The growing interest in student entrepreneurship, research has yet to comprehensively examine both internal and external determinants of startup intentions among private university undergraduates in Thailand, a context shaped by rapid digital transformation and national innovation priorities. This study investigates the factors predicting entrepreneurial intentions among 400 undergraduate students at private universities in Pathum Thani, Thailand. Using a quantitative research design, data were collected via a validated structured questionnaire and analyzed through descriptive statistics and stepwise multiple regression. Five factors significantly predicted startup entrepreneurial intention: financial resources, entrepreneurial skills, prior experience, economic conditions, and technological factors, collectively explaining 60.3% of the variance. Financial resources and entrepreneurial skills emerged as the strongest predictors, while political-legal, socio-cultural, and environmental factors were not significant predictors. The study concludes that entrepreneurial intention is shaped by the interplay between individual competencies and contextual enablers. These findings call for universities to strengthen entrepreneurship education across all faculties and for policymakers to improve students' access to financial resources and startup support mechanisms.
Equity concerns are central to large-scale shifts toward computer-based testing (CBT), yet evidence from developing systems remains limited on whether institutional supports can offset household digital inequalities. This study surveyed 1,197 Vietnamese high school students (grades 10–12) using a 20-item CBT acceptance scale (α=.94) and two single-item fairness indicators. Overall acceptance was moderately positive (M=3.54, SD=0.74), whereas fairness perceptions were markedly weaker: only 31.7%–38.2% agreed that CBT ensures fair scoring and 55.1%–66.7% worried that CBT could create inequality, reflecting unequal fairness perceptions across areas, with concerns strongest in rural settings. Group comparisons showed small but consistent advantages in acceptance for students with prior CBT experience and school-level computer access (g≈.16–.20), while home computer ownership had negligible association (g≈.01). Acceptance did not differ by residential area (η²≈.001), but fairness concerns varied across areas. These findings suggest that institutional exposure and governance practices—rather than household device ownership—are the most actionable levers for equitable CBT implementation. Practical implications include strengthening school-based access and practice opportunities, transparent proctoring and contingency procedures, and integrating fairness monitoring into CBT dashboards.
The rapid integration of artificial intelligence (AI) in higher education has raised questions about how technological competencies influence student outcomes, particularly in foreign language learning where anxiety significantly affects performance. This study investigated whether foreign language anxiety (FLA) mediates the relationship between AI literacy (AIL) and academic engagement (AE) among 1,052 English as a foreign language (EFL) learners enrolled in foreign language programs at Al-Azhar University, Egypt. Participants completed three validated instruments: the artificial intelligence literacy scale (AILS), the short-form foreign language classroom anxiety scale (S-FLCAS), and the academic engagement scale (AES). Mediation analysis was conducted using PROCESS Model 4 with 5,000 bootstrap iterations to generate bias-corrected confidence intervals (CI). Correlation analyses revealed that AIL positively correlated with AE (r=.31, p<.001) and negatively with FLA (r=-.35, p<.001), while anxiety demonstrated a significant negative correlation with engagement (r=-.21, p<.001). Mediation analysis confirmed that FLA partially mediated the AIL –engagement relationship, with the indirect effect accounting for 12.2% of the total effect and the direct effect comprising the remaining 87.8%. These findings indicate that AIL enhances AE both directly and indirectly through anxiety reduction, suggesting that institutions should develop comprehensive AIL programs that address both technical skills and the affective dimensions of technology integration in language learning contexts.
This bibliometric analysis, drawing on data from the Web of Science (WoS) core collection, explores the expanding role of immersive technologies in English language education. Virtual reality (VR) and augmented reality (AR) have shown strong potential to improve learner motivation, engagement, and communicative competence, yet their integration into formal English language settings remains uneven. By analyzing 248 peer-reviewed articles published between 2021 and 2025, this study finds significant trends, influential contributors, and emerging areas of interest within the field. The findings show a steady increase in publications and citations, reflecting growing recognition of the educational value of immersive environments. Prominent themes include emotional engagement, lowered language anxiety, and improved performance in vocabulary, speaking, listening, and cultural understanding. Much of the literature underlines authentic and situated learning, VR-based interactive environments, VR-supported problem-based learning, and AR-assisted vocabulary development. The analysis also identifies leading countries, with China and the United States producing the largest share of research, a pattern supported by strong institutional participation worldwide. These insights help guide educators and policymakers as they consider how to bring immersive technologies into English instruction. The study also establishes a foundation for future research on effective, engaging, and sustainable immersive language learning practices. Overall, these findings clarify how research on immersive technologies in English language education has evolved between 2021 and 2025 and identify influential studies and key contributors. They also point to persisting gaps, such as equity, teacher readiness, and cognitive-load–informed design, that warrant further investigation.
