Reflection: AI Research Insights and Medical Education

Reflection: AI Research Insights and Medical Education

by Hurraira Adrees -

Dear Dr. Nellie and Fellow Participants,

I have completed the readings and video reviews for this task. It was very helpful to see the empirical evidence supporting the AI tools we are learning to use. Below are my reflections based on the AI & Education Research Library and my background in medical imaging.

Reflection Task: AI for Instruction and Learning

1. How do you feel about using AI for instruction and learning?

 I am very optimistic. According to the meta-analysis by Wang et al. (2024), AI-enabled adaptive learning shows a statistically significant positive effect on outcomes. In my field of medical imaging, I believe this technology can help students master complex diagnostic patterns through personalized, repetitive practice that adjusts to their skill level.

2. How do you feel about using AI for course development?

I believe it is essential for efficiency. Research by Selivanova (2025) suggests that AI-generated tasks can match conventional tasks in effectiveness while reducing the workload for instructors. This efficiency allows me to focus on creating high-quality, hands-on simulations for medical students.

3. How do your colleagues feel about using AI for instruction and learning?

Sentiment among my hospital colleagues varies. While many see the "perceived usefulness" (as discussed in Guo et al., 2025), there are still barriers regarding trust and institutional support. In radiology, we are used to technology, but moving from diagnostic AI to educational AI requires a shift in mindset.

4. Selected Article from the APA Bibliography:

5. Why I chose this article:

This article fits my perspective because it synthesizes two decades of research to identify recurring trends. As someone coming from a medical background, I value systematic evidence that proves how digital tools shape practice over time.

I look forward to hearing your thoughts and discussing how we can all apply these research-backed strategies!

Best regards,

Jaweria

Re: Reflection on AI Research and Instructional Design – Update on Reference Link

by Hurraira Adrees -

Dear Dr. Nellie and Peers,

I wanted to provide a quick update regarding the article I selected for my reflection (Alzeebaree, 2026).

It appears that the primary DOI link in the bibliography is currently experiencing some technical routing issues. To ensure everyone can easily access this systematic review, I have located the direct archival link from the journal's hosting site:

Updated Access Link: https://ejournal.upi.edu/index.php/ijost/article/view/89685

As I mentioned in my previous post, I find this specific research very relevant to my medical background because it uses bibliometric data to track the evolution of digital tools. I hope this working link helps anyone else who is interested in reading about evidence-based AI integration!

Best regards,

Jaweria

Re: Reflection on AI Research and Instructional Design – Update on Reference Link

by Dr. Nellie Deutsch -

Hi Jaweria,

Thank you for sharing the updated link and for your diligence in ensuring the article is accessible to everyone. Technical routing issues with DOIs can certainly be a hurdle, so providing the direct archival link is very helpful for the group. It is great to see how you are applying bibliometric data to your specific background, and I agree that tracking the evolution of these tools is essential for evidence-based integration. Just as a general reminder for the class, always remember to verify links and citations provided by AI to ensure the research remains accurate. I look forward to your further reflections on the systematic review.