significant structural interdependencies. The findings of the systematic literature review reveal 13 barriers to online tutoring, including unstable connectivity, inadequate device access, low digital literacy, insufficient pedagogical training, weak content knowledge, poor instructional adaptation, low student engagement, reduced feedback quality, cultural mismatch, poor platform usability, inflexible scheduling, low motivation, and inadequate institutional support. Exploring their interdependencies shows that insufficient pedagogical training and low digital literacy are the key driving barriers that significantly influence online tutoring in pre-university education. When addressed, they contribute to mitigating poor instructional adaptation, low student engagement, reduced feedback quality, and low student motivation to engage in online tutoring. By providing a structured relationship map, this study offers practical insights to guide educators and policymakers in developing targeted interventions and improving implementation.
This study evaluates quality-related characteristics of a long-cycle engineering education model from the perspective of education for sustainable development. The aim was to assess whether the model's documented curricular architecture, its interpretive alignment with international engineering-education benchmarks, and student self-assessments provide convergent evidence of its relevance for sustainability-oriented engineering training. The study combined documentary analysis, program-level mapping of sustainability-relevant elements, interpretation through the frameworks of the United Nations Educational, Scientific and Cultural Organization (UNESCO), the Accreditation Board for Engineering and Technology (ABET), the International Engineering Alliance (IEA), and the Conceive-Design-Implement-Operate (CDIO) standards, and a comparative anonymous survey of engineering students from Russia and Latin America. The final analytical sample comprised 505 questionnaires. The documentary and mapping results indicate that the model has a coherent and practice-oriented program configuration integrating fundamental, specialised, practical, research, economic, and digital components. The survey results do not prove universal superiority; however, they indicate selective student-reported advantages of the experimental trajectory, especially in familiarity with sustainable development, understanding of future professional activity, and self-assessed applied competencies. Overall, the study proposes a structured framework for evaluating sustainability-oriented engineering curricula while explicitly limiting the interpretation to a case-specific, perception-based assessment.
This cross-sectional survey of 123 Swiss adult education educators (August–October 2025) examined AI adoption, barriers, and perceptions. AI tool use is widespread in this non-probability sample (82.1% report active use), and usage frequency is primarily associated with educators’ self-reported AI knowledge rather than demographic characteristics. Educators are largely optimistic about artificial intelligence’s potential to support their work. However, they report substantial constraints, most notably privacy and security concerns and limited perceived institutional support. Reported benefits centre on efficiency-oriented applications (e.g., lesson preparation), indicating that, in this sample, AI use is driven more by productivity gains than by deeper pedagogical integration. Simultaneously, concerns are pronounced, particularly regarding potential impacts on learners’ critical thinking. These findings indicate a sector poised for broader AI adoption yet still reporting institutional support gaps, unresolved privacy concerns, and professional development needs, which coincide with a continued focus on isolated administrative tool use rather than integrated pedagogical AI ecosystems in this sample.
IntroductionArtificial intelligence (AI) literacy has emerged as an important competency for future educators, extending beyond the technical use of AI tools to encompass critical evaluation, ethical awareness, and an understanding of their broader societal implications. At the same time, growing environmental challenges have increased the importance of ecological footprint awareness in teacher education. Although both AI literacy and environmental awareness are increasingly emphasized within contemporary educational and sustainability frameworks, they have largely been examined as separate domains. Exploring their relationship may therefore provide insights into how digital and sustainability-oriented competencies can be addressed together in teacher education.MethodsThis study examined the relationship between AI literacy and ecological footprint awareness among pre-service teachers, with particular attention to the differential roles of AI literacy dimensions. A cross-sectional correlational survey design was employed with 378 pre-service teachers enrolled in faculties of education at four state universities in Türkiye. Data were collected using validated measures of AI literacy and ecological footprint awareness and analyzed through descriptive statistics, group comparisons, and Pearson correlation analyses.ResultsThe findings indicated high overall levels of both AI literacy and ecological footprint awareness, although ecological footprint awareness was comparatively lower in the food and transportation/housing domains. Overall AI literacy was moderately and positively associated with ecological footprint awareness (r = .350, p < .001). However, the strength of this relationship differed substantially across the dimensions of AI literacy. Ethics showed the strongest positive association with ecological footprint awareness (r = .443, p < .001), followed by Evaluation, whereas the Use dimension was not significantly associated with ecological footprint awareness. These findings indicate that the relationship between AI literacy and ecological awareness is more strongly linked to ethical and reflective competencies than to technical or procedural AI use alone.DiscussionThe study highlights the importance of conceptualizing AI literacy as more than technological proficiency within teacher education. Teacher education programmes may benefit from moving beyond predominantly tool-oriented AI training toward approaches that integrate ethical reasoning, critical evaluation, and sustainability education. Connecting AI-related competencies with environmental responsibility may contribute to preparing future teachers who can critically evaluate both the opportunities and broader consequences of emerging technologies.
