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Showing 1 to 15 of 18 results Save | Export
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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
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Mike, Koby; Hazzan, Orit – IEEE Transactions on Education, 2023
Contribution: This article presents evidence that electrical engineering, computer science, and data science students, participating in introduction to machine learning (ML) courses, fail to interpret the performance of ML algorithms correctly, since they fail to consider the application domain. This phenomenon is referred to as the domain neglect…
Descriptors: Engineering Education, Computer Science Education, Data Science, Introductory Courses
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Daniele Traversaro; Giorgio Delzanno; Giovanna Guerrini – Informatics in Education, 2024
Concurrency is a complex to learn topic that is becoming more and more relevant, such that many undergraduate Computer Science curricula are introducing it in introductory programming courses. This paper investigates the combined use of Sonic Pi and Team-Based Learning to mitigate the difficulties in early exposure to concurrency. Sonic Pi, a…
Descriptors: Misconceptions, Programming Languages, Computer Science Education, Undergraduate Students
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Ugray, Zsolt; Dunn, Brian K. – Journal of Information Systems Education, 2022
As Information Systems courses have become both more data-focused and student numbers have increased, there has emerged a greater need to assess technical and analytical skills more efficiently and effectively. Multiple-choice examinations provide a means for accomplishing this, though creating effective multiple-choice assessment items within a…
Descriptors: Quality Assurance, Information Systems, Computer Science Education, Student Evaluation
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Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Journal of Information Systems Education, 2023
Educators who teach programming subjects are often wondering "which programming language should I teach first?" The debate behind this question has a long history and coming up with a definite answer to this question would be farfetched. Nonetheless, several efforts can be identified in the literature wherein pros and cons of mainstream…
Descriptors: Comparative Analysis, Programming Languages, Probability, Error Patterns
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Hsu, Wen-Chin; Gainsburg, Julie – Journal of Educational Computing Research, 2021
Block-based programming languages (BBLs) have been proposed as a way to prepare students for learning to program in more sophisticated, text-based languages, such as Java. Hybrid BBLs add the ability to view and edit the block commands in auto-generated, text-based code. We compared the use of a non-hybrid BBL (Scratch), a hybrid BBL (Pencil…
Descriptors: Computer Science Education, Introductory Courses, Teaching Methods, Student Attitudes
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Yun Huang; Christian Dieter Schunn; Julio Guerra; Peter L. Brusilovsky – ACM Transactions on Computing Education, 2024
Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…
Descriptors: Programming, Computer Science Education, Error Patterns, Classification
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Sbaraglia, Marco; Lodi, Michael; Martini, Simone – Informatics in Education, 2021
Introductory programming courses (CS1) are difficult for novices. Inspired by "Problem solving followed by instruction" and "Productive Failure" approaches, we define an original "necessity-driven" learning design. Students are put in an apparently well-known situation, but this time they miss an essential ingredient…
Descriptors: Programming, Introductory Courses, Computer Science Education, Programming Languages
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Qian, Yizhou; Lehman, James – Journal of Educational Computing Research, 2020
This study implemented a data-driven approach to identify Chinese high school students' common errors in a Java-based introductory programming course using the data in an automated assessment tool called the Mulberry. Students' error-related behaviors were also analyzed, and their relationships to success in introductory programming were…
Descriptors: High School Students, Error Patterns, Introductory Courses, Computer Science Education
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Brown, Michael; DeMonbrun, R. Matthew; Teasley, Stephanie – Journal of Learning Analytics, 2018
In this study, we develop and test four measures for conceptualizing the potential impact of co-enrollment in different courses on students' changing risk for academic difficulty and recovery from academic difficulty in a focal course. We offer four predictors, two related to instructional complexity and two related to structural complexity (the…
Descriptors: At Risk Students, Dropout Prevention, Difficulty Level, College Curriculum
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Taniguchi, Tadanari; Maruyama, Yukiko; Kurita, Daisaku; Tanaka, Makoto – International Association for Development of the Information Society, 2018
We propose developing a method to set key educational skills which students need to achieve for each class using a student self-assessment questionnaire in analytical approach. It is difficult to set key academic skills for class since there are little systematic methods to set them. The questionnaire survey with 25 educational skills was…
Descriptors: Student Attitudes, Computer Science Education, Self Evaluation (Individuals), Information Technology
Velez, Martin – ProQuest LLC, 2019
Software is an integral part of our lives. It controls the cars we drive every day, the ships we send into space, and even our toasters. It is everywhere and we can easily download more. Software solves many real-world problems and satisfies many needs. Thus, unsurprisingly, there is a rising demand for software engineers to maintain existing…
Descriptors: Computer Science Education, Programming, Introductory Courses, Computer Software
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Lee, Nancy; Hong, Eunsook – IAFOR Journal of Education, 2017
The study described here explored the differential effects of two learning strategies, self-explanation and reading questions and answers, on learning the computer programming language JavaScript. Students' test performance and perceptions of effectiveness toward the two strategies were examined. An online interactive tutorial instruction…
Descriptors: Computer Science Education, Programming, Introductory Courses, High School Students
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Mannila, Linda – Informatics in Education, 2010
In this paper, we analyze the errors novice students make when developing invariant based programs. In addition to presenting the general error types, we also look at what students have difficulty with when it comes to expressing invariants. The results indicate that an introductory course utilizing the invariant based approach is suitable from…
Descriptors: Novices, Error Patterns, Difficulty Level, Introductory Courses
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Nikula, Uolevi; Gotel, Orlena; Kasurinen, Jussi – ACM Transactions on Computing Education, 2011
It has been estimated that more than two million students started computing studies in 1999 and 650,000 of them either dropped or failed their first programming course. For the individual student, dropping such a course can distract from the completion of later courses in a computing curriculum and may even result in changing their course of study…
Descriptors: Computer Science Education, Programming, Holistic Approach, College Curriculum
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