Intergenerational learning (IGL) has gained increasing attention as a strategy to address the limited effectiveness of elderly education, particularly in the context of digital literacy and lifelong learning. Despite growing research, the field remains fragmented, with limited synthesis translating evidence into actionable educational strategies. This study aims to systematically examine how IGL enhances elderly learning ability and to identify strategic directions for its implementation. A bibliometric-driven analytical approach was employed using Scopus-indexed publications from 2021 to 2025. The top ten most-cited articles were identified through performance analysis and subsequently analyzed using a strengths, weaknesses, opportunities, and threats (SWOT) framework. The findings reveal that IGL significantly improves digital literacy, cognitive engagement, and social well-being among elderly learners. However, challenges such as internalized ageism, low learning confidence, and the absence of structured and scalable frameworks remain critical barriers. The study also highlights opportunities for integrating IGL into formal education and community-based programs, while identifying threats related to technological change and policy limitations. This study contributes a bibliometric-informed strategic synthesis that advances understanding of IGL and provides actionable insights for educators, program designers, and policymakers in elderly education.
Cyberbullying has emerged as a critical issue among university students in Malaysia, driven by the widespread use of digital technologies and associated with serious psychological consequences. Despite its increasing prevalence, limited research has explored how psychosocial factors shape cyberbullying victimization within the Malaysian higher education context. This study addresses this gap by exploring the psychosocial factors influencing cyberbullying victimization among university students in Malaysia. A qualitative case study approach was employed, involving five university students who had experienced cyberbullying. Data was collected through semi-structured, in-depth interviews and analyzed using thematic analysis. The findings suggest that cyberbullying victimization is influenced by an interplay of psychological and social factors. Psychological factors include passive behavior, low self-esteem, irrational beliefs and personality traits, while social factors encompass peer relationships, parenting styles, social media engagement, and online gaming environments. This study suggests that cyberbullying is a multifaceted phenomenon shaped by both individual vulnerabilities and environmental influences. These findings highlight the need for comprehensive, psychosocial-based interventions to support students’ wellbeing and promote safer digital environments in higher education institutions.
Scientific concepts such as gravity continue to pose challenges for students in rural and under-resourced classrooms, where reliance on a single language of instruction often restricts access to meaning and limits conceptual understanding. This study investigated the impact of a blended English and Urhobo (BEAU) instructional approach on junior secondary one students’ learning and retention of gravity concepts in rural Nigeria. A quasi-experimental pre-test–post-test non-equivalent control group design was employed with 243 students assigned to English-only, Urhobo-only, or BEAU instructional conditions. A validated 30-item multiple-choice gravity test was administered, and analysis of covariance (ANCOVA) was used to examine differences while controlling for pre-test scores. The findings show that students taught using the BEAU language approach achieved better significantly in both post-test and retention tests compared to those taught using English-only or Urhobo-only instructional approaches. The findings provide empirical evidence that the blended language instructional approach enhances science learning outcomes in rural Nigerian contexts. Linguistically responsive instructional approach improves conceptual understanding and supports long-term retention of abstract scientific ideas, underscoring the importance of leveraging students’ linguistic resources to strengthen science education in rural and under-resourced classrooms.
Artificial intelligence (AI) has advanced in the post-pandemic era and is unavoidable in teaching and learning. Teachers’ perceptions, as the primary gatekeepers, are essential for ensuring quality education and inclusive classrooms, with AI as a collaborator. While some teachers resist these technological shifts, others are actively adapting an AI-assisted teaching approach. We conducted this study to understand the reasons for teachers’ resistance (challenges and difficulties) and how they perceive the use of AI in the teaching, learning, and assessment process, because the first step in effective incorporation is having a favorable attitude towards it. Hence, this study explored the perceptions of 15 secondary private school teachers, selected through purposive sampling, regarding the incorporation of AI into teaching, learning, and assessment processes, as well as the challenges they faced. The researchers developed an in-depth interview schedule and conducted interviews to understand participants’ perceptions and challenges. The data is analyzed following the thematic analysis steps by Braun and Clarke. Thematic analysis revealed that teachers demonstrated a positive understanding towards the pedagogical relevance of AI, rather than merely having a favorable perception. Furthermore, teachers predominantly viewed AI as an additional tool to enhance the effectiveness of knowledge transactions and instructional design. The challenges include infrastructure accessibility and professional training; time management for preparation, skill updating, and fulfilling varied teaching and other responsibilities; the inability to verify the accuracy of information; and parental mindset. This study offers insights for developing AI-aided teacher training and relevant curricula for schools.
