DUTIES: Education and Humanities International Journal

Loneliness and Social Connection in Online Higher Education: A Mixed-Methods Study of University Students’ Experiences

2026-08-05T05:33:27+07:00

The rapid expansion of online higher education has transformed not only instructional practices but also students’ social and emotional learning experiences. This study explores university students’ experiences of loneliness and social connection in online higher education contexts through a convergent mixed-methods design grounded in Social Presence Theory. Quantitative and qualitative data were collected concurrently from university students who had experienced online learning for at least one academic semester. The quantitative phase involved an online survey administered to 102 students, while the qualitative phase consisted of semi-structured interviews with 12 purposively selected participants. Quantitative data were analyzed using descriptive statistics, whereas qualitative data were analyzed through thematic analysis. The findings revealed that students experienced moderately high levels of loneliness alongside moderate levels of social connection, peer interaction, instructor interaction, and sense of belonging in online learning environments. Qualitative findings further demonstrated that students frequently perceived online learning as emotionally distant and socially limited due to reduced interpersonal interaction, limited visibility, and minimal emotional engagement. However, meaningful social connection remained possible through collaborative activities, instructor responsiveness, and active participation. The integration of findings suggests that loneliness and social connection coexist dynamically within digitally mediated educational environments. The study highlights the importance of social presence, interpersonal responsiveness, and interaction quality in fostering emotionally supportive online higher education experiences.

University Students' Use of AI Chatbot Companions for Academic Help Seeking: Benefits and Challenges

2026-08-07T07:47:37+07:00

The increasing adoption of generative artificial intelligence (AI) has transformed the ways university students seek academic support, yet little is known about how AI chatbot companions are integrated into students' academic help-seeking behaviours. This qualitative study explored how university students use AI chatbot companions as part of their academic help-seeking processes and examined their perceptions of the benefits and challenges associated with their use. Guided by Karabenick and Dembo's (2011) academic help-seeking process model, the study employed a qualitative descriptive design. Data were collected through semi-structured interviews with university students who had experience using AI chatbot companions for academic purposes. The interview data were analysed using reflexive thematic analysis through a hybrid deductive-inductive approach. The findings revealed that students incorporated AI chatbot companions into a dynamic help-seeking process by recognizing learning difficulties, strategically selecting AI as an academic help source, engaging in iterative dialogue, and critically evaluating AI-generated assistance before applying it to their learning. Participants perceived AI chatbot companions as accessible, personalized, and psychologically safe learning partners that supported self-regulated learning. However, they also expressed concerns regarding the reliability of AI-generated information, the need for information verification, and the potential risk of overreliance. The study extends Karabenick and Dembo's academic help-seeking process model by positioning AI chatbot companions as an emerging academic help source within higher education. The findings further highlight the importance of fostering AI literacy, critical evaluation skills, and responsible AI use to maximize the educational value of AI chatbot companions.

Fostering Social Connectedness Through Discussion-Based Pedagogy: Evidence from University Virtual Learning Environments

2026-08-05T05:32:32+07:00

The increasing prevalence of virtual learning environments has highlighted the importance of fostering students’ social connectedness to support meaningful educational experiences. This study examined the relationship between discussion-based pedagogy and university students’ social connectedness in virtual learning environments and identified the pedagogical dimensions that contribute most significantly to this outcome. Employing a quantitative cross-sectional survey design, data were collected from 286 undergraduate students enrolled in virtual courses at a public university. A structured questionnaire measuring discussion-based pedagogy and social connectedness was administered, and the data were analyzed using descriptive statistics, simple linear regression, and multiple regression analyses. The findings revealed a significant positive association between discussion-based pedagogy and social connectedness, with discussion-based pedagogy explaining a substantial proportion of the variance in students’ social connectedness. Among the pedagogical dimensions examined, peer interaction emerged as the strongest predictor, followed by instructor facilitation, collaborative dialogue, and active participation. In contrast, knowledge sharing did not significantly predict social connectedness when the dimensions were analyzed simultaneously. The findings suggest that discussion-based learning enhances students’ social experiences by promoting meaningful interaction, collaboration, and engagement. The study highlights the importance of interaction-rich pedagogical practices in cultivating socially connected virtual learning communities.

Supporting Low-Proficiency Learners in EFL Classrooms: Strategies for Inclusive Teaching

2026-08-05T05:34:20+07:00

This study investigated the instructional strategies employed by EFL teachers to support low-proficiency learners in inclusive classroom settings and examined the extent to which these strategies influenced learners’ participation and language achievement. Employing a mixed-methods approach with an exploratory sequential design, the study combined qualitative and quantitative data to provide a comprehensive understanding of inclusive teaching practices. Qualitative data were collected through semi-structured interviews with six EFL teachers and focus group discussions with students, while quantitative data were obtained from structured questionnaires and classroom-based assessments. The qualitative findings revealed that teachers implemented various inclusive instructional strategies, including scaffolding, peer collaboration, simplified and contextualized instruction, and differentiated tasks to accommodate learners’ diverse needs. The quantitative findings demonstrated that these strategies positively influenced students’ classroom participation and language achievement, particularly in vocabulary mastery, grammar accuracy, reading comprehension, and writing performance. The study further highlighted that supportive and flexible instructional practices contributed to increased learner confidence and engagement in classroom activities. Overall, the findings emphasize the importance of inclusive pedagogy in creating equitable and participatory EFL learning environments. The study also offers pedagogical implications for teachers, curriculum developers, and educational institutions in supporting low-proficiency learners more effectively.

Who Am I as a Learner in the Age of Artificial Intelligence?: Exploring University Students' Identity Construction in AI-Mediated Learning

2026-07-15T18:28:58+07:00

The rapid integration of artificial intelligence (AI) into higher education has transformed how students access information, engage with learning tasks, and construct knowledge. While previous studies have primarily focused on the adoption, effectiveness, and ethical implications of AI-assisted learning, limited attention has been given to how AI influences students’ identities as learners. This study explores how university students construct their learner identities in the era of artificial intelligence. Employing a qualitative phenomenological design, the study involved six higher education students who regularly used generative AI technologies to support their academic learning. Data were collected through semi-structured interviews and a focus group discussion and analyzed using inductive thematic analysis. The findings revealed four interconnected themes: becoming an AI-enhanced learner, negotiating independence and dependence in learning, redefining competence and expertise, and envisioning future-ready learner identities. Participants perceived AI as a learning companion that enhanced their capabilities while simultaneously requiring them to negotiate issues of autonomy, responsibility, and authenticity. The findings further indicated that students increasingly defined competence in terms of critical evaluation and effective human-AI collaboration rather than information acquisition alone. Moreover, participants’ engagement with AI was strongly connected to their aspirations for future academic and professional participation. The study contributes to the growing literature on AI in higher education by highlighting the identity-related dimensions of AI-mediated learning and offering insights into what it means to be a learner in an increasingly AI-driven educational landscape.