Our Research & Evidence-Base

COGx Research & Evidence Base

Scientific Literature Supporting COGx Programs

Overview

Pedagogical research suggests that teachers are much more effective at reaching a variety of students if they understand the principles of human learning (Chew & Cerbin, 2021). Furthermore, when students master evidence-based learning strategies, they better understand how to acquire and apply new information and feel more confident and autonomous (Finley et al., 2010). Our programs achieve both outcomes by democratizing and translating a vast amount of learning science into application-ready programs in which evidence is distilled into action. The programs represent a research base of over 1,300 scientific sources along with input from academics. Below is a sample of the types of publications that are a part of our research base.

Teaching & Learning Strategies

Information Processing

Emotions & Engagement

Learning Enhancement & Neuroplasticity

Cognitive Diversity

How Learning Happens

This section contains high-level research on the conditions and mental processes that promote learning. The learning process is inclusive of the sub-sections and their topics below it.

Agodini, R., Harris, B., Atkins-Burnett, S., Heaviside, S., Novak, T., & Murphy, R. (2009). Achievement effects of four early elementary school math curricula: Findings from first graders in 39 schools. NCEE 2009-4052. National Center for Education Evaluation and Regional Assistance. https://ies.ed.gov/ncee/pubs/20094052/pdf/20094052.pdf

Akkus, R., Gunel, M., & Hand, B. (2007). Comparing an inquiry‐based approach known as the science writing heuristic to traditional science teaching practices: Are there differences?. International Journal of Science Education, 29(14), 1745-1765. https://doi.org/10.1080/09500690601075629

Ambrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How learning works: Seven research-based principles for smart teaching. John Wiley & Sons. https://firstliteracy.org/wp-content/uploads/2015/07/How-Learning-Works.pdf

American Psychological Association (2015). Top 20 principles from psychology for preK–12 teaching and learning. http://www.apa.org/ed/schools/cpse/top-twenty-principles.pdf

Balduf, M. (2009). Underachievement among college students. Journal of Advanced Academics, 20(2), 274-294. https://doi.org/10.1177/1932202X0902000204

Biggs, J., & Tang, C. (2011). Teaching for quality learning at university. McGraw-Hill Education (UK).

Bjork, E. L., & Bjork, R. A. (2011). Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. In M. A. Gernsbacher, R. W. Pew, L. M. Hough, J. R. Pomerantz (Eds.) & FABBS Foundation, Psychology and the real world: Essays illustrating fundamental contributions to society (pp. 55–64). Worth.

Bjork, R. A. (1994). Memory and metamemory considerations in the training of human beings. In J. Metcalfe, & A Shimamura (Eds.), Metacognition: Knowing About Knowing (pp. 185-205). MIT Press.

Bullmaster-Day, M. L. (2011). Let the learner do the learning: What we know about effective teaching. Graduate School of Education Lander Center for Educational Research. https://quespaco.files.wordpress.com/2011/12/let_the_learner_do_the_learning.pdf

Chew, S. L., & Cerbin, W. J. (2021). The cognitive challenges of effective teaching. The Journal of Economic Education, 52(1), 17-40.

Donker, A. S., De Boer, H., Kostons, D., Van Ewijk, C. D., & van der Werf, M. P. (2014). Effectiveness of learning strategy instruction on academic performance: A meta-analysis. Educational Research Review, 11, 1-26.

Kim, D., Kim, B. N., Lee, K., Park, J. K., Hong, S., & Kim, H. (2008). Effects of cognitive learning strategies for Korean learners: A meta-analysis. Asia Pacific Education Review, 9(4), 409-422.

Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work. Educational Psychologist, 41(2), 75-86. https://doi.org/10.1207/s15326985ep4102_1

Pashler, H., Bain, P. M., Bottge, B. A., Graesser, A., Koedinger, K., McDaniel, M., & Metcalfe, J. (2007). Organizing instruction and study to improve student learning: A practice guide. National Center for Education Evaluation and Regional Assistance. https://ies.ed.gov/ncee/wwc/Docs/PracticeGuide/20072004.pdf

Roediger, H. L., III, & Pyc, M. A. (2012). Inexpensive techniques to improve education: Applying cognitive psychology to enhance educational practice. Journal of Applied Research in Memory and Cognition, 1(4), 242-248. https://doi.org/10.1016/j.jarmac.2012.09.002

Steiner, H. H., Dean, M. L., Foote, S. M., & Goldfine, R. A. (2016). The targeted learning community: A comprehensive approach to promoting the success of first-year students in general chemistry. In L. C. Schmidt, & J. Graziano (Eds.), Building synergy for high impact educational initiatives: First-year seminars and learning communities. National Resource Center.

Svinicki, M., & McKeachie, W. (2013). McKeachie’s teaching tips: Strategies, research, and theory for college and university teachers (14th ed.). Cengage Learning.

Yildirim, İ., Cirak-Kurt, S., & Sedat, S. E. N. (2019). The effect of teaching “learning strategies” on academic achievement: A meta-analysis study. Eurasian Journal of Educational Research, 19(79), 87-114. https://doi.org/10.14689/ejer.2019.79.5

Learning Myths

In the past several decades, scientists have made important discoveries about how people learn (Tokuhama-Espinosa, 2011). In fact, we’ve learned more about the brain in the last ten years than in all previous centuries because of the accelerating pace of research (National Institute of Neurological Disorders and Stroke, 2021). Previously teaching and learning was informed by one’s experience and intuition (De Bruyckere, 2015; Howard-Jones, 2014). COGx programs provide evidence to both affirm and question current teaching and studying practices.

De Bruyckere, P., Kirschner, P. A., & Hulshof, C. D. (2015). Urban myths about learning and education. Academic Press.

Howard-Jones, P. A. (2014). Neuroscience and education: myths and messages. Nature Reviews Neuroscience, 15(12), 817-824. https://doi.org/10.1038/nrn3817

Kirschner, P. A. (2017). Stop propagating the learning styles myth. Computers & Education, 106, 166-171. https://doi.org/10.1016/j.compedu.2016.12.006

Processing Skills

The ability to learn and to manage our learning is built on a strong foundation of the processing skills involved with the intake and integration of sensory information (Kuhn, J.T. 2016; Tanner, J., 2009). In other words, processing skills are critical because they form the basis of our learning. Processing skills include attention, processing speed, and working memory. All three human processing skills are limited in both time and capacity (Baddley, 2009; Kail, R., & Salthouse, T. A. (1994); Simons, D.J, 2000). COGx programs educate the three processing skills and how to support them.

Attention

Attention is a core cognitive skill that plays a critical role in learning (McGuinness, D.,1999; Steinmayr et al., 2010). While students are often told to “pay attention,” they are rarely taught how. In fact, while sustained attention has decreased dramatically in recent years, paralleling the increase in ADHD (Fayyad, J. et al., 2017), our brains process 200x more information than we did one generation ago (Chapman, S. B., 2014). COGx programs teach how to capture, keep, and gauge attention.

Centers for Disease Control and Prevention. (2021, September 23). Data and statistics about ADHD. National Center on Birth Defects and Developmental Disabilities. https://www.cdc.gov/ncbddd/adhd/data.htm

Chapman, S. B. (2014, December 22). Flex your cortex: 7 secrets to turbocharge your brain. HuffPost. https://www.huffpost.com/entry/flex-your-cortex-7-secret_b_6358056L

Fayyad, J., Sampson, N. A., Hwang, I., Adamowski, T., Aguilar-Gaxiola, S., Al-Hamzawi, A., … & Kessler, R. C. (2017). The descriptive epidemiology of DSM-IV adult ADHD in the world health organization world mental health surveys. ADHD Attention Deficit and Hyperactivity Disorders, 9(1), 47-65. https://doi.org/10.1007/s12402-016-0208-3

Kuhn, J. T. (2016). Controlled attention and storage: An investigation of the relationship between working memory, short-term memory, scope of attention, and intelligence in children. Learning and Individual Differences, 52, 167-177. https://doi.org/10.1016/j.lindif.2015.04.009

Mayes, S. D., & Calhoun, S. L. (2007). Learning, attention, writing, and processing speed in typical children and children with ADHD, autism, anxiety, depression, and oppositional-defiant disorder. Child Neuropsychology, 13(6), 469-493. https://doi.org/10.1080/09297040601112773

McGuinness, D. (1999). Why our children can’t read and what we can do about it: A scientific revolution in reading. Simon & Schuster.

Simons, D. J. (2000). Attentional capture and inattentional blindness. Trends in Cognitive Sciences, 4(4), 147-155. https://doi.org/10.1016/s1364-6613(00)01455-8

Steinmayr, R., Ziegler, M., & Träuble, B. (2010). Do intelligence and sustained attention interact in predicting academic achievement? Learning and Individual Differences, 20(1), 14-18. https://doi.org/10.1016/j.lindif.2009.10.009

Tang, Y. Y., Ma, Y., Wang, J., Fan, Y., Feng, S., Lu, Q., Yu, Q., Sui, D., Rothbart, M. K., Fan, M., & Posner, M. I. (2007). Short-term meditation training improves attention and self-regulation. Proceedings of the National Academy of Sciences, 104(43), 17152-17156. https://doi.org/10.1073/pnas.0707678104

Willis, J. (2010, May 9). Want children to “pay attention”? Make their brains curious!. Psychology Today. https://www.psychologytoday.com/us/blog/radical-teaching/201005/want-children-pay-attention-make-their-brains-curious

Wine, J. (1971). Test anxiety and direction of attention. Psychological Bulletin, 76(2), 92-104. https://doi.org/10.1037/h0031332

Processing Speed

Processing speed affects emotional wellbeing, impulsivity, encoding and retrieval as well as communication (Gasper, K., 2004); Takeuchi, H. et al, 2011); The Understood Team., n.d.). For example, students who have fast processing speed may become inattentive because they no longer have anything to attend to (Nigg et al., 2005). Differences in processing speed are guaranteed in every classroom, yet few educators have training on how to effectively identify and personalize accordingly. COGx programs teach how to tailor instruction to accommodate variations in processing speed.

