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Boxuan Ma; Li Chen; Shin’ichi Konomi – International Association for Development of the Information Society, 2024
Generative artificial intelligence (AI) tools like ChatGPT are becoming increasingly common in educational settings, especially in programming education. However, the impact of these tools on the learning process, student performance, and best practices for their integration remains underexplored. This study examines student experiences and…
Descriptors: Artificial Intelligence, Computer Science Education, Programming, Computer Uses in Education
Kumar, Amruth N. – International Educational Data Mining Society, 2023
Is there a pattern in how students solve Parsons puzzles? Is there a difference between the puzzle-solving strategies of C++ and Java students? We used Markov transition matrix to answer these questions. We analyzed the solutions of introductory programming students solving Parsons puzzles involving if-else statements and while loops in C++ and…
Descriptors: Markov Processes, Puzzles, Introductory Courses, Computer Science Education
Phung, Tung; Cambronero, José; Gulwani, Sumit; Kohn, Tobias; Majumdarm, Rupak; Singla, Adish; Soares, Gustavo – International Educational Data Mining Society, 2023
Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…
Descriptors: Computational Linguistics, Feedback (Response), Programming, Computer Science Education
Hoffman, Heather J.; Elmi, Angelo F. – Journal of Statistics and Data Science Education, 2021
Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students' experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures…
Descriptors: Statistics Education, Programming Languages, Troubleshooting, Coding
Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation
Shi, Yang; Schmucker, Robin; Chi, Min; Barnes, Tiffany; Price, Thomas – International Educational Data Mining Society, 2023
Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…
Descriptors: Computer Science Education, Data Analysis, Programming, Coding
Chen, Chen; Haduong, Paulina; Brennan, Karen A.; Sonnert, Gerhard; Sadler, Philip M. – AERA Online Paper Repository, 2017
The impact of a novice programmer's first language on their subsequent achievement in further computing education has been the subject of much study in the field of computer science education. Our research is a retrospective study of more than 10,000 undergraduate students enrolled in CS1 (introduction to computer programming) from 118 US college…
Descriptors: Undergraduate Students, Computer Science Education, Novices, Programming
Maranga, Jemar Jude A.; Matugas, Leilla Keith J.; Lim, Jorge Frederick W.; Romana, Cherry Lyn C. Sta. – International Association for Development of the Information Society, 2019
Teaching an introductory programming course to an average of 40 students while monitoring their performance can be a challenge for instructors. Preparing coding exercises with test cases and checking students' programs can prove to be time consuming at times. Moreover, programming has been known to be quite difficult for students to learn. To…
Descriptors: Online Courses, Programming Languages, Introductory Courses, Computer Science Education
Tan, Wee Lum; Venema, Sven; Gonzalez, Ruben – International Association for Development of the Information Society, 2017
Transitioning to university is recognised as a challenging endeavour for commencing students. For commencing Computer Science students specifically, evidence suggests a link between poor performance in introductory technical courses, such as programming, and high attrition rates. Building resilience in students, particularly at the start of their…
Descriptors: College Freshmen, Computer Science Education, Programming, Introductory Courses
Kortsarts, Yana; Morris, Robert W.; Utell, Janine M. – Information Systems Education Journal, 2010
Bioinformatics is a relatively new interdisciplinary field that integrates computer science, mathematics, biology, and information technology to manage, analyze, and understand biological, biochemical and biophysical information. We present our experience in teaching an interdisciplinary course, Introduction to Bioinformatics, which was developed…
Descriptors: Interdisciplinary Approach, Introductory Courses, Biology, Information Science
Brusilovsky, P.; And Others – 1994
Three different approaches to teaching introductory programming are reviewed: the incremental approach, the sub-language approach, and the mini-language approach. The paper analyzes all three approaches, providing a brief history of each and describing an example of a programming environment supporting this approach. In the incremental approach,…
Descriptors: Computer Science Education, Foreign Countries, Introductory Courses, Programming
Urbaczewski, Andrew; Urbaczewski, Lise – 1997
The objective of this study was to find the answers to two primary research questions: "Do students learn programming languages better when they are offered in a particular order, such as 4th generation languages before 3rd generation languages?"; and "Do students learn programming languages better when they are taken in separate semesters as…
Descriptors: Academic Achievement, Higher Education, Information Science Education, Instructional Effectiveness
Connolly, Mary V. – 1996
Saint Mary's College (Indiana) offers a minor program in computer science. The program's introductory computer science class traditionally taught Pascal. The decision to change the introductory programming language to C++ with an object oriented approach was made when it became clear that there were good texts available for beginning students.…
Descriptors: Computer Science Education, Computer Software Selection, Curriculum Development, Educational Change
Gostowski, Rudy – 1996
A course was developed at Austin Peay State University (Tennessee) which offered an opportunity for hands-on experience with the essential components of modern analytical instruments. The course aimed to provide college students with the skills necessary to construct a simple model instrument, including the design and fabrication of electronic…
Descriptors: Assignments, Authoring Aids (Programming), Course Content, Electric Circuits
Buck, George H. – 1999
A verbal and e-mail survey was conducted of 30 senior high teachers in Alberta who teach computer programming courses in the Career and Technology Studies curriculum, in order to ascertain what courses at the intermediate and advanced levels were being offered, what programming languages were being used, why teachers selected the particular…
Descriptors: Advanced Courses, Authoring Aids (Programming), Computer Assisted Instruction, Computer Science Education