An Analysis of Students’ Cognitive Bias in Experimental Activities Following a Lab Manual
Bibliographic Data
| ID | 22048478 |
|---|---|
| Authors | Seong Un Kim (0000-0001-7455-6077, Korea National University of Education, corresponding author), Il Ho Yang (Korea National University of Education) |
| Year | 2020 |
| Volume | 10 |
| Issue | 3 |
| Pages | 80 |
| Publication date | 2020-03-20 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Education Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci10030080 |
| OpenAlex | W3011661896 |
| Language | EN |
| References cited | 45 |
The purpose of this study is to develop a thinking process model that reveals cognitive bias through analyzing students’ cognitive biases in processing experimental manuals. Twenty-two college students participated in the study. During the “making electromagnets” experimental activity, we collected students’ concurrent verbal protocols, gaze positions, and experimental behaviors. After the experiment, we collected their retrospective verbal protocols and ensured reliability by diversifying the data. The collected data were analyzed inductively using the grounded theory methodology. The results showed that four categories of paradigm (causal conditions, phenomena, interactions, and contextual conditions) and fifteen concepts were derived. Students displayed bias in following the manual instructions due to the influence of causal conditions. When embodying biased representations as workspace entities, biased responses come from the influence of contextual conditions. Therefore, these can be developed in consideration of causal and contextual conditions when developing a manual, thereby reducing cognitive bias among students, and ultimately helping them perform accurate experiments
Cognition · Cognitive psychology · Workspace · Computer Science · Educational Strategies and Epistemologies · Psychology · Science Education and Pedagogy · Visual and Cognitive Learning Processes · Artificial Intelligence
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| Highly cited | No |
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