This analysis explores the profound impact of Large Language Models (LLMs) on curriculum design and innovative work behavior within higher education, leveraging the Technology Acceptance Model (TAM) framework.
The integration of LLMs offers transformative benefits for higher education institutions:
LLMs significantly enhance curriculum design and innovative work behavior (IWB) among faculty members.
Perceived usefulness (PU) is a stronger driver of IWB than perceived ease of use (PEOU) in this context.
The study provides a data-driven pathway for universities to advance pedagogical innovation through LLM adoption.
Key IWB dimensions influenced by LLMs include opportunity exploration, idea generation, idea promotion, and reflection.
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| IWB Dimension | Perceived Usefulness (PU) Impact (β) | Perceived Ease of Use (PEOU) Impact (β) |
|---|---|---|
| Opportunity Exploration (OE) | 0.525 | 0.266 |
| Idea Promotion (IP) | 0.575 | 0.285 |
| Idea Generation (IG) | 0.498 | 0.264 |
| Reflection (Refl.) | 0.622 | 0.242 |
King Faisal University (KFU) and other institutions in the Eastern Region of KSA have successfully integrated LLMs. Faculty members perceive LLMs as valuable tools for improving teaching efficiency and curriculum development, leading to active participation in innovative pedagogical practices. This is driven by effective training and clear demonstration of LLM benefits.
| Construct | Cronbach's Alpha (α) | Composite Reliability (CR) | Average Variance Extracted (AVE) |
|---|---|---|---|
| Idea Generation | 0.925 | 0.928 | 0.727 |
| Idea Promotion | 0.878 | 0.879 | 0.580 |
| Opportunity Exploration | 0.841 | 0.843 | 0.677 |
| Perceived Ease of Use | 0.933 | 0.936 | 0.754 |
| Perceived Usefulness | 0.918 | 0.923 | 0.714 |
| Reflection | 0.779 | 0.780 | 0.694 |
Understand the potential time and cost savings AI can bring to your curriculum development and pedagogical innovation processes.
A phased approach to integrate LLMs effectively into your higher education institution.
Identify specific curriculum areas where LLMs can provide the most value. Conduct a pilot program with early adopter faculty to gather feedback and refine integration strategies. Focus on training for perceived usefulness.
Roll out broader training programs focusing on both usefulness and ease of use. Develop a resource hub with best practices, templates, and support channels. Foster peer support networks.
Integrate LLMs into various academic departments, encouraging diverse applications. Establish feedback loops to continuously improve LLM integration based on faculty experiences and student learning outcomes. Reward innovative use cases.
Measure the impact of LLM adoption on IWB, curriculum quality, and student engagement. Use data to refine strategies and scale successful initiatives across the entire institution. Update policies to support AI-driven innovation.
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