arXiv AI
Jul 16
Analyzing Curricular Pattern Complexity Using AI to Improve On-Time Graduation Rates
arXiv:2607. 13094v1 Announce Type: cross Abstract: The rise of Artificial Intelligence (AI) enables automatic analysis of large amounts of data.
Analyzing Curricular Pattern Complexity Using AI to Improve On-Time Graduation Rates
The rise of Artificial Intelligence (AI) enables automatic analysis of large amounts of data. Previously time-consuming and labor-intensive tasks can be completed much more efficiently with the use of AI.
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arXiv AI
Jun 12
Mapping AI Programs in the U.S: A Status Report from Early 2026 and an Analysis of AI Majors and Minors
arXiv:2606. 12428v1 Announce Type: cross Abstract: We present a report on the status of undergraduate Artificial Intelligence (AI) programs in the United States in Spring 2026.
arXiv AI
Jul 15
A Comparative Analysis of Institutional and Course Generative AI Policies within Higher Education: Implications for Instruction in Computing Education
arXiv:2607. 12296v1 Announce Type: cross Abstract: With the increased use of generative AI (GenAI) applications such as ChatGPT, higher education institutions (HEIs) have released a range of guidelines and policies to direct adoption within their institutions.
arXiv AI
5d ago
Jointly Predicting Courses and Grades Using a Transformer-Based Model
arXiv:2608. 13409v1 Announce Type: new Abstract: Existing predictive models in learning analytics often treat student academic history as a simple sequence, overlooking the concurrent nature of courses taken within a semester.
arXiv AI
Jun 12
AI SciBrief as a Gateway to Research: A Framework for Onboarding Students into New Research Areas
arXiv:2606. 12413v1 Announce Type: cross Abstract: Students at all levels of higher education face a significant barrier in the form of information overload, which often paralyzes the initial stages of the research process and suppresses motivation.
arXiv AI
1d ago
Revisiting the Performance of Generative Artificial Intelligence on Introductory Object-Oriented Programming Assessments: Insights from 2026
arXiv:2608. 16318v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence (GenAI) have substantially improved the ability of large language models (LLMs) to generate and explain source code.
arXiv AI
Jul 16
LessonBench-V1: A Benchmark Dataset for Evaluating AI Lesson Generation Agents
arXiv:2607. 13041v1 Announce Type: cross Abstract: Large Language Model (LLM) based AI educational content generation systems are increasingly being developed, yet no standardised benchmark exists to systematically evaluate them.
arXiv AI
Jun 9
AI-Integrated Learning Management System for Middle School: A Longitudinal Study of Learning Outcomes Through High School and Beyond
arXiv:2606. 07544v1 Announce Type: cross Abstract: Middle school is a key window for building core academic skills and the learning routines students carry into later grades, yet many students still fall behind because help is often limited and comes too late, after they have already been stuck for a while.
arXiv AI
Aug 7
CourseGraph: Finding overlaps and differences in Computer Science courses across universities
arXiv:2608. 05910v1 Announce Type: new Abstract: Student mobility programs such as Erasmus+ enable students to take courses at other universities, broadening their academic and cultural horizons.
arXiv AI
Jun 3
Lean-GAP: A Dataset of Formalized Graduate Algebra Problems
arXiv:2606. 02588v1 Announce Type: cross Abstract: We present Lean-GAP (Lean-Graduate Agebra Problems), 430 formalized graduate-level algebra problems from the textbook Abstract Algebra by Dummit and Foote.
arXiv AI
Jun 9
Impacts of Histories and Models on LLM Grading: A Study in Advanced Software Engineering Courses
arXiv:2606. 08400v1 Announce Type: cross Abstract: Graduate-level research reading report assessment creates a substantial labor burden for educators.
arXiv AI
Jul 14
Commenting with Copilot: A Taxonomy and Multi-Year Analysis of Student Code-Generation Specifications
arXiv:2607. 10674v1 Announce Type: cross Abstract: As AI code tools become integrated into programming environments, students increasingly describe intended behavior in natural language and rely on these tools to generate code, shifting emphasis from code writing to specification.