IntroductionHigher education institutions often rely on STEM viewbooks that display a diverse student body to recruit ethnic-racial minoritized students (ERMs) into STEM. However, the impact of visual representation in recruitment efforts on ERM psychological and behavioral outcomes has yet to be experimentally tested.MethodsIn a first-of-its-kind study, we conducted a naturalistic field experiment targeting admitted college students across eight higher education institutions. Students were given the opportunity to read a STEM viewbook displaying either White and Asian (non-ERM) or Black and Latinx (ERM) STEM professionals.ResultsUnexpectedly, students across all ethnic-racial backgrounds (N = 290) demonstrated stronger STEM engagement, identity, and intentions after reading the non-ERM viewbook compared to the ERM viewbook. Moreover, exploratory student gender analyses revealed that male students (across all ethnic-racial groups) exhibited relatively higher STEM identities, STEM intentions, and recruitment responsive behavior, driven by greater engagement with the non-ERM viewbook.DiscussionThough college recruitment efforts use diverse visual displays within viewbooks with the goal to increase their student diversity, this naturalistic experiment presents inconclusive evidence for the effectiveness of this commonly-used recruitment method.
BackgroundAlgebra remains a challenging aspect of the secondary school mathematics curriculum in Nigeria, contributing to persistent learning difficulties and poor achievement.ObjectivesThis study examined the effect of Gagné's instructional strategy on students’ performance and retention in Algebra, as well as its impact across gender.MethodsA quasi-experimental design was employed involving 382 students selected through multi-stage sampling. An Algebra Performance Test with a reliability coefficient of.69 was used for data collection. Descriptive statistics and Quade's non-parametric ANCOVA were used to analyse the data.ResultsResults showed that students taught using Gagné's instructional strategy performed significantly better than those taught through the conventional approach, F(1, 380) = 518.11, p < .001, partial η2 = .577, indicating a large practical effect. Gagné's instructional strategy also supported retention outcomes, reflecting sustained learning over time. Additionally, no significant gender differences were found in performance after adjusting for pretest scores, F(1, 181) = 0.16, p = .690, partial η2 = .001, suggesting that Gagné's instructional strategy benefits male and female students equally.ConclusionThe findings demonstrate that Gagné's instructional strategy effectively enhances both immediate and sustained Algebra learning. It is recommended that Gagné's instructional strategy be integrated into mathematics instruction and teacher training programmes to improve learning outcomes in secondary schools. Implications of these findings and recommendations for practice are discussed.
This study examined whether instructional scaffolding improves critical-analytical abilities among non-native English literature undergraduates relative to traditional lecture-based teaching. In a within-subjects quasi-experimental design, 101 undergraduates across four sections were taught a poetry unit using scaffolding (Unit 1) and a drama unit using traditional instruction (Unit 2). Students scored significantly higher on the Unit 2 exam than the Unit 1 exam (n = 89; M = 11.88 vs. 10.83/15; t(88) = −3.78, p < .001, d = 0.40), and forced-choice comparisons showed a small, consistent preference for the traditional method; however, because unit order and literary genre were not counterbalanced across sections, this difference cannot be attributed to teaching method alone. Scaffolding activities were rated positively at the activity level despite this pattern. A secondary finding — that group-based scaffolding carried a real implementation cost from uneven group participation — offers actionable guidance independent of this limitation. These results should be read as evidence about scaffolding's implementation under authentic classroom conditions rather than as a causal test of its effectiveness; they motivate a counterbalanced follow-up study and identify specific logistical factors to manage in EFL literature classrooms.
