Sequential Patterns of Strategy Use During Simulation-Based Discovery Learning

• In Event: AERA Poster Session 2
  In Poster Session: Intersections Among Technology, Instruction, Cognition, Learning, and More

Abstract

Simulation-based discovery learning offers learners the opportunity to acquire causal models of scientific phenomena. The purpose of this study was to investigate patterns of learner actions and utterances that affect outcomes of simulation-based discovery. We conducted a sequential analysis of data gathered from 11 undergraduate students engaged in discovery learning. Three related methods were used for the sequential analysis: Levenshtein edit distance, k-means clustering of the Levenshtein distance, and the Kohonen median sequence. The median sequences of high-gaining and low-gaining participants showed qualitative differences in how they gathered evidence, stated claims, and drew explanatory inferences. Differences between the sequences of actions and utterances of high-gaining and low-gaining participants suggested ways that students might be guided to enhance discovery learning.

Authors

• Teeba Obaid, Simon Fraser University

• John Cale Nesbit, Simon Fraser University

• Misha Jain, Simon Fraser University

• Shiva Hajian, Simon Fraser University

• Ahmad Mahmoody