Early-career researchers often have a sound idea yet struggle to turn it into a publishable manuscript that reviewers can trace and evaluate. This paper synthesizes practical guidance on structuring and drafting research articles using the introduction-methods-results-and-discussion (IMRaD) convention, while addressing emerging concerns about the responsible use of generative artificial intelligence (AI) in academic writing. A documentary narrative synthesis was conducted using 36 high-authority sources, including writing guides, guidance from journal editors, publisher and ethics policies, and recent empirical studies on AI-assisted writing. Recommendations were coded using an explicit IMRaD-aligned codebook and then consolidated into a step-by-step workflow from question formulation to submission checks. The synthesis indicates that treating IMRaD as a traceability checklist improves alignment between research questions, methods, results, and claims, and that iterative revision is more effective than one-pass drafting. AI support is most defensible when limited to language and process assistance, combined with disclosure, reference verification, and full human accountability for all content. The paper concludes with an actionable checklist and a visual ‘traceability map’ that can be adapted for research training and supervision.
The present study aims to investigate the impact of integrating artificial intelligence (AI) technologies into teaching Russian as a foreign language (RFL) from the perspective of educators. Employing a mixed-methods research design, the study utilized several methodologies, including a teacher survey, an analytical-descriptive approach to data interpretation, and the development and evaluation of AI-based interventions. The study sample comprised 120 RFL instructors from three public universities in Kazakhstan. Preliminary findings revealed a considerable awareness among teachers regarding various AI technologies, such as chatbots, voice assistants, the ChatGPT neural network, educational platforms, gaming applications, and task design tools. Nonetheless, the practical utilization of these technologies varied significantly, with only a subset of teachers incorporating them into their regular teaching practices. The study culminated in the development of a conceptual framework for AI-driven educational interventions, incorporating platforms such as Coursera, Moodle, Open EdX, and eFront; game-based applications including Duolingo, Talk2Russia, and Russian Verbs Pro; and task creation tools such as Kahoot! and Quizlet. Following the integration of these interventions into the curriculum, post-implementation evaluations indicated that teachers generally perceived the tools as effective, with the average effectiveness rating surpassing 4.0 out of 5.0 across all assessed categories. The findings of this study have practical applicability; they can be used to enhance professional development programs for teachers of the Russian language and to formulate strategies for the integration of AI technologies into language education within the Central Asian region.
This study investigates the integration of Kahoot!, an online gamified platform, in an English for specific purposes (ESP) course at a Vietnamese state-run university. The study examines Kahoot!-use frequency and students perception of its effectiveness in supporting classroom and autonomous learning. Using an explanatory mixed-methods design, the study draws on survey data from 87 technical students and focus groups with 10 volunteers. Findings indicate that while Kahoot! was frequently used in class, its use outside classrooms was limited by insufficient teacher support. Although gamified tasks were perceived as engaging and useful, misalignments between instructional practices and learners’ expectations, including over-emphasis on vocabulary and grammar, inappropriate pacing, insufficient feedback, and overly challenging tasks, reduced its effectiveness and motivational impact. The study highlights the need to align gamified pedagogy with ESP learners’ needs, use platform analytics for pedagogical adaptation, and use Kahoot! beyond classrooms to enhance learners’ engagement and autonomy.
