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An Open-Source Automated Feedback System for STEM Education

ORAL

Abstract

In education, timely, personalized feedback is critical to improving student learning outcomes. This project introduces an open-source automated feedback system designed to support undergraduate students in STEM fields. By providing real-time, adaptive feedback our aim is to guide students through problem-solving processes and reinforcing correct approaches, ultimately fostering more effective, self-regulated learning throughout the course. The system aligns with curriculum goals, offering formative feedback immediately after problem-solving, along with integrated help materials to guide students through challenges. It features interactive dashboards for both students and instructors, providing real-time insights into performance and learning progress. Its flexible design allows instructors to customize content across a wide range of STEM topics, ensuring adaptability to diverse educational needs. Using the Technology Acceptance Model 2 (TAM2), we assessed the system's perceived usefulness and ease of use. This pilot study showed high user acceptance, highlighting the value of formative feedback in enhancing student engagement. In this presentation, we will discuss the system's design, TAM2 findings, and its potential to scale, offering an accessible solution for enhancing STEM education.

Publication: Steinert, S., Krupp, L., Avila, K.E. et al. Lessons learned from designing an open-source automated feedback system for STEM education. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-13025-y

Presenters

  • Karina E Avila

    RPTU Kaiserslautern-Landau

Authors

  • Karina E Avila

    RPTU Kaiserslautern-Landau

  • Steffen Steinert

    Ludwig-Maximilians-University Munich

  • Lars Krupp

    German Research Center for Artificial Intelligence

  • Anke S Janssen

    RPTU Kaiserslautern-Landau

  • Verena Ruf

    Ludwig-Maximilians-University Munich

  • David Dzsotjan

    Ludwig-Maximilians-University Munich

  • Christian De Schryver

    RPTU Kaiserslautern-Landau

  • Jakob Karolus

    German Research Center for Artificial Intelligence

  • Stefan Ruzika

    RPTU Kaiserslautern-Landau

  • Karen Joisten

    RPTU Kaiserslautern-Landau

  • Paul Lukowicz

    German Research Center for Artificial Intelligence

  • Jochen Kuhn

    Ludwig-Maximilians-University Munich, Ludwig-Maximilians-Universität München, Ludwig-Maximilians-Universitaet (LMU-Munich)

  • Norbert Wehn

    RPTU Kaiserslautern-Landau

  • Stefan Küchemann

    Ludwig-Maximilians-University Munich, Ludwig-Maximilians-University of Munich