Journal
COMPUTERS & EDUCATION
Volume 161, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compedu.2020.104060
Keywords
Computational thinking level and growth; Gender and home environment; Reasoning skills; Motivation; Longitudinal study
Funding
- Basic Research Fund at the University of St.Gallen [1031542]
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This study investigated CT predictors among upper secondary students in a longitudinal and natural classroom setting, finding that CT self-concept, reasoning skills, gender, computer literacy, duration of computer use, and formal learning opportunities have strong associations with CT level and growth.
Computational thinking (CT) is a key 21st-century skill. This paper contributes to CT research by investigating CT predictors among upper secondary students in a longitudinal and natural classroom setting. The hypothesized predictors are grouped into three areas: student characteristics, home environment, and learning opportunities. CT is measured with the Computational Thinking Test (CTt), an established performance test. N = 202 high-school students, at three time points over one school year, act as the sample and latent growth curve modeling as the analysis method. CT self-concept, followed by reasoning skills and gender, show the strongest association with the level of CT. Computer literacy, followed by duration of computer use and formal learning opportunities during the school year, have the strongest association with CT growth. Variables from all three areas seem to be important for predicting either CT level or growth. An explained variance of 70.4% for CT level and 61.2% for CT growth might indicate a good trade-off between the comprehensiveness and parsimony of the conceptual framework. The findings contribute to a better understanding of CT as a construct and have implications for CT instruction, e.g., the role of computer science and motivation in CT learning.
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