AI Tools for Instructional Design: Analyzing the Gap Between Technological Potential and Pedagogical Rigor

DOI

10.2991/978-94-6239-634-0_6How to use a DOI?

Keywords

Instructional Design; Generative AI; Educational Technology; Constructive Alignment; Human-AI Collaboration; Pedagogical Engineering

Abstract

Dedicated generative AI applications are increasingly targeting the Instructional Design (ID) sector, claiming to automate tasks ranging from lesson planning to assessment creation. This descriptive study distinguishes these specialized “vertical” tools from general-purpose Large Language Models to evaluate their actual utility. We contrasted the functional output of representative platforms (specifically MagicSchool.ai, CourseAI, and IDEAI) against established ID foundations: needs analysis, Constructive Alignment, and Cognitive Load Theory. The analysis identifies two primary tool categories: Global Design Assistants and Content Generators. While these systems demonstrate high efficiency in drafting initial structures, results indicate substantial limitations regarding pedagogical rigor. The tools generally fail to conduct strategic needs assessments and struggle to generate assessments that reach the higher levels of Bloom’s Taxonomy. Furthermore, the alignment between objectives and activities often appears mechanical rather than conceptual. We conclude that while such AI tools are viable for accelerating specific production tasks, they cannot currently replace the strategic decision-making of human experts. Effective implementation therefore requires a human-in-the-loop approach to validate the relevance and depth of the generated materials.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Abdelmounaim Azinda
AU  - Mohamed Khaldi
PY  - 2026
DA  - 2026/04/02
TI  - AI Tools for Instructional Design: Analyzing the Gap Between Technological Potential and Pedagogical Rigor
BT  - Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2025)
PB  - Atlantis Press
SP  - 79
EP  - 87
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6239-634-0_6
DO  - 10.2991/978-94-6239-634-0_6
ID  - Azinda2026
ER  -