Using Adaptive Content Recommendations to Improve Logic and Programming Teaching and Learning
The high dropout rate in Information Technologies courses is a relevant problem in many countries, mainly because of the increasing demand for professionals in this sector. Usually, high dropout rates in these courses are related to difficulties in algorithms and programming subjects. Content recomm...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Graz University of Technology
2024-11-01
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| Series: | Journal of Universal Computer Science |
| Subjects: | |
| Online Access: | https://lib.jucs.org/article/115016/download/pdf/ |
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| _version_ | 1850065284612751360 |
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| author | Aluizio Haendchen Filho Adson Marques da Silva Esteves Hércules Antonio do Prado Edilson Ferneda André Luis Alice Raabe |
| author_facet | Aluizio Haendchen Filho Adson Marques da Silva Esteves Hércules Antonio do Prado Edilson Ferneda André Luis Alice Raabe |
| author_sort | Aluizio Haendchen Filho |
| collection | DOAJ |
| description | The high dropout rate in Information Technologies courses is a relevant problem in many countries, mainly because of the increasing demand for professionals in this sector. Usually, high dropout rates in these courses are related to difficulties in algorithms and programming subjects. Content recommendation systems are proposed to mitigate this problem, employing adaptive learning environments that facilitate the learning process. This study presents a content recommendation system that uses learning paths to group students and provide personalized recommendations based on peers' progress. The work follows the many efforts of group-based recommendation systems reported in the literature. The system uses intelligent agents and clustering algorithms to implement the recommendation system and was evaluated by submitting the simulation results to the judgment of human experts who significantly agreed with them. This initiative could make programming teaching more adaptive, using the groups' knowledge. Facilitating learning is one of the key issues to reduce dropout rates and resolve the shortage of labor in the technological area in Portuguese-speaking countries. |
| format | Article |
| id | doaj-art-5d5e0a0cd4454665b77f191fff55510d |
| institution | DOAJ |
| issn | 0948-6968 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Graz University of Technology |
| record_format | Article |
| series | Journal of Universal Computer Science |
| spelling | doaj-art-5d5e0a0cd4454665b77f191fff55510d2025-08-20T02:49:02ZengGraz University of TechnologyJournal of Universal Computer Science0948-69682024-11-0130121645166110.3897/jucs.115016115016Using Adaptive Content Recommendations to Improve Logic and Programming Teaching and LearningAluizio Haendchen Filho0Adson Marques da Silva Esteves1Hércules Antonio do Prado2Edilson Ferneda3André Luis Alice Raabe4UnaffiliatedUniversidade do Vale do ItajaíUniversidade Católica de BrasíliaUniversidade Católica de BrasíliaUniversidade do Vale do ItajaíThe high dropout rate in Information Technologies courses is a relevant problem in many countries, mainly because of the increasing demand for professionals in this sector. Usually, high dropout rates in these courses are related to difficulties in algorithms and programming subjects. Content recommendation systems are proposed to mitigate this problem, employing adaptive learning environments that facilitate the learning process. This study presents a content recommendation system that uses learning paths to group students and provide personalized recommendations based on peers' progress. The work follows the many efforts of group-based recommendation systems reported in the literature. The system uses intelligent agents and clustering algorithms to implement the recommendation system and was evaluated by submitting the simulation results to the judgment of human experts who significantly agreed with them. This initiative could make programming teaching more adaptive, using the groups' knowledge. Facilitating learning is one of the key issues to reduce dropout rates and resolve the shortage of labor in the technological area in Portuguese-speaking countries.https://lib.jucs.org/article/115016/download/pdf/Recommendation SystemRecommender SystemAdaptiv |
| spellingShingle | Aluizio Haendchen Filho Adson Marques da Silva Esteves Hércules Antonio do Prado Edilson Ferneda André Luis Alice Raabe Using Adaptive Content Recommendations to Improve Logic and Programming Teaching and Learning Journal of Universal Computer Science Recommendation System Recommender System Adaptiv |
| title | Using Adaptive Content Recommendations to Improve Logic and Programming Teaching and Learning |
| title_full | Using Adaptive Content Recommendations to Improve Logic and Programming Teaching and Learning |
| title_fullStr | Using Adaptive Content Recommendations to Improve Logic and Programming Teaching and Learning |
| title_full_unstemmed | Using Adaptive Content Recommendations to Improve Logic and Programming Teaching and Learning |
| title_short | Using Adaptive Content Recommendations to Improve Logic and Programming Teaching and Learning |
| title_sort | using adaptive content recommendations to improve logic and programming teaching and learning |
| topic | Recommendation System Recommender System Adaptiv |
| url | https://lib.jucs.org/article/115016/download/pdf/ |
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