From Biology to Education: Scoring and Clustering Multilingual Text Sequences and Other Sequential. Research Report. ETS RR-12-25

Autor/inn/en	Sukkarieh, Jane Z.; von Davier, Matthias; Yamamoto, Kentaro
Titel	From Biology to Education: Scoring and Clustering Multilingual Text Sequences and Other Sequential. Research Report. ETS RR-12-25
Quelle	In: ETS Research Report Series, (2012), (52 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2330-8516
Schlagwörter	Scoring; Multilingualism; Test Items; Role; Item Analysis; Guidelines; Simulation; Intelligent Tutoring Systems; Statistical Analysis; Content Analysis; Natural Language Processing; Translation; English; Spanish; Biology; Genetics; Graphemes; French; Japanese; Tests; Computer Assisted Testing + Suchen Sie Ihr Suchwort? Bewertung; Mehrsprachigkeit; Multilingualismus; Test content; Testaufgabe; Rollen; Itemanalyse; Richtlinien; Simulation program; Simulationsprogramm; Intelligentes Tutorsystem; Statistische Analyse; Inhaltsanalyse; Natürliche Sprache; English language; Englisch; Spanisch; Biologie; Humangenetik; Französisch; Japaner; Japanisch; Examination; Prüfung; Examen
Abstract	This document describes a solution to a problem in the automatic content scoring of the multilingual character-by-character highlighting item type. This solution is language independent and represents a significant enhancement. This solution not only facilitates automatic scoring but plays an important role in clustering students' responses; consequently, it has a nontrivial impact on the refinement of the items and/or their scoring guidelines. Furthermore, though designed for a specific problem, the proposed solution is general enough for any educational task that can be transformed into a sequential one. To name a few: It can be used for a set of actions expected from a student in simulations or learning trajectories as projected by a teacher, inside an intelligent tutoring system, or even in a game--or it can simply be used for a set of student clicks, button selections, or keyboard hits expected to reach a correct answer. This solution provides flexibility for existing automatic-scoring techniques and potentially could provide more flexibility if coupled with statistical data-mining techniques. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01