Computer-Supported Assessment of Geometric Exploration Using Variation Theory

Autor/inn/en	Luz, Yael; Yerushalmy, Michal
Titel	Computer-Supported Assessment of Geometric Exploration Using Variation Theory
Quelle	In: Journal for Research in Mathematics Education, 54 (2023) 2, S.141-174 (34 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0021-8251
DOI	10.5951/jresematheduc-2020-0260
Schlagwörter	Algorithms; Computer Assisted Testing; Geometry; Mathematics Instruction; Geometric Concepts; Mathematical Logic; Grade 9; Classification; Error Patterns; Learning Analytics; Mathematical Concepts; Instructional Design; Learning Theories; Concept Formation + Suchen Sie Ihr Suchwort? Algorithm; Algorithmus; Geometrie; Mathematics lessons; Mathematikunterricht; Elementare Geometrie; Mathematical logics; Mathematische Logik; School year 09; 9. Schuljahr; Schuljahr 09; Classification system; Klassifikation; Klassifikationssystem; Fehlertyp; Lesson concept; Lessonplan; Unterrichtsentwurf; Learning theory; Lerntheorie; Concept learning; Begriffsbildung
Abstract	We report on an innovative design of algorithmic analysis that supports automatic online assessment of students' exploration of geometry propositions in a dynamic geometry environment. We hypothesized that difficulties with and misuse of terms or logic in conjectures are rooted in the early exploration stages of inquiry. We developed a generic activity format for if-then propositions and implemented the activity on a platform that collects and analyzes students' work. Finally, we searched for ways to use variation theory to analyze ninth-grade students' recorded work. We scored and classified data and found correlation between patterns in exploration stages and the conjectures students generated. We demonstrate how automatic identification of mistakes in the early stages is later reflected in the quality of conjectures. (As Provided).
Anmerkungen	National Council of Teachers of Mathematics. 1906 Association Drive, Reston, VA 20191. Tel: 800-235-7566; Tel: 703-620-9840; Fax: 703-476-2570; e-mail: publicationsdept@nctm.org; Web site: https://pubs.nctm.org/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01