This study examines the relationship between Generative AI (GenAI) usage and research self-efficacy (RSE) among Chinese doctoral students, a topic of growing importance as AI technologies become embedded in academic practices. Using a quantitative, cross-sectional survey design, data were collected via a survey from 587 doctoral students across STEM and humanities and social sciences (HSS) disciplines. Hierarchical multiple regression and moderation analyses (PROCESS macro) were employed to examine predictive relationships and interaction effects. Results revealed that both the frequency and purpose of GenAI use significantly predicted RSE, with an augmentative approach - using AI as a critical thinking scaffold - emerging as the strongest positive predictor. Furthermore, perceived supervisor support and academic discipline moderated this relationship, with supportive supervision amplifying the benefits of augmentative use, and STEM students demonstrating a stronger link between frequency of use and RSE than their HSS counterparts. The findings underscore the importance of fostering critical AI literacy and providing supervisory guidance to maximize the psychological and scholarly benefits of GenAI integration. This study contributes to doctoral education research by empirically demonstrating how augmentative GenAI usage serves as a psychological scaffold that enhances research self-efficacy, and by identifying supervisor support and disciplinary context as key moderating factors in this relationship.
Financial insecurity is a significant challenge for university students, affecting both wellbeing and study participation. Guided by a socio-ecological perspective, this study examines financial insecurity among university students as a multi-level issue shaped by individual, institutional, and broader structural conditions. A cross-sectional survey examined the prevalence of financial insecurity among Australian university students and its associations with demographic characteristics, health, academic outcomes, and awareness of support services. An online survey was distributed via universities and national student networks (September-October 2024). Financial status was self-reported as adequate ('comfortable'/'just getting by') or inadequate ('struggling'/'severely struggling'). Descriptive statistics, logistic regression, and content analysis were used to analyse quantitative and qualitative data. Of 838 respondents (61% female, 64% domestic), 32% reported inadequate financial status. Independent predictors included international student status, Indigenous identity, disability, and living alone. Financial insecurity was associated with higher odds of perceived poor academic outcomes (OR = 5.5, 95%CI: 3.9-7.6), poor-fair self-rated health (OR = 3.0, 95%CI: 2.4-4.1), and food insecurity (OR = 8.4, 95%CI: 5.7-12.4). Awareness of financial support services was low, with dissatisfaction more common among financially insecure students (OR = 2.1, 95%CI: 1.9-4.1). Findings inform a series of recommendations for universities and policymakers to strengthen student support and address systemic drivers of financial insecurity.
Academic integration plays a critical role in promoting students' academic success. However, few studies have examined how different factors jointly influence the academic integration of academic master's (AM) students, resulting in insufficient support networks for their academic development. Drawing on Tinto's student integration theory and using Chinese AM students as the sample, this study explored how institutional research support (IRS), supervisor academic guidance (SAG), peer academic support (PAS), and cross-institutional graduate enrollment shaped students' academic integration. Using structural equation modeling, the study found that IRS, SAG, and PAS directly influenced academic integration. Specifically, IRS had a significant effect on the cognitive and affective dimensions but not on the behavioral dimension, whereas SAG and PAS significantly influenced all dimensions. Moreover, SAG and PAS fully mediated the relationship between IRS and academic integration, with PAS emerging as the stronger mediator. In the model where SAG served as a mediator, its effects on cognition and behavior were weaker among cross-institutional students. In contrast, in the model where PAS functioned as a mediator, its effect on behavior was stronger among cross-institutional students. These findings are critical for developing AM student-centered support networks and enhancing overall training quality.
Doctoral education in Sub-Saharan Africa has expanded rapidly, yet evidence on post-PhD career trajectories remains limited. This study examines employment outcomes, career pathways, and structural constraints shaping doctoral graduates' experiences in Kenya, Ethiopia, and Rwanda. Using a mixed-methods design, the study integrates survey data (n = 154), key informant interviews (n = 27), and multi-stakeholder policy dialogues under the Regional Scholarship and Innovation Fund. Guided by identity-trajectory theory and academic precarity, the analysis explores how individual aspirations intersect with institutional conditions and broader structural dynamics. Findings show that while career advancement and research engagement motivate doctoral training, graduates navigate fragmented and uncertain career pathways. Academic employment is often characterized by low remuneration, limited research funding, and weak institutional support, prompting engagement in consultancy and externally funded projects. Policy dialogues highlight systemic gaps, including weak research ecosystems, limited industry linkages, and the absence of structured postdoctoral pathways. Alignment between doctoral training and employment is stronger in Kenya and Rwanda than in Ethiopia. The study demonstrates that doctoral career trajectories are shaped by interactions across micro, meso, and macro levels, providing comparative evidence and policy-relevant insights for strengthening doctoral training, research systems, and sustainable academic careers in Sub-Saharan Africa.
Completing a master's degree on time measures higher education efficiency and drives national development. However, on-time completion rates in Sub-Saharan Africa remain critically low. In Tanzanian public universities, for example, fewer than 30% of students finish within the expected 18 to 24 months, delaying workforce entry and exacerbating skill shortages. While institutional barriers are well-documented, the recursive, relational dynamics between students and supervisors remain comparatively under-theorised. This study investigated these relational barriers and developed a model explaining how they interact recursively to produce sustained delays. Using a qualitative design, we conducted semi-structured interviews with 48 participants (students, supervisors, administrators). Thematic analysis, informed by sensitising concepts from Tinto's and Bean's models, exposed their limitations in explaining interactional delays. Findings revealed interdependent student-related (inadequate research skills and emotional burnout) and supervisor-related barriers (inconsistent feedback and limited accessibility). These recursively reinforced disengagement through behavioural feedback loops (fear -> avoidance -> neglect -> stagnation), forming the basis of the Dyadic Interaction Model for Timely Postgraduate Completion (TIM-PGC). The model reconceptualises timely completion as a relationally co-created outcome, shaped by feedback loops within a specific institutional context. It advances theory by integrating structural and relational perspectives and proposes context-sensitive interventions for resource-limited higher education systems worldwide.