The increasing digitalization of education and the growing emphasis on twenty-first-century competencies have expanded expectations for English as a Foreign Language (EFL) teachers’ continuous professional development. However, limited evidence exists on how teachers’ self-regulated professional learning and perceived digital educational opportunities are associated with their readiness to integrate Critical Thinking, Communication, Collaboration, and Creativity (4Cs) into teaching. A cross-sectional quantitative study was conducted with 225 in-service EFL teachers from secondary schools and universities in Shymkent, Kazakhstan. Data were collected using measures of Self-Regulated Professional Learning (SRL), Perceived Digital Educational Opportunities (DEO), and an eight-vignette scenario-based assessment of readiness for 4Cs integration. Descriptive statistics, Pearson correlations, multiple linear regression, Welch's independent-samples t-tests, and adjusted regression analysis were applied. The mean overall scenario-based readiness score was 21.43 (SD = 4.42; theoretical range = 8–32), with Critical Thinking showing the highest mean and Creativity the lowest. Overall readiness was strongly associated with SRL (r = .809, p < .001) and perceived DEO (r = .761, p < .001). In the multiple regression model, SRL (β = .553, p < .001) and perceived DEO (β = .375, p < .001) were independently associated with readiness, with the model explaining 72.3% of its variance (R2 = .723). Creativity showed the strongest dimension-specific relationships with SRL and perceived DEO and the largest proportion of explained variance (R2 = .593). University instructors demonstrated higher unadjusted readiness than secondary-school teachers; however, the institutional association was substantially reduced after adjustment for teaching experience and gender (β = .111, p = .003). EFL teachers’ scenario-based readiness for 4Cs integration is closely associated with both self-regulated professional learning and perceived digital educational opportunities, although the strength of these relationships differs across individual 4Cs dimensions and institutional contexts. The findings highlight the potential value of CPD approaches that combine access to digitally mediated professional-learning opportunities with support for teachers’ planning, reflection, self-monitoring, and pedagogical adaptation. Because the study was cross-sectional and scenario-based, the findings represent statistical associations and stated pedagogical preparedness rather than causal effects or directly observed classroom competence.
Generative artificial intelligence (GenAI) is rapidly reshaping higher education and students’ academic writing practices. However, existing research has largely focused on technology acceptance and usage intention, with less attention to whether and how GenAI use can be sustained. This study investigates the determinants and dimensions of sustainable GenAI use among university students through a mixed-methods approach, combining an online survey of 1,084 Chinese university students with semi-structured interviews. An extended Unified Theory of Acceptance and Use of Technology (UTAUT) model was employed to examine the quantitative relationships. The results indicated that performance expectancy (β = 0.195, p < 0.001), effort expectancy (β = 0.094, p = 0.030), social influence (β = 0.147, p < 0.001), perceived enjoyment (β = 0.224, p < 0.001), and perceived creativity support (β = 0.211, p < 0.001) positively affected behavioral intention, whereas perceived risk had a negative effect (β = −0.044, p = 0.019). Facilitating conditions (β = 0.355, p < 0.001) and behavioral intention (β = 0.531, p < 0.001) were positively associated with actual usage behavior. Additionally, gender, educational level, usage experience, and disciplinary background exerted significant moderating effects. Qualitative findings identified three interconnected dimensions of sustainable GenAI use: long-term continuance, balanced and moderate use, and responsible and ethical use. By extending UTAUT beyond technology acceptance toward a multidimensional conceptualization of sustainable use, this study showed that sustainable GenAI use depended not only on technology acceptance but also on students’ ability to engage with GenAI critically, responsibly, and autonomously. The findings provide practical insights for fostering AI literacy and the appropriate integration of GenAI in higher education.
