Computer‐based performance approach for critical thinking assessment in children.
Published In: British Journal of Educational Psychology, 2023, v. 93, n. 2. P. 531 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Uglanova, Irina; Orel, Ekaterina; Gracheva, Daria; Tarasova, Ksenia 3 of 3
Abstract
Background: Critical thinking (CT) has been identified as one of the key skills in the modern world. Despite a variety of CT assessment systems for secondary school and higher education, there is a shortage of CT assessments for children. Aims: To fill the gap, we developed a computer‐based performance assessment (CPBA) of CT with automatic scoring. In the study, we analysed: (1) To what extent is the internal structure of the critical thinking assessment tool confirmed? (2) What are the patterns of students' behaviour within the CPBA? (3) To what extent is the convergent validity of the CPBA supported? Sample and Methods: The sample consists of 1689 students, aged 9–11 years. To answer the research questions, the following quantitative data analysis methods were selected. The Bayesian Network was applied to investigate the internal structure. Latent Class Analysis was used to investigate the patterns of students' behaviour. To verify the convergent validity, the students were asked to solve the standardized math and language literacy tests. Results and Conclusions: The theoretically expected internal structure of the CPBA was confirmed: the two‐factor structure (the Analysis of information and the Making inferences subskills of CT) describes the data appropriately. Moreover, CT was described not as a list but as a sequence of cognitive operations. Four different strategies that lead to different results of CT were revealed. A weak positive correlation between the results of the CPBA and the achievement tests confirmed the test validity. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:British Journal of Educational Psychology. 2023/06, Vol. 93, Issue 2, p531
- Document Type:Article
- Subject Area:Education
- Publication Date:2023
- ISSN:0007-0998
- DOI:10.1111/bjep.12576
- Accession Number:163604728
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