Does Slow and Steady Win the Race?: Clustering Patterns of Students' Behaviors in an Interactive Online Mathematics Game

Autor/inn/en	Lee, Ji-Eun; Chan, Jenny Yun-Chen; Botelho, Anthony; Ottmar, Erin
Titel	Does Slow and Steady Win the Race?: Clustering Patterns of Students' Behaviors in an Interactive Online Mathematics Game
Quelle	In: Educational Technology Research and Development, 70 (2022) 5, S.1575-1599 (25 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Lee, Ji-Eun) Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1042-1629
DOI	10.1007/s11423-022-10138-4
Schlagwörter	Computer Games; Educational Games; Mathematics Instruction; Learning Processes; Student Behavior; Learning Analytics; Middle School Students; Problem Solving; Behavior Patterns; Learner Engagement; Computer Assisted Testing; Mathematics Tests; Teaching Methods; Computer Mediated Communication + Suchen Sie Ihr Suchwort? Computer game; Computerspiel; Computerspiele; Educational game; Lernspiel; Mathematics lessons; Mathematikunterricht; Learning process; Lernprozess; Student behaviour; Schülerverhalten; Middle school; Middle schools; Student; Students; Mittelschule; Mittelstufenschule; Schüler; Schülerin; Problemlösen; Teaching method; Lehrmethode; Unterrichtsmethode; Computerkonferenz
Abstract	Online educational games have been widely used to support students' mathematics learning. However, their effects largely depend on student-related factors, the most prominent being their behavioral characteristics as they play the games. In this study, we applied a set of learning analytics methods (k-means clustering, data visualization) to clickstream data from an interactive online algebra game to unpack how middle-school students' (N = 227) behavioral patterns (i.e., the number of problems completed, resetting problems, reattempting problems, pause time before first actions) correlated with their understanding of mathematical equivalence. The k-means cluster analysis identified four groups of students based on their behavioral patterns in the game: "fast progressors," "intermediate progressors," "slow progressors," and "slow-steady progressors." The results indicated that students in these clusters, with the exception of slow progressors, showed significant increases in their understanding of mathematical equivalence. In particular, "slow-steady progressors," who reattempted the same problem more often than other students, showed the largest absolute learning gains, suggesting that behavioral engagement played a significant role in learning. With data visualizations, we presented evidence of variability in students' approaches to problem solving in the game, providing future directions for investigating how differences in student behaviors impact learning. [For the corresponding grantee submission, see ED621740.] (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01