Personal Excursions: Investigating the Dynamics of Student Engagement

Autor/in	Azevedo, Flavio S.
Titel	Personal Excursions: Investigating the Dynamics of Student Engagement
Quelle	In: International Journal of Computers for Mathematical Learning, 11 (2006) 1, S.57-98 (42 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1382-3892
DOI	10.1007/s10758-006-0007-6
Schlagwörter	Independent Study; Self Motivation; Videotape Recordings; Secondary School Students; Summer Programs; Competence; Time on Task; Student Participation; Computer Assisted Instruction + Suchen Sie Ihr Suchwort? Selbststudium; Sekundarschüler; Sommerkurs; Kompetenz; Zeitaufwand; Schülermitarbeit; Schülermitwirkung; Studentische Mitbestimmung; Computer based training; Computerunterstützter Unterricht
Abstract	We investigate the dynamics of student engagement as it is manifest in self-directed, self-motivated, relatively long-term, computer-based scientific image processing activities. The raw data for the study are video records of 19 students, grades 7 to 11, who participated in intensive 6-week, extension summer courses. From this raw data we select episodes in which students appear to be highly engaged with the subject matter. We then attend to the fine-grained texture of students' actions, identifying a core set of phenomena that cut across engagement episodes. Analyzed as a whole, these phenomena suggest that when working in self-directed, self-motivated mode, students pursue proposed activities but sporadically and spontaneously venture into self-initiated activities. Students' recurring self-initiated activities--which we call personal excursions--are detours from proposed activities, but which align to a greater or lesser extent with the goals of such activities. Because of the deeply personal nature of excursions, they often result in students collecting resources that feed back into both subsequent excursions and framed activities. Having developed an understanding of students' patterns of self-directed, self-motivated engagement, we then identify four factors that seem to bear most strongly on such patterns: (1) students' competence (broadly construed); (2) features of the software-based activities, and how such features allowed students to express their competence; (3) the time allotted for students to pursue proposed activities, as well as self-initiated ones; and (4) the flexibility of the computational environment within which the activities were implemented. (Author).
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Update	2017/4/10