Chiaravalloti, N. D., Christodoulou, C., Demaree, H. A., & DeLuca, J. (2003). Differentiating simple versus complex processing speed: Influence on new learning and memory performance. Journal of Clinical and Experimental Neuropsychology, 25(4), 489-501. https://doi.org/10.1076/jcen.25.4.489.13878

Edwards, J., Wadley, V., Myers, R.e, Roenker, D. L., Cissell, G., & Ball, K. (2002). Transfer of a speed of processing intervention to near and far cognitive functions. Gerontology, 48(5), 329–340. https://doi.org/10.1159/000065259

Gasper, K. (2004) Do You See What I See? Affect and Visual Information Processing. Cognition and Emotion, 18, 405-421. http://dx.doi.org/10.1080/02699930341000068

Kail, R., & Salthouse, T. A. (1994). Processing speed as a mental capacity. Acta psychologica, 86(2-3), 199–225. https://doi.org/10.1016/0001-6918(94)90003-5Links to an external site.

Kyllonen, P. C., Tirre, W. C., & Chttps://psycnet.apa.org/doi/10.1076/jcen.25.4.489.13878hristal, R. E. (1991). Knowledge and processing speed as determinants of associative learning. Journal of Experimental Psychology: General, 120(1), 57-79. https://doi.org/10.1037/0096-3445.120.1.57

NIH Toolbox for the Assessment of Neurological and Behavioral Function: Cognition Battery (2006-2015) Northwestern University and the National Institutes of Health

Nouchi R, Taki Y, Takeuchi H, Hashizume H, Akitsuki Y, Shigemune Y, et al. (2012) Brain Training Game Improves Executive Functions and Processing Speed in the Elderly: A Randomized Controlled Trial. PLoS ONE 7(1): e29676. https://doi.org/10.1371/journal.pone.0029676

Nouchi, R., Taki, Y., Takeuchi, H., Sekiguchi, A., Hashizume, H., Nozawa, T., Nouchi, H., & Kawashima, R. (2014). Four weeks of combination exercise training improved executive functions, episodic memory, and processing speed in healthy elderly people: evidence from a randomized controlled trial. Age (Dordrecht, Netherlands), 36(2), 787–799. https://doi.org/10.1007/s11357-013-9588-x

Takeuchi, H., Taki, Y., Hashizume, H., Sassa, Y., Nagase, T., Nouchi, R., & Kawashima, R. (2011). Effects of training of processing speed on neural systems. J Neurosci, 31(34), 12139-12148. https://doi.org/10.1523/jneurosci.2948-11.2011

Tanner, J. (2009). The Relationship Between Executive Function and Processing Speed. Brainy Behavior, Psychology, neuroscience and neurology. http://www.brainybehavior.com/blog/2009/07/executive-function-processing-speed/

The Understood Team. (n.d.). Slow processing speed and anxiety: What you need to know. Understood. https://www.understood.org/articles/en/slow-processing-speed-and-anxiety-what-you-need-to-know

Walker (2014) What causes the brain to have slow processing speed, and how can the rate be improved? Scientific American Mind 25

Working Memory

Working memory connects what we know to what we’re trying to learn (Baddeley, A., 2000). Traditional teaching overloads working memory (Paas et al., 2016), and few educators have been trained in strategies to avoid this. COGx programs teach how to arrange content to optimize working memory.

Amalric, M., & Dehaene, S. (2019). A distinct cortical network for mathematical knowledge in the human brain. NeuroImage, 189, 19-31

Ashcraft, M. H., & Kirk, E. P. (2001). The relationships among working memory, math anxiety, and performance. Journal of Experimental Psychology: General, 130(2), 224-237. https://doi.org/10.1037/0096-3445.130.2.224

Baddeley, A. (1986). Working memory. Oxford University Press

Baddeley, A. (2000). The episodic buffer: A new component of working memory?. Trends in Cognitive Sciences, 4(11), 417-423. https://doi.org/10.1016/S1364-6613(00)01538-2

Baddeley, A. (2003). Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4(10), 829-839. https://doi.org/10.1038/nrn1201

Baddeley, A. (2007). Working memory, thought, and action (Vol. 45). OuP Oxford.

Baddeley, A. D., & Andrade, J. (2000). Working memory and the vividness of imagery. Journal of Experimental Psychology: General, 129(1), 126-145. https://doi.org/10.1037/0096-3445.129.1.126

Baddeley, A. D., & Hitch, G. (1974). Working memory. Psychology of Learning and Motivation, 8, 47-89. http://dx.doi.org/10.1016/S0079-7421(08)60452-1

Baumeister, R. F. (1984). Choking under pressure: Self-consciousness and paradoxical effects of incentives on skillful performance. Journal of Personality and Social Psychology, 46(3), 610-620. https://doi.org/10.1037/0022-3514.46.3.610Links to an external site.

Beilock, S. L., & Carr, T. H. (2005). When high-powered people fail: Working memory and “choking under pressure” in math. Psychological Science, 16(2), 101-105. https://doi.org/10.1111/j.0956-7976.2005.00789.x

Beilock, S. L., Gunderson, E. A., Ramirez, G., & Levine, S. C. (2010). Female teachers’ math anxiety affects girls’ math achievement. Proceedings of the National Academy of Sciences, 107(5), 1860-1863.

Chase, W. G., & Ericsson, K. A. (1982). Skill and working memory. Psychology of Learning and Motivation, 16, 1-58. https://doi.org/10.1016/S0079-7421(08)60546-0

Dowker, A., Sarkar, A., & Looi, C. Y. (2016). Mathematics anxiety: What have we learned in 60 years?. Frontiers in psychology, 7, 508. https://internal-journal.frontiersin.org/articles/10.3389/fpsyg.2016.00508/full

Engle, R. W., & Kane, M. J. (2004). Executive attention, working memory capacity, and a two-factor Theory of Cognitive Control. The Psychology of Learning and Motivation, 44, 145–199).

Gathercole, S. E., Pickering, S. J., Knight, C., & Stegmann, Z. (2004). Working memory skills and educational attainment: Evidence from national curriculum assessments at 7 and 14 years of age. Applied Cognitive Psychology, 18(1), 1-16. https://doi.org/10.1002/acp.934

Hart, S. A., & Ganley, C. M. (2019). The nature of math anxiety in adults: Prevalence and correlates. Journal of numerical cognition, 5(2), 122.

Hart, S. A., & Ganley, C. M. (2019). The Nature of Math Anxiety in Adults: Prevalence and Correlates. Journal of numerical cognition, 5(2), 122–139. https://doi.org/10.5964/jnc.v5i2.195

Hofmann, S. G., Heering, S., Sawyer, A. T., & Asnaani, A. (2009). How to handle anxiety: The effects of reappraisal, acceptance, and suppression strategies on anxious arousal. Behaviour research and therapy, 47(5), 389-394.

Kuhn, J. T. (2016). Controlled attention and storage: An investigation of the relationship between working memory, short-term memory, scope of attention, and intelligence in children. Learning and Individual Differences, 52, 167-177. https://doi.org/10.1016/j.lindif.2015.04.009

Maloney, E. A., Ramirez, G., Gunderson, E. A., Levine, S. C., & Beilock, S. L. (2015). Intergenerational effects of parents’ math anxiety on children’s math achievement and anxiety. Psychological Science, 26(9), 1480-1488.

Rai, M. K., Loschky, L. C., Harris, R. J., Peck, N. R., & Cook, L. G. (2011). Effects of stress and working memory capacity on foreign language readers’ inferential processing during comprehension. Language Learning, 61(1), 187-218. https://doi.org/10.1111/j.1467-9922.2010.00592.x

Ramirez, G., Hooper, S. Y., Kersting, N. B., Ferguson, R., & Yeager, D. (2018). Teacher math anxiety relates to adolescent students’ math achievement. Aera Open, 4(1), 2332858418756052.

Uncapher, M. R., K Thieu, M., & Wagner, A. D. (2016). Media multitasking and memory: Differences in working memory and long-term memory. Psychonomic Bulletin & Review, 23(2), 483-490. https://doi.org/10.3758/s13423-015-0907-3

Wine, J. (1971). Test anxiety and direction of attention. Psychological Bulletin, 76(2), 92-104. https://doi.org/10.1037/h0031332

Dual-Coding

Cognition is separated into two processing channels, visual and verbal (Paivio, 1991). Though information is stored independently, images are linked to words (Sweller, Ayres & Kalyuga, 2011). This means it is easier to remember a word when thinking of an image and vice versa. COGx programs teach how to use dual-coding appropriately to aid memory.

McClelland, J. L., Rumelhart, D. E., & PDP Research Group. (1987). Parallel distributed processing: Explorations in the microstructure of cognition: Psychological and biological models (Vol. 2). MIT press.

Paivio, A. (2013). Dual coding theory, word abstractness, and emotion: A critical review of Kousta et al. (2011). Journal of Experimental Psychology: General, 142(1), 282–287. https://doi.org/10.1037/a0027004

Multimedia Learning

Educators and students can be trained in effective multimedia teaching. COGx programs teach how to use multiple modalities, such as visual and auditory information, to enhance learning and avoid situations that result in cognitive overload (Moreno & Mayer, 1999).

Mayer, R. E. (2014). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 43–71). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.005

Mayer, R.E. (2001). Multimedia learning. New York: Cambridge University Press.

Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning: The role of modality and contiguity. Journal of Educational Psychology, 91(2), 358-368. https://doi.org/10.1037/0022-0663.91.2.358

Multitasking

Multi-tasking is one of the many learning myths that pervades society. It often produces inferior performance compared to single tasking (Courage et al., 2015) and makes it more difficult to apply knowledge to new situations (Foerde et al., 2006). COGx programs educate on this myth (and others) and instead, teach the proper way to learn.

