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Over recent decades, the Doctor of Philosophy (PhD) has traditionally served as the pinnacle of scholarly achievement, primarily preparing individuals for academic and research careers. However, shifting academic landscapes, increased competition, and changing industry demands are transforming the PhD's role from a terminal research degree into a foundational step toward academia. The objective of the article is to explore the emerging trends, underlying factors, and implications of the PhD becoming a prerequisite and stepping stone for entering academic professions. Through analysis of global patterns, institutional policies, and career trajectories, the article argue that the PhD is increasingly viewed as an essential credential for those aiming to establish a foothold in academia, shaping the future of doctoral training and academia’s workforce. This article found that PhD qualification does not always confirm the expertise of PhD holders but mostly display the research capabilities. The study also found that there are contradicting views from different scholars on the value of the PhD.

The increasing use of artificial intelligence (AI) tools in higher education has reshaped how students engage with academic research, particularly at Honours level, where students transition from structured undergraduate learning to independent postgraduate research. Guided by Self‑Regulated Learning (SRL) theory, this study examines how reliance on AI by Honours research students influences the supervisor-supervisee relationship, the quality of research produced, and the extent of knowledge gained through the research process. SRL theory emphasises learners’ ability to plan, monitor, and reflect on their own learning, which is central to successful postgraduate research development. This study adopts a conceptual and literature‑based review methodology, drawing on peer‑reviewed studies on AI use in higher education, literature on postgraduate supervision, and academic integrity and research skills development frameworks, with specific attention to Honours‑level contexts. The documents were analysed using thematic content analysis, focusing on self‑regulatory behaviours, supervisory interaction, research skill development, and learning depth. The findings suggest that limited and transparent use of AI can support honours students by reducing surface‑level cognitive load and assisting with language clarity. However, excessive reliance on AI may undermine key self‑regulation processes, weaken critical thinking, and reduce meaningful engagement with supervisors. Supervisors may struggle to accurately assess students’ understanding, potentially straining trust and feedback processes. The review further indicates that over‑reliance on AI risks producing research that is technically adequate but conceptually shallow, with reduced long‑term knowledge acquisition. The study concludes that clear supervision practices and explicit guidance on responsible AI use are necessary to ensure that AI supports, rather than replaces, the self‑regulated learning essential for high‑quality Honours‑level research.

Black postgraduate (PG) students in South African universities and universities of technology experience significant supervisory conflicts, including contradictory guidance, neglect, and favoritism, which delay graduation and intensify inequities rooted in post-apartheid higher education (HE) dynamics. Prevailing research overlooks these students’ lived experiences, creating a gap in understanding systemic barriers to equitable supervision. This qualitative study employed narrative inquiry with six purposively sampled black PG students (four females, two males) from PhD, MTech, and MSc programs across South African universities. Semi-structured interviews explored supervisory conflicts, institutional responses, and academic impacts. Thematic analysis framework, yielding six themes validated through member checking. Key findings revealed conflicting supervisory directions causing years-long stagnation; prolonged neglect and feedback delays demotivating students; irrelevant objectives imposed by additional supervisors leading to academic penalties; inexperienced supervisors contributing to dropouts; power imbalances and ethical breaches such as gift-giving favoring certain students; and inadequate institutional resolutions forcing adversarial advocacy. Supervisory conflicts undermine black students' progress and well-being, demanding decolonial reforms for inclusive practices. Recommendations include mandatory supervisory contracts, accreditation, ombud services, and bias training to enhance throughput and equity. Future research should pursue longitudinal, comparative designs and intervention trials.

The article seeks to explore the factors which restrict doctoral graduate throughput rates at a selected University of Technology faculty located in the Western Cape, South Africa. In a developing economy like South Africa higher education qualifications are important as it is universally accepted that doctoral studies, in particular advance knowledge and innovation is important in any society. Furthermore, doctoral graduates play a significant role in the knowledge economy, promote innovation organisations, boost credibility of organisations and connect ideas between academia and industry. A positive nexus exists between a country’s Gross Domestic Product (GDP) and the number of doctoral candidates produced. To achieve the aim of this article a qualitative interpretive design was adopted to identify the factors which restrict throughput rates and the extent or significance thereof. The locus for this study was a selected faculty in a University of Technology (UoT) located in the Western Cape, South Africa with the target research population delineated as employees who hold a master’s degree within the same faculty. Using qualitative interpretive design and thematic analysis of survey responses from 40 master’s-qualified employees, the study identifies key barriers and proposes targeted interventions. The forty participants were purposively selected to participate in the questionnaire survey. The paper will propose interventions to facilitate the improvement of the doctoral throughput rate premised on the analysis of the results arising from the questionnaire survey. The paper proposes targeted and contextualized interventions to address the systemic challenges restricting doctoral enrolment and completion by the faculty employees.

