Publication Date
In 2025 | 2 |
Since 2024 | 7 |
Since 2021 (last 5 years) | 23 |
Since 2016 (last 10 years) | 44 |
Since 2006 (last 20 years) | 73 |
Descriptor
Feedback (Response) | 76 |
Student Attitudes | 76 |
Programming | 61 |
Computer Science Education | 42 |
Foreign Countries | 36 |
Computer Software | 34 |
Teaching Methods | 30 |
Undergraduate Students | 23 |
College Students | 20 |
Online Courses | 19 |
Programming Languages | 18 |
More ▼ |
Source
Author
Publication Type
Education Level
Audience
Teachers | 3 |
Administrators | 1 |
Researchers | 1 |
Students | 1 |
Location
Brazil | 5 |
Turkey | 5 |
China | 4 |
Germany | 4 |
Japan | 4 |
Taiwan | 4 |
Australia | 3 |
Pennsylvania | 3 |
United Kingdom | 3 |
Asia | 2 |
Connecticut | 2 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
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
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)
Erkan Er; Gökhan Akçapinar; Alper Bayazit; Omid Noroozi; Seyyed Kazem Banihashem – British Journal of Educational Technology, 2025
Despite the growing research interest in the use of large language models for feedback provision, it still remains unknown how students perceive and use AI-generated feedback compared to instructor feedback in authentic settings. To address this gap, this study compared instructor and AI-generated feedback in a Java programming course through an…
Descriptors: Student Evaluation, Student Attitudes, Feedback (Response), Artificial Intelligence
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)
Jenkins, Brian C. – Journal of Economic Education, 2022
The author of this article describes a new undergraduate course where students use Python programming for macroeconomic data analysis and modeling. Students develop basic familiarity with dynamic optimization and simulating linear dynamic models, basic stochastic processes, real business cycle models, and New Keynesian business cycle models.…
Descriptors: Undergraduate Students, Programming Languages, Macroeconomics, Familiarity
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
Xuanyan Zhong; Zehui Zhan – Interactive Technology and Smart Education, 2025
Purpose: The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners' computational thinking. Design/methodology/approach: By…
Descriptors: Intelligent Tutoring Systems, Computer Science Education, Programming, Independent Study
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
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
Rowlett, Peter; Corner, Alexander S. – International Journal of Mathematical Education in Science and Technology, 2022
During the COVID-19 pandemic, the teaching of programming for undergraduate mathematicians was moved online. This was delivered asynchronously, with students working through notes and exercises and asking for help from staff via online messages as needed. Staff delivery time was redirected from content delivery into a formal system of formative…
Descriptors: COVID-19, Pandemics, Programming, Undergraduate Students
Mohsen Asgari; Fong-Chun Tsai; Linda Mannila; Filip Strömbäck; Kazi Masum Sadique – Discover Education, 2024
As programming emerges as a critical skill in the digital age and digital tools continue to evolve, understanding students' perspectives on the integration of such technologies into their education is crucial. This empirical study explores the perspectives of students in Sweden and Taiwan on the use of digital tools in their programming courses.…
Descriptors: Foreign Countries, Comparative Education, Student Attitudes, Technology Uses in Education
Arjan J. F. Kok; Lex Bijlsma; Cornelis Huizing; Ruurd Kuiper; Harrie Passier – Informatics in Education, 2024
This paper presents the first experiences of the use of an online open-source repository with programming exercises. The repository is independent of any specific teaching approach. Students can search for and select an exercise that trains the programming concepts that they want to train and that only uses the programming concepts they already…
Descriptors: Programming Languages, Computer Science Education, Open Source Technology, 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
Kaitlyn Storm; Jerry Zhang; Eileen Haase – Biomedical Engineering Education, 2022
Our first year biomedical engineering course exposes students to multiple engineering and design techniques within an overarching theme of understanding health inequity. Currently, the semester-long curriculum excludes computational methods such as Python programming and Machine Learning, which are usually not introduced until more advanced BME…
Descriptors: Artificial Intelligence, Programming Languages, Learning Modules, Introductory Courses
Neyhart, Jeffrey L.; Watkins, Eric – Natural Sciences Education, 2020
Basic quantitative and population genetics topics are typically taught in introductory plant breeding courses and are critical for success in upper-level study. Active learning, including simulations and games, may be useful for instruction of these concepts, which rely heavily on theory and may be more challenging for students. The statistical…
Descriptors: Genetics, Active Learning, Teaching Methods, Plants (Botany)