Artificial Intelligence-Based Learning Objective-Oriented Formative Feedback for Students in Higher Education Based on the Instructional Design

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Abstract

In recent years, the integration of artificial intelligence (AI) into Learning Management Systems (LMS) has expanded, though many tools lack alignment with learning environment competencies, causing cognitive overload and diminishing learner motivation. This paper explores integrating an AI-based formative feedback system within an LMS, designed to enhance learner competencies and align with curriculum and learning objectives. Utilizing a self-trained large language model, the system processes predefined teaching materials to deliver efficient formative feedback, minimizing cognitive overload. Our study, involving 450 students from the University of Leipzig, assesses the impact of AI-generated feedback during lectures on learning performance, validated against specified learning objectives and competencies. Results emphasize the importance of incorporating sound pedagogical practices in developing AI tools for adaptive learning environments, demonstrating that AI-driven formative feedback can significantly enhance the efficacy of these environments and achieve educational goals.

Details

Original languageEnglish
Title of host publicationFutureproofing Engineering Education for Global Responsibility
EditorsMichael E. Auer, Tiia Rüütmann
PublisherSpringer Science and Business Media B.V.
Pages504-513
Number of pages10
Volume1
ISBN (electronic)978-3-031-85652-5
ISBN (print)978-3-031-85651-8
Publication statusPublished - 2025
Peer-reviewedYes

Publication series

SeriesLecture Notes in Networks and Systems
Volume1260 LNNS
ISSN2367-3370

Conference

Title27th International Conference on Interactive Collaborative Learning & 53rd IGIP International Conference on Engineering Pedagogy
SubtitleFutureproofing Engineering Education for Global Responsibility
Abbreviated titleICL 2024
Duration24 - 27 September 2024
Website
LocationTallinn University of Technology
CityTallinn
CountryEstonia

Keywords

Keywords

  • Adaptive, AI, Competence Model, Feedback, Instruction, Recommender