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Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Do we always need a difference? : testing equivalence in a blended learning setting
Authors: Müller Werder, Claude
Mildenberger, Thoralf
Lübcke, Maren
et. al: No
DOI: 10.1080/1743727X.2019.1680621
Published in: International Journal of Research & Method in Education
Volume(Issue): 43
Issue: 3
Page(s): 283
Pages to: 295
Issue Date: 2020
Publisher / Ed. Institution: Taylor & Francis
ISSN: 1743-727X
Language: English
Subjects: Blended learning; Equivalence testing; Flexible learning; Learning effectiveness
Subject (DDC): 371: Schools and their activities
Abstract: Evidence-based research is becoming increasingly important in educational research. Calculation and test methods available in statistical software packages such as SPSS and STATA are widely used. To evaluate teaching innovations such as blended learning against classical classroom settings, for example, previous studies have mainly applied inference methods such as the t-test or variance analyses. The problem with these methods is that they test for the difference. A non-significant result does not automatically mean equivalence of the treatments examined, which is why we propose the use of equivalence testing. This paper introduces the equivalence test as complementary to the classical t-test and briefly discusses other approaches based on confidence intervals and Bayesian methods. As an example, the introduction of a blended learning format to a Bachelor’s degree programme is used to demonstrate the procedure and discuss the results of conducting an equivalence test. By combining tests for difference and equivalence successfully, it was possible to arrive at more informative statistical statements: Whereas a t-test alone only produced results for three out of 22 courses, a t-test and an equivalence test in combination yielded statistically confirmed statements for 12 out of 22 courses.
Fulltext version: Accepted version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Management and Law
School of Engineering
Organisational Unit: Center for Innovative Teaching and Learning (ZID)
Institute of Data Analysis and Process Design (IDP)
Published as part of the ZHAW project: Flexibles Lernen Research
Appears in collections:Publikationen School of Management and Law

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