Tichavasia Alex Dandadzi

The paper reports on the findings made on an experiential exercise of Bachelor of Science Honours in Statistics (BSc Hons Stat) in the Department of Statistics and Operations Research (SOR) of the Sefako Makgatho Health Sciences University (SMU) in South Africa. SOR is a small, understaffed department, which offers courses for degrees from Bachelor to Doctoral levels in the subfields of Artificial Intelligence, Data Mining, Operations Research, Statistics and related ones. On SMU campus, expertize in some of these fields is also available in the Department of Computer Science (DCS). In the 2015 academic year SOR admitted 20 BSc Hons Stat students beyond its staffing capacity. Then, SOR invited DCS in a crowdsourcing initiative to jointly supervise student projects in the various subfields mentioned. The challenges include conflict and limited experience. These are managed satisfactorily though, but mainly because they occur at low levels. This crowdsourcing arrangement nevertheless results in timely submissions of final projects, improved quality projects worthy of being published, innovation, quality teamwork, and some synergistic outcomes. Coordinators also learn and/or improved some project management skills

The paper addresses the low research standing of Sefako Makgatho Health Sciences University (SMU). SMU is a university established on 1st January 2015 in the Gauteng Province of South Africa. Its weaknesses were inherited through history. The former Medical University of Sothern Africa (MEDUNSA) and University of Limpopo (UL) are the SMU’s predecessor universities from which SMU emerged. One main weakness is that UL appointed managers on Medunsa campus to head divisions but disregarding merit. Hence, many current SMU managers do not necessarily possess the qualities required for a research campus that is technology dominated. In particular, some staff and managerial appointments made prior to the SMU formation, which SMU had to inherit are the causes of deficiencies in SMU’s research and information development. The paper develops an approach for SMU to enable existing resources of information technology and communication (ICT) and statistical sciences to improve research on SMU campus. The approach developed is robust. It also has a built-in monitoring evaluation and control element. Benchmarks are used in the method development