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Oscar Karnalim; Simon; William Chivers – Computer Science Education, 2024
Background and Context: To educate students about programming plagiarism and collusion, we introduced an approach that automatically reports how similar a submitted program is to others. However, as most students receive similar feedback, those who engage in plagiarism and collusion might feel inadequately warned. Objective: When students are…
Descriptors: Teaching Methods, Plagiarism, Computer Science Education, Programming
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Fu, Qian; Zheng, Yafeng; Zhang, Mengyao; Zheng, Lanqin; Zhou, Junyi; Xie, Bochao – Educational Technology Research and Development, 2023
Providing appropriate feedback is important when learning to program. However, it is still unclear how different feedback strategies affect learning outcomes in programming. This study designed four different two-step programming feedback strategies and explored their impact on novice programmers' academic achievement, learning motivations, and…
Descriptors: Feedback (Response), Academic Achievement, Novices, Programming
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Tessa Charles; Carl Gwilliam – Journal for STEM Education Research, 2023
STEM fields, such as physics, increasingly rely on complex programs to analyse large datasets, thus teaching students the required programming skills is an important component of all STEM curricula. Since undergraduate students often have no prior coding experience, they are reliant on error messages as the primary diagnostic tool to identify and…
Descriptors: Automation, Feedback (Response), Error Correction, Physics
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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
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Menon, Pratibha – Journal of Information Systems Education, 2023
This paper introduces a teaching process to develop students' problem-solving and programming efficacy in an introductory computer programming course. The proposed teaching practice provides step-by-step guidelines on using worked-out examples of code to demonstrate the applications of programming concepts. These coding demonstrations explicitly…
Descriptors: Introductory Courses, Programming, Computer Science Education, Feedback (Response)
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Gila Hanna; Brendan Larvor; Xiaoheng Kitty Yan – ZDM: Mathematics Education, 2024
In this paper we develop a case for introducing a new teaching tool to undergraduate mathematics. Lean is an interactive theorem prover that instantly checks the correctness of every step and provides immediate feedback. Teaching with Lean might present a challenge, in that students must write their proofs in a formal way using a specific syntax.…
Descriptors: Undergraduate Study, College Mathematics, Teaching Methods, Feedback (Response)
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Matsuda, Noboru – International Journal of Artificial Intelligence in Education, 2022
This paper demonstrates that a teachable agent (TA) can play a dual role in an online learning environment (OLE) for learning by teaching--the teachable agent working as a synthetic peer for students to learn by teaching and as an interactive tool for cognitive task analysis when authoring an OLE for learning by teaching. We have developed an OLE…
Descriptors: Artificial Intelligence, Teaching Methods, Intelligent Tutoring Systems, Feedback (Response)
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Barbosa Rocha, Hemilis Joyse; Cabral De Azevedo Restelli Tedesco, Patrícia; De Barros Costa, Evandro – Informatics in Education, 2023
In programming problem solving activities, sometimes, students need feedback to progress in the course, being positively affected by the received feedback. This paper presents an overview of the state of the art and practice of the feedback approaches on introductory programming. To this end, we have carried out a systematic literature mapping to…
Descriptors: Classification, Computer Science Education, Feedback (Response), Problem Solving
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David Roldan-Alvarez; Francisco J. Mesa – IEEE Transactions on Education, 2024
Artificial intelligence (AI) in programming teaching is something that still has to be explored, since in this area assessment tools that allow grading the students work are the most common ones, but there are not many tools aimed toward providing feedback to the students in the process of creating their program. In this work a small sized…
Descriptors: Intelligent Tutoring Systems, Grading, Artificial Intelligence, Feedback (Response)
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Meier, Heidi; Lepp, Marina – Journal of Educational Computing Research, 2023
Especially in large courses, feedback is often given only on the final results; less attention is paid to the programming process. Today, however, some programming environments, e.g., Thonny, log activities during programming and have the functionality of replaying the programming process. This information can be used to provide feedback, and this…
Descriptors: Programming, Introductory Courses, Computer Science Education, Teaching Methods
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Benjamin B. Hoar; Roshini Ramachandran; Marc Levis-Fitzgerald; Erin M. Sparck; Ke Wu; Chong Liu – Journal of Chemical Education, 2023
In education, space exists for a tool that valorizes generic student course evaluation formats by organizing and recapitulating students' views on the pedagogical practices to which they are exposed. Often, student opinions about a course are gathered using a general comment section that does not solicit feedback concerning specific course…
Descriptors: Chemistry, Science Instruction, Large Group Instruction, Teaching Methods
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Katie A. McCarthy; Gregory A. Kuhlemeyer – Journal of Statistics and Data Science Education, 2024
To meet the demands of industry, undergraduate business curricula must evolve to prepare analytics-enabled professionals in fields such as finance, accounting, human resource management, and marketing. In this article, we provide a case study of developing a rigorous, integrated finance and data analytics course that was delivered using a…
Descriptors: Statistics Education, Finance Occupations, Course Content, Teaching Methods
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Dan Sun; Azzeddine Boudouaia; Chengcong Zhu; Yan Li – International Journal of Educational Technology in Higher Education, 2024
ChatGPT, an AI-based chatbot with automatic code generation abilities, has shown its promise in improving the quality of programming education by providing learners with opportunities to better understand the principles of programming. However, limited empirical studies have explored the impact of ChatGPT on learners' programming processes. This…
Descriptors: Computer Science Education, Computer Software, Feedback (Response), Artificial Intelligence
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Indriasari, Theresia Devi; Denny, Paul; Lottridge, Danielle; Luxton-Reilly, Andrew – Computer Science Education, 2023
Background and Context: Peer code review activities provide well-documented benefits to students in programming courses. Students develop relevant skills through exposure to alternative coding solutions, producing and receiving feedback, and collaboration with peers. Despite these benefits, low student motivation has been identified as one of the…
Descriptors: Peer Evaluation, Student Motivation, Cooperative Learning, Programming
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Jessica Hunt; Rebekah Davis; Alejandra Duarte – International Journal of Mathematical Education in Science and Technology, 2024
The COVID-19 pandemic prompted a shift in K-12 educational delivery from primarily in-person classroom instruction to remote learning. Developing broadcast instruction is one way to provide learners who experience barriers to contemporary forms of remote learning, which are typically provided over the internet, a way to access quality mathematics…
Descriptors: Teaching Methods, Mathematics Instruction, Instructional Design, Video Technology
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