Earticle

초록

영어

We propose SQLGo, an interactive learning tool designed to help learne.rs intuitively understand the execution flow of SQL queries. SQLGo combines Common Table Expression based visualization techniques with a Large Language Model (LLM)-powered conversational interface to clearly convey intermediate operations and procedural semantics embedded in SQL.Most existing SQL learning tools provide only tabular query results, failing to adequately explain the intermediate states and execution process of a query. As a result, learners often struggle to grasp the actual execution flow underlying SQL’s declarative structure. SQLGo addresses these limitations by offering an interactive environment that supports procedural reasoning and encourages active learner engagement, thereby enabling more effective SQL learning.Through this system, learners are expected to intuitively grasp the execution flow of queries and gain a deeper and more meaningful learning experience compared to conventional tools.

목차

Abstract
1. Introduction
2. Related Work
2.1 Visualization Tools for SQL Learning
2.2 Conversational Systems for SQL Learning
3. System
3.1 Design Goal
3.2 Implementation Environment
3.3 Prompt Engineering for Automated Node Generation
3.4 User Interface and Implementation
3.5 SQL Tree Generation Module
3.6 Node based Chatbot
4. Discussion
4.1 Summary and Potential Contributions
4.2 Limitations and Future Work
Acknowledgement
References

키워드

저자

• Misoo Jung [ Master Student, Department of Artificial Intelligence Convergence, Ewha Womans University, Korea ]
• Uran Oh [ Department of Computer Science and Engineering, Ewha Womans University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  The International Journal of Advanced Smart Convergence

• 간기

  계간

• pISSN

  2288-2847

• eISSN

  2288-2855

• 수록기간

  2012~2025

• 십진분류

  KDC 326 DDC 380