BackgroundGenerative AI is increasingly integrated into education, yet its role in health technology curricula remains underexplored.ObjectiveThis study examines students' perceptions of generative AI use in health technology education, focusing on its benefits, challenges, and implications for learning.MethodsA case study was conducted within a master's-level course using two student surveys (49 baseline and 33 follow-up responses) and 11 semi-structured student interviews. Qualitative data were analyzed using Braun and Clarke's reflexive thematic analysis, and survey data were analyzed descriptively.ResultsMost students actively used generative AI for tasks such as prototyping, writing, visual design, and problem-solving. Students perceived AI as a multifunctional learning resource that supported efficiency, creativity, and collaboration in their learning processes. At the same time, participants identified important challenges, including over-reliance, hallucinations, privacy concerns, and the need for critical evaluation of AI-generated outputs.ConclusionStudents experienced generative AI as a valuable yet complex learning tool. The findings highlight the importance of fostering AI literacy and promoting its critical and responsible use in health technology education.
Despite federal funding, its distributional inequalities disproportionately affected the academic and socioemotional outcomes of racially, geographically, and socioeconomically marginalized students. This literature review synthesizes 20 peer-reviewed articles and policy reports in three broad categories: the digital divide, complex trauma and cognitive load, and limitations in funding and implementation capacity. On average, less than half of the Elementary and Secondary School Emergency Relief (ESSER) was expended at the district level on meeting students’ academic, social, emotional, and other needs, with this phenomenon being even more marked in under-resourced schools. More than 40% of households in counties classified by the Digital Divide Index as having High Digital Divide earn less than $35,000 annually. Schools serving lower-income households, therefore, face instructional, administrative, and infrastructure capacity limitations in implementing recovery frameworks. Both the exacerbation of the digital divide and missed opportunities to invest in evidence-based interventions left the complex trauma resulting from COVID and existing social factors unmitigated, which, coinciding with a critical developmental period, can leave lasting negative consequences on the psychological development of students. Early evidence suggests that pandemic-generated distress may exacerbate academic and social-emotional outcome gaps for underserved students, pointing to a need for supportive school-based mental health intervention. This paper therefore recommends that federal policymakers work with districts and schools to develop standards for trauma-informed SEL instruction tied to recovery funding, disaggregate data on student mental health outcomes by race and income, invest in community-based participatory research on school-based trauma interventions, and fund access to technology for Title I districts.
Laboratory-Based Pedagogy (LBP) is widely advocated for promoting active, inquiry-based science learning. Yet, evidence of its effectiveness at the junior secondary school level remains underexplored in developing educational contexts. Guided by Piaget's constructivist theory, this pilot randomised pretest-posttest study examined the effect of LBP on Basic Science achievement among 30 junior secondary students from a single school, randomly assigned to experimental (n = 15) and control (n = 15) groups. The experimental group engaged in structured hands-on laboratory activities integrated into classroom instruction, whereas the control group received teacher-centred instruction covering the same content. Data was collected using the Basic Science Achievement Test (BSAT), adapted from National Examination Council (NECO) examination items. Mean scores, standard deviations, and Analysis of Covariance were employed to analyse the data, while controlling for pretest scores. Result revealed a significant effect of instructional method on posttest achievement, F(1, 27) = 19.44, p < .001, partial η2 = 0.419, with the laboratory-based group outperforming the control group. Pretest achievement also significantly predicted posttest performance. These findings suggest that LBP can improve Basic Science achievement by promoting active learning. Nevertheless, the findings should be interpreted with caution because the study was conducted at a single school, involved a small sample, and the groups exhibited substantial baseline differences in pretest performance. The study provides preliminary evidence to support larger, well-powered randomised trials in diverse educational settings.
