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West Ashley Library
9 a.m. - 7 p.m.
Phone: (843) 766-6635
Folly Beach Library
9 a.m. - 5:30 p.m.
Phone: (843) 588-2001
Edgar Allan Poe/Sullivan's Island Library
Closed for renovations
Phone: (843) 883-3914
Wando Mount Pleasant Library
9 a.m. - 8 p.m.
Phone: (843) 805-6888
Village Library
9 a.m. - 6 p.m.
Phone: (843) 884-9741
St. Paul's/Hollywood Library
9 a.m. - 8 p.m.
Phone: (843) 889-3300
Otranto Road Library
9 a.m. - 8 p.m.
Phone: (843) 572-4094
Mt. Pleasant Library
9 a.m. - 8 p.m.
Phone: (843) 849-6161
McClellanville Library
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Keith Summey North Charleston Library
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John's Island Library
9 a.m. - 8 p.m.
Phone: (843) 559-1945
Hurd/St. Andrews Library
9 a.m. - 8 p.m.
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Miss Jane's Building (Edisto Library Temporary Location)
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Dorchester Road Library
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John L. Dart Library
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Phone: (843) 722-7550
Baxter-Patrick James Island
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Phone: (843) 795-6679
Main Library
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Phone: (843) 805-6930
Bees Ferry West Ashley Library
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Mobile Library
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An Intelligent E-Learning Course Recommendation Framework Based on Student Learning Style
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- Author(s): Ashraf, Erum; Manickam, Selvakumar; Karuppayah, Shankar; Malik, Sufiana Khatoon
- Language:
English- Source:
Journal of Educators Online. Jan 2023 20(1).- Publication Date:
2023- Document Type:
Journal Articles
Reports - Descriptive - Language:
- Additional Information
- Availability: Journal of Educators Online. Grand Canyon University, 23300 West Camelback Road, Phoenix, AZ 85017. e-mail: [email protected]. Web site: https://www.thejeo.com
- Peer Reviewed: Y
- Source: 10
- Subject Terms:
- ISSN: 1547-500X
- Abstract: As the drive to move from traditional face-to-face classroom learning to e-learning is ever in demand, the knowledge corpus exposed to students can be overwhelming because there is a need to automate certain functions of the e-learning framework. One of these functions is the course recommendation feature. Course recommendations help students save time and effort to explore the courses from a large pool of resources while considering multiple attributes such as social influence, prior knowledge, and learning style. These numerous criteria make the course recommendation a complex process that requires the researcher to promote online education and intelligently assist learners in identifying the relevant online courses. Although various researchers have put forward strategies to address course recommendation problems, learning style, a critical element in ensuring effective learning, has not been considered part of the course recommendation framework. This paper puts forward a learning style-based course recommendation framework that is expected to provide highly automated decision support for learners in identifying the most suitable course to improve their efficiency in e-learning. Additionally, based on this framework, instructors can analyze and re-evaluate the courses according to students' learning styles. The proposed framework reduces the time and effort involved in seeking relevant courses, thereby improving the learning experience.
- Abstract: As Provided
- Publication Date: 2023
- Accession Number: EJ1383939
- Availability:
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