Sunday, April 7, 2024

Book Review: Make it Stick - Faith Whitfield

        Everyone has found themselves at one point or another wishing they felt more prepared, had studied more or were better able to remember what they had studied. This is an uncomfortable feeling that the authors feel could be avoided if the correct methods of studying had been used. Traditional study methods involving re-reading, mass practice, cramming, high-lighting, in-depth note taking may not be as valuable and the best use of our study time. This will give both educators and learners a new way of thinking about their learning and teaching methods.

    Brown, Roediger and McDaniel authored the book, Make it Stick (2014) to explain how learning and memory function through various strategies: reflection, the testing effect, spacing and interleaved practice. They use a variety of examples, across many disciplines to prove their work and make their findings purposeful to a broader audience. The authors strive to convince the readers to be critical about the way they think and learn, using many techniques that differ from what many consider the best way to learn and retain information.

    How does one better remember, understand and recall information? First, we must get comfortable with being uncomfortable. Many of the ideas shared will challenge people to do things they are not familiar with, thus giving them a feeling of not being completely in control; but wait, something better is coming. This book uses strong, research-based case studies to provide useful methods of learning, consolidation and retrieval of memory in a easy to read, understandable and applicable way. It is interesting, engaging and the methods will be useful to a wide variety of professional disciplines.

    While reading through this book, one will notice that it is extremely repetitive. This is intentional. The writers emphasize spaced learning and giving time for information to sink in. “Effortful recall of learning, as happens in spaced practice, requires that you “reload” or reconstruct the components of the skills or material anew from long-term memory rather than mindlessly repeating them from the short-term memory” (pg. 82). Traditionally, one practices the same type of problem or rereads the same material over and over until they feel they understand a concept and then move on. This allows one to be tricked into thinking they have it and will be able to recall later, but when that time comes, they have lost it. Spacing learning out over time and coming back to things time and time again allows learning to move from the short-term memory into the long-term memory through interconnected networks of knowledge that increase and support mastery of information to be applied with versatility. This is the reason the authors repeat their ideas numerous times throughout the book through storytelling and multiple examples.

    Spacing out learning and practice is important, but how the information is presented is equally important. The authors stress the use of interleaving material and the elaboration of concepts. Interleaving can be thought of as the way things are practiced. Mixing up learning by introducing new ideas, methods of practice, types of questioning and the use of different skills builds connections between ideas that would not be there by using only mass practice. This creates new pathways and makes information more retrievable and versatile with future learning. Elaboration is the ability to restate information in one’s own words and create analogies to other subjects, material or information known. When you think or talk about what you’ve learned, it provides your brain new ways of making sense of information. This may seem like hard work, but anything worth doing, is worth doing well. The authors mentioned if learning is not hard, then it is like writing in the sand and it will all be washed away.

    Learning should be a challenge. We need to allow ourselves time to struggle with new information or a different type of problems. This provides the brain time to think about what it needs to solve the problem, attempt to make sense of it and pull information from long-term memory. Unsuccessful attempts to solve a problem make someone think about what they don’t know. The book refers to this as reflection. The authors write, reflection can involve several cognitive activities that lead to stronger learning: retrieval, elaboration and generation of knowledge. Using reflection in learning is powerful! Giving yourself the opportunity to think about what you do know, what you still need to know, and what you need in order to get to that point will deepen mastery and improve learning strategies in the future. Being reflective is a way of monitoring ones learning, being more self-aware and giving one more control of what still needs to be done. We need to be willing to make mistakes! “It is better to solve a problem than to memorize a solution. It’s better to attempt a solution and supply the incorrect answer than not to make the attempt” (pg. 88). This can be very challenging due to our fear of failure. This fear can take away our ability to learn and grow by causing anxiety. Anxiety takes space in our working memory which limits the amount of new information we can hold there and work with. Allowing ourselves time to reflect without judgement, gives us the vital knowledge of what we understand, still need to grasp and the connections to build on what we know.

    The biggest take away for me is the notion of “testing to learn”. Think about your schooling and your association with tests. Are they positive or negative? When you think about testing, are you thinking about individual concepts, units or mid-term and final exams? The authors emphasize frequent self-quizzing and the use of frequent quizzes for educators within their classrooms. “Tests should be cumulative (spaced repetition), varied in content (interleaving), and graded (retrieval practice” (pg. ). The goal of these tests/quizzes is for one to use in a reflective way to understand what they know (strengths) and what they need to work on (weaknesses). “Design quizzing and exercises to reach back to concepts and learning covered earlier in the term, so that retrieval practice continues, and the learning is cumulative, helping students to construct more complex mental models, strengthen conceptual learning, and develop deeper understanding of the relationships between ideas or systems” (pg. 227). Frequent quizzing can be incorporated into study routines and classes. They should be scheduled and not used in a negative or disciplinary way. This will allow one to see material in repetition and in multiple facets over time to increase understanding and knowledge retrieval.

