This research work presents a bibliometric analysis of Large Language Model (LMM)-assisted pedagogy in higher education to study its global research trends and identify key themes, collaboration patterns, and research gaps. Lens (Lens.org) was used to retrieve the dataset by incorporating a logical and expanded structure from December 2015 to December 2025. A total of 17,089 relevant records were retrieved and analysed. VOSviewer was used for keyword co-occurrence, author collaboration, and journal-source network analyses. The results showed that LLM-assisted pedagogy research surged between 2020 and 2022. Journal articles were the main source of literature on LLM-assisted Pedagogy research. Computer science and artificial intelligence were the major disciplines in this field. Curriculum, education, digital learning, and assessment were the outcomes of the keyword co-occurrence analysis. It can be concluded that the findings may play a pivotal role in policy framing in LLM-assisted pedagogy development in higher education.
The COVID-19 pandemic has compelled educational institutions to adopt online instead of traditional classroom instruction as the new norm in education. The study aimed to develop a hybrid-flexible (HyFlex) classroom management framework from one state college in Camarines Sur. The study employed the sequential explanatory strategy under the mixed methods with 191 respondents obtained using Slovin's formula. Setting time allocation of activities of the class, sequencing and integrating additional activities, reinforcing good classroom behaviour, and sustaining an open communication channel, and giving high regard to right conduct and attitudes was mostly practiced and there is no significant difference between these practices. The HyFlex classroom management framework was developed as a springboard for other institutions to craft their own framework for new normal education. However, further validation of the framework is suggested. The developed framework may serve as a basis for the upskilling and retooling of faculty within and outside the institution.
This study investigates the effect of regional language Nagpuri instruction levels on academic achievement in 412 participants from primary grades of 10 government schools in the state of Jharkhand, India. Using quantitative methods, the research analyses academic achievement scores across three instructional levels (low, medium, high) and correlates them with language proficiency and socioeconomic status. Results from t-tests and ANOVA reveal significant differences in mean scores between instructional levels, with higher proficiency associated with higher academic achievement. A strong positive correlation (r = 0.62, p < 0.001) between academic achievement and language proficiency underscores the importance of language skills in educational outcomes. Regression analysis confirms language proficiency as a significant predictor (<(a)over bar> = 0.81, p < 0.001), even when controlling for socioeconomic factors (<(a)over bar> = 0.26, p = 0.001). Findings suggest that incorporating regional language instruction could potentially narrow achievement gaps and improve educational equity.
This empirical study examines accessibility and equity in online learning for Deaf and Hard of Hearing (DHH) students in Saudi Arabia, where digital education has rapidly expanded under Vision 2030. Despite advances in assistive technologies, many DHH learners continue to face systemic barriers related to captioning, sign-language interpretation, platform design, and instructor preparedness. Using a mixed-method design, data were collected from 52 DHH university students and 15 online-learning instructors across three Saudi public universities. Participants were selected using purposive sampling from disability support centers in Saudi Arabia. Quantitative data were analysed descriptively to measure accessibility frequency, perceived inclusion, and satisfaction, while qualitative interviews explored lived experiences and institutional support. Results revealed that although 68 percent of DHH participants accessed online classes weekly, only 41 percent reported reliable captioning, and 56 percent experienced communication delays with instructors. Qualitative findings indicated that institutional awareness and staff training strongly predicted students' sense of inclusion.
This study examined the career aspirations of agricultural students and identified key personal, psychological and informational factors influencing them. Data were collected from undergraduate, postgraduate and Ph.D. students from State Agricultural Universities in Gujarat using a structured interview schedule, and weighted mean scores and Structural Equation Modelling (SEM) were applied for analysis. Results indicated a strong preference for secure and prestigious careers, particularly government jobs such as administrative services, nationalised banks, and UPSC positions, while private and NGO employment was less preferred due to perceived instability. Respondents showed moderate entrepreneurial orientation, favouring agribusiness activities like organic farming, food processing, and dairy enterprises. High economic aspirations were evident, with most aiming for monthly incomes above INR 1,00,000. SEM analysis revealed significant interactions among age, innovativeness, information sources, and critical thinking, influencing overall career aspirations.
