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Addressing Student Dropout Risks with AI

Harmoniplus Corporation, headquartered in Chiyoda, Tokyo, has announced exciting enhancements to its learning outcome visualization platform, dubbed the "Learning Outcome MOE". Leveraging the power of artificial intelligence, this newly fortified feature aims to tackle the pressing issue of student dropout risks, starting its rollout to select customers in the 2026 academic year.

Understanding the Changing Landscape

In recent years, the landscape surrounding universities has dramatically shifted. Many institutions are grappling with declining enrollment numbers, making it crucial for them to establish mechanisms that support each student’s educational journey and curb potential dropouts. The challenges have escalated since the pandemic, with heightened concerns regarding student engagement and motivation surfacing across campuses.

In light of this evolving scenario, Harmoniplus is utilizing its expertise in educational data usage to enhance dropout prevention mechanisms. The platform will incorporate a variety of indicators, ranging from GPA and attendance to assignment submission rates and counseling utilization, to smartly identify students at risk.

A Comprehensive Scoring and Analysis Approach

The newly strengthened AI capabilities will utilize advanced techniques to enhance risk assessment, including:

• - Scoring academic and lifestyle indicators to generate risk scores.
• - Analyzing trends through time-series data to pinpoint changes.
• - Employing machine learning models for accurate dropout predictions.
• - Conducting correlation analyses to detect simultaneous declines in multiple metrics.

With these enhancements, the platform will provide a clearer view of the nuanced dropout risks that might not align with traditional metrics. For instance, identifying students who maintain stable GPAs but face sudden declines in attendance or those experiencing several minor adverse changes simultaneously.

A Unique Student-Centric Approach

Unlike conventional academic systems that rely on straightforward threshold-based dropout risk management, "Learning Outcome MOE" adopts a distinct approach centered around students:

• - Comprehensive risk analyses through AI that evaluate multiple factors simultaneously.
• - A user interface designed from the perspective of students, influenced by direct feedback from student workshops.
• - A framework that encourages self-awareness and deeper understanding while reflecting on their own status through their learning data.
• - Promoting natural dialogue and awareness between students and faculty through thoughtfully designed UI.

MOE stands out not just by identifying dropout risks but by empowering students to introspect through their learning data. This fosters behavioral changes that contribute to their academic success.

Supporting Implementation and Adoption

Harmoniplus emphasizes that its support does not end with just providing the tools. The company prioritizes customer success through post-implementation assistance that goes hand-in-hand with the adoption of the dropout prevention feature. This includes ongoing data analysis support, regular meetings, and sharing effective use cases tailored to meet the needs of educational institutions.

For more information, please contact:
Harmoniplus Corporation
Website: www.harmonyplus.co.jp
Address: 7-5, Nibancho, Chiyoda, Tokyo
Phone: 03-6261-5172
Contact: Contact Us