Active Learning Is Not One-Size-Fits-All: Designing Online Learning for Diverse Students

 

By Xi Lin

Imagine asking every student in your online course to participate in the same discussion, complete the same activity, and demonstrate learning in the same way.

At first glance, this might seem fair. Everyone receives the same assignment and follows the same instructions.

But is it truly equitable?

A recent article published in Active Learning in Higher Education suggests that effective active learning requires more than simply increasing participation. Instead, educators should recognize the diversity of learners and design learning experiences that promote agency, collaboration, and meaningful engagement for all students.

This message is especially important for online higher education, where students often bring a wide range of backgrounds, experiences, goals, and learning preferences.

The Myth of the “Typical” Online Student

When designing courses, it is easy to imagine an average student.

Perhaps they are highly motivated.

Perhaps they have strong technology skills.

Perhaps they enjoy group discussions and collaborative activities.

In reality, online classrooms are much more diverse.

Some students are working full-time jobs.

Some are raising children.

Some are returning to school after many years away from formal education.

Others may be studying from different countries, cultures, and time zones.

As educators, we cannot assume that a single activity will engage every learner equally.

This does not mean we should abandon active learning. Instead, it means we should design active learning experiences that provide flexibility and meaningful opportunities for participation.

From Participation to Agency

One of the most important ideas emerging from recent active learning research is the concept of learner agency.

Agency refers to students’ ownership of aspects of their learning process. Rather than simply completing instructor-designed activities, students have opportunities to make decisions, pursue interests, and contribute their own perspectives.

In online courses, agency can be surprisingly simple to implement.

For example:

• Allow students to select a topic for a project.
• Provide multiple assignment formats such as podcasts, videos, presentations, or written papers.
• Let students choose case studies that connect with their professional interests.
• Encourage learners to bring examples from their own workplaces and communities.

These choices help students see themselves as contributors to learning rather than merely recipients of information.

For adult learners, agency can be particularly powerful because it acknowledges the valuable experiences they already bring to the classroom.

Collaboration Beyond Group Work

Mention collaboration, and many students immediately think about group projects.

Unfortunately, group projects often receive mixed reviews. Some students do most of the work while others contribute very little. Scheduling can also be difficult in online courses.

However, collaboration is much broader than traditional group assignments.

Online instructors can encourage collaboration through:

• Peer feedback activities.
• Small-group problem solving.
• Collaborative resource collections.
• Structured debates.
• Shared annotation of readings.
• AI-supported brainstorming sessions.

The goal is not simply to place students in groups. The goal is to create opportunities for learners to learn from one another.

Research consistently shows that students often deepen their understanding when they explain ideas, defend positions, and engage with different perspectives.

Designing for Inclusion

One challenge with active learning is that some activities unintentionally favor certain students over others.

For example, highly verbal learners may thrive in live discussions, while reflective learners may prefer written responses. Some students enjoy spontaneous conversation, while others need time to organize their thoughts.

Inclusive active learning recognizes these differences.

Instead of asking, “How can I get everyone to participate in the same way?” instructors might ask: “How can I create multiple pathways for meaningful participation?” This small shift can have a significant impact.

Students may engage through discussion boards, reflective journals, collaborative documents, video responses, digital storytelling, or project-based learning.

Different formats allow students to demonstrate learning while respecting individual strengths and preferences.

What Does This Mean in the Age of AI?

The growing presence of generative AI makes learner agency even more important.

Today, students can use AI tools to summarize articles, generate outlines, brainstorm ideas, and provide feedback. These tools can support learning, but they also create a risk that students become passive consumers of AI-generated content.

Active learning offers a solution.

Instead of asking students to simply produce answers, instructors can design activities that require judgment, reflection, critique, and creativity.

For example, students might:

• Evaluate an AI-generated response.
• Compare human and AI perspectives.
• Identify biases in AI outputs.
• Improve AI-generated solutions.
• Reflect on how AI influenced their decision-making.

These activities place students in the role of active thinkers rather than passive users of technology.

Final Thoughts

Active learning is often described as a collection of teaching techniques. However, recent research suggests it may be more useful to think of active learning as a design philosophy.

The goal is not to keep students busy.

The goal is to create learning environments where students have opportunities to contribute, collaborate, and exercise agency.

As online higher education continues to evolve, the most successful courses may not be those with the most activities. Instead, they may be the courses that recognize student diversity and provide multiple pathways for meaningful engagement.

