Josef Guggemos

Computational Thinking (CT) may be an important 21st-century skill. However, due to its multifaceted nature, it is unlikely to observe one overarching computational thinking profile. Rather, students might be assumed to have specific strengths and weaknesses. Hence, a latent profile analysis as a person-centered approach of assessment could yield valuable insights with implications for theory and practice. In the present study, we utilize the Computational Thinking Scales (CTS), an internationally accepted self-assessment instrument, to identify latent CT profiles. CTS comprises five CT dimensions: creativity, algorithmic thinking, cooperativity, critical thinking, and problem solving. Relying on a sample of 202 high-school students from German-speaking Switzerland, we identified four latent profiles. Two of these may be of particular interest. One profile includes students with, on the one hand, moderate to high creative thinking ability, cooperativity, and critical thinking skills and, on the other hand, low algorithmic thinking ability. The second remarkable profile consists of students with particularly low cooperativity. We validate the findings by examining the relationship between the latent profile membership and scores on the Computational Thinking test (CTt), an internationally accepted performance test. Indeed, students in the two remarkable CT profiles differ significantly in their CTt performance.