Each episode explores the art and science of facilitating meaningful learning, featuring candid conversations with educators across disciplines on topics like active learning, inclusive pedagogy, AI in the classroom, and student engagement. Whether you have 20 minutes between classes or a long drive ahead, there’s an episode that meets you where you are — and sends you back to your students with something new to try.

Available on Apple Podcasts, Spotify, and at 

1. The engagement illusion
2. The expertise illusion
3. The student-centred illusion
4. The transfer illusion
5. The easy-wins illusion
6. The motivation illusion
7. The discovery illusion
8. The uniqueness illusion
9. The performance illusion
10. The innovation illusion

Each of these illusions contain an element of truth that makes them appealing and enduring, but they do not have evidence to support their effectiveness in student learning. This blog post explains each of these illusions, describes why they are harmful to learning, and provides guidance for improving instruction.

Read the full post here: Kirschner, P. (2026). Instructional Illusions: Ten Things in Education that Look Right but Aren’t, KirschnerEd. 

Strategies for reassembling parts into the whole include:

• Concept Mapping: Use visual maps to show relationships between ideas. For example, students place key concepts in nodes and draw labeled connections between them. This encourages them to think about how concepts relate, not just what they are. Concept mapping supports schema formation, helping students organize knowledge structures.
• Interleaving: Instead of teaching topics in isolated blocks, mix related topics during practice. Interleaving promotes discrimination between concepts and helps students understand when each idea applies.
• Bridging Questions: Ask questions that explicitly require connections. These questions force students to retrieve prior knowledge and apply it in a new context.
• Retrieval + Integration Activities: After finishing a topic, revisit it when teaching a later topic. This leverages Retrieval Practice, which strengthens connections between knowledge nodes.
• Metacognitive Reflection: Have students reflect on how ideas connect. Reflection builds transferable mental models.

For more on this idea, read Carl Henrick’s post .

Check it out here: 

Ideally, provide detailed worked examples when introducing a new topic, narrating your thought process in live classes or annotating a document in an online class, then gradually provide less detail while students complete more of the steps on their own, fading support over time until they are proficient independently. To boost effectiveness, encourage students to self-explain as they read through a worked example, telling themselves why each step was taken.

What does this look like in practice?

• ������biology, you could provide diagrams demonstrating various metabolic responses, each with labels explaining what happens with each component and why, then provide some practice problems of similar models that are only partially completed, asking students to complete them and provide explanations.
• In a writing lesson, students could be provided with two essays of different quality with various components highlighted and annotated. After students study the two examples, they could fill in missing pieces of another partially completed essay, such as writing their own effective transition sentences or developing an appropriate thesis statement.
• ������business management, detailed case studies are effective worked examples that illustrate course concepts such as financial ratios, market data, or leadership theories. Students could then be provided with a case study that includes analysis of some components while the learner completes the rest.
• ������history, an annotated or think-aloud analysis of a primary source document demonstrates to learners how experts approach these resources. Examples may include thoughts such as, “I notice the date is 1861, which tells me the author’s bias is likely influenced by the start of the Civil War…”. Students could then complete their own annotations or think-aloud on a similar primary source document.

The 8 generative learning strategies (with applied examples)

1. Summarizing: Example (History, face-to-face): After a mini-lecture on Reconstruction, students write a 3-sentence summary explaining its goals, challenges, and outcomes in their own words.
2. Mapping (concept maps / graphic organizers): Example (Biology, online asynchronous): Students create a concept map linking cellular respiration stages (glycolysis, Krebs cycle, ETC) using a shared digital mapping tool.
3. Drawing: Example (Physics, hybrid lab): Students draw a free-body diagram of forces acting on an object before running a simulation on motion.
4. Imagining (mental imagery): Example (Anatomy & Physiology, online synchronous): While reading about blood flow, students mentally visualize the path of oxygenated blood through the heart chambers, guided by instructor prompts.
5. Self-Testing (retrieval practice): Example (Psychology, online asynchronous): Students complete low-stakes quiz questions from memory (no notes) after a module on classical conditioning, followed by immediate feedback.
6. Self-Explaining Example (Mathematics, face-to-face): While solving worked examples, students explain aloud or in writing why each step is taken in solving a system of equations.
7. Teaching (explaining to others) Example (Education, hybrid): Students record a short video teaching a learning theory (e.g., constructivism) to a hypothetical first-year teacher audience.
8. Enacting (gestures or physical manipulation): Example (Chemistry, in-person lab): Students use hand gestures to model electron movement during covalent bonding before writing structural formulas.

Key Takeaway: The most powerful learning gains occur not from what instructors present, but from what learners actively generate—and the effectiveness of each strategy depends on matching it to the content, learner prior knowledge, and learning context. Thoughtful selection and scaffolding of generative strategies can reliably improve comprehension and transfer.

Read the full article here:

Fiorella, L., & Mayer, R. E. (2016). Eight ways to promote generative learning. Educational Psychology Review 28(4):717–41.&�Բ�����;.

Beyond course design, the IP Toolkit helps faculty support day-to-day classroom practice with concrete tools that promote equity and engagement. For instance, it offers strategies for facilitating discussions in ways that encourage participation from quieter students and prevent dominant voices from taking over. It also recommends flexible assignment structures that allow students to demonstrate learning in multiple ways—an approach that supports a wider range of learning preferences and abilities. Together, these resources make the Toolkit a useful, actionable reference for faculty seeking to improve student inclusion, engagement, and learning outcomes.

