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Richey, J. Elizabeth; Nokes-Malach, Timothy J. – Learning and Instruction, 2013
A central goal of the learning sciences is to discover principles that determine the optimal amount of instructional assistance to support robust learning (Koedinger & Aleven, 2007). We examined learning outcomes from providing and withholding stepwise instructional explanations as students studied worked examples and solved physics problems. We…
Descriptors: Demonstrations (Educational), Teaching Methods, Problem Solving, Learning Processes
Moskaliuk, Johannes; Kimmerle, Joachim; Cress, Ulrike – Computers & Education, 2012
Wikis as shared digital artifacts may enable users to participate in processes of knowledge building. To what extent and with which quality knowledge building can take place is assumed to depend on the interrelation between people's prior knowledge and the information available in a wiki. In two experimental studies we examined the impact on…
Descriptors: Social Influences, Prior Learning, Cooperative Learning, Redundancy
Alfieri, Louis; Nokes, Timothy J.; Schunn, Christian D. – Society for Research on Educational Effectiveness, 2011
Analogous thinking has been commonly discussed as being an inherent and distinguishing characteristic of human cognition (e.g., Gentner, 2010; Goldstone, Day, & Son, 2010; Holyoak, in press; Rittle-Johnson & Star, in press). Gentner (2003) has argued that as part of the human cognitive toolbox, comparison accompanied by the relational language to…
Descriptors: Constructivism (Learning), Instructional Design, Experiential Learning, Meta Analysis
Hausmann, Robert G. M.; VanLehn, Kurt – International Journal of Artificial Intelligence in Education, 2010
Self-explaining is a domain-independent learning strategy that generally leads to a robust understanding of the domain material. However, there are two potential explanations for its effectiveness. First, self-explanation generates additional "content" that does not exist in the instructional materials. Second, when compared to…
Descriptors: Instructional Design, Intelligent Tutoring Systems, College Students, Predictor Variables

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