Please note: this module is currently under construction.
This online module is intended to provide you with an evidence-based approach to teaching at the post-secondary level.
Based on Lovett et al.’s (2023)’s book How Learning Works, this workshop will review some general principles of learning that are grounded in evidence-based research on teaching and learning. You will learn why certain teaching approaches support student learning so you can reflect upon and refine your own approach to teaching.
By the end of this module, you should be able to:
Lovett, M. C., Bridges, M. W., DiPietro, M., Ambrose, S. A., & Norman, M. K. (2023). How learning works: Eight research-based principles for smart teaching. John Wiley & Sons.
As instructors, we can and should build on students’ prior knowledge. However, it is also important to recognize that not all prior knowledge provides an equally solid foundation for new learning.
Using students’ own experiences to generate examples helps learners to make connections and increase retention and overall knowledge acquisition. Examples include scaffolding learning from earlier classes and experiences.
Insufficient, inaccurate, or incorrect information can slow or halt learning. For example, Dunbar, Fugelsang, and Stein (2007) found that scientific misconceptions about why we have seasons often persist. Even after having learned and been tested, students tend to revert to “intuitive” ideas, which can hinder further learning that builds upon these foundational principles and concepts.
You can identify some common misconceptions in your discipline by considering your student’s’ prior learning and connecting new knowledge to prior knowledge.
Students learn and retain more when they can connect what they’re learning to accurate and relevant prior knowledge. For example, college students presented with unfamiliar facts about well-known individuals demonstrated twice the capacity to learn and retain those facts as students who were presented with the same number of facts about unfamiliar individuals (Kole & Healy, 2007).
However, we shouldn’t assume that students will draw on their prior knowledge in new learning situations. It is important to help students activate prior knowledge. You can do this with prompts (e.g., Think about what you know about energy conservation from physics. How might that concept apply to the topic of environmental sustainability we’re discussing today?), reminders (e.g., Remember the case study on urban planning we covered last week—those principles will help you analyze today’s topic on public transportation systems), or recall questions (e.g., Can anyone explain the process of photosynthesis we learned earlier this term and how it connects to plant growth in different climates?).
It’s important that we’re clear about the knowledge requirements of different tasks. Don’t assume that because students have one kind of knowledge that they have another. For example, knowing what is a very different kind of knowledge than knowing how or knowing when. An instructor in a writing course might assume that because students know what a thesis statement is (a declarative sentence outlining the main argument of a paper), they also know how to construct an effective one and when to use it in different contexts.
Assessing both the extent and nature of students’ prior knowledge ensures that we design our teaching appropriately. In this example, the instructor could:
Students may draw on knowledge that is inappropriate for the context when learning new material. This can distort their interpretation of new material or impede new learning. To help students learn when their prior knowledge is or is not applicable:
For example, to help students understand when Newton’s First Law applies, you might say, “Newton’s First Law is applicable when there are no net external forces acting on an object. For example, this law works well in outer space where there’s no friction or air resistance. However, it doesn’t apply in everyday situations on Earth where friction, gravity, and other forces are constantly acting on objects.”
You could provide examples from different contexts: “In outer space, a spacecraft will continue to drift in the same direction unless acted upon by an external force. On Earth, a ball rolling on the floor will eventually stop due to friction, which is an external force that isn’t present in the vacuum of space.”
After presenting these examples, emphasize the difference between space (where the law holds perfectly) and Earth (where external forces are constantly influencing motion). Highlight the similarity in that the law theoretically applies in both cases, but external forces modify the outcome.
To activate students’ prior knowledge, you could ask, “Remember when we discussed friction in our previous lesson? How does friction affect an object’s motion on Earth? How might that change if we were in outer space?” This helps students make the connection between friction (a concept they already know) and Newton’s First Law (a new concept).
It’s important to address inaccurate prior knowledge that might otherwise distort or impede learning. Sometimes, simply exposing students to accurate information and evidence that conflicts with flawed understanding is enough to correct these inaccuracies. However, a single correction or refutation is unlikely to change deeply held misconceptions. Guiding students through conceptual change takes time, patience, and creativity.
