Engineering Students' Self-Efficacy, Perceptions, and Performance in a Flipped CS1 Course
- URL: http://arxiv.org/abs/2606.01471v1
- Date: Sun, 31 May 2026 22:07:49 GMT
- Title: Engineering Students' Self-Efficacy, Perceptions, and Performance in a Flipped CS1 Course
- Abstract summary: This research paper investigates how engineering students' course-related beliefs relate to exam performance in a flipped introductory programming course.<n>An exploratory factor analysis identified three latent factors: self-efficacy, attitudes toward learning, and perceived programming difficulty.
- Score: 0.7734726150561086
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: This full research paper investigates how engineering students' course-related beliefs relate to exam performance in a flipped introductory programming course. Understanding factors that influence student learning and performance has long been a focus of computing education research. While prior studies have identified psychological and contextually relevant predictors of success, much of this work has examined students majoring in computer science. Yet introductory programming courses now serve many students from other disciplines, whose beliefs and motivations may differ. To examine these relationships in an engineering-focused CS1 context, we analyze survey and exam data from 602 students. An exploratory factor analysis identified three latent factors: self-efficacy, attitudes toward learning, and perceived programming difficulty. Self-efficacy was positively associated with exam performance, while perceived difficulty was negatively associated. Differences in reported beliefs were also observed across demographic groups, even when performance outcomes were similar. These findings align with and extend prior research, highlighting the role of self-efficacy in achievement and persistence in computing education.
Related papers
- Assessing Engineering Student Perceptions of Introductory CS Courses in an Indian Context [6.237405036268818]
This study explores engineering students' perceptions of assessment practices in an introductory computer science/ programming course.<n>Students largely perceive lab assignments as effective learning activities and view exams and projects as authentic and skill-enhancing.<n>Students appreciated the role of instructors in shaping course content and found teaching assistants to be approachable and helpful.
arXiv Detail & Related papers (2025-08-06T19:04:19Z) - Exploring LLM-based Student Simulation for Metacognitive Cultivation [33.346260553878984]
We propose a pipeline for automatically generating and filtering high-quality simulated student agents.<n>Our work paves the way for broader applications in personalized learning and educational assessment.
arXiv Detail & Related papers (2025-02-17T11:12:47Z) - DASKT: A Dynamic Affect Simulation Method for Knowledge Tracing [51.665582274736785]
Knowledge Tracing (KT) predicts future performance by students' historical computation, and understanding students' affective states can enhance the effectiveness of KT.<n>We propose Affect Dynamic Knowledge Tracing (DASKT) to explore the impact of various student affective states on their knowledge states.<n>Our research highlights a promising avenue for future studies, focusing on achieving high interpretability and accuracy.
arXiv Detail & Related papers (2025-01-18T10:02:10Z) - The Influence and Relationship between Computational Thinking, Learning Motivation, Attitude, and Achievement of Code.org in K-12 Programming Education [0.0]
This study examined the impact of Code.org's block-based coding curriculum on primary school students' computational thinking, motivation, attitudes, and academic performance.
arXiv Detail & Related papers (2024-12-05T00:12:26Z) - Integrating Attentional Factors and Spacing in Logistic Knowledge Tracing Models to Explore the Impact of Training Sequences on Category Learning [37.80414603767789]
This study introduces a novel integration of attentional factors and spacing into the logistic knowledge tracing (LKT) models.
Our findings reveal that incorporating both attentional factors and spacing features in the Additive Factors Model (AFM) significantly enhances its capacity to capture the effects of interleaving and blocking.
arXiv Detail & Related papers (2024-06-22T20:22:19Z) - Overwhelmed software developers: An Interpretative Phenomenological
Analysis [43.18707677931078]
We interviewed two software developers who have experienced overwhelm recently.
We uncover seven categories of overwhelm (communication, disturbance, organizational, variety, technical, temporal, and positive overwhelm)
Participants reported that overwhelm can sometimes be experienced to be positive and pleasant, and it can increase their mental focus, self ambition, and productivity.
arXiv Detail & Related papers (2024-01-05T12:39:08Z) - Psychological Aspects of Pair Programming [0.0]
This study aims to gain quantitative and qualitative insights into pair programming.
The research's goal is to use the findings to design further studies on pairing with artificial intelligence.
arXiv Detail & Related papers (2023-06-12T20:57:50Z) - Understanding Self-Efficacy in the Context of Software Engineering: A
Qualitative Study in the Industry [2.268415020650315]
Self-efficacy is a concept researched in various areas of knowledge that impacts various factors such as performance, satisfaction, and motivation.
This study aims to understand the impact on the software development context with a focus on understanding the behavioral signs of self-efficacy.
arXiv Detail & Related papers (2023-05-26T17:16:37Z) - Task Formulation Matters When Learning Continually: A Case Study in
Visual Question Answering [58.82325933356066]
Continual learning aims to train a model incrementally on a sequence of tasks without forgetting previous knowledge.
We present a detailed study of how different settings affect performance for Visual Question Answering.
arXiv Detail & Related papers (2022-09-30T19:12:58Z) - Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units
and a Unified Framework [83.21732533130846]
The paper focuses on large in-the-wild databases, i.e., Aff-Wild and Aff-Wild2.
It presents the design of two classes of deep neural networks trained with these databases.
A novel multi-task and holistic framework is presented which is able to jointly learn and effectively generalize and perform affect recognition.
arXiv Detail & Related papers (2021-03-29T17:36:20Z) - How Does a Student-Centered Course on Communication and Professional
Skills Impact Students in the Long Run? [0.0]
This paper presents a long-term study about the effects of a student-centered course on students' thoughts, attitudes, and behavior.
The course is offered at a European university as part of a computer science master's program.
Our findings suggest that the course provided significant learning for the vast majority of respondents.
arXiv Detail & Related papers (2021-01-04T10:51:40Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.