Bita Akram

Works (8)

Updated: April 20th, 2024 05:00

2024 article

Detecting ChatGPT-Generated Code Submissions in a CS1 Course Using Machine Learning Models

PROCEEDINGS OF THE 55TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE 2024, VOL. 1, pp. 526–532.

By: M. Hoq n, Y. Shi n , J. Leinonen *, D. Babalola n, C. Lynch n, T. Price n , B. Akram n

author keywords: ChatGPT; large language model; artificial intelligence; introductory programming course; CS1; cheat detection; plagiarism detection
TL;DR: This work evaluated the performance of both traditional machine learning models and Abstract Syntax Tree-based (AST-based) deep learning models in detecting ChatGPT code from student code submissions, and suggested that both traditional machine learning models and AST-based deep learning models are effective in identifying ChatGPT-generated code with accuracy above 90%. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: March 8, 2024

2023 article

Do Intentions to Persist Predict Short-Term Computing Course Enrollments? A Scale Development, Validation, and Reliability Analysis

PROCEEDINGS OF THE 54TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, VOL 1, SIGCSE 2023, pp. 1062–1068.

By: R. Harred n, T. Barnes n, S. Fisk *, B. Akram n, T. Price n  & S. Yoder  n

author keywords: Persistence; enrollment; validated scale; introductory computer science
TL;DR: A scale to measure intentions to persist in computing is developed and validated, and its use in predicting actual persistence as defined by enrolling in another computer science course within two semesters is demonstrated. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: March 4, 2023

2023 article

SANN: Programming Code Representation Using Attention Neural Network with Optimized Subtree Extraction

PROCEEDINGS OF THE 32ND ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, CIKM 2023, pp. 783–792.

By: M. Hoq n, S. Chilla n, M. Ranjbar  n, P. Brusilovsky * & B. Akram n

author keywords: program analysis; code representation; static analysis; algorithm detection; program correctness prediction
TL;DR: The results indicate the effectiveness of the SANN model in capturing important syntactic and semantic information from students' code, allowing the construction of accurate student models, which serve as the foundation for generating adaptive instructional support such as individualized hints and feedback. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Source: Web Of Science
Added: March 25, 2024

2022 journal article

Adaptive Immediate Feedback for Block-Based Programming: Design and Evaluation

IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES, 15(3), 406–420.

By: S. Marwan n, B. Akram n, T. Barnes n & T. Price n 

author keywords: Programming; Task analysis; Codes; Uncertainty; Programming environments; Adaptive systems; Real-time systems; Adaptive feedback; block-based programming; formative feedback; subgoals feedback
TL;DR: This article presents the adaptive immediate feedback (AIF) system, which uses a hybrid data-driven feedback generation algorithm to provide students with information on their progress, code correctness, and potential errors, as well as encouragement in the middle of programming. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 10, 2022

2022 article

Exploring Design Choices to Support Novices' Example Use During Creative Open-Ended Programming

PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 1, pp. 619–625.

By: W. Wang  n, A. Le Meur  n, M. Bobbadi  n, B. Akram n, T. Barnes n, C. Martens n, T. Price n 

author keywords: open-ended programming; code examples; novice programming
TL;DR: This work explores how to design code examples to support novices' effective example use by presenting the experience of building and deploying Example Helper, a system that supports students with a gallery of code examples during open-ended programming. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: December 12, 2022

2022 article

Increasing Students' Persistence in Computer Science through a Lightweight Scalable Intervention

PROCEEDINGS OF THE 27TH ACM CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2022, VOL 1, pp. 526–532.

By: B. Akram n, S. Fisk *, S. Yoder  n, C. Hunt *, T. Price n , L. Battestilli n , T. Barnes n

author keywords: Positive Feedback; Introductory Computer Science; Persistence in Computing; Self-Assessment of Computing Ability
TL;DR: This study investigates the effect of a lightweight, scalable intervention where students received personalized, contextualized feedback from their instructors after two major assignments during the semester, and demonstrates that providing students' sense of belonging, professional role confidence, and the likelihood of stating an intention to pursue a major in computer science are improved. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: July 20, 2022

2019 conference paper

CEO: A Triangulated Evaluation of a Modeling-Based CT-Infused CS Activity for Non-CS Middle Grade Students

Proceedings of the ACM Conference on Global Computing Education - CompEd '19, 58–64.

By: N. Lytle  n, V. Cateté n , Y. Dong n, D. Boulden n , B. Akram n, J. Houchins n, T. Barnes n, E. Wiebe n 

Contributors: N. Lytle n, V. Cateté n , Y. Dong n, D. Boulden n , B. Akram n, J. Houchins n, T. Barnes n, E. Wiebe n 

Event: the ACM Conference

author keywords: Computational Thinking; Modeling and Simulation; Assessment
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Sources: Web Of Science, NC State University Libraries, Crossref, ORCID
Added: July 22, 2019

2018 article

Infusing Computational Thinking into Middle Grade Science Classrooms: Lessons Learned

WIPSCE'18: PROCEEDINGS OF THE 13TH WORKSHOP IN PRIMARY AND SECONDARY COMPUTING EDUCATION, pp. 109–114.

By: V. Catete n , N. Lytle  n, Y. Dong n, D. Boulden n , B. Akram n, J. Houchins n, T. Barnes n, E. Wiebe n  ...

Contributors: V. Cateté n , N. Lytle n, Y. Dong n, D. Boulden n , B. Akram n, J. Houchins n, T. Barnes n, E. Wiebe n  ...

author keywords: Professional Development; STEM plus C; Computational Thinking
TL;DR: Initial lessons learned while conducting design-based implementation research on integrating computational thinking into middle school science classes are presented and case studies suggest that several factors including teacher engagement, teacher attitudes, student prior experience with CS/CT, and curriculum design can all impact student engagement in integrated science-CT lessons. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: January 28, 2019

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