Designing a Real-Time Intervention to Address Negative Self-Assessments While Programming
Melissa Chen, Eleanor O’Rourke · 2023
Enrollments in university-level introductory computing courses are skyrocketing [3], but many students struggle in these courses [2]. Recent research suggests that student perceptions of the programming process may contribute to this problem. Students often have inaccurate expectations of programming that may lead them to negatively assess their abilities in response to natural programming moments [6]. For example, many students believe they are doing poorly when they use resources to look up syntax, even though this is considered good practice [7]. This is important because negative self-assessments correlate with lower self-efficacy [6], or one’s belief that they can achieve a goal [1], and students with lower self-efficacy tend to exhibit lower persistence in undergraduate computing programs [9]. In this poster, we present an initial design and evaluation of an intervention that aims to reduce overly negative self-assessments and improve self-efficacy by providing real-time feedback as students program.