Courage, M. L., Bakhtiar, A., Fitzpatrick, C., Kenny, S., & Brandeau, K. (2015). Growing up multitasking: The costs and benefits for cognitive development. Developmental Review, 35, 5–41. https://doi.org/10.1016/j.dr.2014.12.002

Foerde, K., Knowlton, B. J., & Poldrack, R. A. (2006). Modulation of competing memory systems by distraction. Proceedings of the National Academy of Sciences, 103(31), 11778-11783. https://doi.org/10.1073/pnas.0602659103

Rosen, L. D., Lim, A. F., Carrier, L. M., & Cheever, N. A. (2011). An empirical examination of the educational impact of text message-induced task switching in the classroom: Educational implications and strategies to enhance learning. Educational Psychology, 17(2), 163-177. https://doi.org/10.5093/ed2011v17n2a4

Uncapher, M. R., K Thieu, M., & Wagner, A. D. (2016). Media multitasking and memory: Differences in working memory and long-term memory. Psychonomic Bulletin & Review, 23(2), 483-490. https://doi.org/10.3758/s13423-015-0907-3

Executive Function

Executive function skills predict academic and career success (Kern et al., 2009; Pascual et al., 2019) . Further, executive function skills mediate a person’s tendency toward risky behaviors including crime and addiction, their ability to make and save money, social skills, and mental and physical health (Williams et al., 2009). COGx programs educate about executive functioning skills and managing these human processing limitations while working toward a goal.

Alvarez, J. A., & Emory, E. (2006). Executive function and the frontal lobes: A meta-analytic review. Neuropsychology Review, 16(1), 17-42. https://doi.org/10.1007/s11065-006-9002-x

Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84(3), 261-271. https://doi.org/10.1037/0022-0663.84.3.261

Anderman, L. H., & Anderman, E. M. (2009). Oriented towards mastery: Promoting positive motivational goals for students. In R. Gilman, E. S. Huebner, & M. J. Furlong (Eds.), Handbook of positive psychology in schools (pp. 161–173). Routledge.

Brown, T. E. (2006). Executive functions and attention deficit hyperactivity disorder: Implications of two conflicting views. International Journal of Disability, Development and Education, 53(1), 35-46. https://doi.org/10.1080/10349120500510024

Chan, R. C., Shum, D., Toulopoulou, T., & Chen, E. Y. (2008). Assessment of executive functions: Review of instruments and identification of critical issues. Archives of Clinical Neuropsychology, 23(2), 201-216. https://doi.org/10.1016/j.acn.2007.08.010

Davis, E. L., & Levine, L. J. (2013). Emotion regulation strategies that promote learning: Reappraisal enhances children’s memory for educational information. Child Development, 84(1), 361-374. https://doi.org/10.1111/j.1467-8624.2012.01836.x

Diamond, A., & Lee, K. (2011). Interventions shown to aid executive function development in children 4 to 12 years old. Science, 333(6045), 959-964. https://doi.org/10.1126/science.1204529

Eylon, B. S., & Reif, F. (1984). Effects of knowledge organization on task performance. Cognition and Instruction, 1(1), 5-44. https://doi.org/10.1207/s1532690xci0101_2

Kern, M. L., Friedman, H. S., Martin, L. R., Reynolds, C. A., & Luong, G. (2009). Conscientiousness, career success, and longevity: A lifespan analysis. Annals of Behavioral Medicine, 37(2), 154-163. https://doi.org/10.1007/s12160-009-9095-6

Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57(9), 705-717. https://doi.org/10.1037/0003-066X.57.9.705

Matin, A. J. (2013). Goal setting and personal best goals. In E. M. Anderman, & J. Hattie (Eds.), International guide to student achievement (pp. 356-358). Routledge.

McCabe, D. P., Roediger, H. L., III, McDaniel, M. A., Balota, D. A., & Hambrick, D. Z. (2010). The relationship between working memory capacity and executive functioning: Evidence for a common executive attention construct. Neuropsychology, 24(2), 222-243. https://doi.org/10.1037/a0017619

Meece, J. L., Anderman, E. M., & Anderman, L. H. (2006). Classroom goal structure, student motivation, and academic achievement. Annual Review of Psychology, 57, 487-503. https://doi.org/10.1146/annurev.psych.56.091103.070258

Meltzer, L., & Greschler, M. (2018, October). Executive function strategies: The building blocks for reading to learn. The Examiner, 7(4). https://dyslexiaida.org/executive-function-strategies-the-building-blocks-for-reading-to-learn/#

Pascual, A. C., Muñoz, N. M., & Robres, A. Q. (2019). The relationship between executive functions and academic performance in primary education: Review and meta-analysis. Frontiers in psychology, 10, Article 1582. https://doi.org/10.3389/fpsyg.2019.01582

Williams, P. G., Suchy, Y., & Rau, H. K. (2009). Individual differences in executive functioning: Implications for stress regulation. Annals of Behavioral Medicine, 37(2), 126-140. https://doi.org/10.1007/s12160-009-9100-0

Long-Term Memory

Studies show students rely on ineffective strategies to learn resulting in superficial learning (Bjork & Bjork, 2011). Traditional instruction often leads to surface level learning which is fleeting, prevents mastery and jeopardizes future learning. According to the forgetting curve, approximately 50% of new information is forgotten within 24 hours, and a significant 90% is lost within 7 days of the learning process (Cloke 2018; Ebbinhaus, 1885). Retrieval strategies, which combat the forgetting curve, promote deeper learning and mastery while facilitating intrinsic motivation (Roediger & Karpicke, 2006; Schmidt & Bjork, 1992). COGx programs teach encoding and retrieval strategies that move away from rote memorization and move towards learning for creativity and critical thinking.

Agarwal, P. K., Roediger, H. L., III, McDaniel, M. A., & McDermott, K. B. (2020). How to use retrieval practice to improve learning. Washington University in St. Louis. http://pdf.retrievalpractice.org/RetrievalPracticeGuide.pdf

Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. Psychology of Learning and Motivation, 2, 89-195. https://doi.org/10.1016/S0079-7421(08)60422-3

Arnold, K. M., & McDermott, K. B. (2013). Test-potentiated learning: Distinguishing between direct and indirect effects of tests. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39(3), 940945.https://doi.org/10.1037/a0029199

Bahrick, H. P. (1979). Maintenance of knowledge: Questions about memory we forgot to ask. Journal of Experimental Psychology: General, 108(3), 296-308. https://doi.org/10.1037/0096-3445.108.3.296

Bjork, R. A., & Bjork, E. L. (2019a). Forgetting as the friend of learning: Implications for teaching and self-regulated learning. Advances in Physiology Education, 43(2), 164-167. https://doi.org/10.1152/advan.00001.2019

Bjork, R. A. (1994). Memory and metamemory considerations in the training of human beings. In J. Metcalfe, & A Shimamura (Eds.), Metacognition: Knowing About Knowing (pp. 185-205). MIT Press.

Callender, A. A., & McDaniel, M. A. (2009). The limited benefits of rereading educational texts. Contemporary Educational Psychology, 34(1), 30-41. https://doi.org/10.1016/j.cedpsych.2008.07.001

Carpenter, S. K., Pan, S. C., & Butler, A. C. (2022). The science of effective learning with spacing and retrieval practice. Nature Reviews Psychology, (9), 496-511.

Cloke, H. (2018, March 30). What is the forgetting curve (and how do you combat it)? eLearning Industry. https://elearningindustry.com/forgetting-curve-combat

Ebbinghaus, H. (1885). Memory: A contribution to experimental psychology. Annals of Neuroscience, 20(4), 155-156. https://doi.org/10.5214/ans.0972.7531.200408

Forrin, N. D., & MacLeod, C. M. (2018). This time it’s personal: The memory benefit of hearing oneself. Memory, 26(4), 574-579. https://doi.org/10.1080/09658211.2017.1383434

Gates, A. I. (1917). Recitation as a factor in memorizing. Archives of Scientific Psychology, 6(40), 1-104.

Hinds, P. J. (1999). The curse of expertise: The effects of expertise and debiasing methods on prediction of novice performance. Journal of Experimental Psychology: Applied, 5(2), 205-221. https://doi.org/10.1037/1076-898X.5.2.205

Hoque, E. (2018). Memorization: A proven method of learning. International Journal of Applied Research, 22(3), 142-150.

Jacoby, L. L. (1978). On interpreting the effects of repetition: Solving a problem versus remembering a solution. Journal of Verbal Learning and Verbal Behavior, 17(6), 649-667. https://doi.org/10.1016/S0022-5371(78)90393-6

Karpicke, J. D., & Blunt, J. R. (2011). Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331(6018), 772-775. https://doi.org/10.1126/science.1199327

Karpicke, J. D., & Roediger, H. L., III. (2008). The critical importance of retrieval for learning. Science, 319(5865), 966-968. https://doi.org/10.1126/science.1152408

Leeming, F. C. (2002). The exam-a-day procedure improves performance in psychology classes. Teaching of Psychology, 29(3), 210-212. https://doi.org/10.1207/S15328023TOP2903_06

Lemov, D. (2021, February 8). An annotated forgetting curve. Teach Like a Champion. https://teachlikeachampion.com/blog/an-annotated-forgetting-curve/

McDaniel, M. A., Wildman, K. M., & Anderson, J. L. (2012). Using quizzes to enhance summative-assessment performance in a web-based class: An experimental study. Journal of Applied Research in Memory and Cognition, 1(1), 18-26. https://doi.org/10.1016/j.jarmac.2011.10.001

Miyatsu, T., Nguyen, K., & McDaniel, M. A. (2018). Five popular study strategies: Their pitfalls and optimal implementations. Perspectives on Psychological Science, 13(3), 390-407. https://doi.org/10.1177/1745691617710510

Nesbit, J. C., & Adesope, O. O. (2006). Learning with concept and knowledge maps: A meta-analysis. Review of educational research, 76(3), 413-448.

Pan, S. C., & Rickard, T. C. (2018). Transfer of test-enhanced learning: Meta-analytic review and synthesis [Transferencia del aprendizaje potenciado por pruebas: Revisión metaanalítica y síntesis]. Psychological bulletin, 144(7), 710.

