Assessing the Roles of Student Engagement and Academic Emotions within Middle School Computer- Based Learning in College-Going PathwaysReportar como inadecuado




Assessing the Roles of Student Engagement and Academic Emotions within Middle School Computer- Based Learning in College-Going Pathways - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.



International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (8th, Madrid, Spain, Jun 26-29, 2015)

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.]

Descriptors: 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

International Educational Data Mining Society. e-mail: admin[at]educationaldatamining.org; Web site: http://www.educationaldatamining.org





Autor: San Pedro, Maria Ofelia Z.

Fuente: https://eric.ed.gov/?q=a&ft=on&ff1=dtySince_1992&pg=2754&id=ED560529







Documentos relacionados