Integrating AI and Learning Analytics for Data-Driven Pedagogical Decisions and Personalized Interventions in Education

Ramteja Sajja; Yusuf Sermet; David Cwiertny; Ibrahim Demir

doi:10.1007/s10758-025-09897-9

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Integrating AI and Learning Analytics for Data-Driven Pedagogical Decisions and Personalized Interventions in Education

Journal article

Open access

Peer reviewed

Integrating AI and Learning Analytics for Data-Driven Pedagogical Decisions and Personalized Interventions in Education

Ramteja Sajja, Yusuf Sermet, David Cwiertny and Ibrahim Demir

Technology, knowledge and learning

08/26/2025

DOI: 10.1007/s10758-025-09897-9

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https://doi.org/10.1007/s10758-025-09897-9View

Published (Version of record) Open Access

Abstract

This research explores the conceptualization, development, and deployment of an innovative learning analytics tool, leveraging OpenAI’s GPT-4 model to quantify student engagement, map learning progression, and evaluate diverse instructional strategies within an educational context. By analyzing critical data points such as students’ stress levels, curiosity, confusion, agitation, topic preferences, and study methods, the tool provides a comprehensive view of the learning environment. It also employs Bloom’s taxonomy to assess cognitive development based on student inquiries. In addition to technical evaluation through synthetic data, feedback from a survey of teaching faculty at the University of Iowa was collected to gauge perceived benefits and challenges. Faculty recognized the tool’s potential to enhance instructional decision-making through real-time insights but expressed concerns about data security and the accuracy of AI-generated insights. The study outlines the design, implementation, and evaluation of the tool, highlighting its contributions to educational outcomes, practical integration within learning management systems, and future refinements needed to address privacy and accuracy concerns. This research underscores AI’s role in shaping personalized, data-driven education.

Artificial intelligence (AI)

Natural language processing (NLP)

Large language models (LLM)

Generative pre-training transformer (GPT)

Learning analytics (LA)

Details

Title: Subtitle: Integrating AI and Learning Analytics for Data-Driven Pedagogical Decisions and Personalized Interventions in Education
Creators: Ramteja Sajja - Tulane University
Yusuf Sermet - Tulane University
David Cwiertny - University of Iowa
Ibrahim Demir - Tulane University
Resource Type: Journal article
Publication Details: Technology, knowledge and learning
DOI: 10.1007/s10758-025-09897-9
ISSN: 2211-1662
eISSN: 2211-1670
Publisher: SPRINGER
Grant note: National Oceanic & Atmospheric Administration (NOAA)University of Alabama: NA22NWS4320003 National Science Foundation: 2230710 University of Iowa's Innovations in Teaching with Technology Awards
This project was funded by the National Oceanic & Atmospheric Administration (NOAA) via a cooperative agreement with The University of Alabama (NA22NWS4320003) awarded to the Cooperative Institute for Research to Operations in Hydrology (CIROH), the National Science Foundation (#2230710), and the University of Iowa's Innovations in Teaching with Technology Awards.
Language: English
Electronic publication date: 08/26/2025
Academic Unit: Electrical and Computer Engineering; Center for Health Effects of Environmental Contamination; Civil and Environmental Engineering; Injury Prevention Research Center; Chemistry; Chemical and Biochemical Engineering
Record Identifier: 9984949230802771

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