For example, students may come into a biology class with the misconception that humans evolved directly from monkeys. To correct this inaccurate prior knowledge, the instructor presents evidence explaining that humans and modern monkeys share a common ancestor but evolved along separate evolutionary paths. While some students may adjust their understanding with this new information, others might still hold onto their original misconception.
To guide students through deeper conceptual change, over several lessons the instructor uses visual diagrams showing the evolutionary tree, compares DNA similarities between species, and engages students in discussions that allow them to explore and question their own misconceptions. By integrating these activities across multiple lessons and encouraging critical thinking, the instructor helps students gradually shift their understanding of human evolution. This ongoing process, rather than a single correction, is what ultimately helps to replace deeply held misconceptions with accurate knowledge.
The following strategies offer some ways to help you determine the extent and quality of students’ prior knowledge, activate students’ relevant prior knowledge, address gaps in prior knowledge, help students avoid applying prior knowledge in the wrong contexts, and help students revise and rethink inaccurate knowledge.
Reflect on common misconceptions in your discipline by working through the following questions:
Dunbar, K. N., Fugelsang, J. A., & Stein, C. (2007). Do Naïve Theories Ever Go Away? Using Brain and Behavior to Understand Changes in Concepts: Kevin N. Dunbar & Jonathan A. Fugelsang. In Thinking with data (pp. 205-217). Psychology Press.
Kole, J. A., & Healy, A. F. (2007). Using prior knowledge to minimize interference when learning large amounts of information. Memory & Cognition, 35(1), 124-137.
Consider two students who are asked to identify when the British defeated the Spanish Armada. The first student tells us that the date is 1588, and the second says that he cannot remember the precise date but thinks it must be around 1590. Given that 1588 is the correct answer, the first student appears to have more accurate knowledge.
However, when asked how they arrived at their answers, the first student says that she memorized the date. In contrast, the second student says he knew that the British colonized Virginia just after 1600 and inferred that the British would not organize colonization until navigation was considered safe. Figuring that it would take around 10 years for navigation to be organized, he arrived at the answer of 1590.
These responses reveal very different ways of organizing knowledge, which has implications for future learning.
Experts and novices in a field organize knowledge in different ways. One of the ways these knowledge organizations differ is in the number or density of connections among the concepts, facts, and skills they know. The images below show different examples of how these organizational structures can differ. Pieces of knowledge are represented by nodes (circles), and relationships between them are represented by links (lines).
Although students may not always possess highly connected knowledge organizations, they can develop more sophisticated knowledge organizations over time. You can help your students by providing structures that help them develop more connections among pieces of knowledge.
The following strategies offer some ways for you to assess your own knowledge organizations and help students develop more connected and meaningful ways of organizing their knowledge.
Spatial diffusion refers to the way ideas, goods, and people move across space and the factors influencing this movement (Rubenstein, 2019).
Spatial diffusion is connected to various related concepts such as globalization, migration patterns, urbanization, transportation networks, and cultural exchange. An expert geographer would understand spatial diffusion as part of a complex system that includes physical geography (e.g., natural barriers like mountains), human geography (e.g., political boundaries), and economic geography (e.g., trade routes and market access). They would connect it to historical events like colonization, technological advances like air travel, and social dynamics like the spread of ideologies or diseases.
Students might view spatial diffusion as a simple, linear process, assuming ideas or people spread uniformly without recognizing the influence of geography, political power, or cultural resistance. This misconception might cause them to overlook how uneven diffusion creates inequalities or shapes regional development differently.
To help students, you could use a concept map showing how spatial diffusion intersects with political, economic, and cultural factors. Students could complete a sorting task where they categorize different types of diffusion (e.g., contagious, hierarchical, relocation) and identify real-world examples. Or you could present case studies (like the spread of the internet or the diffusion of global fashion trends) and ask students to analyze how various factors influenced the patterns in different regions.
Rubenstein, J. M. (2019). The Cultural Landscape: An Introduction to Human Geography (13th ed.). Pearson.
There are two important concepts that are central to understanding motivation: the subjective value of a goal and the expectancies, or expectations, for achievement of that goal.
A student will be more motivated to pursue a goal or task that has the highest value to them. Value can be derived from different sources (Wigfield & Eccles, 2000). Click on the accordions below to learn about different sources of value.
