AI Assistant for Virtual Programming Modules: Enhancing Student Interaction and Reducing Delays in Practical Guidance

Abstract

ABSTRACT The transition of programming education to virtual learning has raised significant challenges concerning the delivery of timely interactive support during the programming practical sessions. The delays in guiding the students and limited lecturer-student interaction naturally have negative impacts on the learning outcomes, which is especially true while trying to make sense of complex notions in programming. This study presents a solution called Web-Guru through the development of an Artificial Intelligence (AI) interactive learning environment, especially for virtual web programming modules. The study method used in this work is Design Science Research (DSR), which is especially appropriate for information systems initiatives that develop and assess novel artifacts meant to address recognized organizational issues. LLMs (Large Language Models) in AI assistance enable natural, intelligent interactions by understanding, generating, and personalizing responses to user queries across various tasks and domains. The key function of this environment is to guide and facilitate the students themselves in performing certain programming practical tasks in real time to visualize complex concepts more intuitively. Introducing Natural Language Processing (NLP), an AI assistant can respond instantly to any query raised by a student with no delay in practical guidance, thus making learning even more responsive and engaging. Apart from that, the Web-Guru allows for a flexible template so that it can smoothly integrate the specific forms of practical session content and structure the academics require. Likewise, all content can be appropriately mapped against course objectives and standards. Web-Guru will significantly enhance student engagement while reducing dependence on the lecturer for trivial queries, hence releasing lecturers to concentrate on higher-order teaching. The proposed AI-driven Web- Guru system has the potential to enhance virtual programming education by making it more supportive, efficient, and engaging for students. This study presents a discussion on the design of the system, its implementation challenges, and its expected impact on improving student engagement and learning outcomes within virtual programming modules. Undergraduate students who completed web programming in a virtual mode, use the Web-Guru application. They share and compare both experiences. Study findings illustrate that 87.1% of users are satisfied with the system. Further, students preferred AIgenerated answers that provide thorough explanations with examples over concise, direct remarks (83.5%). Web-guru can be utilized to improve the effectiveness and engagement of an open and distance learning environment. Keywords: AI Assistance, Distance Learning, Virtual Learning, Real-time Guidance, Interactive Learning, LLM