A Visualization System for Predicting Learning Activities Using State Transition Graphs [Konferenzbericht] Paper presented at the International Association for Development of the Information Society (IADIS) International Conference on Cognition and Exploratory Learning in Digital Age (14th, Vilamoura, Algarve, Portugal, Oct 18-20, 2017).

Autor/inn/en	Okubo, Fumiya; Shimada, Atsushi; Taniguchi, Yuta
Titel	A Visualization System for Predicting Learning Activities Using State Transition Graphs [Konferenzbericht] Paper presented at the International Association for Development of the Information Society (IADIS) International Conference on Cognition and Exploratory Learning in Digital Age (14th, Vilamoura, Algarve, Portugal, Oct 18-20, 2017).
Quelle	(2017), (8 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Learning Activities; Graphs; Prediction; Grades (Scholastic); Markov Processes; Accuracy; Validity; Foreign Countries; Computer Uses in Education; College Students; Questionnaires; Integrated Learning Systems; Japan + Suchen Sie Ihr Suchwort? Lernaktivität; Grafische Darstellung; Vorhersage; Notenspiegel; Markowscher Prozess; Gültigkeit; Ausland; Computernutzung; Collegestudent; Fragebogen
Abstract	In this paper, we present a system for visualizing learning logs of a course in progress together with predictions of learning activities of the following week and the final grades of students by state transition graphs. Data are collected from 236 students attending the course in progress and from 209 students attending the past course for prediction. From these data, the system constructs a state transition graph, where the prediction is based on the Markov property. We verify the performance of predictions by experiments in which the accuracy of prediction using the data of the course in progress and the one by 5-fold cross validation. [The research results have been achieved by "Research and Development on Fundamental and Utilization Technologies for Social Big Data" (178A03), the Commissioned Research of National Institute of Information and Communications Technology (NICT), Japan. For the complete proceedings, see ED579395.] (As Provided).
Anmerkungen	International Association for the Development of the Information Society. e-mail: secretariat@iadis.org; Web site: http://www.iadisportal.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01