When motivation is due to attainment value, you get personal satisfaction and sense of accomplishment from successfully mastering a goal or task. For example, a student may feel a deep sense of fulfillment after solving complex analytical problems, which motivates them to spend time working on these tasks to demonstrate and further develop their problem-solving abilities.
When motivation is due to intrinsic value, you get satisfaction simply from doing the task rather than from a particular outcome of the task. For example, a student spends hours writing a computer program because of the enjoyment they derive from the task.
When motivation is due to instrumental value, an activity or goal helps you accomplish other important goals. For example, a student may be motivated to study in a challenging organic chemistry course because they know it will help them do better on the MCAT and strengthen their medical school application, ultimately helping them achieve their goal of becoming a doctor.
People are motivated to pursue goals and outcomes that they believe they can successfully achieve. Two forms of expectancies inform our understanding of motivated behaviour.
Outcome expectancies refer to belief about the likely result or consequence of your actions (Carver & Scheier, 2001). It’s about whether you think your efforts will lead to a desirable outcome, regardless of your ability to perform the task. For example, even if a student believes they can study well and do everything right, they might still doubt that doing so will improve their grade if they think the exam is unfair or too difficult (i.e., negative outcome expectancy).
Efficacy expectancies refer to belief in your ability to successfully perform a task or take specific actions to achieve a goal (Bandura, 1997). It’s about your confidence in whether you can do what’s needed to succeed, which can influence how much effort you put into tasks and how persistent you are when facing challenges.
This perception is shaped by several factors, including:
For example, a student preparing for a big math exam feels confident because they’ve done well on previous math tests and their instructor’s positive feedback on their homework boosts their belief that they can handle the upcoming exam.
Values and expectancies interact within the broader environmental context in which they exist. Click on the plus icons in the image below to learn how differences in value, efficacy, and the supportive nature of the environment can influence students’ motivation. Each of these dimensions are features of the learning environment over which we can have substantial influence. If we neglect any single dimension, motivation can suffer substantially.
(Image adapted from Ambrose et al. (2010), p. 80.)
Reflect on how you can increase student motivation by working through the following questions:
Bandura, A. (1997). Self-efficacy: The exercise of control. Macmillan.
Carver, C. S., & Scheier, M. F. (2001). On the self-regulation of behavior. Cambridge University Press.
Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary educational psychology, 25(1), 68-81.
Practice and feedback are essential for learning. Within the context of a learning environment, practice refers to any activity where students engage their knowledge or skills. Feedback, on the other hand, refers to information provided to students about their performance on a task that is intended to guide future behaviour. Practice and feedback are at their most effective when they are aligned with one another and with the specific learning goals they aim to support.
The greatest challenge in providing students ample practice and feedback is the time required from both students and faculty. While we can’t change the duration of a term or class session, we can make the design of practice activities and delivery of feedback more efficient.
Research suggests that, to advance student learning, practice should focus on a specific goal or criterion, target an appropriate level of challenge, and be of sufficient frequency.
Research indicates that time spent in deliberate practice, as opposed to more general forms of practice, predicts ongoing learning and the development of expertise in a specific field (Ericsson et al., 2003). A key feature of deliberate practice is that it involves working toward specific goals. Goals provide students with a focus for their learning, which leads to more time and energy going to that area of focus. Having goals also allows students to more accurately measure their progress in learning.
Instructors often make the mistake of thinking that they are providing students with goal-directed practice, when they are not. This is due mainly to expert blind spot – experts can sometimes fail to see when stated goals are unclear to students. When instructors do not clearly articulate goals, it can be difficult for students to know what (or how) to practice.
For example, in an introductory psychology course an instructor asks students to “analyze a case study.” The instructor assumes that students understand that “analyze” means identifying key psychological theories, applying them to the case, critically assessing their relevance, and drawing evidence-based conclusions. However, some students end up summarizing the case, while others list relevant psychological concepts without much analysis. Because the instructor did not break down the specific goal of “analyzing,” students misinterpreted the task and struggled to focus their practice on the correct skills.
A clearer, goal-directed practice might involve explicitly stating: “The goal is to apply at least two psychological theories to the case study, assess their strengths and weaknesses in explaining the behavior, and support your assessment with evidence from the course readings.” By articulating specific goals, students can more effectively measure their progress and focus their practice on developing the analytical skills needed for the task.
