Student Learning in Higher Education
The Pain Point
The average U.S. college dropout rate is 40% (Hanson, 2021), affecting all student ethnic groups. Moreover, underserved populations with STEM majors are significantly more likely to leave school without a degree (Riegle-Crumb, King, & Irizarry, 2019).
Due to the COVID-19 pandemic, the 2020-21 academic year also saw financial insecurity and mental health challenges increase significantly for students having to balance family responsibilities, jobs, and classes, resulting in lower college enrollment and retention, especially for underserved communities (Dept of Ed Office for Civil Rights, 2021). Those who drop out of college are 3% more likely to be unemployed (US Labor Statistics, 2022) and could cost taxpayers $31B over ten years.
The Prenostik Student Learning Dashboard (SLD) aims to help students learn more effectively and improve retention and graduation rates. It is a chatbot, AI-powered, and scalable Software-as-a-Service tool acting as a copilot during students' learning journey by delivering targeted, personalized, and real-time actionable assistance to improve learning.
The SLD holistically identifies each student's unique learning motivation challenges (subject difficulty, relevance to career goals, social and economic constraints, etc.) and provides specific recommendations to overcome the barriers.
Coaching students on how to learn effectively by fostering a growth mindset, grit, and agency will help them become successful lifelong learners and prepare them for the continuously evolving future workforce demands.
The Prenostik SLD's key innovations are its scalable adaptability requiring minimal instructor and student input, seemless integration with the institution’s Learning Management System (LMS), and AI-powered chatbot and guidance conversations to assess a student’s unique learning context to prevent unintentional bias in the analysis.
The SLD is both a diagnostic and intervention tool that identifies individual student learning challenge root causes and context by correlating student's learning motivation with LMS learning engagement behavior data.
Understanding each student’s learning context is critical to help improve diversity, equity, and inclusion in higher education, particularly in STEM fields.
The SLD’s originality and core differentiators are its translation of research-based Expectancy-Value-Cost motivation for learning model into a real-world tool. It can be used by any education institution providing in-person, flipped/hybrid, remote, synchronous, or asynchronous instruction formats.