In Kazakhstan, social support for families with hearing-impaired children remains a pressing issue requiring further research and improvement. The aim of this study is to assess the social support provided to families of hearing parents with children who have hearing impairments in Kazakhstan. The study involved 176 families from Kazakhstan, in which the parents are hearing, and the children have hearing loss. This study employed a convergent mixed-methods approach, combining the simultaneous collection and analysis of qualitative (interviews) and quantitative (surveys) data with the subsequent integration of the findings to gain a more comprehensive understanding of the situation. The results showed that 89% of respondents were aware of existing social assistance programs; financial and medical support were considered particularly important, while psychological support was deemed insufficient. Socioeconomic and geographic factors significantly influenced access to services. The data also showed that income level and type of settlement significantly influence families’ access to social services and awareness of support programs, while the age of parents and children has less influence, although the needs of children of different ages vary. The practical significance of the study lies in identifying problems within the social assistance system, such as low information accessibility, long waiting times, inadequate support, and service quality fluctuations. The obtained data can be used to improve social support mechanisms and raise awareness among families with children who have hearing impairments. These findings can be used to improve social support mechanisms and raise awareness of this issue among families with hearing-impaired children.
Scientific argumentation is a core practice in science education, yet many students struggle to construct arguments that effectively integrate claims, evidence, and reasoning. With the growing use of artificial intelligence (AI) in education, AI-supported feedback has emerged as a potential tool to scaffold students’ argumentation processes. This study examined the effects of AI-supported feedback on students’ scientific argumentation using a quasi-experimental, explanatory sequential mixed-methods design. Two intact groups participated: an experimental group receiving AI-supported formative feedback on written arguments and a control group receiving conventional teacher feedback. Quantitative data were collected using a validated rubric based on the claim–evidence–reasoning (CER) framework and Toulmin’s argument pattern (TAP), while qualitative data from student interviews and written responses provided contextual insights. Results showed that the experimental group achieved greater improvements in overall argumentation quality, particularly in evidence use and reasoning. Qualitative findings further indicated that AI feedback supported iterative revision and strengthened students’ understanding of evidence–claim relationships.
Emotional resilience (ER) is a critical competence for pre-service teachers, enabling them to manage stress, adapt to change, and maintain professional functioning. Digital learning (DL) environments present both challenges and opportunities for developing ER, yet empirical studies on structured interventions in these contexts remain limited, particularly in early childhood education (ECE). This study examined the effect of a structured DL intervention on the development of ER among pre-service teachers in ECE contexts in Kazakhstan. A quasi-experimental pretest-posttest design with non-equivalent groups was employed, involving 165 female pre-service teachers. The intervention included scaffolded digital tasks, reflective exercises, and instructor-led feedback. Baseline ER scores were comparable between groups. Following the intervention, participants in the experimental group (EG) demonstrated significantly higher ER compared to those in the control group (CG). These results indicate that structured DL interventions can effectively enhance ER by fostering adaptive coping, self-regulation, and problem-solving skills. Embedding scaffolded digital tasks combined with reflection and feedback into teacher education programs may support the preparation of resilient, reflective, and emotionally competent educators.
This study investigates parental perceptions of school climate, teachers’ accountability, and students’ academic performance, as well as the relationship among these three factors. The descriptive research uses the demographic background of parents as a stratified sampling method to collect primary data. The statistical procedure shows that Pearson’s product-moment correlations between school climate and teachers’ accountability affect the academic achievement, with effect sizes of r=0.632, r=.646, which significantly correlate with each other. Regression analysis reveals the variability of the effect sizes of school climate and teachers’ accountability on academic achievement, with the values of β=0.070 and β=0.115. The independent variable, school climate and teachers’ accountability, explains 45.4% of the variability of academic performance of the students in early childhood care and education. The present study recommends that training teachers would link their accountability and measures to track the supportive climate of school to improve the student’s academic performance. Future research should conduct longitudinal studies to examine how relationships between school climates and teachers’ accountability affect different student populations and their academic performance.
Teacher evaluation shapes the quality of classroom instruction and, through it, student learning outcomes; yet in Indian higher education the dominant single-source model, student feedback channeled through the internal quality assurance cell (IQAC), is widely critiqued as ritualistic and developmentally inert. To the authors’ knowledge, no prior study has integrated student feedback, structured self-evaluation, and peer review into a coherent operational framework for regional Global South contexts. Drawing on primary data collected between 2009 and 2025 from approximately 200 undergraduate arts and science students, principally at North Lakhimpur College (now North Lakhimpur University) and other institutions across Assam, this study employs a qualitative-descriptive design with thematic analysis and triangulation of open-ended questionnaires and semi-structured interviews. Two contributions emerge. First, it yields a culturally grounded fivefold taxonomy of good teaching from Assamese student articulations, including culturally distinctive expectations: the teacher’s public moral role in the community and the obligation of intellectual life beyond the syllabus, that standardized student evaluation of teaching (SET) instruments routinely miss. Second, it proposes a developmental three-pillar framework integrating reformed student feedback, disciplined teacher self-evaluation, and structured peer review to restore the formative function of evaluation and improve student learning outcomes. Both the taxonomy and the framework are scalable across comparable institutions in the Global South.
