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Cheers, Hayden; Lin, Yuqing – Computer Science Education, 2023
Background and Context: Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, such tools do not identify plagiarism, nor suggest what assignment submissions are suspicious of plagiarism. Source code plagiarism…
Descriptors: Plagiarism, Programming, Computer Science Education, Identification
Shindler, Michael; Pinpin, Natalia; Markovic, Mia; Reiber, Frederick; Kim, Jee Hoon; Carlos, Giles Pierre Nunez; Dogucu, Mine; Hong, Mark; Luu, Michael; Anderson, Brian; Cote, Aaron; Ferland, Matthew; Jain, Palak; LaBonte, Tyler; Mathur, Leena; Moreno, Ryan; Sakuma, Ryan – Computer Science Education, 2022
Background and Context: We replicated and expanded on previous work about how well students learn dynamic programming, a difficult topic for students in algorithms class. Their study interviewed a number of students at one university in a single term. We recruited a larger sample size of students, over several terms, in both large public and…
Descriptors: Misconceptions, Programming, Computer Science Education, Replication (Evaluation)
Hugo G. Lapierre; Patrick Charland; Pierre-Majorique Léger – Computer Science Education, 2024
Background and Context: Current programming learning research often compares novices and experienced programmers, leaving early learning stages and emotional and cognitive states under-explored. Objective: Our study investigates relationships between cognitive and emotional states and learning performance in early stage programming learners with…
Descriptors: Programming, Computer Science Education, Psychological Patterns, Cognitive Processes
Frede, Christiane; Knobelsdorf, Maria – Computer Science Education, 2021
Background and Context: Considerable numbers of Computer science (CS) undergraduate majors struggle in Theory of Computation (ToC) courses, which strengthen bimodality beliefs of student performance. Reasons for students struggling are assumed to be manifold but substantial ground is based on studies providing singular insights into this matter.…
Descriptors: Computer Science Education, Academic Achievement, Introductory Courses, Computation
Akkaya, Ali; Akpinar, Yavuz – Computer Science Education, 2022
Background and Context: Though still a nascent area of research, serious games have been presented as means of engaging students in computer programming and computational thinking due to their immersive and interactive nature. Existing research is limited in its ability to provide systems based on sound instructional design models, and only a few…
Descriptors: Experiential Learning, Educational Games, Instructional Design, Programming
Amanda A. Barrett; Colin T. Smith; Courtni H. Hafen; Emilee Severe; Elizabeth G. Bailey – Computer Science Education, 2024
Background and Context: While biology has strong female representation, computer science is the least gender equitable of the STEM fields. A better understanding of the barriers that keep women out of computational fields will help overcome those barriers to create a more diverse workforce. Objective: We investigated the complexities that…
Descriptors: Sex Role, Majors (Students), Prior Learning, Computer Science Education
Hawlitschek, Anja; Dietrich, André; Zug, Sebastian – Computer Science Education, 2023
Background and Context: During online learning, it is essential to provide instructional guidance to support learning. However, guidance can be given in different forms and quantities. Thus, one important challenge is to provide the right amount and type of instructional guidance. Objective: The aim of the study is to investigate types of guidance…
Descriptors: Computer Science Education, Electronic Learning, Distance Education, Teaching Methods
Hao, Qiang; Smith, David H., IV; Ding, Lu; Ko, Amy; Ottaway, Camille; Wilson, Jack; Arakawa, Kai H.; Turcan, Alistair; Poehlman, Timothy; Greer, Tyler – Computer Science Education, 2022
Background and Context: automated feedback for programming assignments has great potential in promoting just-in-time learning, but there has been little work investigating the design of feedback in this context. Objective: to investigate the impacts of different designs of automated feedback on student learning at a fine-grained level, and how…
Descriptors: Computer Science Education, Feedback (Response), Teaching Methods, Comparative Analysis
Lehman, Kathleen J.; Newhouse, Kaitlin N. S.; Sundar, Sarayu; Sax, Linda J. – Computer Science Education, 2023
Background and Context: As computing fields aim to both expand and diversify, narrowing representation gaps in undergraduate computing majors requires focus on retaining women and racially/ethnically minoritized students to the point of degree attainment. Objective: This study addresses the factors that contribute to persistence in computing…
Descriptors: Majors (Students), Undergraduate Students, Academic Persistence, Computer Science Education
Mouza, Chrystalla; Sheridan, Scott; Lavigne, Nancy C.; Pollock, Lori – Computer Science Education, 2023
Background and Context: A key challenge in advancing computer science education in K-12 schools is teacher preparation and support. School-university partnerships and service-learning programs where undergraduates assist teachers represent one promising approach to supporting K-12 computer science teaching. Objectives: In this work, we examine the…
Descriptors: Undergraduate Students, Elementary Secondary Education, Computer Science Education, College School Cooperation
Aljumaily, Harith; Cuadra, Dolores; Laefer, Debra F. – Computer Science Education, 2019
Background: Conceptual models are an essential phase in software design, but they can create confusion and reduced performance for students in Database Design courses. Objective: A novel Relational Data Model Validation Tool (MVTool) was developed and tested to determine (1) if students who use MVTool perform better than those who do not, and (2)…
Descriptors: Models, Databases, Computer Science Education, Skills
Pantic, Katarina; Clarke-Midura, Jody – Computer Science Education, 2023
Background and Context: Despite over 30 years of research on broadening participation, women are still underrepresented in Computer Science (CS) education. While enrolment in CS majors has increased, women earn only 18% of the CS baccalaureate degrees in the US. Objective: Most research focuses on why women leave CS. This study explores factors…
Descriptors: Computer Science Education, Majors (Students), Females, Womens Education
Xie, Benjamin; Loksa, Dastyni; Nelson, Greg L.; Davidson, Matthew J.; Dong, Dongsheng; Kwik, Harrison; Tan, Alex Hui; Hwa, Leanne; Li, Min; Ko, Andrew J. – Computer Science Education, 2019
Background and Context: Current introductory instruction fails to identify, structure, and sequence the many skills involved in programming. Objective: We proposed a theory which identifies four distinct skills that novices learn incrementally. These skills are tracing, writing syntax, comprehending templates (reusable abstractions of programming…
Descriptors: Programming, Skill Development, Computer Science Education, Instructional Design
Moskal, Adon Christian Michael; Wass, Rob – Computer Science Education, 2019
Background and Context: Encouraging undergraduate programming students to think more about their software development processes is challenging. Most programming courses focus on coding skill development and mastering programming language features; subsequently software development processes (e.g. planning, code commenting, and error debugging) are…
Descriptors: Computer Software, Undergraduate Students, Programming, Programming Languages
Gal-Ezer, Judith; Trakhtenbrot, Mark – Computer Science Education, 2016
Reduction is one of the key techniques used for problem-solving in computer science. In particular, in the theory of computation and complexity (TCC), mapping and polynomial reductions are used for analysis of decidability and computational complexity of problems, including the core concept of NP-completeness. Reduction is a highly abstract…
Descriptors: Computer Science Education, Problem Solving, Computation, Difficulty Level