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WEKA: A Tool for Shaping Effective Student Learning Strategies for College School Leavers

Year: 2024

Type: article

Abstract: As college school leavers transition into higher education or the workforce, they face numerous challenges in adapting to new learning environments and expectations. Effective learning strategies are crucial to ensuring their success in these new settings. This paper explores how WEKA, a powerful data mining tool, can be leveraged to shape and enhance student learning strategies for college school leavers. By analysing educational data, WEKA can provide insights into the most effective learning methods, helping educators tailor their approaches to meet the specific needs of these students. The paper discusses the application of WEKA in educational data mining, highlights its capabilities, and presents case studies demonstrating its effectiveness in shaping learning strategies.

Source: East African Scholars Journal of Engineering and Computer Sciences

DOI: 10.36349/easjecs.2024.v07i07.001

Authors: Aiyegbusi Akinyemi Edward, Adeyemi Toyin Sidikat, Agoi Adeolu Moses, Kehinde Esther Olabisi

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W4403657413

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