Assessing the Roles of Student Engagement and Academic Emotions within Middle School Computer- Based Learning in College-Going Pathways [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (8th, Madrid, Spain, Jun 26-29, 2015).

Autor/in	San Pedro, Maria Ofelia Z.
Institution	International Educational Data Mining Society
Titel	Assessing the Roles of Student Engagement and Academic Emotions within Middle School Computer- Based Learning in College-Going Pathways [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (8th, Madrid, Spain, Jun 26-29, 2015).
Quelle	(2015), (3 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Learner Engagement; Psychological Patterns; Middle School Students; Student Behavior; Longitudinal Studies; High School Students; Statistical Analysis; College Bound Students; Outcomes of Education; Student Interests; Educational Experience; Computer Uses in Education; Multiple Regression Analysis; Questionnaires; Multivariate Analysis; Structural Equation Models + Suchen Sie Ihr Suchwort? Middle school; Middle schools; Student; Students; Mittelschule; Mittelstufenschule; Schüler; Schülerin; Student behaviour; Schülerverhalten; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; High school; High schools; Oberschule; Studentin; Statistische Analyse; Lernleistung; Schulerfolg; Studieninteresse; Bildungserfahrung; Computernutzung; Fragebogen; Multivariate Analyse
Abstract	This dissertation research focuses on assessing student behavior, academic emotions, and knowledge from a middle school online learning environment, and analyzing their potential effects on decisions about going to college. Using students' longitudinal data ranging from their middle school, to high school, to postsecondary years, I leverage quantitative methodologies to investigate antecedents to college-going outcomes that can occur as early as middle school. The research first looks at whether assessments of learning, emotions and engagement from middle school computer-based curriculum are predictive at all of college-going outcomes years later. I then investigate how these middle school factors can be associated with college-going interests formed in high school, using the same assessments during middle school, together with self-report measures of interests in college when they were in high school. My dissertation then culminates in developing an overall model that examines how student interests in high school can possibly mediate between the educational experiences students have during middle school technology-enhanced learning and their eventual college-going choices. This gives a richer picture of the cognitive and motivational mechanisms that students experience throughout varied phases in their years in school. [For complete proceedings, see ED560503.] (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