Properties and Applications of Wrong Answers in Online Educational Systems [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (9th, Raleigh, NC, Jun 29-Jul 2, 2016).

Autor/inn/en	Pelánek, Radek; Rihák, Ji?rí
Titel	Properties and Applications of Wrong Answers in Online Educational Systems [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (9th, Raleigh, NC, Jun 29-Jul 2, 2016).
Quelle	(2016), (6 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Foreign Countries; Online Systems; Geography; Anatomy; Arithmetic; Comparative Analysis; Graphs; Data Analysis; Classification; Misconceptions; Error Patterns; Elementary Secondary Education; Feedback (Response); Computer Assisted Testing; Test Preparation; Test Items; Item Analysis; Mathematics Instruction; Maps; Computer Software; Czech Republic + Suchen Sie Ihr Suchwort? Ausland; Online; Geografie; Anatomie; Addition; Arithmetik; Arithmetikunterricht; Rechnen; Grafische Darstellung; Auswertung; Classification system; Klassifikation; Klassifikationssystem; Missverständnis; Fehlertyp; Test content; Testaufgabe; Itemanalyse; Mathematics lessons; Mathematikunterricht; Map; Karte; Tschechische Republik
Abstract	In online educational systems we can easily collect and analyze extensive data about student learning. Current practice, however, focuses only on some aspects of these data, particularly on correctness of students answers. When a student answers incorrectly, the submitted wrong answer can give us valuable information. We provide an overview of possible applications of wrong answers and analyze wrong answers from three different educational systems (geography, anatomy, basic arithmetic). Using this cross-system comparison we illustrate some common properties of wrong answers. We also propose techniques for processing of wrong answers and their visualization, particularly an approach to item clustering based on community detection in a confusion graph. (As Provided).
Anmerkungen	International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01