The Neuroscience of Engagement

Tokuhama-Espinosa, T. (2021). Bringing theneuroscience of learning to online teaching: an educator's handbook. Teachers College Press.

Tokuhama-Espinosa, T. (2018). Neuromyths: Debunkingfalse ideas about the brain. WW Norton & Company.

University of Central Oklahoma, Center for Neuroeducationand Embodied Learning. (n.d.). Center for Neuroeducation and EmbodiedLearning Institute [Micro-credential]. https://uco.edu/programs/microcredentials/neuroeducation-embodied-learning

Attention:

Craik, F. I. M. (2019). Remembering: An Activity of Mindand Brain.

Ernst, D., Becker, S., & Horstmann, G. (2020). Noveltycompetes with saliency for attention. Vision Research, 168,42–52. https://doi.org/10.1016/j.visres.2020.01.004

Fernandez, N. B., Trost, W. J., & Vuilleumier, P.(2019). Brain networks mediating the influence of background music on selectiveattention. Social Cognitive and Affective Neuroscience, 14(12),1441–1452. https://doi.org/10.1093/scan/nsaa004

Franklin, M. S., Smallwood, J., Zedelius, C. M., Broadway,J. M., & Schooler, J. W. (2016). Unaware yet reliant on attention:Experience sampling reveals that mind-wandering impedes implicit learning. PsychonomicBulletin & Review, 23(1), 223–229. https://doi.org/10.3758/s13423-015-0885-5

Ghassemzadeh, H., Rothbart, M. K., & Posner, M. I.(2019). Anxiety and Brain Networks of Attentional Control. Cognitive andBehavioral Neurology, 32(1), 54–62. https://doi.org/10.1097/WNN.0000000000000181

Graziano, M. S. A., Guterstam, A., Bio, B. J., &Wilterson, A. I. (2020). Toward a standard model of consciousness: Reconcilingthe attention schema, global workspace, higher-order thought, and illusionisttheories. Cognitive Neuropsychology, 37(3–4), 155–172. https://doi.org/10.1080/02643294.2019.1670630

Hitch, G. J., Allen, R. J., & Baddeley, A. D. (2020).Attention and binding in visual working memory: Two forms of attention and twokinds of buffer storage. Attention, Perception, & Psychophysics, 82(1),280–293. https://doi.org/10.3758/s13414-019-01837-x

Keller, A. S., Davidesco, I., & Tanner, K. D. (2020).Attention Matters: How Orchestrating Attention May Relate to ClassroomLearning. CBE—Life Sciences Education, 19(3), fe5. https://doi.org/10.1187/cbe.20-05-0106

Mather, E. (2013). Novelty, attention, and challenges fordevelopmental psychology. Frontiers in Psychology, 4. https://doi.org/10.3389/fpsyg.2013.00491

Posner, M. I., Rothbart, M. K., Sheese, B. E., &Voelker, P. (2014). Developing Attention: Behavioral and Brain Mechanisms. Advancesin Neuroscience, 2014, 1–9. https://doi.org/10.1155/2014/405094

Posner, M. I., Rothbart, M. K., & Tang, Y.-Y. (2015).Enhancing attention through training. Current Opinion in Behavioral Sciences,4, 1–5. https://doi.org/10.1016/j.cobeha.2014.12.008

Cognitive Load:

Alemdag, E. (2022). Effects of instructor-present videos onlearning, cognitive load, motivation, and social presence: A meta-analysis. Educationand Information Technologies, 27(9), 12713–12742. https://doi.org/10.1007/s10639-022-11154-w

Article: Cognitive Load and Expertise Reversal.(n.d.).