After all, active learning works best when students are not only active, but also empowered.

Reference

McNally, S. (2026). Celebrating diversity in active learning: Prioritising agency and collaboration to support all students' engagement in higher education. Active Learning in Higher Education, 27(2). https://doi.org/10.1177/14697874261439422

 

Active Learning Is Not About Keeping Students Busy: Lessons for the AI Era

 

By Xi Lin

Imagine walking into an online class where students are constantly clicking buttons, posting comments, and answering polls. It certainly looks active. But are students learning?

For many years, higher education instructors have embraced active learning to increase engagement and improve student outcomes. We have replaced long lectures with discussions, group projects, simulations, and collaborative activities. These approaches often lead to better participation and deeper learning than passive instruction.

However, a recent article published in Active Learning in Higher Education challenges us to rethink what active learning really means. The authors argue that active learning should not simply be about having students do more. Instead, it should focus on purposeful activity, learner agency, and meaningful participation in knowledge creation.

In other words, active learning is not about keeping students busy. It is about helping students become active thinkers.

The Problem with “Activity for Activity’s Sake”

As instructors, we sometimes fall into a common trap. We assume that if students are participating, they must be learning.

Discussion boards are full.

Poll responses are submitted.

Breakout rooms are active.

Everyone appears engaged.

But participation alone does not guarantee meaningful learning. Students can complete activities without deeply processing ideas or making connections to prior knowledge.

Think about the last online professional development session you attended. Did clicking through polls automatically make the session memorable? Probably not.

The same is true for our students.

This article encourages educators to move beyond the simple question, “Are students active?” and instead ask, “What kind of activity is taking place, and why does it matter?”

Active Learning in an AI World

This conversation becomes even more important as artificial intelligence becomes a common part of higher education.

A few years ago, active learning often meant students discussing ideas with classmates, solving problems together, or creating projects. Today, students may also collaborate with AI systems.

For example, students can:

• Brainstorm ideas with ChatGPT.
• Practice job interviews with AI role-play tools.
• Generate case studies and scenarios.
• Receive instant feedback on writing.
• Explore multiple perspectives on complex issues.

These possibilities create exciting opportunities, but they also raise important questions.

If AI generates the first draft of a student’s work, where does learning occur?

If AI suggests solutions, how can students develop independent judgment?

If students rely heavily on AI, how can instructors support agency and ownership of learning?

The authors argue that future active learning designs must carefully consider the relationship between human learners and AI tools. The goal should not be replacing thinking with technology. Instead, AI should create more opportunities for reflection, critique, creativity, and decision-making.

Three Questions for Designing Active Learning

As higher education instructors, we can use three simple questions to guide the design of online learning activities.

1. Are Students Making Meaning?

Students should do more than repeat information.

For example, rather than asking students to summarize a reading, ask them to apply the concepts to a real-world situation, evaluate competing viewpoints, or connect the ideas to their professional experiences.

Meaningful learning happens when students actively construct understanding.

2. Do Students Have Agency?

Agency refers to students having some ownership over their learning process.

Can students choose topics?

Can they select tools or resources?

Can they decide how to demonstrate their learning?

Giving students appropriate choices often increases motivation and engagement while encouraging self-directed learning.

3. Are Students Creating Something New?

The strongest active learning activities often involve creation rather than consumption.

Students might develop a proposal, design a solution, produce a podcast, create an infographic, or develop an AI-supported project.

When learners create something meaningful, they move beyond remembering information and begin to apply, analyze, and synthesize knowledge.

Practical Ideas for Online Courses

The good news is that active learning does not require a complete course redesign.

Here are a few simple strategies that align with these emerging ideas:

·      AI Debate Partner: Students ask an AI tool to argue an opposing viewpoint and then evaluate the strengths and weaknesses of the response.

·      Real-World Problem Challenges: Present authentic workplace problems and ask students to develop evidence-based solutions.

·      Student-Generated Resources: Have students create study guides, instructional videos, or collections of resources for future learners.

·      Reflective AI Journals: Ask students to document how they used AI during a project and critically evaluate its strengths and limitations.

·      Choice-Based Assignments: Allow students to select from multiple project formats such as presentations, podcasts, infographics, or reports.

These activities emphasize thinking, decision-making, and ownership rather than simply completing tasks.

Looking Ahead

The future of active learning is not about adding more activities to our courses. It is about designing experiences that help students become thoughtful participants in their own learning.

