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Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2024
Assessing students' answers and in particular natural language answers is a crucial challenge in the field of education. Advances in transformer-based models such as Large Language Models (LLMs), have led to significant progress in various natural language tasks. Nevertheless, amidst the growing trend of evaluating LLMs across diverse tasks,…
Descriptors: Student Evaluation, Computer Assisted Testing, Artificial Intelligence, Comprehension
Cai, Zhiqiang; Marquart, Cody; Shaffer, David W. – International Educational Data Mining Society, 2022
Regular expression (regex) coding has advantages for text analysis. Humans are often able to quickly construct intelligible coding rules with high precision. That is, researchers can identify words and word patterns that correctly classify examples of a particular concept. And, it is often easy to identify false positives and improve the regex…
Descriptors: Coding, Classification, Artificial Intelligence, Engineering Education
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
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
Shi, Yang; Mao, Ye; Barnes, Tiffany; Chi, Min; Price, Thomas W. – International Educational Data Mining Society, 2021
Automatically detecting bugs in student program code is critical to enable formative feedback to help students pinpoint errors and resolve them. Deep learning models especially code2vec and ASTNN have shown great success for "large-scale" code classification. It is not clear, however, whether they can be effectively used for bug…
Descriptors: Artificial Intelligence, Program Effectiveness, Coding, Computer Science Education
Höppner, Frank – International Educational Data Mining Society, 2021
Various similarity measures for source code have been proposed, many rely on edit- or tree-distance. To support a lecturer in quickly assessing live or online exercises with respect to "approaches taken by the students," we compare source code on a more abstract, semantic level. Even if novice student's solutions follow the same idea,…
Descriptors: Coding, Classification, Programming, Computer Science Education
Dave, Neisarg; Bakes, Riley; Pursel, Barton; Giles, C. Lee – International Educational Data Mining Society, 2021
We investigate encoder-decoder GRU networks with attention mechanism for solving a diverse array of elementary math problems with mathematical symbolic structures. We quantitatively measure performances of recurrent models on a given question type using a test set of unseen problems with a binary scoring and partial credit system. From our…
Descriptors: Multiple Choice Tests, Mathematics Tests, Problem Solving, Attention
First Graders Coordination of Counting and Movements on a Grid When Programming with Tangible Blocks
Abigail Erskine; Laura Bofferding; Sezai Kocabos; Haoran Tang – North American Chapter of the International Group for the Psychology of Mathematics Education, 2023
As elementary students begin to program using tangible blocks, they must coordinate their use of counting with the movements, directions, and numbers they use to move a character. In our study, we analyzed 13 first graders' first attempts at coordinating these elements when playing a programming game on the iPad that used tangible programming…
Descriptors: Elementary School Students, Elementary School Mathematics, Grade 1, Computation
Cai, Zhiqiang; Siebert-Evenstone, Amanda; Eagan, Brendan; Shaffer, David Williamson – Grantee Submission, 2021
When text datasets are very large, manually coding line by line becomes impractical. As a result, researchers sometimes try to use machine learning algorithms to automatically code text data. One of the most popular algorithms is topic modeling. For a given text dataset, a topic model provides probability distributions of words for a set of…
Descriptors: Coding, Artificial Intelligence, Models, Probability
Swaminathan, Sudha; Mazza, Jenna; Lisenbee, Peggy S. – AERA Online Paper Repository, 2021
Our goal was to study the impact of coding on preschoolers' math abilities and to analyze their coding behaviors. Participants were six preschoolers, four years of age, from a play-based accredited program. We measured their Math abilities using TEAM and observed their coding behaviors with a structured instrument. Children used a robotic toy to…
Descriptors: Coding, Preschool Children, Preschool Education, Mathematics Skills

Arun-Balajiee Lekshmi-Narayanan; Priti Oli; Jeevan Chapagain; Mohammad Hassany; Rabin Banjade; Vasile Rus – Grantee Submission, 2024
Worked examples, which present an explained code for solving typical programming problems are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide…
Descriptors: Coding, Computer Science Education, Computational Linguistics, Artificial Intelligence
Asmaa Bengueddach; Djamila Hamdadou – International Society for Technology, Education, and Science, 2024
The COVID-19 pandemic, an unprecedented global health crisis, has not only significantly impacted public health but has also caused substantial disruptions to conventional education systems. In response to these challenges, our institution has undertaken innovative measures within the realm of education. A pivotal aspect of our response involves…
Descriptors: Personal Autonomy, Online Courses, Educational Change, Coding
Zhou, Guojing; Moulder, Robert G.; Sun, Chen; D'Mello, Sidney K. – International Educational Data Mining Society, 2022
In collaborative problem solving (CPS), people's actions are interactive, interdependent, and temporal. However, it is unclear how actions temporally relate to each other and what are the temporal similarities and differences between successful vs. unsuccessful CPS processes. As such, we apply a temporal analysis approach, Multilevel Vector…
Descriptors: Cooperative Learning, Problem Solving, College Students, Physics
Iseli, Markus; Feng, Tianying; Chung, Gregory; Ruan, Ziyue; Shochet, Joe; Strachman, Amy – Grantee Submission, 2021
Computational thinking (CT) has emerged as a key topic of interest in K-12 education. Children that are exposed at an early age to STEM curriculum, such as computer programming and computational thinking, demonstrate fewer obstacles entering technical fields. Increased knowledge of programming and computation in early childhood is also associated…
Descriptors: Computation, Thinking Skills, STEM Education, Coding
Demir-Kaçan, Sibel; Kaçan, Ahmet – International Journal of Psychology and Educational Studies, 2022
Students can develop their creative thinking processes and problem scenarios with robotic applications. Therefore, the research objective is that robotic applications can solve students' problem scenarios. This study was conducted in Samsun/Turkey in the Ministry of Education for 10 weeks and involved 8 elementary school students.. For this study,…
Descriptors: Foreign Countries, Creative Thinking, Problem Solving, Robotics