Ernesto Panadero , Leire Pinedo , Javier Fernández Ruiz
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Unleashing think-aloud data to investigate self-assessment: Quantitative and qualitative approaches
Background
Think-aloud is a process data method that provides detailed insights into students’ cognitive, emotional, and motivational processes. This makes it an ideal method for investigating self-assessment as, the vast majority of times, it occurs internally without obvious external cues. In this paper, we present a methodological overview based on three previous empirical studies, utilizing both quantitative and qualitative methods to analyze think-aloud data and explore the ‘black box’ of self-assessment.
Methods
A total of 67 secondary education students and 126 university students participated concurrently thinking-aloud while self-assessing academic tasks they had previously completed.
Results
We compare our two methodological approaches to analyzing think-aloud data, highlighting the coding schemes, data analysis techniques, and the critical decisions made during the think-aloud process.
Conclusions
Our findings demonstrate how think-aloud can be effectively employed through complementary quantitative and qualitative methods, providing a comprehensive understanding of the self-assessment phenomena.
期刊介绍:
As an international, multi-disciplinary, peer-refereed journal, Learning and Instruction provides a platform for the publication of the most advanced scientific research in the areas of learning, development, instruction and teaching. The journal welcomes original empirical investigations. The papers may represent a variety of theoretical perspectives and different methodological approaches. They may refer to any age level, from infants to adults and to a diversity of learning and instructional settings, from laboratory experiments to field studies. The major criteria in the review and the selection process concern the significance of the contribution to the area of learning and instruction, and the rigor of the study.