Check it out here: 

You may have noted in your AI policy in your syllabus that students may not use AI for assessments, but what about during the learning process? Many aspects of effective learning are counterintuitive: productive struggle leads to better learning, re-reading and highlighting do not improve memory, we don’t always prefer the most effective learning techniques, etc.

We can’t assume that students will intuitively understand the most effective ways to use AI for learning, so it’s up to us to provide this guidance for them. Consider providing some suggestions to learners about how they might use AI to help them understand a reading assignment, quiz themselves to prepare for an assessment, or explore difficult concepts with personally relevant examples. You can find more ideas here: .

Key Takeaways for Faculty

• Active learning works—even when students doubt it. Students may feel uncomfortable or “lost,” but their actual learning improves.
• Student evaluations may undervalue effective teaching. Feeling of learning and actual learning can diverge; resistance doesn’t mean the approach is ineffective.
• Set expectations early. Tell students that increased effort and struggle are normal—and beneficial—in active learning.
• Support metacognition. Brief reflection activities can help students see their progress and reduce the perception gap.
• Use multiple measures of teaching effectiveness. Pair student feedback with learning assessments or performance data.

Read the full article online:

Deslauriers, L., McCarty, L.S., Miller, K., &amps; Kestin, G. (2019). Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. PNAS, 116(39). 

The Nine Cognitive Challenges & Our Suggestions

1. Cognitive Challenge: Student mental mindset — students’ attitudes, beliefs, expectations about the course, their ability, and value of the content.
   Our recommendation: Be intentional about student mindset: From day one, communicate clearly the value of the course, the relevance to students’ goals, and emphasize that ability can grow with effort (growth mindset). Setting this tone helps mitigate fixed-mindset beliefs and promotes belonging and self-efficacy.
2. Cognitive Challenge: Metacognition and self-regulation — students’ ability to monitor their own learning, judge their understanding, regulate study behaviors.
   Our recommendation: Support metacognition and self-regulation: Rather than assume students will monitor their own learning, build-in scaffolds (like study plans, exam-wrappers, reflective prompts) that ask students to reflect on what they know, what they need to do, and how they will adjust.
3. Cognitive Challenge: Student fear and mistrust — negative emotions, anxiety, and lack of trust in the instructor or course that interfere with learning.
   Our recommendation: Foster trust and reduce anxiety: Create an environment of openness and fairness; explicitly explain your course policies, offer supportive feedback, allow revision when possible, and express a genuine belief in student capability. For adult learners especially, acknowledge diverse backgrounds and potential anxieties about re-entry, prior experience, or balancing responsibilities.
4. Cognitive Challenge: Insufficient prior knowledge — students may lack the necessary background or foundation to learn new content effectively.
   Our recommendation: Assess and build prior knowledge: Especially for adult learners who may have varied or interrupted educational backgrounds, assess what they bring and fill the gaps early. Low-stakes pre-quizzes, review tasks, or scaffolded assignments help ensure a more even starting line.
5. Cognitive Challenge: Misconceptions — students may hold inaccurate or deeply entrenched beliefs that interfere with learning new concepts.
   Our recommendation: Expose and correct misconceptions: Don’t assume that prior knowledge is accurate. Use diagnostic tools, ask students to predict, observe, explain (POE) experiments, and explicitly challenge common misconceptions.
6. Cognitive Challenge: Ineffective learning strategies — students may use study approaches that are inefficient or counter-productive (e.g., highlighting, rereading).
   Our recommendation: Teach effective learning strategies explicitly: Rather than assuming students know how to learn, model and embed strategies like retrieval practice, spaced practice, self-explanation, elaboration. This is especially useful for adult learners who may default to habits from earlier schooling.
7. Cognitive Challenge: Transfer of learning — students often fail to apply what they’ve learned in one context to new or novel contexts (near/far transfer).
   Our recommendation: Design for transfer — not just for content mastery: Encourage students to apply concepts in new contexts. Use varied examples, encourage analogy, scaffold tasks that require application, and help students reflect on how what they learned in your class might connect beyond it (e.g., their workplace, future courses, real-world problems).
8. Cognitive Challenge: Constraints of selective attention — students’ limited capacity to focus, susceptibility to distractions, multitasking issues.
   Our recommendation: Manage attention and minimize distractions: In online or in-person settings, pay attention to how easily students can become distracted or multitask. Use frequent re-orientation to topic, build in short breaks, keep one clear focus at a time, and design activities that require active engagement rather than passive listening.
9. Cognitive Challenge: Constraints of mental effort and working memory — limits on how much new information students can process at once; cognitive overload.
   Our recommendation: Reduce cognitive load and structure information clearly: Recognize that students’ working memory is limited. Present material in manageable chunks, use advance organizers (outlines, conceptual roadmaps), use dual-modality (verbal + visual) thoughtfully, avoid “seductive details” that distract, and gradually build complexity as students’ automaticity grows.

This framework reminds us that there is no one “best method” for all students and all contexts. Effective teaching involves diagnosing which challenges are most relevant to your specific learners and adapting practices accordingly.

Read the full article online:

Chew & Cerbin (2020). The cognitive challenges of effective teaching. The Journal of Economic Education, 52(1).