Dynamic Bayesian Network Modeling of Game Based Diagnostic Assessments. CRESST Report 837

Autor/in	Levy, Roy
Institution	National Center for Research on Evaluation, Standards, and Student Testing
Titel	Dynamic Bayesian Network Modeling of Game Based Diagnostic Assessments. CRESST Report 837
Quelle	(2014), (32 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Video Games; Educational Games; Bayesian Statistics; Observation; Evaluation Methods; Inferences; Student Evaluation; Diagnostic Tests; Models; Misconceptions; Psychometrics; Performance Based Assessment; Addition; Mathematics Skills; Problem Solving; Grade 6; Grade 7; Grade 8; Markov Processes; Monte Carlo Methods + Suchen Sie Ihr Suchwort? Video game; Videospiel; Videospiele; Educational game; Lernspiel; Beobachtung; Inference; Inferenz; Schulnote; Studentische Bewertung; Diagnostic test; Diagnostischer Test; Analogiemodell; Missverständnis; Psychometry; Psychometrie; Leistungsermittlung; Mathmatics achievement; Mathematics ability; Mathematische Kompetenz; Problemlösen; School year 06; 6. Schuljahr; Schuljahr 06; School year 07; 7. Schuljahr; Schuljahr 07; School year 08; 8. Schuljahr; Schuljahr 08; Markowscher Prozess; Monte-Carlo-Methode
Abstract	Digital games offer an appealing environment for assessing student proficiencies, including skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian network modeling approach for observations of student performance from an educational video game. A Bayesian approach to model construction, calibration, and use in facilitating inferences about students on the fly is described. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01