ICLF: An Immersive Code Learning Framework based on Git for Teaching and Evaluating Student Programming Projects

2026-01-21

AI Summary

This work addresses the challenges of scaling programming instruction—namely, inefficient assessment and the absence of authentic development environments—by proposing the Immersive Code Learning Framework (ICLF). ICLF innovatively leverages Git’s native mechanisms to construct a scalable instructional pipeline: instructors seed a hidden master repository that automatically generates public intermediate repositories stripped of solution code, while students iteratively develop within private forks that trigger predefined automated tests. This approach seamlessly integrates teaching, automated grading, transparent scoring, and plagiarism detection within an authentic collaborative workflow. Validated through years of deployment in edX MOOCs and other courses, ICLF effectively supports fine-grained progress tracking and high-fidelity skill development without reliance on any proprietary platform.

Technology Category

• Natural Language Processing: Code Generation / Program Synthesis from Natural Language
• Machine Learning: Imitation Learning & Inverse Reinforcement Learning
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding

Application Category

• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Search and Retrieval-Augmented AI: Search Tool Learning with LLM: Teaching LLMs to invoke search and make use of retrieved information
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Programming projects are essential in computer science education for bridging theory with practice and introducing students to tools like Git, IDEs, and debuggers. However, designing and evaluating these projects (especially in MOOCs)can be challenging. We propose the Immersive Code Learning Framework (ICLF), a scalable Git-based organizational pipeline for managing and evaluating student programming project. Students begin with an existing code base, a practice that is crucial for mirroring real-world software development. Students then iteratively complete tasks that pass predefined tests. The instructor only manages a hidden parent repository containing solutions, which is used to generate an intermediate public repository with these solutions removed via a templating system. Students are invited collaborators on private forks of this intermediate repository, possibly updated throughout the semester whenever the teacher changes the parent repository. This approach reduces grading platform dependency, supports automated feedback, and allows the project to evolve without disrupting student work. Successfully tested over several years, including in an edX MOOC, this organizational pipeline provides transparent evaluation, plagiarism detection, and continuous progress tracking for each student.

Problem

• programming projects
• evaluation
• Git-based management
• MOOCs
• plagiarism detection

Innovation

• Git-based framework
• automated feedback
• plagiarism detection
• continuous progress tracking
• scalable evaluation pipeline