Online judge MySQL for learning process of database practice course

Puspitasari, Duwi; Arhandi, Putra Prima; Saputra, None Panji Inu Jaya; Syaifudin, Yan Watequlis; Himawan, Hidayatulah; Sholihah, P. A.

doi:10.1088/1757-899x/523/1/012046

Cited by 7 publications

(2 citation statements)

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“…An OJ for practicing MYSQL queries was developed to assist instructors of Database Management System courses in evaluating Structured Query Language (SQL) queries. The OJ MYSQL database is built using the Node.js and React.js frameworks, which enable comparisons between results of student queries and results of teacher-written key queries [13]. Several research studies and surveys have also focused on the impact of learning programming through POJ platforms.…”

Section: Introductionmentioning

confidence: 99%

Context-Aware Practice Problem Recommendation Using Learners’ Skill Level Navigation Patterns

Ramesh¹,

Kannimuthu²

2023

Intelligent Automation &Amp; Soft Computing

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The use of programming online judges (POJs) has risen dramatically in recent years, owing to the fact that the auto-evaluation of codes during practice motivates students to learn programming. Since POJs have greater number of programming problems in their repository, learners experience information overload. Recommender systems are a common solution to information overload. Current recommender systems used in e-learning platforms are inadequate for POJ since recommendations should consider learners' current context, like learning goals and current skill level (topic knowledge and difficulty level). To overcome the issue, we propose a context-aware practice problem recommender system based on learners' skill level navigation patterns. Our system initially performs skill level navigation pattern mining to discover frequent skill level navigations in the POJ and to find learners' learning goals. Collaborative filtering (CF) and content-based filtering approaches are employed to recommend problems in the current and next skill levels based on frequent skill level navigation patterns. The sequence similarity measure is used to find the top k neighbors based on the sequence of problems solved by the learners. The experiment results based on the real-world POJ dataset show that our approach considering the learners' current skill level and learning goals outperforms the other approaches in practice problem recommender systems.

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Section: Introductionmentioning

confidence: 99%

Context-Aware Practice Problem Recommendation Using Learners’ Skill Level Navigation Patterns

Ramesh¹,

Kannimuthu²

2023

Intelligent Automation &Amp; Soft Computing

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“…Databases are implemented in many fields not only in computer science and business. In the fields of computer science and software engineering, databases have become compulsory subjects [1], [2]. In the field of statistics, databases have become one of the technologies that have been adopted, especially on the topic of computational statistics [3], database also used to storing, retrieving and searching dataset on biology related research [4].…”

Section: Introductionmentioning

confidence: 99%

Preliminary study on SQLearn : Sql Query Learning Tool Using Close Ended Drag and Drop Approach

Arhandi¹,

Firdausi²,

Andoko³

et al. 2022

Proceedings of the 2022 Annual Technology, Applied Science and Engineering Conference (ATASEC 2022)

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Structured Query Language (SQL) is an industry standard for writing query. Writing SQL query is one of main competencies that must be possessed when learning database. Writing an SQL query could be challenging for novice students. SQLearn is a web-based application that give several cases study and questions. Our hypothesis is learning by using SQLearn will improve the students's understanding in SQL query. SQLearn uses close ended questions approach. Close ended questions are used to minimize possibility of syntax error. The lecturer will create the open-ended questions with a predefined answers and set of draggable SQL blocks. Student can learn while answer the questions by dragging provided SQL blocks into the correct position, when students finish dragging SQL Blocks, SQLearn will check their answer automatically. Twentyeight sophomore students from Information Technology department are involved in the experiment. Pre-test and post-test are used to measure students' understanding before using and after using SQLearn. T-test analysis result shows that there is a significant difference between pre-test and post-test score where the post-test score is overachieved the pre-test score. Based on the early result analysis, a promising result occurred, where the use of SQLearn could improve the students' test score.

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Function Execution Log Based Judgment System for Arduino Learning Practice

Seo

Lee

2022

Intelligent Tutoring Systems

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Online judge MySQL for learning process of database practice course

Cited by 7 publications

References 0 publications

Context-Aware Practice Problem Recommendation Using Learners’ Skill Level Navigation Patterns

Context-Aware Practice Problem Recommendation Using Learners’ Skill Level Navigation Patterns

Preliminary study on SQLearn : Sql Query Learning Tool Using Close Ended Drag and Drop Approach

Function Execution Log Based Judgment System for Arduino Learning Practice

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