Asaadi, A. H., Amiri, S. H., Bosaghzadeh, A., &Ebrahimpour, R. (2024). Effects and prediction of cognitive load on encodingmodel of brain response to auditory and linguistic stimuli in educationalmultimedia. Scientific Reports, 14(1), 9133. https://doi.org/10.1038/s41598-024-59411-x

Ayres, P. (2020). Something old, something new fromcognitive load theory. Computers in Human Behavior, 113, 106503. https://doi.org/10.1016/j.chb.2020.106503

Cai, H., & Gu, X. (2019). Supporting collaborativelearning using a diagram‐based visible thinking tool basedon cognitive load theory. British Journal of Educational Technology, 50(5),2329–2345. https://doi.org/10.1111/bjet.12818

Chen, O., Paas, F., & Sweller, J. (2023). A CognitiveLoad Theory Approach to Defining and Measuring Task Complexity Through ElementInteractivity. Educational Psychology Review, 35(2), 63. https://doi.org/10.1007/s10648-023-09782-w

Cognitive Load Theory. (n.d.).

Ellerton, P. (2022). On critical thinking and contentknowledge: A critique of the assumptions of cognitive load theory. ThinkingSkills and Creativity, 43, 100975. https://doi.org/10.1016/j.tsc.2021.100975

Gauvain, M. (n.d.). COGNITIVE LOAD THEORY. Cognitive LoadTheory.

Hartelt, T., & Martens, H. (2024). Self-regulatory andmetacognitive instruction regarding student conceptions: Influence on students’self-efficacy and cognitive load. Frontiers in Psychology, 15,1450947. https://doi.org/10.3389/fpsyg.2024.1450947

Le Cunff, A.-L., Giampietro, V., & Dommett, E. (2024).Neurodiversity and cognitive load in online learning: A systematic review withnarrative synthesis. Educational Research Review, 43, 100604. https://doi.org/10.1016/j.edurev.2024.100604

Leppink, J. (2017). Cognitive load theory: Practicalimplications and an important challenge. Journal of Taibah UniversityMedical Sciences, 12(5), 385–391. https://doi.org/10.1016/j.jtumed.2017.05.003

Paas, F., & Van Merriënboer, J. J. G. (2020).Cognitive-Load Theory: Methods to Manage Working Memory Load in the Learning ofComplex Tasks. Current Directions in Psychological Science, 29(4),394–398. https://doi.org/10.1177/0963721420922183

Plass, J. L., & Kalyuga, S. (2019). Four Ways ofConsidering Emotion in Cognitive Load Theory. Educational Psychology Review,31(2), 339–359. https://doi.org/10.1007/s10648-019-09473-5

Skulmowski, A. (2023). Learners Emphasize Their IntrinsicLoad if Asked About It First: Communicative Aspects of Cognitive LoadMeasurement. Mind, Brain, and Education, 17(3), 165–169. https://doi.org/10.1111/mbe.12369

Sozio, G., Agostinho, S., Tindall-Ford, S., & Paas, F.(2024). Enhancing Teaching Strategies through Cognitive Load Theory: Processvs. Product Worked Examples. Education Sciences, 14(8), 813. https://doi.org/10.3390/educsci14080813

Sweller, J. (2024). Cognitive load theory and individualdifferences. Learning and Individual Differences, 110, 102423. https://doi.org/10.1016/j.lindif.2024.102423

Wu, Q., Petsangsri, S., & Morris, J. (2022). Students’Technology, Cognitive, and Content Knowledge (TSCCK) Instructional Model Effecton Cognitive Load and Learning Achievement. Education Sciences, 12(12),916. https://doi.org/10.3390/educsci12120916

Zeitlhofer, I., Zumbach, J., & Schweppe, J. (2024).Complexity affects performance, cognitive load, and awareness. Learning andInstruction, 94, 102001. https://doi.org/10.1016/j.learninstruc.2024.102001

Zheng, L., Li, X., Zhang, X., & Sun, W. (2019). Theeffects of group metacognitive scaffolding on group metacognitive behaviors,group performance, and cognitive load in computer-supported collaborativelearning. The Internet and Higher Education, 42, 13–24. https://doi.org/10.1016/j.iheduc.2019.03.002

Feedback:

Boud, D., & Molloy, E. (2013). Rethinking models offeedback for learning: The challenge of design. Assessment & Evaluationin Higher Education, 38(6), 698–712. https://doi.org/10.1080/02602938.2012.691462

Gillmore, J. (n.d.). From Training Chaos to LearningMastery.

