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.

*This work was supported by BMBF within the project KI4TUK.

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