Roediger, H. L., III, & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15(1), 20-27. https://doi.org.10.1016/j.tics.2010.09.003

Roediger, H. L., III, & Karpicke, J. D. (2006). The power of testing memory: Basic research and implications for educational practice. Perspectives on Psychological Science, 1(3), 181-210. https://doi.org/10.1111/j.1745-6916.2006.00012.x

Roediger, H. L., & McDermott, K. B. (1995). Creating false memories: Remembering words not presented in lists. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21(4), 803-814. https://doi.org/10.1037/0278-7393.21.4.803

Roediger, H. L. III, Putnam, A. L., & Smith, M. A. (2011). Ten benefits of testing and their applications to educational practice. In J. P. Mestre & B. H. Ross (Eds.), The psychology of learning and motivation: Cognition in education (Vol. 55, pp. 1–36). Elsevier Academic Press. https://doi.org/10.1016/B978-0-12-387691-1.00001-6

Sana, F., Yan, V. X., Clark, C. M., Bjork, E. L., & Bjork, R. A. (2021). Improving conceptual learning via pretests. Journal of Experimental Psychology: Applied, 27(2), 228.

Sana, F., & Yan, V. X. (2022). Interleaving retrieval practice promotes science learning. Psychological Science, 33(5), 782-788.

Smith, E. E., Adams, N., & Schorr, D. (1978). Fact retrieval and the paradox of interference. Cognitive Psychology, 10(4), 438-464. https://doi.org/10.1016/0010-0285(78)90007-5

Tulving, E. (1985). How many memory systems are there?. American Psychologist, 40(4), 385-398. https://doi.org/10.1037/0003-066X.40.4.385

Wang, Y., Liu, D., & Wang, Y. (2003). Discovering the capacity of human memory. Brain and Mind, 4(2), 189-198. https://doi.org/10.1023/A:1025405628479

Willingham, D. T. (2008). Ask the Cognitive Scientist: What Will Improve a Student’s Memory?. American Educator, 32(4), 17- 25.

Yildirim, İ., Cirak-Kurt, S., & Sedat, S. E. N. (2019). The effect of teaching “learning strategies” on academic achievement: A meta-analysis study. Eurasian Journal of Educational Research, 19(79), 87-114. https://doi.org/10.14689/ejer.2019.79.5

Prior Knowledge

We rely on prior learning when filtering and interpreting new information (Ambrose et al., 2010; National Research Council, 2000). Learning requires that we constantly form connections between new information and things that we already know (Bransford et al., 2000). For someone with robust prior knowledge, new information quickly receives meaning, and, as a result, memory (encoding) is strong. COGx programs educate on the importance of prior knowledge and provide strategies to fill gaps.

Clement, J. (1982). Students’ preconceptions in introductory mechanics. American Journal of Physics, 50(1), 66-71. https://doi.org/10.1119/1.12989

Hailikari, T., Katajavuori, N., & Lindblom-Ylanne, S. (2008). The relevance of prior knowledge in learning and instructional design. American Journal of Pharmaceutical Education, 72(5), Article 113. https://doi.org/10.5688/aj7205113

Peeck, J., Van den Bosch, A. B., & Kreupeling, W. J. (1982). Effect of mobilizing prior knowledge on learning from text. Journal of Educational Psychology, 74(5), 771-777. https://doi.org/10.1037/0022-0663.74.5.771

Mastery & Transfer

In order to have mastered content, students must acquire component skills, practice integrating them, and know when to apply what they have learned (Ambrose et al., 2010). Transfer does not happen naturally or easily; therefore, it is critical that educators teach for transfer and provide students opportunities for practice and reflection across contexts (Bransford et al., 2000). COGx programs walk educators through how to do this effectively step-by-step.

Boser, U. (2017). Learn better: Mastering the skills for success in life, business, and school, or, how to become an expert in just about anything. Rodale.

Cooper, G., & Sweller, J. (1987). Effects of schema acquisition and rule automation on mathematical problem-solving transfer. Journal of Educational Psychology, 79(4), 347-362. https://doi.org/10.1037/0022-0663.79.4.347

Gick, M. L., & Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology, 12(3), 306-355. https://doi.org/10.1016/0010-0285(80)90013-4

Lowenstein, J., Thompson, L., & Gentner, D. (2003). Analogical learning in negotiation teams: Comparing cases promotes learning and transfer. Academy of Management Learning & Education, 2(2), 119-127. https://doi.org/10.5465/amle.2003.9901663

Paas, F. G., & Van Merriënboer, J. J. (1994). Variability of worked examples and transfer of geometrical problem-solving skills: A cognitive-load approach. Journal of Educational Psychology, 86(1), 122-133. https://doi.org/10.1037/0022-0663.86.1.122

Schmidt, R. A., & Bjork, R. A. (1992). New conceptualizations of practice: Common principles in three paradigms suggest new concepts for training. Psychological Science, 3(4), 207-218. https://doi.org/10.1111/j.1467-9280.1992.tb00029.x

Metacognition

Teaching metacognitive reflection is an effective strategy to accelerate student achievement (Education Endowment Foundation, 2018). Among research conducted globally on what contributes the most to learning success, few things match the effect size metacognition produces (Hattie, 2015). COGx programs teach practical strategies that foster metacognitive awareness and create the foundation for learning independently, effectively and efficiently.

Benjamin, A. S., & Bird, R. D. (2006). Metacognitive control of the spacing of study repetitions. Journal of Memory and Language, 55(1), 126-137. https://doi.org/10.1016/j.jml.2006.02.003

Bjork, R. A. (1999). Assessing our own competence: Heuristics and illusions. In D. Gopher & A Koriat (Eds.), Attention and performance XVII: Cognitive regulation of performance: Interaction of theory and application, (pp. 435 – 459). The MIT Press.

Bjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-regulated learning: Beliefs, techniques, and illusions. Annual Review of Psychology, 64, 417-444. https://doi.org/10.1146/annurev-psych-113011-143823

Brockett, R. G., & Hiemstra, R. (1991). Self-direction in adult learning: Perspectives on theory, research, and practice. Routledge.

Burkholder, E., Salehi, S., Sackeyfio, S., Mohamed-Hinds, N., & Wieman, C. (2021). An equitable and effective approach to introductory mechanics. Cornell University: Physics Education. https://doi.org/10.48550/arXiv.2111.12504

Cambridge International Education Teaching and Learning Team. (n.d.). Getting started with metacognition. https://cambridge-community.org.uk/professional-development/gswmeta/index.html

Chua, E. F., Schacter, D. L., & Sperling, R. A. (2009). Neural correlates of metamemory: A comparison of feeling-of-knowing and retrospective confidence judgments. Journal of Cognitive Neuroscience, 21(9), 1751-1765. https://doi.org/10.1162/jocn.2009.21123

Cohen, M. (2012). The importance of self-regulation for college student learning. College Student Journal, 46(4), 892-902.

Couchman, J. J., Miller, N. E., Zmuda, S. J., Feather, K., & Schwartzmeyer, T. (2016). The instinct fallacy: The metacognition of answering and revising during college exams. Metacognition and Learning, 11(2), 171-185. https://doi.org/10.1007/s11409-015-9140-8

Donker, A. S., De Boer, H., Kostons, D., Van Ewijk, C. D., & van der Werf, M. P. (2014). Effectiveness of learning strategy instruction on academic performance: A meta-analysis. Educational Research Review, 11, 1-26.

Dunlosky, J., & Metcalfe, J. (2008). Metacognition. Sage Publications.

Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3), 363-406. https://doi.org/10.1037/0033-295X.100.3.363

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Finley, J. R., Tullis, J. G., & Benjamin, A. S. (2010). Metacognitive control of learning and remembering. In M. S. Khine, & I. M. Saleh (Eds.), New science of learning, (pp. 109-131). Springer.

Flavell, J. H. (1976). Metacognitive aspects of problem solving. In L. B. Resnick (Ed.), The nature of intelligence (pp. 231-235). Lawrence Erlbaum.

Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive developmental inquiry. American Psychologist, 34(10), 906–911. https://doi.org/10.1037/0003-066X.34.10.906

Gilovich, T. (1991). How we know what isn’t so: The fallibility of human reason in everyday life. Free Press.

Gobet, F., & Campitelli, G. (2007). The role of domain-specific practice, handedness, and starting age in chess. Developmental Psychology, 43(1), 159-172. https://doi.org/10.1037/0012-1649.43.1.159a

Isaacson, R., & Fujita, F. (2006). Metacognitive knowledge monitoring and self-regulated learning. Journal of the Scholarship of Teaching and Learning, 6(1), 39-55.

Karpicke, J. D., Butler, A. C., & Roediger, H. L., III. (2009). Metacognitive strategies in student learning: Do students practise retrieval when they study on their own?. Memory, 17(4), 471-479. https://doi.org/10.1080/09658210802647009

Kim, H. J., & Pedersen, S. (2010). Young adolescents’ metacognition and domain knowledge as predictors of hypothesis-development performance in a computer-supported context. Educational Psychology, 30(5), 565-582. https://doi.org/10.1080/01443410.2010.491937

Kitsantas, A. (2002). Test preparation and performance: A self-regulatory analysis. The Journal of Experimental Education, 70(2), 101-113. https://doi.org/10.1080/00220970209599501

Knaack, L., & Robertson,, M. (n.d.). Ten metacognitive teaching strategies. Centre for Innovation and Excellence in Learning.

Koriat, A., & Bjork, R. A. (2005). Illusions of competence in monitoring one’s knowledge during study. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(2), 187-194. https://doi.org/10.1037/0278-7393.31.2.187

Koriat, A., & Levy-Sadot, R. (1999). Processes underlying metacognitive judgments: Information-based and experience-based monitoring of one’s own knowledge. In S. Chaiken & Y. Trope (Eds.), Dual-process theories in social psychology (pp. 483–502). The Guilford Press.

Kornell, N., & Bjork, R. A. (2007). The promise and perils of self-regulated study. Psychonomic Bulletin & Review, 14(2), 219-224.

