Optimising postgraduate supervision using multilevel modeling techniques in a constrained higher education environment

Abstract

The paper developed a multilevel model (MLM) of postgraduate (PG) supervision to improve the academic publication and PG completion rate. Crowdsourcing essentials were used in the development of the model. The crowds consisted of the MLM made of students from Honours to doctoral levels. Teamwork was also implored, where the teams were level mates and supervisory teams. The simplest form of the model has the potential to generate over 65 academic manuscripts for journals. Monitoring of the supervision process can provide maximized completion of the PG research studies. Research capacity building would be effected for the doctoral and master’s students making them able to supervise and co-supervise from Honours to doctoral levels upon completion of their studies. The study condemned the use of a single supervisor for several doctoral students. It recommended the implementation of the model (the MLM PG Supervision Framework). It further recommended that doctoral students should be assigned co-supervisors, preferably varied for different students, to enable diversity in the supervision experience.

Keywords: {'name': 'Capacity building, multilevel modeling, optimized student supervision'}

Authors & affiliations

Mamelang Molaba
Affiliation not supplied

Sechene Stanley Gololo
Affiliation not supplied

Solly Matshonisa Seeletse
Affiliation not supplied

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