Scaffolding – Center for Teaching and Learning /ctl Wed, 25 Mar 2026 20:25:51 +0000 en-US hourly 1 /ctl/wp-content/uploads/sites/88/2024/01/cropped-android-chrome-512x512-1-32x32.png Scaffolding – Center for Teaching and Learning /ctl 32 32 Teaching the Parts AND the Whole /ctl/teaching-the-parts-and-the-whole/ Wed, 11 Mar 2026 21:20:10 +0000 /ctl/?p=5570 Most instructors quickly realize that they cannot just explain what they know and students will immediately understand it. Experts have so much context to their understanding that novices are missing. We then realize we have to break down a concept or topic into smaller parts to help the learner understand the bigger idea. Sometimes, though, we spend so much time on the smaller parts, we neglect to support students in assembling them into the whole that we understand. We emphasize specific pieces of information, skills, or approaches and assess them, then become disappointed when learners are not able to apply their learning in new contexts. Effective learning must use a combination of breaking down concepts and skills into smaller parts as well as strategically helping students to understand how they relate and differ across contexts.

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Most instructors quickly realize that they cannot just explain what they know and students will immediately understand it. Experts have so much context to their understanding that novices are missing. We then realize we have to break down a concept or topic into smaller parts to help the learner understand the bigger idea. Sometimes, though, we spend so much time on the smaller parts, we neglect to support students in assembling them into the whole that we understand. We emphasize specific pieces of information, skills, or approaches and assess them, then become disappointed when learners are not able to apply their learning in new contexts. Effective learning must use a combination of breaking down concepts and skills into smaller parts as well as strategically helping students to understand how they relate and differ across contexts.

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 .

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Worked Examples /ctl/worked-examples/ Wed, 28 Jan 2026 18:09:51 +0000 /ctl/?p=5137 When students are provided with practice or application assignments after learning new content, they often use incorrect strategies because they do not fully understand the underlying concepts. You can prevent this ineffective struggle by providing students with worked examples when introducing a new skill or process.

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When students are provided with practice or application assignments after learning new content, they often use incorrect strategies because they do not fully understand the underlying concepts. You can prevent this ineffective struggle by providing students with worked examples when introducing a new skill or process. It is most beneficial to provide multiple examples that illustrate the same underlying concept or skill with different surface features, as well as correct and incorrect examples where students are asked to identify the differences. Providing worked examples during initial instruction reduces cognitive load, but they are not effective when students already understand the underlying concept.

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.
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Eight Ways to Promote Generative Learning /ctl/eight-ways-to-promote-generative-learning/ Wed, 21 Jan 2026 21:28:25 +0000 /ctl/?p=5173 Fiorella and Mayer argue that learning is generative—students learn best when they actively make sense of new information by selecting, organizing, and integrating it with prior knowledge. They synthesize research identifying eight evidence-based strategies that consistently promote deeper understanding and transfer across contexts. These strategies shift learners from passive reception to active sense-making.

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Fiorella and Mayer argue that learning is generative—students learn best when they actively make sense of new information by selecting, organizing, and integrating it with prior knowledge. They synthesize research identifying eight evidence-based strategies that consistently promote deeper understanding and transfer across contexts. These strategies shift learners from passive reception to active sense-making.

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;.

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Reach out to Missing Students /ctl/reach-out-to-missing-students/ Wed, 21 Jan 2026 18:17:13 +0000 /ctl/?p=5161 It's important to identify missing students as soon as possible in the beginning of the semester and to encourage those who have not yet engaged. A simple way to do this is to create a small assignment in Brightspace that all students should submit to by the end of the first or second week of class. After the due date, click on the name of the assignment in Brightspace, and then click Email Users Without Submissions. This will open a new email draft window with the students who have not submitted the assignment in the BCC field. Send a quick message to remind them about the assignment and to let you know if they are having issues with the course.

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It’s important to identify missing students as soon as possible in the beginning of the semester and to encourage those who have not yet engaged. A simple way to do this is to create a small assignment in Brightspace that all students should submit to by the end of the first or second week of class. After the due date, click on the name of the assignment in Brightspace, and then click Email Users Without Submissions. This will open a new email draft window with the students who have not submitted the assignment in the BCC field. Send a quick message to remind them about the assignment and to let you know if they are having issues with the course.

Screenshot of Brightspace assignment with Email Users without Submissions button highlighted
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Guide your students on the use of AI for learning /ctl/guide-your-students-on-the-use-of-ai-for-learning/ Wed, 17 Dec 2025 21:31:35 +0000 /ctl/?p=5188 While there are mixed feelings about generative AI among faculty and students, it's undeniable that AI is not going away and will continue to become embedded in all aspects of life. Even if students choose not to use it, they still need to understand how it works and ethical implications of its use. Who is going to teach them this?

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While there are mixed feelings about generative AI among faculty and students, it’s undeniable that AI is not going away and will continue to become embedded in all aspects of life. Even if students choose not to use it, they still need to understand how it works and ethical implications of its use. Who is going to teach them this?

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: .

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The Cognitive Challenges of Effective Teaching /ctl/the-cognitive-challenges-of-effective-teaching/ Wed, 19 Nov 2025 22:01:13 +0000 /ctl/?p=5329 Chew & Cerbin propose a research-based framework of nine interacting cognitive challenges that teachers must address in order to promote “optimal learning” rather than merely acceptable performance. They emphasize that teaching is not just delivering content but creating the conditions in which students learn. Each of the nine challenges represents a characteristic of how students think, learn, or struggle — the idea being that failure to address any one of these can undermine learning. The authors describe each challenge, provide examples, and suggest instructional strategies for mitigation.

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Chew & Cerbin propose a research-based framework of nine interacting cognitive challenges that teachers must address in order to promote “optimal learning” rather than merely acceptable performance. They emphasize that teaching is not just delivering content but creating the conditions in which students learn. Each of the nine challenges represents a characteristic of how students think, learn, or struggle — the idea being that failure to address any one of these can undermine learning. The authors describe each challenge, provide examples, and suggest instructional strategies for mitigation.

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). 

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A safe and transparent AI platform for learning? Sign me up! /ctl/a-safe-and-transparent-ai-platform-for-learning-sign-me-up/ Thu, 06 Nov 2025 17:24:27 +0000 /ctl/?p=4064  

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 is a secure, collaborative platform that helps faculty and students use AI safely and responsibly. It provides access to multiple AI models in one space—allowing students to compare responses, evaluate accuracy, and reflect on ethical use. Designed for education, BoodleBox prioritizes data privacy, transparency, and low-power AI operations, ensuring environmentally conscious use and protection of student information. Faculty can create shared workspaces, AI-integrated assignments, and reflective activities that make the AI process visible and teach critical evaluation skills. In short, BoodleBox supports responsible, sustainable AI engagement for both teaching and learning.

Read about how faculty are using Boodlebox: .

Find more resources here: 

Watch a short demo showing how to create a course, an assignment, and view student chat conversations below.

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