This study examined the leadership characteristics associated with emergent leaders and explored how these characteristics are perceived by administrators and faculty members within an academic context. Guided by a convergent parallel mixed-methods approach, data were gathered from 189 respondents drawn from nine satellite campuses of a state university, comprising 54 administrators and 135 faculty members. Quantitative data were collected using a structured survey questionnaire measuring percipience across leadership domains, while qualitative data were obtained through written narrative reflections. Descriptive statistics and independent samples t-tests were employed to determine levels of percipience and significant differences between groups, and thematic analysis was used to analyze qualitative narratives. The study aimed to describe leadership traits expressed through participants’ accounts, determine the level of percipience across key leadership domains, compare perceptions between administrators and faculty members, and identify significant differences in their assessments. Findings revealed that emergent leadership is recognized through consistent ethical conduct, effective communication, relational engagement, and adaptive decision-making rather than formal position alone. Although both groups shared similar views on core leadership attributes, variations emerged in the emphasis placed on delegation, adaptability, and change-oriented behaviors, reflecting differences in professional roles and responsibilities. Integrating quantitative and qualitative findings, the study developed the LEADWISE integrated leadership framework, which explains leadership emergence as a dynamic and relational process shaped by leader-ship traits, wisdom, integrity, social engagement, and ethical awareness. The study contributes to leadership research by offering an empirically grounded framework that supports leadership identification and development in complex organizational settings, particularly within higher education institutions.
In the field of education, assessment and evaluation (AE) are defining strategies for improving school practices with the overall goal of enhancing student outcomes. While AE is understood and considered by educators as two distinctly different domains, they are often used interchangeably among practitioners in the field. The aim of this paper is three-fold: to identify and clarify the epistemological and ontological differences between AE; develop operational definitions of AE that are transferable from research to classroom through a comprehensive literature review; clarify any misconceptions between the two domains, if any. A comprehensive meta-synthesis of literature from articles published in 32 journals between 2014 and 2024 revealed four frames to distinguish assessment from evaluation: i) information gathered; ii) methodology; iii) purposes and outcomes; and iv) stakeholders. To corroborate these conclusions, we also conducted a social lab which is based on the principle of the Delphi method with 11 participants. Additionally, insights from two social lab sessions revealed that apart from the ontological distinctions between AE, there were also epistemological distinctions. Eventually, three frames for exploring the difference between AE emerged from the data: ontology, epistemology, and stakeholders. By refining and developing this area of AE, the research hopes to contribute to a more informed and integrated educational landscape, encouraging further work in areas of AE.
This study investigated the effects of artificial intelligence (AI)-assisted speaking instruction using a generative AI (GenAI) chatbot on Chinese vocational college English as a foreign language (EFL) learners’ oral accuracy and fluency. A quasi-experimental pretest-posttest control group design was adopted with 80 students. The experimental group engaged in AI-mediated speaking activities, while the control group received conventional instruction. Oral performance was assessed using analytic rubrics adapted from international English language testing system (IELTS) criteria. Results showed significant improvement in oral fluency for the experimental group, while gains in accuracy were not statistically significant. These findings suggest that GenAI chatbots provide interaction-rich environments that enhance fluency development but require complementary form-focused support to improve accuracy. Implications are discussed for integrating AI tools into vocational EFL speaking instruction.
Mental health issues of students are among the primordial concerns of educational institutions in the post-pandemic era. Thus, resilience as an innate trait has been in frequent discussions for its positive impact on well-being. This study aimed to analyze whether social support and social connectedness were predictors of resilience among undergraduate students. Utilizing a predictive non-experimental research design, data were gathered from 402 randomly selected students from a higher education institution in eastern Philippines through standardized scales. Statistical analyses employed descriptive and inferential statistics. Results revealed that students had high levels of social support, social connectedness, and resilience and that the three variables are significantly correlated. Moreover, results of regression analysis showed that both variables significantly predicted resilience, with social support exerting a stronger influence. In conclusion, the positive influence of social support and social connectedness on students’ resilience highlights the importance of fostering supportive networks in higher education settings.
