Designing an Online Self-assessment for Informed Study Decisions: The User Perspective

Laurie Delnoij*, J.P.W. Janssen, K.J.H. Dirkx, R.L. Martens

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

This paper presents the results of a study, carried out as part of the design-based development of an online self-assessment for prospective students in higher online education. The self-assessment consists of a set of tests – predictive of completion – and is meant to improve informed decision making prior to enrolment. The rationale being that better decision making will help to address the ongoing concern of non-completion in higher online education. A prototypical design of the self-assessment was created based on an extensive literature review and correlational research, aimed at investigating validity evidence concerning the predictive value of the tests. The present study focused on investigating validity evidence regarding the content of the self-assessment (including the feedback it provides) from a user perspective. Results from a survey among prospective students (N = 66) indicated that predictive validity and content validity of the self-assessment are somewhat at odds: three out of the five tests included in the current prototype were considered relevant by prospective students. Moreover, students rated eleven additionally suggested tests – currently not included – as relevant concerning their study decision. Expectations regarding the feedback to be provided in connection with the tests include an explanation of the measurement and advice for further preparation. A comparison of the obtained scores to a reference group (i.e., other test-takers or successful students) is not expected. Implications for further development and evaluation of the self-assessment are discussed.
Original languageEnglish
Title of host publicationAddressing Global Challenges and Quality Education
EditorsCarlos Alario-Hoyos, María Jesús Rodríguez-Triana, Maren Scheffel, Immaculada Arnedillo-Sánchez, Sebastian Maximilian Dennerlein
Place of PublicationSwitzerland
PublisherSpringer Nature Switzerland AG
Pages74-86
Number of pages13
ISBN (Print)9783030577162
DOIs
Publication statusPublished - 1 Sept 2020
Externally publishedYes

Publication series

SeriesLecture Notes in Computer Science
Number12315

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