Misconception Analysis Based on Feedback of Computational Thinking Result of College Students

Abstract

This research has purposes to analyse misconceptions of college students based on feedback of their computational thinking test. This descriptive quantitative research involves fourth semester college students of 4C class of primary school education teacher program by using random sampling. The instruments are test instrument consisting of computational thinking indicators and questionnaires semi structured to identify and analyse of factor causing misconception of the students. The results were then analysed descriptively by using cluster analysis and crosschecked to questionnaire and interview results. The findings show computational thinking of the students was within algorithm stage meanwhile misconception is found in movement system material. The causal reasons of the misconception are grouped into 3 clusters. Cluster 1, the students have already understood the concept but their misconception is 33.3%. Cluster 2, misconception of the students is 38.1%. Cluster 3, the students have not understood the concept with percentage 28.6%. The contributing factors to misconception are students' arguments that animals/plants have similar natures to human, handbook, lecturer's explanation, scientific name, mathematics calculation, formula, graphic understanding, influences of peer in answering, and students' experiences in daily life.