Design of AI-Based Learning Analytics Dashboards for University Administrators in Bayero University, Kano, Kano State
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Background of the Study
Learning analytics refers to the collection, analysis, and interpretation of data regarding students' learning behaviors, performance, and outcomes (Wang et al., 2023). Universities have increasingly turned to learning analytics to inform decision-making and improve educational outcomes. However, the information derived from learning analytics can often be overwhelming and difficult to interpret without proper visualization tools. AI-powered learning analytics dashboards provide administrators with a user-friendly interface to make sense of complex data, enabling more informed decisions regarding curriculum design, student support, and institutional policies (Chen et al., 2024).
Bayero University, Kano, Kano State, with its diverse student body and wide-ranging academic programs, stands to benefit from AI-driven dashboards to track and analyze key learning metrics. The implementation of such a system could provide valuable insights into student performance, retention rates, and the effectiveness of teaching methods, aiding in the university’s academic planning and development. This study seeks to design and evaluate the effectiveness of AI-based learning analytics dashboards for university administrators.
Statement of the Problem
University administrators at Bayero University, Kano, face challenges in effectively utilizing learning data to improve academic performance and institutional planning. Current methods of data analysis are often manual, time-consuming, and prone to errors. As a result, decision-making processes may not be based on accurate or timely insights. This study aims to design an AI-based learning analytics dashboard to assist university administrators in analyzing student performance data and making data-driven decisions.
Objectives of the Study
- To design an AI-based learning analytics dashboard for Bayero University, Kano.
- To assess the effectiveness of the dashboard in aiding administrators' decision-making processes.
- To evaluate how the AI-based dashboard improves the university's ability to monitor and enhance student performance.
Research Questions
- How effective is the AI-based learning analytics dashboard in helping administrators monitor student performance?
- What impact does the AI dashboard have on the decision-making process regarding academic policies and interventions?
- How does the use of the AI dashboard improve institutional academic planning and resource allocation?
Research Hypotheses
- The AI-based learning analytics dashboard will provide more accurate and timely insights into student performance compared to traditional methods.
- University administrators using the AI dashboard will make more informed decisions regarding academic policies.
- The AI dashboard will lead to improvements in student outcomes by providing data-driven interventions and support.
Significance of the Study
The study will provide insights into how AI-based learning analytics dashboards can improve decision-making processes in universities. By implementing such dashboards, Bayero University will be better equipped to monitor student performance, design more effective academic interventions, and allocate resources more efficiently.
Scope and Limitations of the Study
This study will focus on the design and evaluation of an AI-based learning analytics dashboard for university administrators at Bayero University, Kano. The study will be limited to the university's administration and will not include other stakeholders such as students or faculty members.
Definitions of Terms
AI-Based Learning Analytics Dashboard: A data visualization tool powered by artificial intelligence designed to present and analyze educational data for decision-making.
Learning Analytics: The collection, measurement, and analysis of data related to student learning behavior and outcomes.
Data-Driven Decision Making: The process of making decisions based on the analysis of data rather than intuition or personal experience.
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