As AI continues to reshape higher education, this distinction becomes increasingly important. Students will always have access to information. They will increasingly have access to AI-generated answers as well.

What they need from higher education is something different: opportunities to question, analyze, create, and make informed judgments.

The next time you design an online activity, consider asking yourself one simple question:

Does this activity help students think, or does it merely keep them busy?

The answer may be the difference between active participation and active learning.

Reference

Børte, K., & Zeivots, S. (2026). Active learning in higher education: Inheriting pasts and emerging futures. Active Learning in Higher Education, 27(2), 207–219. https://doi.org/10.1177/14697874261426575

 

Active Learning Online: Five Strategies That Make Students Want to Click “Join”

 

 

By Xi Lin

Have you ever spent hours creating online lectures, only to discover that students watched the videos at double speed—or perhaps did not watch them at all? If so, you are not alone. One of the biggest challenges in online higher education is keeping students engaged in meaningful learning rather than simply completing course requirements.

Recent research offers some encouraging news. A 2025 study published in Frontiers in Education found that active learning strategies can significantly improve students' learning experiences and attitudes in online courses. Rather than treating students as passive recipients of information, active learning encourages them to discuss, collaborate, analyze, and apply what they are learning in authentic ways.

The message is clear: online learning works best when students are actively involved in the learning process.

What Is Active Learning?

Active learning is any instructional approach that requires students to do more than simply listen, read, or watch. Students engage with ideas, solve problems, participate in discussions, create products, and reflect on their learning.

Think of it this way:

• Passive learning asks students to consume information.
• Active learning asks students to use information.

In online environments, active learning is particularly important because it helps address common challenges such as isolation, disengagement, and lack of interaction.

Five Active Learning Strategies for Online Higher Education

1. Think-Pair-Share Goes Digital

Think-pair-share is a classic active learning strategy that works surprisingly well online.

Start by presenting a question or scenario. Give students time to think independently and post their responses. Then place them in pairs or small groups to compare ideas before sharing key insights with the class.

For example, in an educational technology course, students might discuss whether generative AI should be used to provide feedback on student writing. The initial reflection encourages independent thinking, while the discussion exposes students to diverse perspectives.

2. Use Case Studies Instead of Content Dumps

Students often remember what they do more than what they read.

Instead of assigning another chapter summary, present a realistic problem that requires students to apply course concepts. Case studies encourage critical thinking and help students connect theory with practice.

Adult learners, in particular, often appreciate case-based learning because it allows them to draw on their professional experiences and compare new ideas with real-world situations.

3. Try the Jigsaw Method Online

The jigsaw strategy transforms students into experts.

Assign different groups different resources, topics, or perspectives. Each group becomes responsible for mastering one section of the content and then teaching it to classmates.

This approach promotes accountability and collaboration while reducing the tendency for students to rely solely on the instructor as the source of knowledge.

In online courses, students can create short videos, discussion posts, infographics, or presentations to share their expertise.

4. Conduct Structured Interviews

One strategy highlighted in the 2025 study is the three-step interview.

Students interview one another about a topic, summarize what they learned, and then share insights with a larger group. This simple technique promotes active listening, communication skills, and deeper understanding.

The activity works particularly well in graduate and professional programs where students bring diverse experiences to the learning environment.

5. Use AI as a Learning Partner

Generative AI tools create exciting opportunities for active learning when used thoughtfully.

Students can use AI to brainstorm ideas, simulate workplace scenarios, generate examples, critique arguments, or practice professional conversations. The goal is not to let AI do the thinking. Instead, students should evaluate, refine, and build upon AI-generated responses.

When used this way, AI becomes a tool for inquiry and reflection rather than a shortcut.

Why Active Learning Matters More Than Ever

Today’s students have access to more information than any previous generation. The challenge is no longer finding information; it is making sense of it.

Active learning helps students move beyond memorization toward higher-order thinking skills such as analysis, evaluation, and creation. These skills are increasingly important in a world where artificial intelligence can provide instant answers but cannot replace human judgment, creativity, or critical thinking.

Moreover, active learning helps create a sense of community in online courses. Students are more likely to remain engaged when they interact regularly with peers, instructors, and course content.

Final Thoughts

Online learning should not feel like watching an endless playlist of recorded lectures. The most effective online courses invite students to participate, collaborate, and apply their knowledge in meaningful ways.