Artificial intelligence (AI) is increasingly reshaping higher education, influencing how students access knowledge, engage with learning tasks, and regulate their learning processes. While existing research has largely focused on efficiency and performance, comparatively limited attention has been given to how AI affects metacognitive processes such as planning, monitoring, and evaluation. This study addresses this gap through a qualitative systematic literature review with thematic synthesis of peer-reviewed studies published between 2018 and 2026, supplemented by foundational theoretical work on metacognition. The findings indicate that AI does not exert a uniform effect on metacognition. Instead, its impact is dynamic, context-dependent, and shaped by the interaction between technological, pedagogical, and socio-economic conditions. AI can enhance metacognition by externalising cognitive processes and supporting feedback, but it can also enable cognitive offloading, reducing learners’ engagement in regulation. A third mode, hybrid regulation, emerges in which metacognitive processes are co-constructed between learners and AI systems. These findings are particularly relevant to AI-supported and technology-rich learning environments, including STEM education contexts where intelligent tutoring systems and generative AI tools increasingly mediate learning processes. The study proposes a conceptual framework that positions AI along a continuum from support to offloading, shaped by contextual conditions. The findings reframe AI as a system that reorganises, rather than simply enhances or erodes, metacognition in higher education.
BackgroundGlobalization plays a pivotal role in shaping adult and higher education across the regions of the world, driven by rapid technological advancement, the diffusion of knowledge, and expanding cross-border educational practices. This study examined globalization of adult and higher education in Africa with qualitative evidence and proposed a future research agenda for Nigeria that can inform policy on adult education.MethodologyA qualitative case study design was adopted, and the study was conducted between 23 April and 19 May 2026. Purposive and snowball sampling techniques were employed to select (n = 15) highly experienced participants involved in adult and higher education policy implementation from various institutions and organizations. Semi-structured interviews were used to collect data, which were audio-recorded and verbatim transcribed. The transcripts were then analysed using NVivo Software and coded. The study adhered to all ethical considerations.ResultsParticipants identified inadequate funding, weak institutional capacity, limited government support, poor infrastructure, and gaps between policy formulation and implementation as major challenges affecting the globalization of adult and higher education in Nigeria.LimitationsThis study used a qualitative approach, which limits its statistically generalizable findings to the broader population because of the relatively small sample size.Implications for future research directionsFuture research should adopt diverse methodological approaches, including quantitative, mixed-methods, and longitudinal research designs, to generate a more comprehensive understanding of how globalization influences adult and higher education.Originality/valueThis review contributes to adult education and lifelong learning by advancing an integrated understanding of how globalization influences the policy and practice of adult and higher education in Nigeria.
This cross-sectional study examined the extent to which self-regulation skills (attention, inhibitory control, and working memory) statistically predict sustainable environmental behaviors (consciousness and awareness) in 224 preschool children aged 61–72 months. The Self-Regulation Skills Scale (Teacher Form) and the Environmental Sustainability Scale for Children 60–72 Months Old were administered. All three components were entered as candidate predictors in stepwise regression analyses stratified by age and gender; inhibitory control did not meet the entry criterion (p < 0.05) in any model and was therefore retained in exploratory zero-order analyses only. Attention statistically and positively predicted environmental consciousness across the full sample (R2 = 0.041, p = 0.002) and in 6-year-olds (R2 = 0.057, p = 0.007) and predicted environmental awareness in 5-year-old girls (R2 = 0.099, p = 0.024) and in all children (R2 = 0.021, p = 0.030); however, no model met the Bonferroni-corrected threshold (adjusted α = 0.00625), so all findings are reported as exploratory. Formal moderation analyses revealed that gender did not significantly moderate the attention–environment relationship. These findings identify attentional self-regulation as a specific cognitive pathway to environmental sensitivity in early childhood, consistent with Bandura's Social Cognitive Theory. Curriculum implications and directions for confirmatory longitudinal research are discussed.
