Unlocking the power of robots: enhancing computational thinking through innovative teaching methods

Abstract

This research proposes the integration of robotic education and scenario-based learning (SBL) paradigm for teaching computational thinking (CT) to enhance the computational abilities of primary school students, based on digital innovation and a teaching assistant robot acceptance model. The sample group consisted of 532 primary school teachers and 33 first-grade students in Thailand. The study demonstrated that a causal model was consistent with the empirical data (Chi-square = 216.06, df = 262, p = 0.000, GFI = 0.98, AGFI = 0.95, RMR = 0.018, RMSEA = 0.000). The result found that "Facilitating Conditions' have a positive effect on "Perceived Usefulness' (β = 0.19), "Subjective Norm Conformance" influences "Perceived Usefulness' (β = 0.49), "Perceived Ease of Use" influences "Perceived Usefulness' (β = 0.26), "Perceived Usefulness' influenced "Attitudes Toward Technology" (β = 0.12), "Attitudes Toward Technology" influenced "Behavioral Intention" (β = 0.88), and "The Facilitating Conditions' had an inverse effect on "Behavioral Intention" (β = −0.16). Moreover, teaching assistant robots for primary school students were developed, which consist of: (1) characteristics and components of teaching assistant robots, namely the central processing unit, driving system, wheels, recognition part, display and sound section, power supply, etc. and (2) seven scenario-based learning activities designed to guide teachers, instructors, and educators to effectively implement a robot aimed at improving young students' computational thinking abilities.