| Type of Material: | Thesis |
| Title: | A Graph based Learning Path Recommendation Model for Adaptive Personalized Learning Environments |
| Researcher: | Raj, Nisha S |
| Guide: | Renumol, V G |
| Department: | Department of Information Technology |
| Publisher: | Cochin University of Science & Technology, Cochin |
| Place: | Cochin |
| Year: | 2022 |
| Language: | English |
| Subject: | Computer Science | E- Learning | Engineering and Technology | Learning Management Systems | Ontology | Recommender Systems | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Department of Information Technology, Cochin University of Science & Technology, Cochin, Cochin; 2022 |
| Fulltext: | Shodhganga |
| 000 | 00000ntm a2200000ua 4500 | |
| 001 | 456492 | |
| 003 | IN-AhILN | |
| 005 | 2024-10-10 14:22:06 | |
| 008 | __ | 241010t2022||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_456492 |
| 040 | __ | |aCUST_682022|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aRaj, Nisha S|eResearcher |
| 110 | __ | |aDepartment of Information Technology|bCochin University of Science & Technology, Cochin|dCochin|ein|0U-0253 |
| 245 | __ | |aA Graph based Learning Path Recommendation Model for Adaptive Personalized Learning Environments |
| 260 | __ | |aCochin|bCochin University of Science & Technology, Cochin|c2022 |
| 300 | __ | |axiii,186|dDVD |
| 502 | __ | |cDepartment of Information Technology, Cochin University of Science & Technology, Cochin, Cochin|d2022|bPhD |
| 518 | __ | |d2023|oDate of Award |
| 518 | __ | |oDate of Registration|d2017 |
| 520 | __ | |aE-learning Recommender Systems are gaining great importance nowadays due to their ability to enhance the learning experience by providing tailor-made services based on learner preferences. The main focus of a Personalized Learning Environment is to understand and adapt to the learners needs. Learners have different individual needs, goals, and preferences that affect their learning process. Similarly, different learners have different characteristics regarding learner s background knowledge, learners history, competency level, learning style and learning activities. This difference in learner characteristics makes the recommendation of learning resources to a particular learner more difficult. One solution to this problem is integrating knowledge about the learner and learning resources in the recommendation process. This thesis proposed an adaptive learning path recommendation method, which suggests a learning path, an ordered set of cognitively connected learning materials according to the learning need. |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aComputer Science |
| 653 | __ | |aE- Learning |
| 653 | __ | |aEngineering and Technology |
| 653 | __ | |aLearning Management Systems |
| 653 | __ | |aOntology |
| 653 | __ | |aRecommender Systems |
| 700 | __ | |eGuide|aRenumol, V G |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/479922|yShodhganga |
| 905 | __ | |afromsg |
User Feedback Comes Under This section.