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Gibbs, Jennifer C.; Taylor, Jim D. – Active Learning in Higher Education, 2016
The literature confirms the commonsense belief that feedback promotes learning. However, personalized feedback, especially in an online environment, can be exceedingly time-consuming for the instructor and may not improve student learning. To test this, a non-random sample of students in three sections of an online statistics course received…
Descriptors: Comparative Analysis, Self Evaluation (Individuals), Feedback (Response), Graduate Students
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Ma, Wenting; Adesope, Olusola O.; Nesbit, John C.; Liu, Qing – Journal of Educational Psychology, 2014
Intelligent Tutoring Systems (ITS) are computer programs that model learners' psychological states to provide individualized instruction. They have been developed for diverse subject areas (e.g., algebra, medicine, law, reading) to help learners acquire domain-specific, cognitive and metacognitive knowledge. A meta-analysis was conducted on…
Descriptors: Intelligent Tutoring Systems, Outcomes of Education, Meta Analysis, Individualized Instruction
Hickerson, Danielle – ProQuest LLC, 2012
Previous research has indicated that there is no relationship between traditional homework completion and academic achievement among elementary grade students. Yet, elementary school teachers continue to utilize this practice. The purpose of this quantitative study was to investigate the relationship between nontraditional, differentiated reading…
Descriptors: Academic Achievement, Reading Achievement, Homework, Student Motivation
Swab, A. Geoffrey – ProQuest LLC, 2012
This study of cooperative learning in post-secondary engineering education investigated achievement of engineering students enrolled in two intact sections of a computer-aided drafting (CAD) course. Quasi-experimental and qualitative methods were employed in comparing student achievement resulting from out-of-class cooperative and individualistic…
Descriptors: Engineering Education, Postsecondary Education, Cooperative Learning, Academic Achievement
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection