Presenters:
Zixin Mao, Ed.D. | Olga Castillo, M.S. | Mariah Hagadone-Bedir, Ph.D. | Pauline Salim Muljana, Ph.D.

👉 Will you be at AECT 2025? Let’s connect!

Register at convention.aect.org

We’re making this conversation interactive with stories (Session 1) and a game (Session 2)—because learning can be more memorable when it’s fun!

Join us for thought-provoking discussions and practical insights on building trust in instructional design.

✅ Session 1: What Do Instructional Designers Talk About When They Talk About Trust
📅 Oct 22 | 🕗 8:00 AM | 📍 Melrose 2

✅ Session 2: Dive Deeper Into the Concept of Trust Through the Lens of ABI Trustworthiness Model
📅 Oct 23 | 🕥 10:30 AM | 📍 Celebrity Ballroom 2

The Journal of Applied Instructional Design (JAID) is an AECT journal. (AECT = @aect.bsky.social)

All articles in this issue can be read (for FREE) at jaid.edtechbooks.org/jaid_14_3

This special issue is to encourage meaningful discussions on how GenAI can be integrated into different parts of instructional/training design, including its advantages, challenges, and the best ways to use it,from analysis and design to development, implementation,and evaluation (Yang et al.,2025).

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4. Challenges:
Issues w/ accuracy, bias, and maintaining an authentic voice. ​Concerns about data breaches and ethical handling of sensitive information. ​Worries about academic integrity, copyright, and the potential for plagiarism. ​Acceptance varies. ​
[Summarized by Adobe Reader AI Assistant]

3. Benefits:
GenAI helps overcome creative blocks and generate ideas. ​Handles low-stake tasks, reducing time spent on writing and creating content. Acts as a virtual assistant, optimizing workflows and supporting unstructured problem-solving. ​Enhances teamwork and communication w/ SMEs. ​

2. Perceived Usefulness: GenAI tools valuable for tasks in the analysis, design, and development phases of instructional design, such as writing performance objectives, selecting instructional content, and creating design documents. ​Less utility in the implementation and evaluation phases. ​

Findings:
1. Familiarity and Usage: IDs are familiar with various GenAI tools, with ChatGPT being the most frequently used. ​