    The book references Bloom’s taxonomy and the 6 levels of classified cognitive learning levels and taking one’s learning from gaining knowledge through the most sophisticated level by being able to evaluate opinions and ideas and make critical judgements based on evidence. The authors stress that this can best be done by learning with a “growth mindset”. This term was created by Dr. Dweck to describe the underlying beliefs people have about learning and their level of intelligence. When a person believes they can get smarter, they understand that the effort they put into something makes them stronger. Therefore, they put in extra time and effort, and that leads to higher achievement. Simply put, if you think you can, you can! “Learning comes down to the simple fact that the path to complex mastery or expert performance does not necessarily start from exceptional genes, but it most certainly entails self-discipline, grit and persistence”, (page 199). The authors encourage readers to use phrases such as, “you worked really hard at that” or “you have strong work ethic and persevered” instead of phrases that are locked in such as, “you are smart” or “you are very intelligent”. These phrases are static and do not encourage people to continue to work hard, but rather that they already have what it takes and do not necessarily need to put more into their learning/understanding. People respond better to being praised for diligence and hard work (malleable) over mere intelligence (static).

    If you have found yourself unprepared for tests, not comprehending your reading or retaining information over time, this is a great book for you! Through the use of spacing, interleaving, repetition, reflection and the testing effect, you will become more critical of your learning and create new pathways for information to be retrieved. Putting these new skills into practice will create better recall through reflection and encoding strategies. For all the strategies this book offers to help, it is equally effective in teaching those that don’t and should be taken out of our studying tool box due to their proven ineffectiveness. This book does not have all the answers for educators, but it does provide strong research-based strategies to help students create stronger learning methods and new strategies to help deepen their knowledge base and create pathways for knowledge retrieval. These techniques will help them be more critical of the way they learn and the knowledge they gain.

About the author: Faith Whitfield teaches middle-school math at Heritage Grove Middle School in Plainfield District 202 and is a CISLL affiliate. 

References

Dweck, C. S. (2007). Mindset: The New Psychology of Success. Random House Publishing Group.

Roediger III, H. L., Brown, P. C., & McDaniel, M. A. (2014). Make It Stick: The Science of Successful Learning. Harvard University Press.

Tuesday, April 2, 2024

CISLL Presents: A Language and Literacy Podcast Featuring Dr. Gary Lupyan

 CISLL is excited to share its second episode of CISLL Presents: A Language and Literacy Podcast! Our guest speaker is Dr. Gary Lupyan. The co-hosts, CISLL graduate assistant Megan Andrzejewski, and content expert Dr. Lindsay Harris, join Dr. Lupyan.

Dr. Lindsay Harris is an associate professor of educational psychology at Northern Illinois University. Her research interests include reading across writing systems and sensory modalities, individual differences in lexical knowledge, and language and reading development in blind individuals.

Dr. Gary Lupyan is a professor and the Cognition and Cognitive Neuroscience Area Group Chair at the University of Wisconsin-Madison. He also runs the Lupyan lab at the university. His research interests include understanding the effects of language on cognition and perception.

Listen Here:





Happy listening!

Thursday, March 7, 2024

Can we ever really know what we know? - Lindsey Kojich

So… can we ever really know what we know? As with most things in life, it depends, and we don't fully know! Before embarking on the quest to figure out the answer to this question, we must first understand a little bit of history about what it means to know things.

The History of Epistemic Cognition and Metacognition

Back in the 1970s, William Perry constructed a model of epistemic cognition.…what is epistemic cognition you ask? According to Perry, individuals transition through successive levels of beliefs and views about knowledge (Greene et al., 2018). There have been many additional models proposed about epistemic cognition over the years all based on Perry’s work. Many of these models share the premise that individuals shift to more sophisticated views of knowledge and what it means to know things as they progress through education (Greene et al., 2018). Individuals typically begin viewing knowledge from a realist perspective, which means that you believe knowledge is essentially objective facts (Greene & Yu, 2016). Beyond the realist perspective is absolutism. Absolutism reflects the perspective that individuals can have objective knowledge, but also understand that their knowledge or perspective may not reflect reality (Greene & Yu, 2016). The following phase is multiplist. Multiplist perspective views knowledge as a “construction of reality” (Greene & Yu, 2016, pp. 47) meaning that knowledge is subjective and can change over time. The final phase is evaluativist. Evaluativsts believe that understanding or knowing everything is impossible, however we can use objective and subjective knowledge to help us understand the world around us (Greene & Yu, 2016).

At this point you are probably wondering why I am giving you a history lesson? Because without understanding an individual's beliefs about knowledge or epistemic cognition, it would be very difficult to know what we really know. That big question partially hinges on what an individual believes is knowledge and how knowledge is defined.