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

Metcalfe, J., & Kornell, N. (2005). A region of proximal learning model of study time allocation. Journal of Memory and Language, 52(4), 463-477. https://doi.org/10.1016/j.jml.2004.12.001

Ng, W. (2008). Self-directed learning with web-based sites: How well do students’ perceptions and thinking match with their teachers? Teaching Science, 54(2), 27-30.

Owen, D. & Vista, A. (2017, November 15). Strategies for teaching metacognition in classrooms. Brookings. https://www.brookings.edu/blog/education-plus-development/2017/11/15/strategies-for-teaching-metacognition-in-classrooms/

Paris, S. G., & Paris, A. H. (2001). Classroom applications of research on self-regulated learning. Educational Psychologist, 36(2), 89-101. https://doi.org/10.1207/S15326985EP3602_4

Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational Psychologist, 37(2), 91-105. https://doi.org/10.1207/S15326985EP3702_4

Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33-40. https://doi.org/10.1037/0022-0663.82.1.33

Price-Mitchell, M. (2015, April 7). Metacognition: Nurturing self-awareness in the classroom. Edutopia. https://www.edutopia.org/blog/8-pathways-metacognition-in-classroom-marilyn-price-mitchell

Quigley, A., & Stringer, E. (2018). Metacognition and self-regulated learning: Guidance report. Education Endowment Foundation. https://d2tic4wvo1iusb.cloudfront.net/eef-guidance-reports/metacognition/EEF_Metacognition_and_self-regulated_learning.pdf?v=1635355221

Son, L. K., & Metcalfe, J. (2000). Metacognitive and control strategies in study-time allocation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26(1), 204-221. https://doi.org/10.1037/0278-7393.26.1.204

Schraw, G. (1998). Promoting general metacognitive awareness. Instructional Science, 26(1), 113-125. https://doi.org/10.1023/A:1003044231033

Thiede, K. W., & Dunlosky, J. (1999). Toward a general model of self-regulated study: An analysis of selection of items for study and self-paced study time. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25(4), 1024-1037.

Yan, V. X., Thai, K., & Bjork, R. A. (2014). Habits and beliefs that guide self-regulated learning: Do they vary with mindset? Journal of Applied Research in Memory and Cognition, 3(3), 140-152. https://doi.org/10.1016/j.jarmac.2014.04.003

Young, A., & Fry, J. D. (2008). Metacognitive awareness and academic achievement in college students. Journal of the Scholarship of Teaching and Learning, 8(2), 1-10.

Feedback, Formative Assessment, & Peer-based Learning

Research suggests effective feedback (Hattie, J., & Timperley, H., (2007); Wisniewski et al., 2020), formative assessments ((Paschler et al., 2007), and peer-based learning (Sedlacek, M., & Sedova, K., (2017) are among the most effective ways a student can learn information. In the majority of classrooms, learning is assessed using tests and exams. As a result, students are indirectly trained to avoid feedback because it is painful and comes to them at a cost – through a low grade (Sadler, D. R., (1989). COGx programs train educators to integrate these concepts into their classrooms.

Alber, R. (2011, February 15). Why formative assessments matter. Edutopia. https://www.edutopia.org/blog/formative-assessments-importance-of-rebecca-alber

Bakula, N. (2010). The benefits of formative assessments for teaching and learning. Science Scope, 34(1), 37-43.

Boud, D., Cohen, R., & Sampson, J. (2001). Peer learning in higher education. Taylor & Francis.

Brookhart, S. M. (2017). How to give effective feedback to your students (2nd ed.). ASCD.

Burnett, P. C. (2002). Teacher praise and feedback and students’ perceptions of the classroom environment. Educational Psychology, 22(1), 5-16. https://doi.org/10.1080/01443410120101215

Burnett, P. C., & Mandel, V. (2010). Praise and feedback in the primary classroom: Teachers’ and students’ perspectives. Australian Journal of Educational & Developmental Psychology, 10, 145-154.

Chappuis, S., & Chappuis, J. (2007). The best value in formative assessment. In M. Sherer (Ed.), Challenging the whole child: Reflections on best practice in learning, teaching and leadership (pp. 219-226). ASCD.

Cho, K., Schunn, C. D., & Wilson, R. W. (2006). Validity and reliability of scaffolded peer assessment of writing from instructor and student perspectives. Journal of Educational Psychology, 98(4), 891-901. https://doi.org/10.1037/0022-0663.98.4.891

Chung, H. M., & Behan, K. J. (2010). Peer sharing facilitates the effect of inquiry-based projects on science learning. The American Biology Teacher, 72(1), 24-29. https://doi.org/10.1525/abt.2010.72.1.7

Graham, S., Harris, K., and Hebert, M. A. (2011). Informing writing: The benefits of formative assessment. A Carnegie corporation time to act report. Alliance for Excellent Education.

Gupta, M. L. (2004). Enhancing student performance through cooperative learning in physical sciences. Assessment & Evaluation in Higher Education, 29(1), 63-73. https://doi.org/10.1080/0260293032000158162

Hanover Research. (2014). The impact of formative assessment and learning intentions on student achievement. District Administration Practice. https://www.hanoverresearch.com/media/The-Impact-of-Formative-Assessment-and-Learning-Intentions-on-Student-Achievement.pdf

Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81-112. https://doi.org/10.3102/003465430298487

Hattie, J. A., & Yates, G. C. (2014). Using feedback to promote learning. In. V. A. Benassi, C. E. Overson, & C. M. Hakala (Eds.), Applying science of learning in education: Infusing psychological science into the curriculum, (pp. 45-58). Society for the Teaching of Psychology.

King, A. (2002). Structuring peer interaction to promote high-level cognitive processing. Theory Into Practice, 41(1), 33-39. https://doi.org/10.1207/s15430421tip4101_6

Köse, S., Şahin, A., Ergü, A., & Gezer, K. (2010). The effects of cooperative learning experience on eighth grade students’ achievement and attitude toward science. Education, 131(1). https://doi.org/10.5430/ijhe.v3n2p131

Kulhavy, R. W. (1977). Feedback in written instruction. Review of Educational Research, 47(1), 211-232. https://doi.org/10.3102/00346543047002211

Leahy, S., Lyon, C., Thompson, M., & Wiliam, D. (2005). Classroom assessment: Minute by minute, day by day. Educational Leadership, 63(3), 18-24.

Lord, T. R. (2001). 101 reasons for using cooperative learning in biology teaching. The American Biology Teacher, 63(1), 30-38. https://doi.org/10.2307/4451027

Mazur, E. (1997). Peer instruction: A user’s manual. Prentice Hall.

Opitz, B., Ferdinand, N. K., & Mecklinger, A. (2011). Timing matters: The impact of immediate and delayed feedback on artificial language learning. Frontiers in Human Neuroscience, 5(8), 1-9.

Samuels, S. J., & Wu, Y. (2003). The effects of immediate feedback on reading achievement. University of Minnesota.

Sadler, D. R. (1989). Formative assessment and the design of instructional systems. Instructional Science, 18(2), 119-144. https://doi.org/10.1007/BF00117714

Smith, H., & Higgins, S. (2006). Opening classroom interaction: The importance of feedback. Cambridge Journal of Education, 36(4), 485-502. https://doi.org/10.1080/03057640601048357

Sparks, S. P. (2015). Types of assessments: A head-to-head comparison. Education Week. https://www.edweek.org/teaching-learning/types-of-assessments-a-head-to-head-comparison

Sousa, D. A., & Toth, M. D. (2020, May 28). Neuroscience supports successful student academic teams. ASCD. https://www.ascd.org/el/articles/neuroscience-supports-successful-student-academic-teams

Sprouls, K., Mathur, S. R., & Upreti, G. (2015). Is positive feedback a forgotten classroom practice? Findings and implications for at-risk students. Preventing School Failure: Alternative Education for Children and Youth, 59(3), 153-160. https://doi.org/10.1080/1045988X.2013.876958

Thurston, A., Topping, K. J., Tolmie, A., Christie, D., Karagiannidou, E., & Murray, P. (2010). Cooperative learning in science: Follow‐up from primary to high school. International Journal of Science Education, 32(4), 501-522. https://doi.org/10.1080/09500690902721673

Voerman, L., Meijer, P. C., Korthagen, F. A., & Simons, R. J. (2012). Types and frequencies of feedback interventions in classroom interaction in secondary education. Teaching and Teacher Education, 28(8), 1107-1115. https://doi.org/10.1016/j.tate.2012.06.006

Wasserman, J., & Beyerlein, S. W. (2007). SII method for assessment reporting. In S. W. Beyerlein, C. Holmes, & D. K. Apple (Eds.), Faculty guidebook: A comprehensive tool for improving faculty performance (4th ed.). Pacific Crest.

William, D. (2016, April 1). The secret of effective feedback. ASCD. https://www.ascd.org/el/articles/the-secret-of-effective-feedback

Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research. Frontiers in Psychology, 10, 3087.

Emotions & Engagement

Learning is emotional, and positive emotions enhance grades and test scores over a span of years, negative emotions hinder achievement (Pekrun et al., 2002). When students experience anxiety in school, cortisol is released which triggers the “fight or flight” response. Long-term activation is associated with memory and concentration impairment (Tyng et al., 2017). Inversely, studies have shown that a classroom climate of belonging can foster learning (Yeager et al., 2013). Attention is no longer bifurcated between academics and social threat (Hennessey, 2018). Fortunately, similar to cognitive skills, social and emotional skills can be taught. COGx programs educate on the interdependencies between cognition and emotion and how to better support students.

Student engagement often decreases with every year of schooling; Yet, student learning requires their engagement and motivation (Gallup, 2016). Students’ motivation can influence judgment of their own ability to complete a task. Studies show that if students feel more confident and in control of their own behavior, they are more likely to be motivated, persist, and ultimately achieve (Hulleman & Barron, 2015). COGx programs educate on the most effective ways to stay motivated and engaged.

