Research exploring the connection between students’ learning and their psychological factors (e.g., emotions, attitudes, and beliefs) is often grounded in models and theories from literature related to psychology and learning sciences. These theories provide insights into how psychological factors influence students’ learning, motivation, and academic performance. To deepen our understanding of the interplay between these factors and students’ learning and performance, this paper provides findings from a systematic literature review (SLR) of research studies about theories and methods used to understand the emotions and self-efficacy of undergraduate computing and engineering students. We examined thirty studies published between 2005 and 2023 in top-tier academic venues for computing and engineering education research. These studies leverage diverse methodologies, including validated surveys, physiological biomarkers, and grounded theory approaches, to explore the nuances of students’ emotions and self-efficacy in computing and engineering education. We discuss how these factors are defined in the literature, the methods applied to measure and analyze them, and the implications for future research and educational practice. This SLR could assist computing and engineering education researchers in designing rigorous research studies focused on exploring these factors in students’ learning. Furthermore, this may provide educators with a reference for devising effective teaching strategies to improve students’ perceptions of computing, thereby enhancing their academic achievement.