Can multiple choice questions be successfully used as an assessment format in undergraduate mathematics?

Abstract

In this study we propose a taxonomy for assessment in mathematics, which we call the assessment component taxonomy, to identify those components of mathematics that can be successfully assessed using alternative assessment formats. Based on the literature on assessment models and taxonomies in mathematics, this taxonomy consists of seven mathematics assessment components, hierarchically ordered by cognitive level, as well as the nature of the mathematical tasks associated with each component. Using a model that we developed earlier for measuring the quality of mathematics test items, we investigate which of the assessment components can be successfully assessed in the provided response question (PRQ) format, in particular multiple choice questions (MCQs), and which can be better assessed in the constructed response question (CRQ) format. The results of this study show that MCQs can be constructed to evaluate higher order levels of thinking and learning. The conclusion is that MCQs can be successfully used as an assessment format in undergraduate mathematics, more so in some assessment components than in others. The inclusion of the PRQ assessment format in all seven assessment components can reduce the large marking loads, associated with continuous assessment practices in undergraduate mathematics, without compromising the validity of the assessment.

Empirical evidence of deep learning in learning communities

“…Williams (2006) asserts that ARQ multiple choice questions can serve as substitutes for, and can predict performance on, other types of questions, such as short answer and essay questions. Huntley et al . (2009) find that well-designed multiple choice questions can effectively evaluate complex thinking and learning in undergraduate mathematics courses.…”

The Usefulness of the Rasch Model for the Refinement of Likert Scale Questionnaires

“…A number of mathematics education researchers have applied the Rasch model in their work in South African studies, e.g. Huntley, Engelbrecht, and Harding (2009), who chose the Rasch model for statistical analysis because it does not depend on the assumption of a normal distribution of scores, Julie, Holtman, and Mbekwa (2011), who used the Rasch model to verify the viability of a newly developed instrument for measuring teacher preferences, and Long (2009) The Rasch model, also referred to as the Rasch Latent Trait Theory, is part of modern test theory developed by George Rasch (Rasch, 1960). The term latent refers to an underlying or unobservable or hidden trait that is to be measured, such as the spelling ability of a respondent on a spelling test.…”