As instructors, a useful question to ask is not, “What content should I cover?” but rather, “What should students do with this content?”

That small shift in perspective can transform an online course from a passive experience into an active learning community.

Reference

Rakha, A. H. (2025). Promoting online teaching through active learning strategies: Applications and innovations. Frontiers in Education, 10, 1546208. https://doi.org/10.3389/feduc.2025.1546208

AI-lization in Academic Writing: Are We Starting to Write Like AI?

 

By Xi Lin

Artificial intelligence tools such as ChatGPT, Grammarly, and other generative AI platforms are rapidly transforming academic writing. Students now use AI to brainstorm ideas, refine grammar, organize arguments, and even generate drafts within seconds.

While these tools improve efficiency and accessibility, a new concern is emerging:
What happens when human writing begins to sound increasingly like AI?

In their January 2026 article, Xi Lin and Tianjiao Zhao introduce the concept of “AI-lization” to describe this growing phenomenon. Their work explores how AI is reshaping academic writing, originality, and learning in higher education.

What Is AI-lization?

AI-lization refers to the process by which human writing gradually adopts patterns commonly associated with AI-generated text. Over time, writers may unconsciously internalize AI-like sentence structures, vocabulary, and stylistic choices.

AI-generated writing often includes:

• Grammatically polished sentences
• Clear and concise organization
• Predictable structures
• Neutral or emotionally detached language

In contrast, human writing typically includes:

• Personal voice and individuality
• Emotional depth
• Cultural references and lived experiences
• Creative phrasing and stylistic variation

The concern is that heavy reliance on AI may make student writing increasingly standardized and machine-like, potentially reducing originality and creativity.

AI-lization Is Not the Same as Plagiarism

The article emphasizes that AI-lization differs from plagiarism.

Plagiarism involves directly copying someone else’s work without attribution. AI-lization, however, reflects the gradual convergence between human and machine writing styles. Even without intentionally copying AI output, repeated exposure to AI-generated language may still shape how students write.

The authors also distinguish AI-lization from responsible AI-assisted writing. When used thoughtfully, AI can support:

• Brainstorming
• Editing and proofreading
• Idea generation
• Organizational improvement

In this way, AI can complement human thinking rather than replace it.

Why Educators Are Concerned

AI-lization creates several challenges for higher education.

Difficulty Identifying Authentic Work

Many instructors struggle to determine whether writing reflects genuine student effort or excessive AI assistance. Although AI detection tools are widely used, they often produce:

• False positives (human writing flagged as AI)
• False negatives (AI-generated writing missed)

These inaccuracies may damage student trust and create anxiety around academic integrity.

Over-Reliance on AI

The article also warns that excessive dependence on AI tools may weaken:

• Critical thinking
• Creativity
• Problem-solving skills
• Independent writing abilities

If students rely too heavily on AI to generate ideas and arguments, they may engage less deeply with the learning process itself.

Moving Beyond AI Detection

Rather than focusing only on detecting AI use, the authors argue that educators should rethink how originality and learning are evaluated.

Instead of asking: “Did the student use AI?”

We may need to ask: “How did the student engage with the writing process?”

This means placing greater emphasis on:

• Draft development
• Revision processes
• Reflection and decision-making
• Critical engagement with AI suggestions

For example, students could explain how they used AI, justify their acceptance or rejection of suggestions, and reflect on how AI influenced their writing.

This process-oriented approach may provide a more meaningful understanding of student learning than simply evaluating the final product.

Recommendations for Students and Educators

The article encourages students to:

• Critically evaluate AI-generated content
• Maintain their personal voice
• Use AI as a support tool, not a replacement
• Reflect on and document AI usage
• Seek feedback from educators and peers

For educators, the authors recommend:

• Integrating AI literacy into the curriculum
• Designing assignments that value creativity and critical thinking
• Encouraging peer review and discussion
• Establishing clear AI-use policies
• Emphasizing process over polished output

Final Thoughts

AI is transforming academic writing, but the challenge is not simply whether students use AI. The deeper question is how AI influences creativity, originality, and learning.

The authors argue that education should focus less on detecting AI and more on understanding how students think, revise, and learn in AI-supported environments.

AI tools can enhance efficiency and accessibility, but meaningful learning still depends on critical thinking, reflection, and authentic human expression.

