Process data from electronic textbooks indicate students' classroom engagement
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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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, Jahrgang 83-84, 101934, 01.10.2020.Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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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 -