NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Chin, Doris B.; Dohmen, Ilsa M.; Cheng, Britte H.; Oppezzo, Marily A.; Chase, Catherine C.; Schwartz, Daniel L. – Educational Technology Research and Development, 2010
One valuable goal of instructional technologies in K-12 education is to prepare students for future learning. Two classroom studies examined whether Teachable Agents (TA) achieves this goal. TA is an instructional technology that draws on the social metaphor of teaching a computer agent to help students learn. Students teach their agent by…
Descriptors: Concept Mapping, Educational Technology, Elementary School Students, Science Instruction
Fisher, Kathleen M. – 1985
A small set of relationships has been identified which appears to be sufficient for describing all molecular and cellular reactions and structures discussed in an introductory biology course. A precise definition has been developed for each relationship. These 20 relationships are of four types: (1) analytical; (2) spatial; (3) temporal; and (4)…
Descriptors: Artificial Intelligence, Biology, Cognitive Psychology, College Science
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
Smith, Karl A. – Engineering Education, 1987
Differentiates between learning efficiency (enhancing the rate of learning) and learning effectiveness (enhancing the mastery and retention of facts, concepts, and relationships). Discusses some of the contributions of knowledge engineering to metalearning. Provides a concept map for constructing knowledge bases, along with some possible…
Descriptors: Artificial Intelligence, College Science, Concept Formation, Concept Mapping