Process data from electronic textbooks indicate students' classroom engagement

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Process data from electronic textbooks indicate students' classroom engagement. / Reinhold, Frank; Strohmaier, Anselm; Hoch, Stefan et al.
In: Learning and Individual Differences, Vol. 83-84, 101934, 01.10.2020.

Research output: Journal contributionsJournal articlesResearchpeer-review

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Reinhold F, Strohmaier A, Hoch S, Reiss K, Böheim R, Seidel T. Process data from electronic textbooks indicate students' classroom engagement. Learning and Individual Differences. 2020 Oct 1;83-84:101934. doi: 10.1016/j.lindif.2020.101934

Bibtex

@article{e5f0091ade5b4ce9af5331bf315ba168,
title = "Process data from electronic textbooks indicate students' classroom engagement",
abstract = "Electronic learning environments used in mathematics lessons offer new ways to assess and analyze students' classroom engagement during authentic learning settings. In this study, we investigated students' electronic textbook-use as a measure for their individual engagement during mathematics instruction. To this end, we combined quantity measures (i.e., time on task, text length) and quality measures (i.e., on topic, mathematically valid, mathematical language used). Cluster analysis based on process data of 253 six-graders—who worked on three writing-to-learn exercises during fraction instruction—revealed four different clusters that we ordered hierarchically in terms of engagement, revealing gender differences in favor of girls. Analyses showed negligible differences in prior knowledge between the clusters, yet significant achievement differences in a posttest—with higher engaged clusters reaching higher outcomes. Our approach offers a viable way to unobtrusively measure students' classroom engagement utilizing process data from electronic textbooks.",
keywords = "Educational science, Cluster analysis, Engagement, Fractions, Process data, Unobtrusive measurement",
author = "Frank Reinhold and Anselm Strohmaier and Stefan Hoch and Kristina Reiss and Ricardo B{\"o}heim and Tina Seidel",
year = "2020",
month = oct,
day = "1",
doi = "10.1016/j.lindif.2020.101934",
language = "English",
volume = "83-84",
journal = "Learning and Individual Differences",
issn = "1041-6080",
publisher = "Elsevier B.V.",

}

RIS

TY - JOUR

T1 - Process data from electronic textbooks indicate students' classroom engagement

AU - Reinhold, Frank

AU - Strohmaier, Anselm

AU - Hoch, Stefan

AU - Reiss, Kristina

AU - Böheim, Ricardo

AU - Seidel, Tina

PY - 2020/10/1

Y1 - 2020/10/1

N2 - Electronic learning environments used in mathematics lessons offer new ways to assess and analyze students' classroom engagement during authentic learning settings. In this study, we investigated students' electronic textbook-use as a measure for their individual engagement during mathematics instruction. To this end, we combined quantity measures (i.e., time on task, text length) and quality measures (i.e., on topic, mathematically valid, mathematical language used). Cluster analysis based on process data of 253 six-graders—who worked on three writing-to-learn exercises during fraction instruction—revealed four different clusters that we ordered hierarchically in terms of engagement, revealing gender differences in favor of girls. Analyses showed negligible differences in prior knowledge between the clusters, yet significant achievement differences in a posttest—with higher engaged clusters reaching higher outcomes. Our approach offers a viable way to unobtrusively measure students' classroom engagement utilizing process data from electronic textbooks.

AB - Electronic learning environments used in mathematics lessons offer new ways to assess and analyze students' classroom engagement during authentic learning settings. In this study, we investigated students' electronic textbook-use as a measure for their individual engagement during mathematics instruction. To this end, we combined quantity measures (i.e., time on task, text length) and quality measures (i.e., on topic, mathematically valid, mathematical language used). Cluster analysis based on process data of 253 six-graders—who worked on three writing-to-learn exercises during fraction instruction—revealed four different clusters that we ordered hierarchically in terms of engagement, revealing gender differences in favor of girls. Analyses showed negligible differences in prior knowledge between the clusters, yet significant achievement differences in a posttest—with higher engaged clusters reaching higher outcomes. Our approach offers a viable way to unobtrusively measure students' classroom engagement utilizing process data from electronic textbooks.

KW - Educational science

KW - Cluster analysis

KW - Engagement

KW - Fractions

KW - Process data

KW - Unobtrusive measurement

UR - http://www.scopus.com/inward/record.url?scp=85091772849&partnerID=8YFLogxK

U2 - 10.1016/j.lindif.2020.101934

DO - 10.1016/j.lindif.2020.101934

M3 - Journal articles

VL - 83-84

JO - Learning and Individual Differences

JF - Learning and Individual Differences

SN - 1041-6080

M1 - 101934

ER -

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