Virtual Learning Environments now record behavioral data at a scale traditional classrooms never reached, yet most online platforms still serve every student the same content, pacing, and evaluation. The learners who most need adaptive support pay the highest price for this uniformity. In the Open University Learning Analytics Dataset (OULAD), students who self-declare a disability pass 10.0 percentage points less often than their non-disabled peers and withdraw 9.1 points more often. We present an Internet of Behaviors (IoB) analytics ecosystem for adaptive e-learning that turns this behavioral record into timely, accountable support, closing the loop between observation and intervention. The ecosystem links four working parts: a forecasting model that predicts drop-out, pass/fail, and near-term disengagement from routine course activity; an explanation layer that makes each prediction legible to the instructor who has to act on it; a fairness audit centered on students with a declared disability; and a tamper-evident record of every automated decision, so that actions affecting a learner's path can be reviewed under GDPR Article 22 and FERPA. We evaluate the analytical layers on OULAD using multi-seed runs with confidence intervals and cross-validation across unseen course presentations. The model holds up on those presentations (drop-out AUC 0.916), and its explanations agree closely across methods. The fairness gaps it leaves stay small. Three results complicate the story: a strong gradient-boosting baseline outperforms the deep model on drop-out; an external sentiment signal adds nothing over a simple week indicator; and the multi-task design is smaller and faster rather than more accurate. On a public blockchain testnet, each decision was anchored within a single block at a median 23,965 gas. Inclusion and accountability can be designed into an e-learning analytics pipeline and then measured.
Belonging has become an increasingly important concept in educational research, yet it is often treated as a pupil experience, relational outcome or psychological state rather than as a condition shaped by the organisation of school life. This conceptual article argues that mainstream schools need to move from provision-led inclusion towards belonging-led inclusion. Provision remains necessary: policies, interventions, adjustments, staffing arrangements, monitoring systems and review processes protect entitlement and organise support. However, provision can also become proxy evidence for inclusion while leaving the lived conditions of membership, care and participation underexamined. Drawing on school belonging research, critical theories of belonging, inclusive education, social justice theory, inclusive pedagogy, mattering and school leadership scholarship, the article positions belonging as a central evaluative condition of pastoral and inclusive education. It argues that schools should evidence not only what support is provided, but how pupils become recognised, connected, participatory and consequential members of the school community. The article develops a Belonging-Led Inclusion Framework organised around six dimensions: recognition, participation, relationship, curriculum access and identity, agency, and mattering. The article contributes to school belonging, pastoral care and inclusive education scholarship by showing that belonging is not only an individual feeling or relational experience, but a whole-school organisational achievement. It reframes inclusion as a question of school architecture rather than support accumulation: not simply what provision is organised, but how the relational, curricular, pastoral and spatial conditions of school enable pupils to belong on dignified and self-defining terms.
IntroductionThis study examined the motivational factors influencing the decision to pursue a career in teaching physical education (PE) among 256 preservice and in service teacher education students in Israel, including both undergraduate students and academic career changers.MethodologyUsing a newly adapted questionnaire derived from the AFPE instrument, we assessed five motivational dimensions: work, mission, personal fit, self-development, and family influence. A series of repeated-measures General Linear Models were conducted to explore within-subject differences across motivational domains and between-group differences based on sex, ethnicity, and program type. We also performed a thematic content analysis of open-ended responses from academic career changers to further illuminate the personal narratives underlying their decisions to retrain in PE.ResultsFindings revealed a clear motivational hierarchy across all participants: mission- and value-driven motives were the strongest, followed by personal fit, self-development, and work-related factors, whereas family influence was consistently the weakest motivator. Minority students (Druze, Muslim, Christian) reported significantly higher overall motivation than the majority (Jewish) students, particularly in self-development and work-related dimensions. Sex showed no significant effect on overall motivation. Comparison between undergraduate students and academic career changers revealed broadly similar overall motivation levels, although academic career changers reported a slightly higher overall motivation, reflecting a small but statistically significant effect. Despite between-group differences in motivational intensity, the shape of the motivational profile remained stable across demographic groups and program types. Qualitative themes further supported these findings, highlighting motives related to personal meaning, long-standing aspirations, and employment stability among career changers.DiscussionThis study contributes to theoretical understandings of teacher motivation by providing findings that are consistent with the centrality of autonomous, intrinsic, and value-based motivations proposed by Self-Determination Theory, and by extending findings from the Factors Influencing Teaching Choice model to a culturally diverse Middle Eastern context. Practical implications include the need for selection of strategies emphasizing mission, personal fit, and opportunities for growth, as well as targeted support for minority students and career changers.