To identify the appropriate level of challenge for student practice, instructors need to ensure that tasks are neither too difficult, causing frustration, nor too easy, leading to disengagement. Effective practice lies in the “zone of proximal development” (Vygotsky, 1978), where students can succeed with some assistance, enabling learning and growth.
In large or diverse student groups, adjusting the difficulty of practice tasks at the group level is more efficient than tailoring instruction to individual students’ needs. Clarke et al. (2005) demonstrated that for students with little prior knowledge, sequential learning (focusing on one skill at a time) was more effective than concurrent learning, which posed too great a challenge. For more knowledgeable students, the opposite was true. Instructional scaffolding, such as providing structured support and breaking tasks into smaller steps, can help students at different levels engage with appropriately challenging material (Palinscar & Brown, 1984).
When tasks are too easy, strategies like retrieval practice, spaced practice, or interleaved practice create “desirable difficulties” that enhance learning without overwhelming students (Bjork & Bjork, 2020). These approaches adjust the challenge level across time and tasks, ensuring that all students are appropriately challenged to promote learning.
Students need enough practice for the benefits of practice to accumulate (Martin et al., 2007). Practical constraints of time and resources often prompts instructors to move through material too quickly, giving students little opportunity to practice a skill. It often takes more than one opportunity to learn something new, especially if the goal is for that new knowledge to be retained across time and transferred to new contexts.
Accumulating practice helps students progress through different stages of learning. Early on, students may struggle to see improvement, but as they practice more and reach the middle phase of learning, they often experience significant performance gains. Repeated practice enables students to refine their skills and better detect improvements in their performance.
Imagine a student learning to play the piano. At first, they struggle with basic finger placement and reading sheet music. During the early phase of learning, despite practicing daily, they may feel frustrated by slow progress and frequent mistakes. It’s difficult for the student to detect any real improvement, and they might feel as though they’re stuck on a plateau.
However, as the student continues practicing over several weeks, they enter the middle phase of learning. The repetition of scales and simple songs begins to pay off—they can now play more fluently, make fewer mistakes, and even detect where their technique has improved, such as smoother transitions between chords. This progression reflects the accumulation of practice, where repeated efforts help refine their skills and lead to noticeable performance gains.
The purpose of feedback is to help learners achieve a desired level of performance. Research points to two features of feedback that make student learning more effective and efficient: content and timing.
Consider two students who share the same misconception, leading them to solve several problems incorrectly. However, they receive feedback at different times and with different levels of detail. The first student completes all the problems in one large homework assignment and receives it back a week later with a C grade. Noticing that points were deducted from every problem, he concludes that he is completely lost on the topic.
In contrast, the second student is in a class where the instructor incorporates regular problem-solving practice during each lesson. After attempting a few problems, the instructor highlights common mistakes and demonstrates how to correct them. This student quickly receives feedback indicating that he made the same error in two practice problems. With this prompt input, he corrects his understanding and applies this knowledge to complete his homework problems correctly.
Due to the differences in the timing and content of the feedback, these two students may take very different paths moving forward. The first student, unaware that his poor performance stemmed from a single misconception, may feel discouraged and avoid practicing further, perhaps even skipping preparation for the upcoming exam. In contrast, the second student, having identified and corrected his error early on, can continue practicing and strengthen his understanding of the topic. This illustrates how timely, targeted feedback can not only enhance immediate learning but also set the stage for future success.
Research has consistently shown that feedback is most effective when it highlights specific areas where students need improvement, rather than offering general assessments of their performance. In one study, students learning to solve geometry problems received automatic feedback when they made errors. One group received general messages indicating an error, while another group was given specific details about their mistakes and how to correct them. The students who received targeted feedback performed significantly better on a post-test measuring problem-solving skills (McKendree, 1990).
On the other hand, providing excessive feedback is not always helpful. Too much feedback can overwhelm students, making it unclear which aspects of their performance need the most attention. For example, studies have found that when students receive numerous margin comments on their writing, they either become overwhelmed or focus on easily fixable issues, such as minor details, rather than addressing more significant conceptual or structural problems (Schreibersdorf, 2014).
The full benefits of feedback can be realized only when the feedback adequately directs students’ subsequent practice and when students can incorporate that feedback into further practice.