The increasing use of artificial intelligence (AI) tools in higher education has reshaped how students engage with academic research, particularly at Honours level, where students transition from structured undergraduate learning to independent postgraduate research. Guided by Self‑Regulated Learning (SRL) theory, this study examines how reliance on AI by Honours research students influences the supervisor-supervisee relationship, the quality of research produced, and the extent of knowledge gained through the research process. SRL theory emphasises learners’ ability to plan, monitor, and reflect on their own learning, which is central to successful postgraduate research development. This study adopts a conceptual and literature‑based review methodology, drawing on peer‑reviewed studies on AI use in higher education, literature on postgraduate supervision, and academic integrity and research skills development frameworks, with specific attention to Honours‑level contexts. The documents were analysed using thematic content analysis, focusing on self‑regulatory behaviours, supervisory interaction, research skill development, and learning depth. The findings suggest that limited and transparent use of AI can support honours students by reducing surface‑level cognitive load and assisting with language clarity. However, excessive reliance on AI may undermine key self‑regulation processes, weaken critical thinking, and reduce meaningful engagement with supervisors. Supervisors may struggle to accurately assess students’ understanding, potentially straining trust and feedback processes. The review further indicates that over‑reliance on AI risks producing research that is technically adequate but conceptually shallow, with reduced long‑term knowledge acquisition. The study concludes that clear supervision practices and explicit guidance on responsible AI use are necessary to ensure that AI supports, rather than replaces, the self‑regulated learning essential for high‑quality Honours‑level research.

Black postgraduate (PG) students in South African universities and universities of technology experience significant supervisory conflicts, including contradictory guidance, neglect, and favoritism, which delay graduation and intensify inequities rooted in post-apartheid higher education (HE) dynamics. Prevailing research overlooks these students’ lived experiences, creating a gap in understanding systemic barriers to equitable supervision. This qualitative study employed narrative inquiry with six purposively sampled black PG students (four females, two males) from PhD, MTech, and MSc programs across South African universities. Semi-structured interviews explored supervisory conflicts, institutional responses, and academic impacts. Thematic analysis framework, yielding six themes validated through member checking. Key findings revealed conflicting supervisory directions causing years-long stagnation; prolonged neglect and feedback delays demotivating students; irrelevant objectives imposed by additional supervisors leading to academic penalties; inexperienced supervisors contributing to dropouts; power imbalances and ethical breaches such as gift-giving favoring certain students; and inadequate institutional resolutions forcing adversarial advocacy. Supervisory conflicts undermine black students' progress and well-being, demanding decolonial reforms for inclusive practices. Recommendations include mandatory supervisory contracts, accreditation, ombud services, and bias training to enhance throughput and equity. Future research should pursue longitudinal, comparative designs and intervention trials.

Over recent decades, the Doctor of Philosophy (PhD) has traditionally served as the pinnacle of scholarly achievement, primarily preparing individuals for academic and research careers. However, shifting academic landscapes, increased competition, and changing industry demands are transforming the PhD's role from a terminal research degree into a foundational step toward academia. The objective of the article is to explore the emerging trends, underlying factors, and implications of the PhD becoming a prerequisite and stepping stone for entering academic professions. Through analysis of global patterns, institutional policies, and career trajectories, the article argue that the PhD is increasingly viewed as an essential credential for those aiming to establish a foothold in academia, shaping the future of doctoral training and academia’s workforce. This article found that PhD qualification does not always confirm the expertise of PhD holders but mostly display the research capabilities. The study also found that there are contradicting views from different scholars on the value of the PhD.

The article seeks to explore the factors which restrict doctoral graduate throughput rates at a selected University of Technology faculty located in the Western Cape, South Africa. In a developing economy like South Africa higher education qualifications are important as it is universally accepted that doctoral studies, in particular advance knowledge and innovation is important in any society. Furthermore, doctoral graduates play a significant role in the knowledge economy, promote innovation organisations, boost credibility of organisations and connect ideas between academia and industry. A positive nexus exists between a country’s Gross Domestic Product (GDP) and the number of doctoral candidates produced. To achieve the aim of this article a qualitative interpretive design was adopted to identify the factors which restrict throughput rates and the extent or significance thereof. The locus for this study was a selected faculty in a University of Technology (UoT) located in the Western Cape, South Africa with the target research population delineated as employees who hold a master’s degree within the same faculty. Using qualitative interpretive design and thematic analysis of survey responses from 40 master’s-qualified employees, the study identifies key barriers and proposes targeted interventions. The forty participants were purposively selected to participate in the questionnaire survey. The paper will propose interventions to facilitate the improvement of the doctoral throughput rate premised on the analysis of the results arising from the questionnaire survey. The paper proposes targeted and contextualized interventions to address the systemic challenges restricting doctoral enrolment and completion by the faculty employees.