What Are the Educational Benefits of Data Analytics Tools?

Tina Rosen, Education Technology Insights | Monday, July 12, 2021

Educational analytics enables the discovery of meaningful correlations and the mining of intelligence in educational contexts.

FREMONT, CA : Learning analytics assist schools and institutions in making more informed, data-driven decisions. They can also empower students. Education data insights can provide students with real-time visualization of their performance and assist them in selecting the study concentration or significance that is most appropriate for them.

The following are some of the educational benefits of data analytics tools:

Demonstrating the value of higher education analytics is best accomplished through real-world examples, such as setting performance thresholds in mathematics and comparing education data stores in such a way that a low-test score triggers a cascade of suggested improvement interventions. This is consistent with supplemental online coursework and tutoring in resource and infrastructure data, for example.

Identifying problematic academic subject areas for individual students is a critical use case for the significant data insights in today's learning analytics. An intelligent system could suggest tried-and-true methods for overcoming obstacles and email suggestions such as online labs that address specific difficulties (using the student contact information stored in the system).

With proven performance benefits, AI and machine learning can assist in balancing accreditation requirements and college acceptance rates. Machine learning identifies correlations that contradict previously held beliefs. For example, a traditional condition may not be optimal for preparing a student to transition from differential equations to function analysis, or a tenured instructor may skew the assessment. Whichever is occurring can be determined using AI-based analytics. Testing alternative hypotheses and extracting the truth from the resulting data are the pinnacle applications of AI-based learning analytics.

By intelligently planning resource locations to minimize student and faculty travel time, optimizing campus physical plant resources can help reduce transportation costs at a large university.

Correlating facility usage for budget planning and allocation purposes can help maximize the utilization of at-risk sites or determine which buildings to close or rent out.

Even non-technical staff can easily integrate analytics into a learning management system web application these days. Enterprise training that incorporates a gamification-based learning management system (LMS) benefits from learning analytics because users associate their success with the system with learning outcomes. For example, the effectiveness of executive and management training is constantly adjusted to achieve performance in branching scenario games. AI-based analytics can instantly display performance data from student outcomes, allowing administrators to determine the most effective courses and methods.

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