From Inky Pinky Ponky to Improving Student Understanding in Assessment: Exploring the Value of Supplemental Instruction in a Large First-Year Class

  • Mianda Erasmus
Keywords: supplemental instruction, assessment, MCQs, feedback, modelling


Large classes are a reality in many tertiary programmes in the South African context and this involves several challenges. One of these is the assessment process, including the provision of meaningful feedback and implementing strategies to support struggling students. Due to large student numbers, multiplechoice questions (MCQs) are often used in tests, even though researchers have found possible negative consequences of using MCQs. Giving appropriate feedback has been identified as a strategy to remedy some of these negative consequences. This paper reports on action research in which an intervention strategy was implemented in a large first year Psychology class where Supplemental Instructors (SIs) were used to give detailed feedback to students after assessments. The lecturer first modelled how to give feedback by discussing the MCQs in detail with the SIs and identifying possible errors in their reasoning and meta-cognitive processes. The SIs subsequently repeated this feedback process in their small-group sessions. After each assessment, students who performed poorly were advised to attend a certain number of SI sessions before the next test, and their attendance, even though voluntary, was monitored to determine the effectiveness of the intervention. Students’ performance in subsequent tests was compared and the results seem to indicate that attending SI sessions was mostly associated with improved test results. This strategy also appears to encourage attendance of SI sessions. In addition, students’ responses in a feedback survey indicate an overall positive perception of this practice. These results can inform other lecturers teaching large classes and contribute to quality enhancement in assessment and better support for students.

Keywords supplemental instruction; assessment; MCQs; feedback; modelling

Research Articles

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eISSN: 2307-6267