Generally, more frequent feedback leads to more efficient learning by helping students correct their errors early, preventing misconceptions from becoming ingrained. Extensive research supports this idea (Hattie & Timperley, 2007). However, providing frequent feedback is often challenging due to practical constraints. Fortunately, even minimal feedback on student writing can lead to improved second drafts, as it helps students better understand what their readers grasp and what they do not (Traxler & Gernsbacher, 1992).
This does not mean that more frequent feedback is always better. The timing of feedback is also crucial. For example, a study on college students learning to write mathematical functions in a spreadsheet (Mathan & Koedinger, 2017) found that students who received immediate feedback after making an error performed worse on final assessments than those who received delayed feedback. The immediate feedback group had fewer opportunities to practice recognizing and correcting their own mistakes. In contrast, the delayed feedback group had more chances to self-correct, as feedback was only provided if they didn’t recognize their error or made several failed attempts to fix it. In this way, the feedback, though delayed, was more aligned with the learning goals of error recognition and correction.
The following strategies can help you implement effective practice opportunities for students in your course and provide efficient and effective feedback opportunities.
Reflect on the role of goal-directed practice and feedback in your teaching by working through the following questions:
An instructor of an introductory economics course has found that many students struggle with applying the concept of “opportunity cost” in decision-making problems.
Currently, students practice this concept through a single assignment where they analyze a business scenario and identify the opportunity costs involved. However, this assignment is graded, and they do not have opportunities to revise their work or apply the feedback to future tasks. Upon reflection, this practice may not be sufficiently goal-directed or repeated.
The feedback provided is detailed but comes at the end of the assignment with no chance for students to use it in subsequent work. The feedback is aligned with learning goals, but without additional practice, students cannot apply the feedback to improve their understanding of opportunity cost.
To accumulate practice more efficiently, the instructor could add low-stakes practice opportunities, such as in-class polling questions where students analyze opportunity costs in various scenarios. Students could submit a draft of their assignment, receive targeted feedback, and resubmit a final version. This would provide more chances to practice and apply feedback without significantly increasing grading time. Incorporating retrieval practice during class lessons could also help solidify their understanding over time.
Bjork, R. A., & Bjork, E. L. (2020). Desirable difficulties in theory and practice. Journal of Applied research in Memory and Cognition, 9(4), 475.
Clarke, T., Ayres, P., & Sweller, J. (2005). The impact of sequencing and prior knowledge on learning mathematics through spreadsheet applications. Educational technology research and development, 53(3), 15-24.
Ericsson, K. A., Starkes, J., & Ericsson, K. (2003). Development of elite performance and deliberate practice. Expert performance in sports: Advances in research on sport expertise, 49-83.
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of educational research, 77(1), 81-112.
Martin, F., Klein, J. D., & Sullivan, H. (2007). The impact of instructional elements in computer‐based instruction. British Journal of Educational Technology, 38(4), 623-636.
Mathan, S. A., & Koedinger, K. R. (2018). Fostering the intelligent novice: Learning from errors with metacognitive tutoring. In Computers as Metacognitive Tools for Enhancing Learning (pp. 257-265). Routledge.
McKendree, J. (1990). Effective feedback content for tutoring complex skills. Human-computer interaction, 5(4), 381-413.
Palinscar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities. Cognition and instruction, 1(2), 117-175.
Schreibersdorf, L. (2014). Literary discipline in the margins: How students read comments on literature papers. Pedagogy, 14(3), 499-530.
Traxler, M. J., & Gernsbacher, M. A. (1992). Improving written communication through minimal feedback. Language and Cognitive Processes, 7(1), 1-22.
Vygotsky, L. S. (1978). Mind in society. Cambridge, MA: MIT Press. Wertsch, J. V. (1985). Vygotsky and the social formation of mind. Cambridge, MA: Harvard University Press
Congratulations! You have completed this online module on Research-Based Principles for Smart Teaching!
You should now be able to:
This module covered:
The four research-based principles reviewed include:
Because these principles are interconnected, you can design strategies that simultaneously address how students build knowledge, stay motivated, and develop their own learning strategies, leading to more robust and effective learning experiences.
You can find more information about these and other research-based principles in Lovett et al. (2023)’s book How Learning Works.
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