The value of introspective measures in aptitude-treatment interaction research
A window on individual differences in action
To explore the value of introspective measures in aptitude-treatment interaction (ATI) research, this study
analyzed the cognitive profiles and concurrent think-alouds of six university learners of Japanese who were highly successful,
moderately successful, or unsuccessful under two computer-mediated feedback conditions in a larger (N = 80)
quantitative ATI investigation (Sachs, 2011). That study had made indirect inferences
regarding relationships among individual differences (IDs), cognitive processes, and learning on the basis of correlational
results. Using Leow’s (2015) depth-of-processing (DoP) framework as a lens, what we
found in the qualitative verbalization data highlighted that learners in the same condition with similar strengths in the IDs that
are statistically associated with performance at the group level may nonetheless engage in different cognitive processes and
achieve different learning outcomes, and vice versa. The findings also pointed toward more complex ID-DoP and ID-ID interactions
that future research could explore, such as the possibility that a weakness in memory might limit the benefits of metalinguistic
knowledge and analytic processing in a condition where group-level correlations suggest analysis is relevant to success, or that
analytic processing might enhance the value of memory in a condition where memory is relevant to success. In our conclusions, we
argue for the value of mixed-methods research in this area.
Article outline
- Introduction
- Review of literature
- The value of introspective measures in feedback research
- The value of introspective measures in ATI research
- Methods
- Participants
- Linguistic target
- Procedure
- Treatments and tests
- Concurrent think-alouds
- Results and discussion
- Right/Wrong-feedback condition
- Marvin vs. Henry: Fairly similar on the IDs predicting performance in the Right/Wrong condition, but with different processing and different learning outcomes
- Nora: Weaknesses in IDs plus shallow processing confirm the overall ATI patterns
- Diagrams-feedback condition
- Matt vs. Heath: Fairly similar on the IDs predicting performance in the Diagrams condition, but with different processing and different learning outcomes, possibly related to other IDs
- Natalie: IDs might interact and limit one another
- Limitations, conclusions, and future research
- Note
-
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Cited by
Cited by 1 other publications
Al-Chalabi, Humam K. Majeed & Aqeel M. Ali Hussein
2020.
2020 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI),
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