Emotions & Learning

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Durlak, J. A., Weissberg, R. P., Dymnicki, A. B., Taylor, R. D., & Schellinger, K. B. (2011). The impact of enhancing students’ social and emotional learning: A meta‐analysis of school‐based universal interventions. Child Development, 82(1), 405-432. https://doi.org/10.1111/j.1467-8624.2010.01564.x

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Immordino-Yang, M. H. (2016). Emotions, learning, and the brain: Exploring the educational implications of affective neuroscience. W. W. Norton.

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Nakamura J., & Csikszentmihalyi, M. (2014) The concept of flow. In Csikszentmihalyi, M (Ed.), Flow and the foundations of positive psychology, (pp. 239-263). https://doi.org/10.1007/978-94-017-9088-8_16

Newberry, M. (2010). Identified phases in the building and maintaining of positive teacher-student relationships. Teaching and Teacher Education, 26(8), 1695-1703. https://doi.org/10.1016/j.tate.2010.06.022

Norrish, J. M., Williams, P., O’Connor, M., & Robinson, J. (2013). An applied framework for positive education. International Journal of Wellbeing, 3(2), 147-161. https://doi.org/10.5502/ijw.v3i2.2

Taylor, R. D., Oberle, E., Durlak, J. A., & Weissberg, R. P. (2017). Promoting positive youth development through schoolbased social and emotional learning interventions: A meta-analysis of follow-up effects. Child Development, 88(4), 1156- 1171.

Teven, J. J., & McCroskey, J. C. (1997). The relationship of perceived teacher caring with student learning and teacher evaluation. Communication Education, 46(1), 1-9. https://doi.org/10.1080/03634529709379069

Trigwell, K., Ellis, R. A., & Han, F. (2011). Relations between students’ approaches to learning, experienced emotions and outcomes of learning. Studies in Higher Education, 37(7), 811-824. https://doi.org/10.1080/03075079.2010.549220

Tyng, C. M., Amin, H. U., Saad, M. N., & Malik, A. S. (2017). The influences of emotion on learning and memory. Frontiers in Psychology, 8, Article 1454. https://doi.org/10.3389/fpsyg.2017.01454

Seligman, M. E. (2002). Authentic happiness: Using the new positive psychology to realize your potential for lasting fulfillment. Simon & Schuster.

Seligman, M. E. (2012). Flourish: A visionary new understanding of happiness and well-being. Atria Books.

Social and emotional learning: A short history. (2011, October 6). Edutopia. https://www.edutopia.org/social-emotional-learning-history

Watz, M. (2011). An historical analysis of character education. Journal of Inquiry & Action in Education, 4(2), 34-53.

Wentzel, K. R. (2009). Peers and academic functioning at school. In K. H. Rubin, W. M. Bukowski, & B. Laursen (Eds.), Handbook of peer interactions, relationships, and groups (pp. 531–547). The Guilford Press.

Whiting, S. B., Wass, S. V., Green, S., & Thomas, M. S. (2021). Stress and learning in pupils: Neuroscience evidence and its relevance for teachers. Mind, Brain, and Education, 15(2), 177-188. https://doi.org/10.1111/mbe.12282

World Health Organization. (n.d.) Violence against children. https://www.who.int/health-topics/violence-against-children#tab=tab_1

Engagement & Motivation

(Inclusive of Active/Inquiry-Based/Problem-Based/Project-Based Learning and Mindsets)

Ames, C. (1990). Motivation: What teachers need to know. Teachers College Record, 91(3), 409-421.

Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84(3), 261-271. https://doi.org/10.1037/0022-0663.84.3.261

Anderman, L. H., & Anderman, E. M. (2009). Oriented towards mastery: Promoting positive motivational goals for students. In R. Gilman, E. S. Huebner, & M. J. Furlong (Eds.), Handbook of positive psychology in schools (pp. 161–173). Routledge.

Anderman, E. M., Urdan, T., & Roeser, R. (2003, March). The patterns of adaptive learning survey: History, development, and psychometric properties. Paper prepared for the Indicators of Positive Development Conference, Washington D.C.

Anderman, E. M., & Wolters, C. A. (2006). Goals, Values, and Affect: Influences on Student Motivation. In P. A. Alexander & P. H. Winne (Eds.), Handbook of educational psychology (pp. 369–389). Lawrence Erlbaum Associates Publishers.

Aronson, J., Fried, C. B., & Good, C. (2002). Reducing the effects of stereotype threat on African American college students by shaping theories of intelligence. Journal of Experimental Social Psychology, 38(2), 113-125. https://doi.org/10.1006/jesp.2001.1491

Balduf, M. (2009). Underachievement among college students. Journal of Advanced Academics, 20(2), 274-294. https://doi.org/10.1177/1932202X0902000204

Belland, B. R., Kim, C., & Hannafin, M. J. (2013). A framework for designing scaffolds that improve motivation and cognition. Educational Psychologist, 48(4), 243-270. https://doi.org/10.1080/00461520.2013.838920

Benson, P. (2013). Teaching and researching autonomy (2nd ed.). Routledge.

Blackwell, L. S., Trzesniewski, K. H., & Dweck, C. S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78(1), 246-263. https://doi.org/10.1111/j.1467-8624.2007.00995.x

Blondal, K. S., & Adalbjarnardottir, S. (2012). Student disengagement in relation to expected and unexpected educational pathways. Scandinavian Journal of Educational Research, 56(1), 85-100. https://doi.org/10.1080/00313831.2011.568607

Broda, M., Yun, J., Schneider, B., Yeager, D. S., Walton, G. M., & Diemer, M. (2018). Reducing inequality in academic success for incoming college students: A randomized trial of growth mindset and belonging interventions. Journal of Research on Educational Effectiveness, 11(3), 317-338.

Brown, J., & Wong, J. (2017, June 6). How gratitude changes you and your brain. Greater Good Magazine. https://greatergood.berkeley.edu/article/item/how_gratitude_changes_you_and_your_brain

Burkholder, E., Blackmon, L., & Wieman, C. (2020) What factors impact student performance in introductory physics? PLoS ONE 15(12): e0244146. https://doi.org/10.1371/journal. pone.0244146

Calderon, V. J., & Yu, D. (2017, June 1). Student enthusiasm falls as high school graduation nears. Gallup. https://news.gallup.com/opinion/gallup/211631/student-enthusiasm-falls-high-school-graduation-nears.aspx

Cents-Boonstra, M., Lichtwarck-Aschoff, A., Denessen, E., Aelterman, N., & Haerens, L. (2020). Fostering student engagement with motivating teaching: An observation study of teacher and student behaviours. Research Papers in Education, 36(6), 754–779. https://doi.org/10.1080/02671522.2020.1767184

Colley, K. E. (2006). Understanding ecology content knowledge and acquiring science process skills through project-based science instruction. Science Activities, 43(1), 26-33. https://doi.org/10.3200/SATS.43.1.26-33

Christopher, C. & Newman, K. (2022) Exploring classroom practices associated with greater student engagement that may benefit low-income students in the early grades. Front. Educ., 27 September 2022 Sec. Special Educational Needs Volume 7 – 2022. https://doi.org/10.3389/feduc.2022.944731

Davis, K. D., Winsler, A., & Middleton,M. (2006). Students’ perceptions of rewards for academic performance by parents and teachers: Relations with achievement and motivation in college. Journal of Genetic Psychology, 167(2), 211-220. https://doi.org/10.3200/GNTP.167.2.211-220.

Deci, E. L., & Ryan, R. M. (2002). The paradox of achievement: The harder you push, the worse it gets. In J. Aronson (Ed.), Improving academic achievement: Impact of psychological factors on education (pp. 61-87). Academic Press.

Deci, E. L., & Ryan, R. M. (2016). Optimizing students’ motivation in the era of testing and pressure: A self-determination theory perspective. In W. C. Liu, J. C. K. Wang, & R. M. Ryan (Eds.), Building autonomous learners, (pp. 9-29). Springer, Singapore.

Deslauriers, L., Schelew, E., & Wieman, C. (2011). Improved learning in a large-enrollment physics class. Science, 332(6031), 862-864. https://doi.org/10.1126/science.1201783

Di Domenico, S. I., & Ryan, R. M. (2017). The emerging neuroscience of intrinsic motivation: A new frontier in self-determination research. Frontiers in Human Neuroscience, 11(145), 1-14. https://doi.org/10.3389/fnhum.2017.00145

Diener, C. I., & Dweck, C. S. (1980). An analysis of learned helplessness: II. The processing of success. Journal of Personality and Social Psychology, 39(5), 940-952. https://doi.org/10.1037/0022-3514.39.5.940

Dweck, C. S. (2008). Mindsets and math/science achievement. Carnegie Corp. of New York–Institute for Advanced Study Commission on Mathematics and Science Education.

Dweck, C. S. (2008). Mindset: The new psychology of success. Ballantine Books.

Dweck, C. S. (2015, September 22). Carol Dweck revisits the ‘growth mindset’. Education Week. https://www.edweek.org/leadership/opinion-carol-dweck-revisits-the-growth-mindset/2015/09

Dweck, C. S., & Yeager, D. S. (2019). Mindsets: A view from two eras. Perspectives on Psychological science, 14(3), 481-496.

English, M. C. , & Kitsantas, A. (2013). Supporting Student Self-Regulated Learning in Problem- and Project-Based Learning. Interdisciplinary Journal of Problem-Based Learning, 7(2). https://doi.org/10.7771/1541-5015.1339

Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59-109. https://doi.org/10.3102/00346543074001059

Freedman, M. P. (1997). Relationship among laboratory instruction, attitude toward science, and achievement in science knowledge. Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching, 34(4), 343-357. https://doi.org/10.1002/(SICI)1098-2736(199704)34:4<343::AID-TEA5>3.0.CO;2-R

Gallup Student Poll. (2016). Engaged today — ready for tomorrow. http://www.gallupstudentpoll.com/

Gallup (2023) How to Improve Teacher Retention and Burnout. https://www.gallup.com/education/316709/how-to-improve-teacher-retention-burnout.aspx

Gibson, H. L., & Chase, C. (2002). Longitudinal impact of an inquiry‐based science program on middle school students’ attitudes toward science. Science Education, 86(5), 693-705. https://doi.org/10.1002/sce.10039

Hennessey, J. (2018). Mindsets and the learning environment: Understanding the impact of “psychologically wise” classroom practices on student achievement. Mindset Scholars Network, 1-4.

