Predicting School Performance and Early Risk of Failure from an Intelligent Tutoring System

Autor/inn/en	Haridas, Mithun; Gutjahr, Georg; Raman, Raghu; Ramaraju, Rudraraju; Nedungadi, Prema
Titel	Predicting School Performance and Early Risk of Failure from an Intelligent Tutoring System
Quelle	In: Education and Information Technologies, 25 (2020) 5, S.3995-4013 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-020-10144-0
Schlagwörter	Foreign Countries; Predictor Variables; English (Second Language); Second Language Learning; Academic Achievement; Mathematics Achievement; Summative Evaluation; Formative Evaluation; At Risk Students; Reading Difficulties; Scores; Intelligent Tutoring Systems; Rural Schools; India + Suchen Sie Ihr Suchwort? Ausland; Prädiktor; English as second language; English; Second Language; Englisch als Zweitsprache; Zweitsprachenerwerb; Schulleistung; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Reading difficulty; Leseschwierigkeit; Intelligentes Tutorsystem; Rural area; Rural areas; School; Schools; Ländlicher Raum; Schule; Schulen; Indien
Abstract	In many rural Indian schools, English is a second language for teachers and students. Intelligent tutoring systems have good potential because they enable students to learn at their own pace, in an exploratory manner. This paper describes a 3-year longitudinal study of 2123 Indian students who used the intelligent tutoring system, AmritaITS. The aim of the study was to use the students' interaction logs with AmritaITS to: (1) predict student performance, in English and Mathematics subjects, via summative and formative assessments, (2) predict students who may be at risk of failing the final examination and (3) screen students who may have reading difficulties. The prediction models for summative assessments were significantly improved by formative assessments scores, along with AmritaITS logs. The receiver operating characteristic (ROC) curve showed that students at risk of failing a class could be identified early, with high sensitivity and specificity. The models also provide recommendations for the amount of time required for students to use the system, and reach the appropriate grade level. Finally, the models demonstrated promise in identifying students who might be at risk of suffering from reading difficulties. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01