Promoting Self-Efficacious Computer Science Education

Abstract

Computer science literacy is the key to surviving and thriving in the digital era. Unfortunately, given the negative stereotypes about who does computer science related work and what such work entails, many individuals are dissuaded from learning more about computer science and lack belief in their competence in computer science. As such, this dissertation aims to identify ways to make computer science education more self-efficacious using three connected studies, including (1) a mixed methods study on an intervention project for non-STEM major college students, (2) a practitioner study on a novel curriculum for middle school students, and (3) a study on the internal structure of a novel concept inventory for AI concepts. Findings from the first study confirm the importance of providing learners with mastery experiences in terms of helping them developing self-efficacy in coding. Findings from the second study provide teachers with teaching tips they could use while teaching the AI curriculum in their classrooms. Findings from the third study reveal the strengths and weaknesses of the AI concept inventory in accurately measuring respondents’ knowledge about AI.