On the Predictors of Computational Thinking and Its Relationship with Artificial Intelligence

Computational thinking (CT) is an important twenty-first-century skill. Since the edited volume at hand aims to look at artificial intelligence, the relationship between CT and artificial intelligence is first discussed. CT comprises computational concepts, computational practices, and computational perspectives. This chapter aims to investigate the predictors of computational perspectives among high-school students. The hypothesized predictors are grouped into three areas: (1) student characteristics, (2) home environment, and (3) learning opportunities. Computational perspectives are captured with the Computational Thinking Scale (CTS) that comprises five dimensions: creativity, algorithmic thinking, cooperativity, critical thinking, and problem solving. N = 202 high-school students act as the sample, and linear regression is the analysis method used. The best in-sample prediction is possible for algorithmic thinking (R2 = .511). For cooperativity, the explanatory power of our model is rather weak (R2 = .146). Across all five CTS dimensions, CT self-concept is the best predictor for computational perspectives. There are also findings that contradict the developed hypotheses. Mathematics skills negatively predicted creativity. The association between reasoning ability and cooperativity was negative, contrary to evidence that more intelligent individuals are better at cooperating. Moreover, critical thinking was negatively associated with the duration of computer use. The results are compared with findings from a study that relies on a performance test to measure CT.