Hooker, C. (2023) Improving Teacher and Student Engagement Through Creativity. Sposored content from Adobe For Education. https://www.edsurge.com/news/2023-03-09-improving-teacher-and-student-engagement-through-creativity

Hulleman, C. S., & Barron, K. E. (2016). Motivation interventions in education. In L. Corno, & E. M. Anderman (Eds.), Handbook of educational psychology (3rd ed., pp. 160-171). Routledge.

Hynes, M. (2014, May 20). Don’t call them dropouts: Understanding the experiences of young people who leave high school before graduation. America’s Promise Alliance. https://www.americaspromise.org/report/dont-call-them-dropouts

Jacoby, L. L., Bjork, R. A., & Kelley, C. M. (1994). Illusions of comprehension, competence, and remembering. In D. Druckman, & R. A. Bjork (Eds.), Learning, remembering, believing: Enhancing human performance, (pp. 57-80). National Academy Press.

Jussim, L., Eccles, J., & Madon, S. (1996). Social perception, social stereotypes, and teacher expectations: Accuracy and the quest for the powerful self-fulfilling prophecy. In M. P. Zanna (Ed.), Advances in experimental social psychology, (Vol. 28, pp. 281–388). Academic Press. https://doi.org/10.1016/S0065-2601(08)60240-3

Jussim, L., & Harber, K. D. (2005). Teacher expectations and self-fulfilling prophecies: Knowns and unknowns, resolved and unresolved controversies. Personality and Social Psychology Review, 9(2), 131-155. https://doi.org/10.1207/s15327957pspr0902_3

Jussim, L., Robustelli, S. L., & Cain, T. R. (2009). Teacher expectations and self-fulfilling prophecies. In K. R. Wentzel, & A. Wigfield (Eds.), Handbook of motivation at school, (pp. 349-380). Routledge.

Kanter, D. E., & Schreck, M. (2006). Learning content using complex data in project‐based science: An example from high school biology in urban classrooms. New Directions for Teaching and Learning, 2006(108), 77-91. https://doi.org/10.1002/tl.257

Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work. Educational Psychologist, 41(2), 75-86. https://doi.org/10.1207/s15326985ep4102_1

Kramer, D. (2008). Sea perch is a fun, hands-on approach to teaching science. Physics Today, 61(3), 22. https://doi.org/10.1063/1.2897940

Lei, H., Cui, Y., & Zhou, W. (2018). Relationships between student engagement and academic achievement: A meta-analysis. Social Behavior and Personality: An International Journal, 46(3), 517-528. https://doi.org/10.2224/sbp.7054

Liu, O. L., Lee, H. S., & Linn, M. C. (2010). Multifaceted assessment of inquiry-based science learning. Educational Assessment, 15(2), 69-86. https://doi.org/10.1080/10627197.2010.491067

Lord, T., & Orkwiszewski, T. (2006). Moving from didactic to inquiry-based instruction in a science laboratory. American Biology Teacher, 68(6), 342-345. https://doi.org/10.2307/4452009

Maehr, M. L., & Meyer, H. A. (1997). Understanding motivation and schooling: Where we’ve been, where we are, and where we need to go. Educational Psychology Review, 9(4), 371-409. http://dx.doi.org/10.1023/A:1024750807365

Martin, A. J. (2006). The relationship between teachers’ perceptions of student motivation and engagement and teachers’ enjoyment of and confidence in teaching. Asia‐Pacific Journal of Teacher Education, 34(1), 73-93. https://doi.org/10.1080/13598660500480100

Martin, J., & Torres, A. (2016). I. What is student engagement and why is it important. In User’s guide and toolkit for the surveys of student engagement: The high school survey of student engagement (HSSSE) and the middle grades survey of student engagement (MGSSE). National Association of Independent Schools.

Meece, J. L., Anderman, E. M., & Anderman, L. H. (2006). Classroom goal structure, student motivation, and academic achievement. Annual Review of Psychology, 57, 487-503. https://doi.org/10.1146/annurev.psych.56.091103.070258

Meiklejohn J., Phillips C., Freedman M. L., Griffin M. L., Biegel G. M., Roach A., Frank, J., Burke, C., Pinger, L., Soloway, G., Isberg, R., Sibinga, E., Grossman, L., & Saltzman, A.. (2012). Integrating mindfulness training into K-12 education: Fostering the resilience of teachers and students. Mindfulness 3, 291–307. https://doi.org/10.1007/s12671-012-0094-5

Mindset Kit. (n.d.). Three simple cues that promote belonging. https://www.mindsetkit.org/belonging/cues-belonging/simple-cues-promote-belonging

Nathan, M. J., & Koedinger, K. R. (2000). An investigation of teachers’ beliefs of students’ algebra development. Cognition and Instruction, 18(2), 209-237. https://doi.org/10.1207/S1532690XCI1802_03

Nathan, M. J., & Petrosino, A. (2003). Expert blind spot among preservice teachers. American Educational Research Journal, 40(4), 905-928. https://doi.org/10.3102/00028312040004905

National Academy Foundation and Pearson Foundation. (2011) Project-based learning: A resource for instructors and program coordinators. https://en.calameo.com/read/004202143ffcd40987809

Nickerson, R. S. (1999). How we know—and sometimes misjudge—what others know: Imputing one’s own knowledge to others. Psychological Bulletin, 125(6), 737-759. https://doi.org/10.1037/0033-2909.125.6.737

Nosek, B. A., Smyth, F. L., Sriram, N., Lindner, N. M., Devos, T., Ayala, A., Bar-Anan, Y., Bergh, R., Cai, H., Gonsalkorale, K., Kesebir, S., Maliszewski, N., Neto, F., Olli, E., Park, J., Schnabel, K., Shiomura, K., Tulbure, B. T., Wiers, R. W., … Greenwald, A. G. (2009). National differences in gender–science stereotypes predict national sex differences in science and math achievement. Proceedings of the National Academy of Sciences, 106(26), 10593-10597. https://doi.org/10.1073/pnas.0809921106

Randler, C., & Hulde, M. (2007). Hands‐on versus teacher‐centred experiments in soil ecology. Research in Science & Technological Education, 25(3), 329-338. https://doi.org/10.1080/02635140701535091

Romero, C. (2015). What we know about purpose and relevance from scientific research. Mindset Scholars Network.

Romero, C. (2018). What we know about belonging from scientific research. Mindset Scholars Network.

Ryan, M. and Deci, E. (2020) Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61. https://selfdeterminationtheory.org/wp-content/uploads/2020/04/2020_RyanDeci_CEP_PrePrint.pdf

Satterthwait, D. (2010). Why are ‘hands-on’ science activities so effective for student learning?. Teaching Science, 56(2), 7-10.

Sarrasin, J. B., Nenciovici, L., Foisy, L. M. B., Allaire-Duquette, G., Riopel, M., & Masson, S. (2018). Effects of teaching the concept of neuroplasticity to induce a growth mindset on motivation, achievement, and brain activity: A meta-analysis. Trends in Neuroscience and Education, 12, 22-31. https://doi.org/10.1016/j.tine.2018.07.003

Schunk, D. H. (1989). Self-efficacy and achievement behaviors. Educational Psychology Review, 1(3), 173-208. https://doi.org/10.1007/BF01320134

Sedlacek, M., & Sedova, K. (2017). How many are talking? The role of collectivity in dialogic teaching. International Journal of Educational Research, 85, 99-108. https://doi.org/10.1016/j.ijer.2017.07.001

Seymour, E., & Hewitt, N. M. (1997). Talking about leaving: Why undergraduates leave the sciences. Westview Press.

Schmidt, & J. Graziano (Eds.), Building synergy for high impact educational initiatives: First-year seminars and learning communities. National Resource Center

Schunk, D. H., Meece, J. L., & Pintrich, P. R. (2014). Motivation in education: Theory, Research, and Applications. Pearson.

Shrigley, R. L. (1990). Attitude and behavior are correlates. Journal of Research in Science Teaching, 27(2), 97-113. https://doi.org/10.1002/tea.3660270203

Stipeck, D. J. (2002). Motivation to learn: Integrating theory and practice. Allyn and Bacon.

Stohr‐Hunt, P. M. (1996). An analysis of frequency of hands‐on experience and science achievement. Journal of Research in Science Teaching, 33(1), 101-109. https://doi.org/10.1002/(SICI)1098-2736(199601)33:1<101::AID-TEA6>3.0.CO;2-Z

Stroman, C. (2021, March 1). Structures for belonging: A synthesis of research on belonging-supportive learning environments. Student Experience Research Network. https://studentexperiencenetwork.org/structures-for-belonging-a-synthesis-of-research-on-belonging-supportive-learning-environments/#

Sturm, H., & Bogner, F. X. (2008). Student‐oriented versus teacher‐centered: The effect of learning at workstations about birds and bird flight on cognitive achievement and motivation. International Journal of Science Education, 30(7), 941-959. https://doi.org/10.1080/09500690701313995

Taraban, R., Box, C., Myers, R., Pollard, R., & Bowen, C. W. (2007). Effects of active‐learning experiences on achievement, attitudes, and behaviors in high school biology. Journal of Research in Science Teaching, 44(7), 960-979. https://doi.org/10.1002/tea.20183

Thomas, J. W. (2000). A review of research on project-based learning. Autodesk Foundation.

Tuckman, B. W. (2003). The effect of learning and motivation strategies training on college students’ achievement. Journal of College Student Development, 44(3), 430-437. https://doi.org/10.1353/csd.2003.0034

Turner, S. L. (2011). Student-centered instruction: Integrating the learning sciences to support elementary and middle school learners. Preventing School Failure, 55(3), 123-131. https://doi.org/10.1080/10459880903472884

Vroom, V. H. (1964). Work and motivation. Wiley.