Havnes, A., Smith, K., Dysthe, O., & Ludvigsen, K.(2012). Formative assessment and feedback: Making learning visible. Studiesin Educational Evaluation, 38(1), 21–27. https://doi.org/10.1016/j.stueduc.2012.04.001

Hinojosa, D. M. (2022). Practice what you teach: Onsitecoaching and dialogic feedback to promote the appropriation of instructionalstrategies. Teaching and Teacher Education, 111, 103582. https://doi.org/10.1016/j.tate.2021.103582

Loftin, R., Peng, B., MacGlashan, J., Littman, M. L.,Taylor, M. E., Huang, J., & Roberts, D. L. (2016). Learning behaviors viahuman-delivered discrete feedback: Modeling implicit feedback strategies tospeed up learning. Autonomous Agents and Multi-Agent Systems, 30(1),30–59. https://doi.org/10.1007/s10458-015-9283-7

Lubianiker, N., Paret, C., Dayan, P., & Hendler, T.(2022). Neurofeedback through the lens of reinforcement learning. Trends inNeurosciences, 45(8), 579–593. https://doi.org/10.1016/j.tins.2022.03.008

Nieminen, J. H., Tai, J., Boud, D., & Henderson, M.(2022). Student agency in feedback: Beyond the individual. Assessment &Evaluation in Higher Education, 47(1), 95–108. https://doi.org/10.1080/02602938.2021.1887080

Palminteri, S., Lefebvre, G., Kilford, E. J., &Blakemore, S.-J. (2017). Confirmation bias in human reinforcement learning:Evidence from counterfactual feedback processing. PLOS Computational Biology,13(8), e1005684. https://doi.org/10.1371/journal.pcbi.1005684

Sadler, I., Reimann, N., & Sambell, K. (2023).Feedforward practices: A systematic review of the literature. Assessment& Evaluation in Higher Education, 48(3), 305–320. https://doi.org/10.1080/02602938.2022.2073434

Yang, M., & Carless, D. (2013). The feedback triangleand the enhancement of dialogic feedback processes. Teaching in HigherEducation, 18(3), 285–297. https://doi.org/10.1080/13562517.2012.719154

Motivation:

Barbier, K., Struyf, E., Verschueren, K., & Donche, V.(2023). Fostering cognitive and affective-motivational learning outcomes forhigh-ability students in mixed-ability elementary classrooms: A systematicreview. European Journal of Psychology of Education, 38(1),83–107. https://doi.org/10.1007/s10212-022-00606-z

Berridge, K. C. (2018). Evolving Concepts of Emotion andMotivation. Frontiers in Psychology, 9, 1647. https://doi.org/10.3389/fpsyg.2018.01647

Braver, T. S., Krug, M. K., Chiew, K. S., Kool, W.,Westbrook, J. A., Clement, N. J., Adcock, R. A., Barch, D. M., Botvinick, M.M., Carver, C. S., Cools, R., Custers, R., Dickinson, A., Dweck, C. S.,Fishbach, A., Gollwitzer, P. M., Hess, T. M., Isaacowitz, D. M., Mather, M., …for the MOMCAI group. (2014). Mechanisms of motivation–cognition interaction:Challenges and opportunities. Cognitive, Affective, & BehavioralNeuroscience, 14(2), 443–472. https://doi.org/10.3758/s13415-014-0300-0

Buil, I., Catalán, S., & Martínez, E. (2019). Theinfluence of flow on learning outcomes: An empirical study on the use ofclickers. British Journal of Educational Technology, 50(1),428–439. https://doi.org/10.1111/bjet.12561

