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The Quality of Supervision and Assessment in Industry-Based Learning

Domaine:

education

Type de record:

paper
Créateur:
NduLun
Éditeur:
Ind
Hôte:
Effective student assessment measures the rigor, effectiveness and quality of learning and teaching. There is a persistent concern among higher education practitioners about the accuracy and quality of academic supervision and assessment, particularly in areas of experiential learning. The purpose of this study was to critically evaluate practitioner conceptions on the effectiveness of supervision and assessment practices of industry-based learning in enhancing quality academic practices carried out at five universities in Zimbabwe. This paper analyses stakeholder views, reflections and understandings on student supervision and assessment processes in industry-based learning programs in Zimbabwe universities.  Through interviews, focus group discussions, and open and closed questions in structured questionnaires, the participants in the mixed methods study, drawn from universities and their workplace partner organizations, give insights into their activities that characterize the dominant student supervision and assessment practices. The research results show that the participants were moderately satisfied with the overall assessment processes, raising concerns on quality issues, supervisor qualities and competencies, assessment visits by lecturers, and student guidance in the workplace. It is evident that the assessment systems in the work-integrated learning program in the affected universities not only compromised the desired confidence and trust of the students in their assessors but unsettled the assessors themselves, a situation that would naturally invite appropriate corrective action. Participative assessment, an approach where the facilitator seeks to directly involve and share the responsibility for assessment with learners is compatible with industry-based learning approaches because students can engage in self-regulation and intrinsically sanctioned learning.

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doi.org

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