OKAY, so now that we have a little background on what epistemic cognition is and how beliefs about our knowledge can influence what we think knowledge is, we now need to understand more about reflecting on our knowledge, or metacognition. Metacognition is commonly described as thinking about thinking. Going back to the big question, if we are really able to know what we know, we HAVE to be able to think about what we know and self-assess our own knowledge. Metacognition has been well studied in a variety of fields and all agree that humans are able to self-reflect or think about their thinking (Greene et al., 2018).

Measuring Knowledge

Great, so we have established that we can in fact think about our thinking so the final step is to figure out how we measure our knowledge! The concept of evaluating how accurate we are about our knowledge is also known as knowledge calibration. Individuals can either be well calibrated (meaning that their assessment of their knowledge is accurate) or poorly calibrated depending on how they assess their knowledge compared to what they actually know. If an individual is poorly calibrated, they are either overconfident and know less than they think they do, or underconfident, knowing more than they think they do. Knowledge calibration is a field of research that goes back many decades. In fact, back in 1999 psychology researchers David Dunning and Justin Kruger … (Yes, THE Dunning and Kruger!!) performed four experiments on undergraduate students that evaluated participants’ ability to assess their knowledge. Four studies were performed in a variety of subjects. The first study investigated the calibration of humor and participants' ability to decide what jokes are funny and what jokes others would find funny. Results of this study found that generally, participants overestimated their ability to deduce what is funny and that individuals who were the most overconfident were the least aware of it … ouch (Kruger & Dunning, 1999)! The second study investigated the ability of participants to self-assess their logical reasoning compared to that of other students and estimate their success on a 20-item reasoning test. Dunning and Kruger found the same results on the logical reasoning study that they did with the humor study. Researchers went on to perform two additional studies focusing on grammar and metacognition. During these two studies, it was found that individuals with the poorest grammar were also deficient in metacognitive skills, however, if individuals are trained to improve their metacognitive skills, their knowledge calibration can improve (Kruger & Dunning, 1999).

So, relating this back to metacognition, individuals who have poor knowledge calibration typically have poor metacognition to judge their own knowledge, thus resulting in a poor self-assessment (Kruger & Dunning, 1999). The interesting other finding that they found throughout their studies is not just that individuals with poor competence have inflated self-assessment, but that individuals on the opposite end of the spectrum with high knowledge, tend to underestimate their knowledge (Kruger & Dunning, 1999). Thus, individuals can be poorly calibrated two ways, either under-confident or over-confident.

Knowledge Calibration in the 20th Century

So now that we’ve learned about knowledge calibration and that a good chunk of us is pretty bad at evaluating how much we really know (yikes!) let's discuss how these concepts have been put to use in today’s society. Knowledge calibration has been well studied in the fields of psychology and education, and recently it is also being applied to other fields such as marketing and consumer sciences. Obviously, the use and dependency on computers and technology has skyrocketed over the last two decades. The quick rise and development of technology has really caused a spectrum of ability to use the internet. In fact, Dunning and Kruger’s research on knowledge calibration has now permeated other fields including studies on the world wide web. In 2007, Kishore Pillai and Charles Hofacker investigated knowledge calibration of the web and explored how involvement, usage, gender, knowledge type, and experience impact an individual's knowledge calibration. The researchers recruited two groups, one with 151 undergraduate business students and another group consisting of 153 adults (Pillai & Hofacker, 2007). Participants completed a questionnaire about their web usage, experience, knowledge, and involvement, and researchers then compared the answers of the two groups. At the end of the study, researchers concluded that involvement with the web assists in knowledge calibration and appropriate knowledge calibration in turn reduces user frustration with the web. Furthermore, researchers found that an individual's usage, experience, and gender did not affect their knowledge calibration (Pillai & Hofacker, 2007). Obviously, the concept of knowledge calibration can be applied to many different fields and may be different depending on topic being studied.

Bottom Line

So, what do we think? Can we ever really know what we know? Based on current research I’d say I’m not too confident, however, we can get closer to knowing what we know by being more calibrated and skilled at metacognition. Tips and tricks for that in another post. Thanks for reading!

About the author: Lindsey Kojich is a doctoral student in Health Sciences and a CISLL affiliate.

References

Greene, J. A., Cartiff, B. M., & Duke, R. F. (2018). A meta-analytic review of the relationship between epistemic cognition and academic achievement. Journal of Educational Psychology, 110(8), 1084–1111. https://doi.org/10.1037/edu0000263

Greene, J. A., & Yu, S. B. (2016). Educating Critical Thinkers: The Role of Epistemic Cognition. Policy Insights from the Behavioral and Brain Sciences, 3(1), 45–53. https://doi.org/10.1177/2372732215622223

Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one's own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121–1134. https://doi.org/10.1037/0022-3514.77.6.1121

Pillai, K. G., & Hofacker, C. (2007). Calibration of consumer knowledge of the web. International Journal of Research in Marketing, 24(3), 254–267. https://doi.org/10.1016/j.ijresmar.2007.02.001