Burgers, C., Eden, A., Van Engelenburg, M. D., &Buningh, S. (2015). How feedback boosts motivation and play in a brain-traininggame. Computers in Human Behavior, 48, 94–103. https://doi.org/10.1016/j.chb.2015.01.038

Chang, Y.-S. (2019). The mediating role of motivation forcreative performance of cloud-based m-learning. Australasian Journal ofEducational Technology, 35(4). https://doi.org/10.14742/ajet.4418

Corr, P. J., DeYoung, C. G., & McNaughton, N. (2013).Motivation and Personality: A Neuropsychological Perspective. Social andPersonality Psychology Compass, 7(3), 158–175. https://doi.org/10.1111/spc3.12016

Law, K. M. Y., Geng, S., & Li, T. (2019). Studentenrollment, motivation and learning performance in a blended learningenvironment: The mediating effects of social, teaching, and cognitive presence.Computers & Education, 136, 1–12. https://doi.org/10.1016/j.compedu.2019.02.021

Legault, L., & Inzlicht, M. (2013). Self-determination,self-regulation, and the brain: Autonomy improves performance by enhancingneuroaffective responsiveness to self-regulation failure. Journal ofPersonality and Social Psychology, 105(1), 123–138. https://doi.org/10.1037/a0030426

Luna, B., Paulsen, D. J., Padmanabhan, A., & Geier, C.(2013). The Teenage Brain: Cognitive Control and Motivation. CurrentDirections in Psychological Science, 22(2), 94–100. https://doi.org/10.1177/0963721413478416

Mkrtchian, A., Qiu, Z., Abir, Y., Erdmann, T., Dercon, Q.,Sedlinska, T., Browning, M., Costello, H., & Huys, Q. J. M. (2025). Dopamineand serotonin differentially associated with reward and punishment processes inhumans: A systematic review and meta-analysis. https://doi.org/10.1101/2025.01.08.631868

Proudfit, G. H., Inzlicht, M., & Mennin, D. S. (2013).Anxiety and error monitoring: The importance of motivation and emotion. Frontiersin Human Neuroscience, 7. https://doi.org/10.3389/fnhum.2013.00636

Richard, J. M., Castro, D. C., DiFeliceantonio, A. G.,Robinson, M. J. F., & Berridge, K. C. (2013). Mapping brain circuits ofreward and motivation: In the footsteps of Ann Kelley. Neuroscience &Biobehavioral Reviews, 37(9), 1919–1931. https://doi.org/10.1016/j.neubiorev.2012.12.008

Törmänen, T., Ketonen, E., Lehtoaho, E., Turunen, M.,Zabolotna, K., Shubina, T., & Järvenoja, H. (2025). Situational Motivationin Academic Learning: A Systematic Review. Educational Psychology Review,37(2), 56. https://doi.org/10.1007/s10648-025-10036-0

Neuromyths:

Alferink, L. A., & Farmer-Dougan, V. (2010). Brain-(not)Based Education: Dangers of Misunderstanding and Misapplication of NeuroscienceResearch. Exceptionality, 18(1), 42–52. https://doi.org/10.1080/09362830903462573

Almarzouki, A. F., Alqahtani, A. I., Baessa, J. K., Badaood,D. K., Nujoom, R. R., Malibari, R. W., Aljared, E. M., & Alghamdi, R. S.(2025). Neuroscience Literacy and Academic Outcomes: Insights from a UniversityStudent Population. Brain Sciences, 15(1), 44. https://doi.org/10.3390/brainsci15010044

Benedek, M., Karstendiek, M., Ceh, S. M., Grabner, R. H.,Krammer, G., Lebuda, I., Silvia, P. J., Cotter, K. N., Li, Y., Hu, W.,Martskvishvili, K., & Kaufman, J. C. (2021). Creativity myths: Prevalenceand correlates of misconceptions on creativity. Personality and IndividualDifferences, 182, 111068. https://doi.org/10.1016/j.paid.2021.111068

Carboni, A., Maiche, A., & Valle-Lisboa, J. C. (2021).Teaching the Science in Neuroscience to Protect From Neuromyths: From Coursesto Fieldwork. Frontiers in Human Neuroscience, 15, 718399. https://doi.org/10.3389/fnhum.2021.718399

Deibl, I., Zeitlhofer, I., Geroldinger, A., & Zumbach,J. (2024). Overcoming the Myths: Interactive Learning Environments as MythBusters in Teaching and Learning. Psychology Learning & Teaching, 23(3),346–365. https://doi.org/10.1177/14757257241261351

Ferreira, R. A., & Rodríguez, C. (2022). Effect of aScience of Learning Course on Beliefs in Neuromyths and Neuroscience Literacy. BrainSciences, 12(7), 811. https://doi.org/10.3390/brainsci12070811

Gardner, H. (2020). “Neuromyths”: A Critical Consideration. Mind,Brain, and Education, 14(1), 2–4. https://doi.org/10.1111/mbe.12229

Grospietsch, F., & Mayer, J. (2020). Misconceptionsabout neuroscience – prevalence and persistence of neuromyths in education. Neuroforum,26(2), 63–71. https://doi.org/10.1515/nf-2020-0006

Guley, O., Pasquinelli, E., Zenasni, F., & Mercier, H.(2024). Neuromyths About Learning and the Allure of Neuroscience.2173–2174. https://doi.org/10.22318/icls2024.688461

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

Seccia, A., & Allee, K. (2024). Teaching – It’s a NoBrainer, Right?: Using an Assessment Course to Bust Educators’ Neuromyths. Journalof Neuroeducation, 5(1). https://doi.org/10.1344/joned.v5i1.46856

Torrijos-Muelas, M., González-Víllora, S., &Bodoque-Osma, A. R. (2021). The Persistence of Neuromyths in the EducationalSettings: A Systematic Review. Frontiers in Psychology, 11,591923. https://doi.org/10.3389/fpsyg.2020.591923

Ulusoy, T., Bakir, S., & Zorluoğlu, S. L. (2023).Neuromyths in Education. Eğitimde Kuram ve Uygulama, 19(1),74–82. https://doi.org/10.17244/eku.1256588

Van Dijk, W., & Lane, H. B. (2020). The brain and the USeducation system: Perpetuation of neuromyths. Exceptionality, 28(1),16–29. https://doi.org/10.1080/09362835.2018.1480954

Bresnahan, C., Peterson, E. G., & Hattan, C. (2024). Whyeducators endorse a neuromyth: Relationships among educational priorities,beliefs about learning styles, and instructional decisions. Frontiers inPsychology, 15, 1407518. https://doi.org/10.3389/fpsyg.2024.1407518

Clinton-Lisell, V., & Litzinger, C. (2024). Is it reallya neuromyth? A meta-analysis of the learning styles matching hypothesis. Frontiersin Psychology, 15, 1428732. https://doi.org/10.3389/fpsyg.2024.1428732

Gentrup, S., Lorenz, G., Kristen, C., & Kogan, I.(2020). Self-fulfilling prophecies in the classroom: Teacher expectations,teacher feedback and student achievement. Learning and Instruction, 66,101296. https://doi.org/10.1016/j.learninstruc.2019.101296

His brain, her brain? Research exploring sex differencesin the human brain must overcome “neurosexist” interpretations. (2026).

