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We present a study that examines the effects of guidance on learning about addressing ill-defined problems in undergraduate bi- ology education. Two groups of college students used an online labo- ratory named VERA to learn about ill-defined ecological phenomena. While one group received guidance, such as giving the learners a specific problem and instruction on problem-solving methods, the other group re- ceived minimal guidance. The results indicate that, while performance in a problem-solving task was not different between groups receiving more vs. minimal guidance, the group that received minimal guidance adopted a more exploratory strategy and generated more interesting models of the given phenomena in a problem-solving task.
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Scientific Modeling Using Large Scale Knowledge
The intelligent research assistant, VERA, supports inquiry- based modeling by supplying contextualized large-scale domain knowl- edge in the Encyclopedia of Life. Learners can use VERA to construct conceptual models of ecological phenomena, run them as simulations, and review their predictions. A study on the use of VERA by college-level students indicates that providing access to large scale but contextual- ized knowledge helped students build more complex models and generate more hypotheses in problem-solving.
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- Award ID(s):
- 1636848
- PAR ID:
- 10205829
- Date Published:
- Journal Name:
- AIED 2020
- Volume:
- LNCS 12164
- Page Range / eLocation ID:
- 20-24
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/https://doi.org/10.1007/978-3-030-52240-7_4
