RMIT University
Browse

A Research-Led Approach to Authentic Assessment Design for an Introductory Accounting Course

chapter
posted on 2024-10-30, 21:53 authored by Mathews NkhomaMathews Nkhoma, Clara NkhomaClara Nkhoma
Authentic assessment helps graduates acquire skills that will prepare them for work and help them to handle real-life work scenarios. However, there are few studies and research on practical examples and design of authentic assessment for accounting courses. This chapter discusses how the authors used a research-led approach in designing authentic assessment for an introductory accounting course. After conducting a literature review, a toolkit for authentic assessment design was developed to assist both novices and experts in this area tasked with authentic assessment design. The use of this toolkit led to the development of assessments that aimed to nurture the desirable but often-neglected graduate attributes for accounting and business school students. The authors also discussed the types of authentic assessment that were developed for an introductory accounting course using this toolkit. With an increased assessment of these skills, the need for rubrics was highlighted. It is evident from the authors’ experience that feedback and reflective practices are crucial when implementing authentic assessment.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1007/978-981-13-9957-2
  2. 2.
    ISBN - Is published in 9789811399565 (urn:isbn:9789811399565)

Start page

199

End page

211

Total pages

13

Outlet

Transformations in Tertiary Education

Editors

Belinda Tynan, Tricia McLaughlin, Andrea Chester, Catherine Hall-van den Elsen, Belinda Kennedy

Publisher

Springer

Place published

Singapore

Language

English

Copyright

© Springer Nature Singapore Pte Ltd. 2019

Former Identifier

2006093955

Esploro creation date

2020-06-22

Fedora creation date

2019-09-23

Usage metrics

    Scholarly Works

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC