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Muntasir Hoq; Ananya Rao; Reisha Jaishankar; Krish Piryani; Nithya Janapati; Jessica Vandenberg; Bradford Mott; Narges Norouzi; James Lester; Bita Akram – International Educational Data Mining Society, 2025
In Computer Science (CS) education, understanding factors contributing to students' programming difficulties is crucial for effective learning support. By identifying specific issues students face, educators can provide targeted assistance to help them overcome obstacles and improve learning outcomes. While identifying sources of struggle, such as…
Descriptors: Computer Science Education, Programming, Misconceptions, Error Patterns
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Haoze Du; Richard Li; Edward Gehringer – International Educational Data Mining Society, 2025
Evaluating the performance of Large Language Models (LLMs) is a critical yet challenging task, particularly when aiming to avoid subjective assessments. This paper proposes a framework for leveraging subjective metrics derived from the class textual materials across different semesters to assess LLM outputs across various tasks. By utilizing…
Descriptors: Artificial Intelligence, Performance, Evaluation, Automation
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Jesper Dannath; Alina Deriyeva; Benjamin Paaßen – International Educational Data Mining Society, 2025
Research on the effectiveness of Intelligent Tutoring Systems (ITSs) suggests that automatic hint generation has the best effect on learning outcomes when hints are provided on the level of intermediate steps. However, ITSs for programming tasks face the challenge to decide on the granularity of steps for feedback, since it is not a priori clear…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Undergraduate Students
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Muhammad Fawad Akbar Khan; Max Ramsdell; Erik Falor; Hamid Karimi – International Educational Data Mining Society, 2024
This paper undertakes a thorough evaluation of ChatGPT's code generation capabilities, contrasting them with those of human programmers from both educational and software engineering standpoints. The emphasis is placed on elucidating its importance in these intertwined domains. To facilitate a robust analysis, we curated a novel dataset comprising…
Descriptors: Artificial Intelligence, Automation, Computer Science Education, Programming
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Yunsung Kim; Jadon Geathers; Chris Piech – International Educational Data Mining Society, 2024
"Stochastic programs," which are programs that produce probabilistic output, are a pivotal paradigm in various areas of CS education from introductory programming to machine learning and data science. Despite their importance, the problem of automatically grading such programs remains surprisingly unexplored. In this paper, we formalize…
Descriptors: Grading, Automation, Accuracy, Programming
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Maciej Pankiewicz; Yang Shi; Ryan S. Baker – International Educational Data Mining Society, 2025
Knowledge Tracing (KT) models predicting student performance in intelligent tutoring systems have been successfully deployed in several educational domains. However, their usage in open-ended programming problems poses multiple challenges due to the complexity of the programming code and a complex interplay between syntax and logic requirements…
Descriptors: Algorithms, Artificial Intelligence, Models, Intelligent Tutoring Systems
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Kevin Johnston; Norman van Wyk; Joachim Schuler; Brian Eyre – International Society for Technology, Education, and Science, 2024
To create a Futures Literacy course. Background: A previously developed and tested Framework to develop IT courses for emerging technologies was used to develop a Futures Literacy course. A literature review was conducted to discover theories, models, and frameworks that could be used to create IT courses. A Course Development Framework was used…
Descriptors: Computer Science Education, Curriculum Development, Course Content, Futures (of Society)
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Mehmet Arif Demirta¸; Max Fowler; Kathryn Cunningham – International Educational Data Mining Society, 2024
Analyzing which skills students develop in introductory programming education is an important question for the computer science education community. These key skills and concepts have been formalized as knowledge components, which are units of knowledge that can be measured by performance on a set of tasks. While knowledge components in other…
Descriptors: Programming, Computer Science Education, Skill Development, Knowledge Level
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Gyuhun Jung; Markel Sanz Ausin; Tiffany Barnes; Min Chi – International Educational Data Mining Society, 2024
We presented two empirical studies to assess the efficacy of two Deep Reinforcement Learning (DRL) frameworks on two distinct Intelligent Tutoring Systems (ITSs) to exploring the impact of Worked Example (WE) and Problem Solving (PS) on student learning. The first study was conducted on a probability tutor where we applied a classic DRL to induce…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Artificial Intelligence, Teaching Methods
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David A. Joyner; Zoey Anne Beda; Michael Cohen; Melanie Duffin; Amy Garcia Fernandez; Liz Hayes-Golding; Jonathan Hildreth; Alex Houk; Rebecca Johnson; Kayla Matcheck; Ana Santos – International Educational Data Mining Society, 2024
This study examines log data from proctored examinations from two classes offered as part of a large online graduate program in computer science. In these two classes, students are permitted to access any internet content during their exams, which themselves have remained largely unchanged over the last several semesters. As a result, when ChatGPT…
Descriptors: Computer Assisted Testing, Tests, Internet, Graduate Students
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Gao, Zhikai; Erickson, Bradley; Xu, Yiqiao; Lynch, Collin; Heckman, Sarah; Barnes, Tiffany – International Educational Data Mining Society, 2022
In computer science education timely help seeking during large programming projects is essential for student success. Help-seeking in typical courses happens in office hours and through online forums. In this research, we analyze students coding activities and help requests to understand the interaction between these activities. We collected…
Descriptors: Computer Science Education, College Students, Programming, Coding
Swanson, Dewey A.; Gusev, Dmitri A. – Association Supporting Computer Users in Education, 2022
We developed a paper for the 2016 ASCUE Conference with the topic of software tools to use in the classroom. As mentioned in the original paper, our Computer and Information Technology Department (CIT) curriculum at Purdue University statewide locations includes classes in database, networking, programming and systems areas. Most of these classes…
Descriptors: Information Technology, Computer Software, Educational Technology, Computer Science Education
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Cleuziou, Guillaume; Flouvat, Frédéric – International Educational Data Mining Society, 2021
Improving the pedagogical effectiveness of programming training platforms is a hot topic that requires the construction of fine and exploitable representations of learners' programs. This article presents a new approach for learning program embeddings. Starting from the hypothesis that the function of a program, but also its "style", can…
Descriptors: Programming, Computer Science Education, Electronic Learning, Data Analysis
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Sümeyra Akkaya; Anil Erkan – International Journal of Contemporary Educational Research, 2025
Coding means writing down the steps to be followed in order to carry out any operation through computers, using commands step by step. In other words, it is the job of finding a solution to an existing problem by using the language that the computer understands. Thanks to coding education, students are provided with skills such as research,…
Descriptors: Stakeholders, Opinions, Coding, Computer Science Education
Gusev, Dmitri A.; Swanson, Dewey A.; Casner, Melissa R. – Association Supporting Computer Users in Education, 2023
Recruiting tomorrow's information technology students is getting to be a challenging job even though there are a variety of many good-paying jobs in the field when they graduate. This is not just an issue for our department, Computer and Information Technology (CIT). According to experts, with declining birthrates, students determining there are…
Descriptors: Information Technology, Student Recruitment, College Students, Learning Activities
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