Education Commons^™

Revealing Online Learning Behaviors And Activity Patterns And Making Predictions With Data Mining Techniques In Online Teaching, Jui-Long Hung, Ke Zhang

Educational Technology Faculty Publications and Presentations

This study was conducted with data mining (DM) techniques to analyze various patterns of online learning behaviors, and to make predictions on learning outcomes. Statistical models and machine learning DM techniques were conducted to analyze 17,934 server logs to investigate 98 undergraduate students’ learning behaviors in an online business course in Taiwan. The study scientifically identified students’ behavioral patterns and preferences in the online learning processes, differentiated active and passive learners, and found important parameters for performance prediction. The results also demonstrated how data mining techniques might be utilized to help improve online teaching and learning with suggestions for online …

Challenges And Questions Concerning “Culturally-Sensitive Design”, Ross Perkins

Educational Technology Faculty Publications and Presentations

Since the inception of the field of anthropology, scholars have debated the definition for the word "culture." Lonner and Adamapoulos (1997) note that "there are 200 or more definitions of 'culture' in the literature of the social sciences, not one of which has been embraced by a substantial number of social scientists" (p. 76). Strauss and Quinn (1997) provide an overview of four schools of thought regarding the interpretations of "culture":

"Geertzian interpretivists have stressed the publicness of meaning, cognition, and culture. Foucauldian postmodernists have argued for the constructedness of culture and of the self. Some contemporary historical materialists highlight …

Computer-Based Instruction And Cognitive Load, Jui-Long Hung, Brandon Randolph-Seng, Kittikunanant Monsicha, Steven M. Crooks

Educational Technology Faculty Publications and Presentations

Following cognitive load theory, we used a computer-based software training paradigm to determining the optimal number of steps or information chunks to present before practice opportunities. Results demonstrating that the size of information chunks presented and the type of practice used individually influenced participants' ability to effectively learn via computer-based instruction. These findings contribute to the literature by showing the importance of practice and optimal segment sizes for learning via a computer.