Walton, G. M., & Cohen, G. L. (2007). A question of belonging: Race, social fit, and achievement. Journal of Personality and Social Psychology, 92(1), 82-96. https://doi.org/10.1037/0022-3514.92.1.82

Walton, G. M., & Cohen, G. L. (2011). A brief social-belonging intervention improves academic and health outcomes of minority students. Science, 331(6023), 1447-1451. https://doi.org/10.1126/science.1198364

Wieman, C. E. (2014). Large-scale comparison of science teaching methods sends clear message. Proceedings of the National Academy of Sciences, 111(23), 8319-8320. https://doi.org/10.1073/pnas.1407304111

Wylie, C., & Hodgen, E. (2012). Trajectories and patterns of student engagement: Evidence from a longitudinal study. In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 585-599). Springer.

Learning Enhancement & Neuroplasticity

The brain is always capable of changing in response to experiences and relationships (Darling Hammon & Cook-Harvey, 2018; Maguire et al., 2006; Taya et al., 2015). Learners and educators should acknowledge and take advantage of this principle (Costandi, 2016). COGx programs teach faculty and students about neuroplasticity and the brain’s ability to change which is a powerful intervention that can increase motivation and achievement (Sarrasin et al., 2018).

Similarly, every learner has a unique cognitive profile. Oftentimes, learning difficulties are rooted in cognitive skills that aren’t visible or measured in school. COGx individual learning enhancement programs target and strengthen the cognitive skills essential for learning and develop metacognitive awareness.

Carlsson, M., Dahl, G. B., Öckert, B., & Rooth, D. O. (2015). The effect of schooling on cognitive skills. Review of Economics and Statistics, 97(3), 533-547. https://doi.org/10.1162/REST_a_00501

Costandi, M. (2016). Neuroplasticity. MIT Press.

Cipriano, C., Strambler, M. J., Naples, L., Ha, C., Kirk, M. A., Wood, M., Sehgal, K., Zeiher, A., Eveleigh, A., McCarthy, M. F., Funaro, M., Ponnock, A., Chow, J., & Durlak, J. (2023). Stage 2 report: The state of the evidence for social and emotional learning: A contemporary meta-analysis of universal school-based SEL interventions. Child Development https://osf.io/mk35u/

Darling-Hammond, L., & Cook-Harvey, C. M. (2018). Educating the whole child: Improving school climate to support student success. Palo Alto, CA: Learning Policy Institute. https://doi.org/10.54300/145.655.

Doidge, N. (2007). The brain that changes itself: Stories of personal triumph from the frontiers of brain science. Penguin Books.

Herculano-Houzel, S. (2012). The remarkable, yet not extraordinary, human brain as a scaled-up primate brain and its associated cost. Proceedings of the National Academy of Sciences, 109(Supplement 1), 10661-10668. https://doi.org/10.1073/pnas.1201895109

Jensen, A. (1969). How much can we boost IQ and scholastic achievement? Harvard Educational Review, 39(1), 1–123.

https://doi.org/10.17763/haer.39.1.l3u15956627424k7

Maguire, E. A., Woollett, K., & Spiers, H. J. (2006). London taxi drivers and bus drivers: a structural MRI and neuropsychological analysis. Hippocampus, 16(12), 1091-1101. https://doi.org/10.1002/hipo.20233

National Institute of Neurological Disorders and Stroke. (2021, June 9). Brain basics: Know your brain. National Institutes of Health. https://www.ninds.nih.gov/Disorders/Patient-Caregiver-Education/Know-Your-Brain

Protzko, J., Aronson, J., & Blair, C. (2013). How to make a young child smarter: Evidence from the database of raising intelligence. Perspectives on Psychological Science, 8(1), 25-40. https://doi.org/10.1177/1745691612462585

Ritchie, S. J., Bates, T. C., & Deary, I. J. (2015). Is education associated with improvements in general cognitive ability, or in specific skills? Developmental Psychology, 51(5), 573-582. https://doi.org/10.1037/a0038981

Ritchie, S. J., & Tucker-Drob, E. M. (2018). How much does education improve intelligence? A meta-analysis. Psychological Science, 29(8), 1358-1369. https://doi.org/10.1177/0956797618774253

Taya, F., Sun, Y., Babiloni, F., Thakor, N., & Bezerianos, A. (2015). Brain enhancement through cognitive training: A new insight from brain connectome. Frontiers in Systems Neuroscience, 9, Article 44. https://doi.org/10.3389/fnsys.2015.00044

Zull, J. E. (2002). The art of changing the brain: Enriching the practice of teaching by exploring the biology of learning. Stylus Publishing.

Cognitive Diversity

Cognitive diversity is guaranteed in every classroom and it affects learning. For example, approximately, 10% students are twice-exceptional (2e) (Rankin, 2016) while 20% students have a language processing disorder (NIDCD, 2024). Therefore, it requires effective personalization (CAST, n.d.). Few educators know how to identify and personalize accordingly.

Learning Disabilities Association of America. (n.d.). Types of learning disabilities. https://ldaamerica.org/types-of-learning-disabilities/

Mayo Clinic Staff. (n.d.). Types of learning disabilities. Mayo Clinic. https://ldaamerica.org/types-of-learning-disabilities/

Autism

American Speech-Language-Hearing Association. (n.d.) Autism spectrum disorder. https://www.asha.org/Practice-Portal/Clinical-Topics/Autism

ADHD

Brown, T. E. (2009). ADD/ADHD and impaired executive function in clinical practice. Current Attention Disorders Reports, 1(1), 37-41. https://doi.org/10.1007/s11920-008-0065-7

Brown, T. E. (2006). Executive functions and attention deficit hyperactivity disorder: Implications of two conflicting views. International Journal of Disability, Development and Education, 53(1), 35-46. https://doi.org/10.1080/10349120500510024

Fayyad, J., Sampson, N. A., Hwang, I., Adamowski, T., Aguilar-Gaxiola, S., Al-Hamzawi, A., … & Kessler, R. C. (2017). The descriptive epidemiology of DSM-IV adult ADHD in the world health organization world mental health surveys. ADHD Attention Deficit and Hyperactivity Disorders, 9(1), 47-65. https://doi.org/10.1007/s12402-016-0208-3

Pontifex, M. B., Saliba, B. J., Raine, L. B., Picchietti, D. L., & Hillman, C. H. (2013). Exercise improves behavioral, neurocognitive, and scholastic performance in children with attention-deficit/hyperactivity disorder. The Journal of Pediatrics, 162(3), 543-551. https://doi.org/10.1016/j.jpeds.2012.08.036

The Understood Team. (n.d.). What is ADHD? https://www.understood.org/articles/en/what-is-adhd

Dyslexia

Alloway, T. P. (2016, January 5). Dyslexia and working memory. Psychology Today. https://www.psychologytoday.com/us/blog/keep-it-in-mind/201601/dyslexia-and-working-memory

Hudson, R. F., High, L., & Otaiba, S. A. (2007). Dyslexia and the brain: What does current research tell us?. The Reading Teacher, 60(6), 506-515.

International Dyslexia Association. (2020). Dyslexia basics. https://dyslexiaida.org/dyslexia-basics/https://doi.org/10.1598/RT.60.6.1

Mayo Clinic. (2017, July 22). Dyslexia. Mayo Foundation for Medical Education and Research. https://www.mayoclinic.org/diseases-conditions/dyslexia/symptoms-causes/syc-20353552

Meltzer, L., & Greschler, M. (2018, October). Executive function strategies: The building blocks for reading to learn. The Examiner, 7(4). https://dyslexiaida.org/executive-function-strategies-the-building-blocks-for-reading-to-learn/#

Reading Horizons At-Home Solutions. (n.d.). Executive functioning and dyslexia symptoms. https://athome.readinghorizons.com/research/executive-functioning-and-dyslexia

Learning Disorders

American Speech-Language-Hearing Association. (n.d.) Central auditory processing disorder. https://www.asha.org/Practice-Portal/Clinical-Topics/Central-Auditory-Processing-Disorder/

Division for Emotional & Behavioral Health. (2020, November 6). Behavior disorders: Definitions, characteristics & related information. Council for Exceptional Children. https://debh.exceptionalchildren.org/behavior-disorders-definitions-characteristics-related-information

LD Online. (2006). Timeline of learning disabilities. WETA. http://www.ldonline.org/article/11244/

Learning Disabilities Association of America. (n.d.). Types of learning disabilities. https://ldaamerica.org/types-of-learning-disabilities/

Mayes, S. D., & Calhoun, S. L. (2007). Learning, attention, writing, and processing speed in typical children and children with ADHD, autism, anxiety, depression, and oppositional-defiant disorder. Child Neuropsychology, 13(6), 469-493. https://doi.org/10.1080/09297040601112773

Mayo Clinic Staff. (n.d.). Types of learning disabilities. Mayo Clinic. https://ldaamerica.org/types-of-learning-disabilities/

National Center for Learning Disabilities. (2017, January 27). Supporting academic success. https://www.ncld.org/research/state-of-learning-disabilities/supporting-academic-success/

No Child Left Behind Act. 9 U.S.C. § 9101 (2001). https://www.congress.gov/107/plaws/publ110/PLAW-107publ110.pdf

Twice-Exceptionality

Ali, M. (2015, June 19). 2e children: How the see the invisible. Learning Ally. https://learningally.org/Blog/2e-children-how-to-see-the-invisible

Morin, A. (n.d.). 7 myths about twice-exceptional (2e) students. Understood. https://www.understood.org/articles/en/7-myths-about-twice-exceptional-2e-students

Szabos, J. (1989). Bright child, gifted learner. Challenge, 34(4), 3.

TEDx Talks. (2017, March 7). Twice-exceptional learners (2e) | Jim Russell [Video]. YouTube. https://www.youtube.com/watch?v=H-THZbFEmWU

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