Reverse SQL Question Generation Algorithm in the DBLearn Adaptive E-Learning System
Using a traditional e-learning system, when teaching structured query language (SQL) queries in classical classrooms help instructors, to improve the students' SQL skills and learning effectiveness. However several problems in using e-learning as a teaching and learning assistant remain - such...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8703745/ |
| _version_ | 1818613407072387072 |
|---|---|
| author | Kanokwan Atchariyachanvanich Srinual Nalintippayawong Thanakrit Julavanich |
| author_facet | Kanokwan Atchariyachanvanich Srinual Nalintippayawong Thanakrit Julavanich |
| author_sort | Kanokwan Atchariyachanvanich |
| collection | DOAJ |
| description | Using a traditional e-learning system, when teaching structured query language (SQL) queries in classical classrooms help instructors, to improve the students' SQL skills and learning effectiveness. However several problems in using e-learning as a teaching and learning assistant remain - such as difficulties in differences in learning ability and knowledge level. We solved these problems by applying an adaptation module to our e-learning system. However, we still found it required considerable effort to create enough exercises to make the adaptation effective enough. So, we developed a novel automatic question generating algorithm, named Reverse SQL Question Generation Algorithm (RSQLG), to automatically generate exercises (including both answer and question) from a source database. RSQLG reverses the traditional manual process used previously by instructors. Instead of creating questions and answers for them, RSQLG creates the answers first. The generated exercises are presented to students by applying question adaptation methodology based on student knowledge level in each supported learning objective. We evaluated the learning effectiveness of our approach by using outcome-based learning. After post-test to pre-test scores were compared, we found students using our system improved their scores by 26%. Consequently, the adaptive e-learning framework using RSQLG could be applied in any adaptive or traditional e-learning for a database course to benefit the instructors leading to less effort in exercise management and to improve the learning outcome from the students allowing as much practice as they need. |
| first_indexed | 2024-12-16T16:01:37Z |
| format | Article |
| id | doaj.art-236f16f58fed41c5b942d50006fb13c1 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T16:01:37Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-236f16f58fed41c5b942d50006fb13c12022-12-21T22:25:28ZengIEEEIEEE Access2169-35362019-01-017549935500410.1109/ACCESS.2019.29125228703745Reverse SQL Question Generation Algorithm in the DBLearn Adaptive E-Learning SystemKanokwan Atchariyachanvanich0https://orcid.org/0000-0002-2705-7942Srinual Nalintippayawong1Thanakrit Julavanich2Faculty of Information Technology, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, ThailandFaculty of Information Technology, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, ThailandFaculty of Information Technology, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, ThailandUsing a traditional e-learning system, when teaching structured query language (SQL) queries in classical classrooms help instructors, to improve the students' SQL skills and learning effectiveness. However several problems in using e-learning as a teaching and learning assistant remain - such as difficulties in differences in learning ability and knowledge level. We solved these problems by applying an adaptation module to our e-learning system. However, we still found it required considerable effort to create enough exercises to make the adaptation effective enough. So, we developed a novel automatic question generating algorithm, named Reverse SQL Question Generation Algorithm (RSQLG), to automatically generate exercises (including both answer and question) from a source database. RSQLG reverses the traditional manual process used previously by instructors. Instead of creating questions and answers for them, RSQLG creates the answers first. The generated exercises are presented to students by applying question adaptation methodology based on student knowledge level in each supported learning objective. We evaluated the learning effectiveness of our approach by using outcome-based learning. After post-test to pre-test scores were compared, we found students using our system improved their scores by 26%. Consequently, the adaptive e-learning framework using RSQLG could be applied in any adaptive or traditional e-learning for a database course to benefit the instructors leading to less effort in exercise management and to improve the learning outcome from the students allowing as much practice as they need.https://ieeexplore.ieee.org/document/8703745/E-learningadaptive systemautomated question generating algorithmcomputer-aided instructionSQL learning |
| spellingShingle | Kanokwan Atchariyachanvanich Srinual Nalintippayawong Thanakrit Julavanich Reverse SQL Question Generation Algorithm in the DBLearn Adaptive E-Learning System IEEE Access E-learning adaptive system automated question generating algorithm computer-aided instruction SQL learning |
| title | Reverse SQL Question Generation Algorithm in the DBLearn Adaptive E-Learning System |
| title_full | Reverse SQL Question Generation Algorithm in the DBLearn Adaptive E-Learning System |
| title_fullStr | Reverse SQL Question Generation Algorithm in the DBLearn Adaptive E-Learning System |
| title_full_unstemmed | Reverse SQL Question Generation Algorithm in the DBLearn Adaptive E-Learning System |
| title_short | Reverse SQL Question Generation Algorithm in the DBLearn Adaptive E-Learning System |
| title_sort | reverse sql question generation algorithm in the dblearn adaptive e learning system |
| topic | E-learning adaptive system automated question generating algorithm computer-aided instruction SQL learning |
| url | https://ieeexplore.ieee.org/document/8703745/ |
| work_keys_str_mv | AT kanokwanatchariyachanvanich reversesqlquestiongenerationalgorithminthedblearnadaptiveelearningsystem AT srinualnalintippayawong reversesqlquestiongenerationalgorithminthedblearnadaptiveelearningsystem AT thanakritjulavanich reversesqlquestiongenerationalgorithminthedblearnadaptiveelearningsystem |