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Assessing students' self-assessment ability in an interdisciplinary domain

Sarah Alturki (Data and Web Science Group, Faculty of Business Informatics and Mathematics, University of Mannheim, Mannheim, Germany)
Heiner Stuckenschmidt (Data and Web Science Group, Faculty of Business Informatics and Mathematics, University of Mannheim, Mannheim, Germany)

Journal of Applied Research in Higher Education

ISSN: 2050-7003

Article publication date: 30 August 2021

35

Abstract

Purpose

The purpose of this study is to determine whether students' self-assessment (SSA) could be used as a significant attribute to predict students' future academic achievement.

Design/methodology/approach

The authors address how well students can assess their abilities and study the relationship between this ability and demographic properties and previous study performance. The authors present the study results by measuring the relationship between the SSA across five different topics and comparing them with the students' performance in these topics using short tests. The test has been voluntarily taken by more than 300 students planning to enroll in the School of Business Informatics and Mathematics master's programs at the University of Mannheim.

Findings

The study results reveal which attributes are mostly associated with the accuracy level of SSA in higher education. The authors conclude that SSA, it can be valuable in predicting master's students' academic achievement when taking specific measures when designing the predictive module.

Research limitations/implications

Due to time constraints, the study was restricted only to students applying to master's programs at the Faculty of Business Informatics and Mathematics at the University of Mannheim. This resulted in collecting a limited data set. Also, the scope of this study was restricted to testing the accuracy of SSA and did not test using it as an attribute for predicting students' academic achievement.

Originality/value

Predicting students' academic performance in higher education is beneficial from different perspectives. The literature reveals that a considerable amount of work is published to analyze and predict academic performance in higher education. However, most of the published work relies on attributes such as demographics, teachers' assessment, and examination scores for performing their prediction while neglecting the use of other forms of evaluation such as SSA or self-evaluation.

Keywords

Citation

Alturki, S. and Stuckenschmidt, H. (2021), "Assessing students' self-assessment ability in an interdisciplinary domain", Journal of Applied Research in Higher Education, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JARHE-01-2021-0034

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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