Does an individualized learning design improve university student online learning? A randomized field experiment

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Does an individualized learning design improve university student online learning? A randomized field experiment. / Dietrich, Julia; Greiner, Franziska; Weber-Liel, Dorit et al.
In: Computers in Human Behavior, Vol. 122, 106819, 01.09.2021.

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Dietrich J, Greiner F, Weber-Liel D, Berweger B, Kämpfe N, Kracke B. Does an individualized learning design improve university student online learning? A randomized field experiment. Computers in Human Behavior. 2021 Sept 1;122:106819. doi: 10.31234/osf.io/hkq7m, 10.1016/j.chb.2021.106819

Bibtex

@article{6d4d0b8a45284050a969202f09ae1edf,
title = "Does an individualized learning design improve university student online learning? A randomized field experiment",
abstract = "University courses often employ “one-size-fits-all” approaches, disregarding the heterogeneity in students' cognitive and motivational characteristics. This intervention study reports on an individualized learning design for online teaching in higher education. In a randomized field experiment with N = 438 university students (57% female, mean age M = 20.96 years), we investigated the effects of the learning design on students' motivation (self-concept, self-efficacy, intrinsic and utility task values), on their performance, and, because our sample consisted of teacher students, on their professional development with regard to inclusive education. Employing structural equation modeling, we found that the intervention positively affected the self-concepts of effort avoidant students. The intervention also positively impacted students' attitudes and self-efficacy towards inclusive education, but had no effect on course performance, course-related self-efficacy and task values. Moreover, learning analytics data revealed in-depth information on students{\textquoteright} learning behavior. Results are discussed regarding possible intervention strategies to be implemented in future versions of the learning design.",
keywords = "Individualized learning design, Online learning, Student motivation, Performance, Attitudes towards inclusive education, Teacher students, Educational science",
author = "Julia Dietrich and Franziska Greiner and Dorit Weber-Liel and Belinda Berweger and Nicole K{\"a}mpfe and B{\"a}rbel Kracke",
note = "Funding Information: This work was supported by a grant from the Stifterverband f{\"u}r die Deutsche Wissenschaft , Germany, and the Thuringian Ministry for Economic Affairs, Science and Digital Society awarded to Julia Dietrich, and by grant no. 01JA1808 from the Federal Ministry of Education and Research , Germany, awarded to B{\"a}rbel Kracke. Publisher Copyright: {\textcopyright} 2021 Elsevier Ltd",
year = "2021",
month = sep,
day = "1",
doi = "10.31234/osf.io/hkq7m",
language = "English",
volume = "122",
journal = "Computers in Human Behavior",
issn = "0747-5632",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Does an individualized learning design improve university student online learning? A randomized field experiment

AU - Dietrich, Julia

AU - Greiner, Franziska

AU - Weber-Liel, Dorit

AU - Berweger, Belinda

AU - Kämpfe, Nicole

AU - Kracke, Bärbel

N1 - Funding Information: This work was supported by a grant from the Stifterverband für die Deutsche Wissenschaft , Germany, and the Thuringian Ministry for Economic Affairs, Science and Digital Society awarded to Julia Dietrich, and by grant no. 01JA1808 from the Federal Ministry of Education and Research , Germany, awarded to Bärbel Kracke. Publisher Copyright: © 2021 Elsevier Ltd

PY - 2021/9/1

Y1 - 2021/9/1

N2 - University courses often employ “one-size-fits-all” approaches, disregarding the heterogeneity in students' cognitive and motivational characteristics. This intervention study reports on an individualized learning design for online teaching in higher education. In a randomized field experiment with N = 438 university students (57% female, mean age M = 20.96 years), we investigated the effects of the learning design on students' motivation (self-concept, self-efficacy, intrinsic and utility task values), on their performance, and, because our sample consisted of teacher students, on their professional development with regard to inclusive education. Employing structural equation modeling, we found that the intervention positively affected the self-concepts of effort avoidant students. The intervention also positively impacted students' attitudes and self-efficacy towards inclusive education, but had no effect on course performance, course-related self-efficacy and task values. Moreover, learning analytics data revealed in-depth information on students’ learning behavior. Results are discussed regarding possible intervention strategies to be implemented in future versions of the learning design.

AB - University courses often employ “one-size-fits-all” approaches, disregarding the heterogeneity in students' cognitive and motivational characteristics. This intervention study reports on an individualized learning design for online teaching in higher education. In a randomized field experiment with N = 438 university students (57% female, mean age M = 20.96 years), we investigated the effects of the learning design on students' motivation (self-concept, self-efficacy, intrinsic and utility task values), on their performance, and, because our sample consisted of teacher students, on their professional development with regard to inclusive education. Employing structural equation modeling, we found that the intervention positively affected the self-concepts of effort avoidant students. The intervention also positively impacted students' attitudes and self-efficacy towards inclusive education, but had no effect on course performance, course-related self-efficacy and task values. Moreover, learning analytics data revealed in-depth information on students’ learning behavior. Results are discussed regarding possible intervention strategies to be implemented in future versions of the learning design.

KW - Individualized learning design

KW - Online learning

KW - Student motivation

KW - Performance

KW - Attitudes towards inclusive education

KW - Teacher students

KW - Educational science

UR - http://www.scopus.com/inward/record.url?scp=85105695643&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/fb5ff7ec-f84d-3c10-aa21-3284fd44d2b7/

U2 - 10.31234/osf.io/hkq7m

DO - 10.31234/osf.io/hkq7m

M3 - Journal articles

VL - 122

JO - Computers in Human Behavior

JF - Computers in Human Behavior

SN - 0747-5632

M1 - 106819

ER -

DOI