Lindell, A. K., & Kidd, E. (2011). Why Right‐BrainTeaching is Half‐Witted: A Critique of the Misapplication ofNeuroscience to Education. Mind, Brain, and Education, 5(3),121–127. https://doi.org/10.1111/j.1751-228X.2011.01120.x

Nancekivell, S. E., Sun, X., Gelman, S. A., & Shah, P.(2021). A Slippery Myth: How Learning Style Beliefs Shape Reasoning aboutMultimodal Instruction and Related Scientific Evidence. Cognitive Science,45(10), e13047. https://doi.org/10.1111/cogs.13047

Newton, P. M. (2015). The Learning Styles Myth is Thrivingin Higher Education. Frontiers in Psychology, 6. https://doi.org/10.3389/fpsyg.2015.01908

Papadatou-Pastou, M., Touloumakos, A. K., Koutouveli, C.,& Barrable, A. (2021). The learning styles neuromyth: When the same termmeans different things to different teachers. European Journal of Psychologyof Education, 36(2), 511–531. https://doi.org/10.1007/s10212-020-00485-2

Rosen, C. (n.d.). The Myth of Multitasking.

Social and Emotional

Alcalá-López, D., Mei, N., Margolles, P., & Soto, D.(2024). Brain-wide representation of social knowledge. Social Cognitive andAffective Neuroscience, 19(1), nsae032. https://doi.org/10.1093/scan/nsae032

Andrews-Todd, J., Salovich, N. A., & Rapp, D. N. (2021).Differential effects of pressure on social contagion of memory. Journal ofExperimental Psychology: Applied, 27(2), 258–275. https://doi.org/10.1037/xap0000346

Aslanidou, A., Andreatta, M., Wong, A. H. K., & Wieser,M. J. (2025). Generalized expectancy of threat in threatening compared to safecontexts. Social Cognitive and Affective Neuroscience, 20(1),nsae097. https://doi.org/10.1093/scan/nsae097

Block, P., & Burnett Heyes, S. (2022). Sharing the load:Contagion and tolerance of mood in social networks. Emotion, 22(6),1193–1207. https://doi.org/10.1037/emo0000952

Burgess, L. G., Riddell, P. M., Fancourt, A., &Murayama, K. (2018). The Influence of Social Contagion Within Education: AMotivational Perspective. Mind, Brain, and Education, 12(4),164–174. https://doi.org/10.1111/mbe.12178

Cheng, X., Wang, S., Guo, B., Wang, Q., Hu, Y., & Pan,Y. (2024). How self-disclosure of negative experiences shapes prosociality? SocialCognitive and Affective Neuroscience, 19(1), nsae003. https://doi.org/10.1093/scan/nsae003

Heyes, C., & Catmur, C. (n.d.). What Happened toMirror Neurons?

Immordino-Yang, M. H., & Gotlieb, R. (2017). EmbodiedBrains, Social Minds, Cultural Meaning: Integrating Neuroscientific andEducational Research on Social-Affective Development. American EducationalResearch Journal, 54(1_suppl). https://doi.org/10.3102/0002831216669780

Lieberman, M. D. (2024). Social cognitive and affectiveneuroscience: The college years. Social Cognitive and Affective Neuroscience,19(1), nsad080. https://doi.org/10.1093/scan/nsad080

Özel, E. H. (2025). Affective Neuroscience and Theory ofMind: An Analysis on Neural Connections. Psikiyatride Güncel Yaklaşımlar,17(2), 244–260. https://doi.org/10.18863/pgy.1455639

Schenk, S., Waldie, K., & Grimshaw, G. (2021). Cognitiveand affective neuroscience: Approaches and applications. Journal of theRoyal Society of New Zealand, 51(1), 1–3. https://doi.org/10.1080/03036758.2020.1851732

Sievers, B., & Thornton, M. A. (2024). Deep socialneuroscience: The promise and peril of using artificial neural networks tostudy the social brain. Social Cognitive and Affective Neuroscience, 19(1),nsae014. https://doi.org/10.1093/scan/nsae014

Tyng, C. M., Amin, H. U., Saad, M. N. M., & Malik, A. S.(2017). The Influences of Emotion on Learning and Memory. Frontiers inPsychology, 8, 1454. https://doi.org/10.3389/fpsyg.2017.01454