Reference

Lin, X., & Zhao, T. (2026). The AI-lization in Academic Writing: Challenges and Opportunities. eLearn Magazine. https://doi.org/10.1145/3793702.3776563

 

Human vs. AI Feedback: What Really Helps Preservice Teachers Learn?

 

 

By Xi Lin

 

As artificial intelligence becomes more common in education, one important question emerges: Can AI provide feedback as effectively as humans, especially in teacher preparation?

 

A recent study explores this question by comparing AI-generated feedback (ChatGPT) with human peer feedback in a literacy methods course for preservice teachers. The findings offer timely insights into how future educators learn, reflect, and improve their teaching practice in an AI-supported world.

 

Why Feedback Matters in Teacher Education

Feedback plays a central role in helping preservice teachers improve their lesson planning, critical thinking, and instructional decision-making. Traditionally, peer review has been widely used to support:

 

• Reflective thinking
• Collaborative learning
• Pedagogical development

 

With the rise of AI tools like ChatGPT, feedback is no longer limited to human interaction. AI can now provide instant, rubric-based suggestions, raising an important question:

“Does faster feedback mean better learning?”

 

The Study: AI vs. Human Peer Review

The study used a quasi-experimental design with 25 preservice teachers:

• 👥 Human feedback group (n = 9): Students reviewed each other’s lesson plans in class
• 🤖 AI feedback group (n = 16): Students used ChatGPT to generate feedback

 

All students:

1. Created a guided reading lesson plan
2. Received feedback (human or AI)
3. Revised their work
4. Reflected on the feedback experience

 

Data included:

• Survey results (critical thinking and peer learning)
• Open-ended responses
• Written reflections

 

Key Findings: What Did We Learn?

1. Both AI and Humans Support Critical Thinking

Students in both groups reported improved critical thinking.

 

AI helped by:

• Providing structured, rubric-aligned feedback
• Identifying gaps quickly
• Supporting revision efficiency

 

This suggests that AI can function as a useful cognitive scaffold, helping students refine their work.

 

2. Only Human Feedback Fostered Peer Learning

Here is where the difference becomes clear:

• Human feedback → significantly improved peer learning
• AI feedback → no significant effect on peer learning

 

Why? Students emphasized that human interaction provides:

• Dialogue and discussion
• Shared understanding
• Immediate clarification
• Emotional support

 

In contrast, AI lacks true interaction and collaboration, which are essential for peer learning.

 

3. Strengths and Weaknesses of AI Feedback

Strengths of AI:

• ⏱️ Immediate and always available
• 📊 Strong alignment with rubrics
• 🧾 Detailed and structured suggestions

 

Limitations of AI:

• ❗ Sometimes irrelevant or inaccurate
• 🤖 Lacks contextual understanding
• 💬 Feels impersonal or “robotic”
• 🔁 Can be inconsistent across responses

 

Some students even questioned its reliability and authenticity.

 

4. Human Feedback Brings What AI Cannot

 

Human peer feedback stood out for:

• ❤️ Emotional support and encouragement
• 🎯 Contextual relevance (real classroom understanding)
• 🤝 Trust and collaboration
• 🧠 Pedagogical nuance

 

Students reported feeling:

• More confident
• More engaged
• More supported

 

These socio-emotional and relational aspects are still beyond AI’s current capabilities.

 

The Future: A Hybrid Feedback Model

Rather than choosing between AI and humans, the study suggests a more effective approach:

 

Combine both!

 

AI for:

• Fast, structured, rubric-based feedback
• Identifying surface-level issues

 

Humans for:

• Deep discussion and reflection
• Emotional and contextual support
• Collaborative meaning-making

 

A hybrid feedback model may provide the best of both worlds.

 

Implications for Educators

For teacher educators and instructional designers:

• ✔ Use AI as a support tool, not a replacement
• ✔ Teach students how to critically evaluate AI feedback
• ✔ Design activities that include both AI and human interaction
• ✔ Emphasize AI literacy and ethical use

Final Thoughts

AI is transforming education—but not in a way that replaces human connection.

This study shows that while AI can enhance efficiency and support critical thinking,
Human interaction remains essential for meaningful learning.

 

👉 The future of education is not AI or humans.
👉 It is AI and humans—working together.

 

Reference

Yang-Heim, G. Y. A., & Lin, X. (2026). Preservice teachers’ perceptions of AI-and human-generated feedback on lesson plans. Cogent Education, 13(1), 2624898. https://doi.org/10.1080/2331186X.2026.2624898