Read and Reflect on AI for Instruction and Learning

Read and Reflect on AI for Instruction and Learning

by janet ayoub -

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Reflection on AI for Instruction and Learning

My perspective on using AI for instruction and learning is cautiously positive and evidence-based. Recent research shows that AI is not simply a technological trend, but a tool that can meaningfully support learning processes. For example, the study by Q. Du demonstrates that AI conversational agents can enhance self-regulated learning, helping students set goals, monitor their progress, and retain knowledge more effectively. This aligns with what I observe in my own teaching: students benefit when they are given tools that promote autonomy rather than passive learning.

However, I do not see AI as a replacement for the teacher. Its value lies in augmentation, particularly in providing immediate feedback, personalization, and continuous learner support.

Reflection on AI for Course Development

I view AI as highly useful for course development, especially in improving efficiency and instructional design. AI can assist in:

  • Structuring course content
  • Generating formative assessments
  • Personalizing learning pathways

The systematic review by S. Essa and colleagues highlights how machine learning enables adaptive learning systems that respond to individual learner needs. This is particularly relevant in higher education, where student diversity is significant.

That said, course development still requires pedagogical judgment, contextual awareness, and ethical considerations, areas where human expertise remains essential.

Perception of Colleagues

Among my colleagues, attitudes toward AI are mixed but evolving. Some are enthusiastic and already integrating AI tools into their teaching, while others remain hesitant due to concerns about:

  • Academic integrity
  • Over-reliance on technology
  • Lack of training

The work of S. Guo et al. (2025) is particularly relevant here, as it shows that perceived usefulness, ease of use, and trust are key determinants of AI adoption among educators. In my context, increasing familiarity and institutional support are gradually improving acceptance.

Selected Article

The article that best reflects my perspective is:

“How AI conversational agents influence EFL learners' self-regulated learning and retention”
by Q. Du (2025)

Explanation

I selected this article because it provides empirical evidence supporting a balanced view of AI in education. It does not present AI as a disruptive force replacing teachers, but rather as a supportive tool that enhances learner autonomy and engagement. This aligns closely with my teaching philosophy, which emphasizes student-centered learning, self-regulation, and meaningful use of technology.

In the Lebanese higher education context, where resources and learning conditions can be challenging, such tools can play a significant role in extending learning beyond the classroom while maintaining academic rigor.

 

 

Read and Reflect on AI for Instruction and Learning

by Dr. Nellie Deutsch -

Hi Janet,

Thank you for sharing your post. You’ve articulated a very thoughtful and grounded perspective, and what stands out is your ability to balance optimism with clear boundaries. That balance is exactly what many educators struggle to achieve when thinking about AI.

Your emphasis on self regulated learning is particularly strong. When you connect AI tools to goal setting, monitoring, and retention, you move the conversation away from “tools for convenience” and toward “tools for deeper learning.” That shift is important. It shows you are not just using AI, but thinking pedagogically about why it matters.

I also appreciate how clearly you position the teacher’s role. You’re right to push back against the idea of replacement. In practice, the real value of AI shows up when teachers design the learning experience and let AI support it, not lead it. Without that structure, even the best tools fall flat.

Your course development insights are practical and realistic. Efficiency is a real benefit, but you didn’t fall into the trap of assuming efficiency equals quality. Your point about pedagogical judgment and context is where many AI driven courses fail, so it’s good that you’re holding that line.

The section on colleagues feels honest and relevant. Resistance is not just about fear, it’s often about lack of clarity and support. You’re already identifying the right levers for change, especially trust and ease of use. That suggests you’re thinking not only as a teacher but also as a leader in your context.

Your choice of article fits well with everything you’ve said. It reinforces your focus on autonomy and aligns with your teaching philosophy rather than just adding theory for the sake of it.

If you want to strengthen this even further, one direction to consider is adding a concrete example from your own teaching. Even a short scenario of how you used AI to support self regulated learning would make your reflection even more powerful and grounded in practice.

Overall, this is not just a reflection, it reads like the foundation of a strong position paper.

Read and Reflect on AI for Instruction and Learning

by janet ayoub -

Hello Dr.

For example, in my teaching, I have already used AI tools to support self-regulated learning. I asked students to interact with an AI chatbot to practice vocabulary and grammar, then reflect on their learning by identifying what they improved, where they struggled, and how they planned to progress. This encouraged goal-setting, monitoring, and reflection—key elements of self-regulated learning.

Read and Reflect on AI for Instruction and Learning

by Dr. Nellie Deutsch -

Hi Janet,

Please call me Nellie or Dr. Nellie.

That’s a strong example of using AI in a purposeful way. You’re not just adding a tool, you’re guiding students through a full learning cycle of practice, reflection, and planning, which is exactly what supports real progress.

What stands out is how you moved beyond simple interaction with the chatbot and required students to think about their learning. That reflection piece is where the value really is. Many teachers stop at practice, but you pushed students into goal setting and self-monitoring, which builds independence over time.

If you want to take this even further, you might consider structuring the reflection a bit more. For example, asking students to compare their first and last responses, or to identify one specific strategy they will use differently next time. Small adjustments like that deepen the learning without adding much extra work.

You’re clearly on the right track here. Keep designing with that intention, where AI supports thinking rather than replaces it, and you’ll see meaningful impact on your students.