IntroductionInternship is a critical component of teacher education, yet existing research has focused primarily on competency development, with less attention to how student teachers develop capacities associated with self-determined professional learning. Drawing on heutagogy, this study examined mentor-perceived professional growth during internship and explored behaviours and dispositions consistent with agency, reflective feedback engagement, capability, and professional identity.MethodsA qualitative interpretive case study was conducted using the complete corpus of mentor evaluation reports for 30 final-year pre-service teachers enrolled in a Bachelor of Education (Early Childhood Education) programme at a university in the United Arab Emirates. The reports, originally generated through routine internship assessment, were subjected to secondary qualitative analysis using reflexive thematic analysis.ResultsFour interconnected themes emerged: Emerging Agency, Reflective Feedback Engagement, Capability Development, and Mentor-Perceived Indicators of Professional Identity. These themes informed the provisional Heutagogical Internship Development Model (HIDM), a non-linear interpretive framework connecting mentor-documented indicators of professional growth.DiscussionThe findings suggest that internship may provide opportunities extending beyond competency development toward professional initiative, engagement with feedback, adaptive practice, and professional participation. HIDM is presented as a provisional conceptual framework rather than a validated developmental sequence. Further research incorporating student-teacher voice, direct observation, longitudinal evidence, and additional institutional contexts is required to examine and refine the model.
BackgroundThe bridge-in, objective, preassessment, participatory learning, postassessment, summary (BOPPPS) instructional model and flipped classroom pedagogy are increasingly recognized as effective active learning strategies in medical education. However, their combined application in gastroenterology residency training has not been systematically evaluated. This study investigated the impact of the BOPPPS + flipped classroom model on clinical practice competency, clinical thinking, self-directed learning, and teaching satisfaction among gastroenterology residents.MethodsA randomized controlled design was employed. A total of 120 first-year undergraduate-degree residents who completed their gastroenterology rotation at the Third People's Hospital of Yunnan Province between January 2025 and December 2025 were enrolled and randomly assigned to an observation group (n = 60; BOPPPS + flipped classroom) or a control group (n = 60; traditional lecture-based teaching). The intervention lasted 12 weeks (one session per week, two class hours per session). Teaching effectiveness was assessed using standardized clinical practice simulations (admission interview/consultation, clinical reasoning case analysis, and procedural skills), the primary trait analysis (PTA) clinical thinking scale (eight domains), the Self-Directed Learning Readiness Scale (SDLRS), and a validated satisfaction questionnaire. Primary analyses employed analysis of covariance adjusting for corresponding baseline values, with effect sizes reported as adjusted Cohen's d. For multiple secondary comparisons, the Benjamini–Hochberg false discovery rate (FDR) correction was applied. Ordinal PTA scale data were additionally analyzed using non-parametric Mann–Whitney U-tests as sensitivity analyses.ResultsThe observation group achieved significantly higher scores than the control group across all clinical performance measures: admission interview [adjusted mean difference (aMD) = 3.02, 95% confidence interval (CI): 1.46–4.58, P < 0.001, adjusted d = 0.69], clinical reasoning (aMD = 6.85, 95% CI: 4.75–8.95, P < 0.001, adjusted d = 1.36), and clinical skills (aMD = 9.52, 95% CI: 7.22–11.82, P < 0.001, adjusted d = 2.18). PTA scores were significantly higher in the observation group for all eight clinical thinking dimensions (all P < 0.001 after FDR correction). SDLRS total scores were also markedly higher in the observation group (aMD = 13.82, 95% CI: 10.35–17.29, P < 0.001, adjusted d = 1.38). Satisfaction rates exceeded 86% across all domains in the observation group, compared with 34.3%–54.3% in the control group (all P < 0.05).ConclusionsThe BOPPPS + flipped classroom model significantly enhances clinical practice competency, clinical thinking, self-directed learning, and teaching satisfaction among gastroenterology residents compared with traditional instruction. However, the very large effect sizes observed should be interpreted with caution, as the intervention combined multiple instructional components (preclass preparation, supervised hands-on practice, and structured feedback) that were not isolated. Implementation decisions should consider local resources and the specific training contexts.
