Assessing Instructors’ Perceptions of Critical Skills in Computational Thinking and Block-Based Programming: A Needs Assessment Approach

This study investigates the discrepancy between instructors' perceptions of students' computational thinking (CT) and block-based programming (BBP) skills and the actual competence of the students. The sample comprised 47 instructors from five Rajabhat Universities in Southern Thailand, teaching programming-related courses at undergraduate and graduate levels during the 2023 academic year. Data were collected via online questionnaires, with reliability scores of 0.89 and 0.88 for the CT skills assessment, and 0.77 and 0.76 for the BBP skills assessment, for both desired (I) and actual (D) states. Analysis using means, standard deviations, the modified Priority Needs Index (PNImodified), and t-tests for dependent groups revealed significant gaps between desired and actual skill levels. The most critical needs were identified in algorithm design and decomposition for CT skills, and function writing for BBP skills. These results highlight the need for targeted interventions to address the discrepancy between instructors' expectations and students' abilities.