Assessing computational thinking: A systematic review of empirical studies. (April 2020) - Tang, Xiaodan; Yin, Yue; Lin, Qiao; Hadad, Roxana; Zhai, Xiaoming
Abstract: With the increasing attention to Computational Thinking (CT) in education, there has been a concomitant rise of needs and interest in investigating how to assess CT skills. This study systematically reviewed how CT has been assessed in the literature. We reviewed 96 journal articles to analyze specific CT assessments from four perspectives: educational context, assessment construct, assessment type, and reliability and validity evidence. Our review results indicate that (a) more CT assessments are needed for high school, college students, and teacher professional development programs, (b) most CT assessments focus on students' programming or computing skills, (c) traditional tests and performance assessments are often used to assess CT skills, and surveys are used to measure students' CT dispositions, and (d) more reliability and validity evidence needs to be collected and reported in future studies. This review identifies current research gaps and future directions to conceptualize and assess CT skills, and the findings are expected to be beneficial for researchers, curriculum designers, and instructors. Highlights: A review of current CT assessments about context, construct, assessment type, and psychometric evidence. Fewer CT assessments were examined in high school, college, and professional development than in elementary school. Most CT assessments focused on students' programming or computing skills. Traditional and portfolio assessments were often used to assess CT, and surveys were used to measure CT dispositions. Half of the studies reported reliability and validity evidence of their CT assessment.