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Recently, higher education has seen an increasing emphasis on the prominent role of computational thinking in all disciplines. Computational thinking is advocated as not only a fundamental skill or concept in computer science but also a core competency for all disciplines. Teaching students in non-computer science majors computing thinking is challenging because students do not have experts' mental models. This study investigates the knowledge gap that non-computing major college students (n=126) possess about computational thinking in an introductory MS Excel course by measuring their performance using spreadsheet functions in three categories: recall, application, and problem solving. The empirical result, analyzed using ANOVA, shows that students can recall the meaning of those functions but seem to have trouble using them correctly and precisely (cued or uncued). Students' test results suggest the following issues: (1) problems with understanding the data type, (2) failure in translating problems to productive representations using spreadsheet functions, and (3) inadequate stipulation of the computational representations in precise forms. Addressing these problems early and explicitly in future classes could improve the education of computational thinking and alleviate difficulties students may experience in using computational thinking in learning and problem solving.