Man (Echo) Su
Pattern, Agent, Interaction, Relation & Causality
To address students' persistent misconceptions about the cause-effect relations of scientific phenomena, the PAIR-C project developed and tested a series of interventions to teach the common structure that appears to underlie many science concepts and phenomena, and in particular, those in which students have misconceptions (i.e., the "emergence" schema). The new interventions we designed at the Learning and Cognition Lab are notably different from current instructional approaches in that they will address multiple process concepts and phenomena across a variety of disciplines by teaching the structure that underlies those concepts and phenomena rather than focusing on remediating one misconception at a time.
I am currently working on designing a PAIR-C Tutor using Cognitive Tutoring Authorization Tool (CTAT), you can check out some preliminary designs and ideas in this poster.
Highlights
In this multi-study project, I focused on designing and investigating the effectiveness of different types of simulations from the lens of the PAIR-C framework:
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Study 1: focused on examining the effect of business-as-usual (BAU) simulation with PAIR-C emergent prompts vs. BAU simulation with generic prompts (setting: high school classroom)
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No statistically significant difference was found between the two conditions
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In our efforts that use PAIR-C prompt questions to measure students’ understanding of diffusion and natural selection during simulation activities, we noticed that they continued to have persistent misconceptions. These misconceptions are not random ideas, but rather have underlying structures that can be coded systematically to align with the features of the PAIR-C framework. [paper in ICLS 2020]
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Study 2: focused on examining the effect of a PAIR-C agent-based modeling (ABM) simulation module with PAIR-C emergent prompts vs. a BAU simulation module with PAIR-C emergent prompts (setting: online summer school for high school students)
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No statistically significant difference was found between the two conditions
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In our efforts to measure students' understanding of natural selection, although the pre-posttest did not capture significant differences between the two conditions, PAIR-C prompt questions embedded in both simulation modules successfully captured the differences. Students from the Intervention condition showed fewer frequencies and categories of misconceptions than the control condition. [paper in ICLS 2021]
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Study 3 (My dissertation): focused on examining the effect of PAIR-C agent-based simulation module with generic prompts vs. Regular agent-based simulation module with generic prompts (setting: online class for college students)
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PAIR-C ABM simulation module with generic prompts(Intervention condition) > Regular ABM simulation module with generic prompts (Control condition)
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Statistically significant difference was found between the two conditions in their performance on deep-level understanding of natural selection.
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The intervention group demonstrated drastically fewer categories and numbers of misconceptions while those in the control group did not show such drastic changes. [paper in ICLS 2023]
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