JOURNAL ARTICLE

Evaluating the use of e-assessment in a first-year pure mathematics module.

  • Published In: Teaching Mathematics & its Applications, 2023, v. 42, n. 2. P. 109 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Zegowitz, Stefanie 3 of 3

Abstract

This article examines a two-year case study on the use of bi-weekly online quizzes as an assessment-for-learning tool in a first-year UK undergraduate pure mathematics module, Introduction to Proofs. The quizzes aimed to support students' transition from A-Level to university-level mathematics by motivating early engagement with learning material and emphasizing small but crucial details within mathematical proofs, such as defining notation. Implemented via the Blackboard e-learning platform, the quizzes combined multiple-choice, fill-in-the-blank, matching, and multiple-answer questions, providing automatic, individualized feedback tailored to students' responses. Survey data indicated increased student engagement with lecture notes and feedback over time, though fewer students felt the quizzes helped with writing their own proofs, suggesting a gap between recognizing proof details and applying them independently. The study concludes that online quizzes can effectively complement traditional assessments in pure mathematics, recommending periodic scheduling, encoding common misconceptions, detailed feedback, randomization, and linking quiz content with other coursework to enhance learning outcomes.

Additional Information

  • Source:Teaching Mathematics & its Applications. 2023/06, Vol. 42, Issue 2, p109
  • Document Type:Article
  • Subject Area:Mathematics
  • Publication Date:2023
  • ISSN:0268-3679
  • DOI:10.1093/teamat/hrac011
  • Accession Number:164129295
  • Copyright Statement:Copyright of Teaching Mathematics & its Applications is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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