This paper, titled “Self-efficacy Feedback Loops and Learning Experiences in CS1”, ITiCSE ‘23: the 28th ACM Conference on on Innovation and Technology in Computer Science Education. The conference took place from July 10-12 in Turku, Finland.

The abstract of the paper is:

Self-efficacy refers to a students’ beliefs about whether they can succeed in a particular domain. Students’ self-efficacy beliefs are known to influence learning outcomes, through the effect they have on students’ goal setting, learning strategies, and resilience behaviors. The strongest precursor to the formation of self-efficacy beliefs are students’ own experiences completing learning tasks. Students complete learning exercises, they receive feedback, and they use this information to revise their self-beliefs. Successes can bolster an individual’s self-efficacy for future learning tasks, and failures can damage an individual’s self-efficacy. Self-efficacy can also form a reciprocal feedback loop, because performance feedback informs revisions to individuals’ self-efficacy beliefs, and self-efficacy beliefs in turn influence adaptive behaviors that lead to better or worse learning outcomes. In this study we examined the self-efficacy beliefs of CS1 students at a large university during two semesters in an intensive longitudinal examination of the development of these beliefs. We examined CS1 students’ self-efficacy beliefs and course performance over the course of a semester, using structural equation models designed to detect reciprocal effects. We found strong evidence in both semesters that such reciprocal feedback loops for self-efficacy can occur in CS1, although the reciprocal effects may die down by the end of the semester.

The paper can be viewed here:

ITICSE 2023 Paper