SUPERVISION CHALLENGES AND DELAYS IN COMPLETION OF PHD PROGRAMMES IN PUBLIC AND PRIVATE UNIVERSITIES: EXPERIENCES OF SUPERVISORS AND GRADUATE STUDENTS IN SELECTED UNIVERSITIES IN NAIROBI, KENYA

In the year 2014, the Commission for University Education (CUE), gave a directive that only those with PhD qualifications will be eligible to teach in the Kenyan universities beyond 2018. This was due to the realisation that, majority of the teaching workforce in Universities in Kenya were holders of Masters’ Degrees in their respective disciplines. Majority of these lecturers, however, were already enrolled in PhD programmes with some having spent up to eight years, more than the expected period of three to four years. The long time it takes to complete PhD studies has psychological, social, and financial implications on the students. It also undermines human resource capacities of the universities in which they teach and should be a concern to all the stakeholders in higher education. One of the main issues often cited for this delay is the challenge of supervision experienced by PhD students as they work with their supervisors on their theses and dissertations. In addition to other issues, this matter is an ethical one demanding critical redress by ethical leadership. This study therefore sought to investigate the supervision challenges encountered by such students in public and private universities in Kenya and strategies that can be put in place to overcome such challenges. Using both primary and secondary data, the study sought to provide answers to three research questions: What are the supervision challenges faced by PhD students in public and private universities in Kenya? What contextual factors have contributed to such challenges? and, What strategies can be employed by students and supervisors to provide quality supervision in a timely manner? The mixed methods design was used to address these research questions drawn from both private and public universities in Kenya after which the collected data was analysed through SPSS presented in both descriptive and regression forms. Article visualizations