Références :

1. Blanchette Sarrasin, J., Riopel, M., & Masson, S. (2019). Neuromyths and their origin among teachers in Quebec. Mind, Brain, and Education, 13(2), 100-109.

2. Masson, S. (2015). Les apports de la neuroéducation à l’enseignement: des neuromythes aux découvertes actuelles. Approche neuropsychologique des apprentissages chez l’enfant, 134, 11-22.

3. Pasquinelli, E. (2012). Neuromyths: Why do they exist and persist?. Mind, Brain, and Education, 6(2), 89-96.

4. Pasquinelli, E. (2015). Mon cerveau, ce héros: mythes et réalité. Éd. le Pommier.

5. Tardif, E., Doudin, P. A., & Meylan, N. (2015). Neuromyths among teachers and student teachers. Mind, brain, and Education, 9(1), 50-59.

Références :

1. Opillard, T. (2008). La dégradation Cambridge : même pas vrai. Actes de Lecture, (102).

Références :

1. Hultin, E., & Westman, M. (2013). Early literacy practices go digital. Literacy Information and Computer Education Journal (LICEJ), 4(2), 1005-1013. 

2. Mueller, P. A., & Oppenheimer, D. M. (2014). The pen is mightier than the keyboard: Advantages of longhand over laptop note taking. Psychological science, 25(6), 1159-1168.

3. Ose Askvik, E., Van der Weel, F. R., & van der Meer, A. L. (2020). The importance of cursive handwriting over typewriting for learning in the classroom: a high-density EEG study of 12-year-old children and young adults. Frontiers in Psychology, 11, 1810. 

4. Osugi, K., Ihara, A. S., Nakajima, K., Kake, A., Ishimaru, K., Yokota, Y., & Naruse, Y. (2019). Differences in Brain Activity After Learning With the Use of a Digital Pen vs. an Ink Pen—An Electroencephalography Study. Frontiers in human neuroscience, 13, 275. 

5. Sana, F., Weston, T., & Cepeda, N. J. (2013). Laptop multitasking hinders classroom learning for both users and nearby peers. Computers & Education, 62, 24-31. 

6. Stacy, E. M., & Cain, J. (2015). Note-taking and handouts in the digital age. American journal of pharmaceutical education, 79(7). 

Références :

1. Guéguen, N. (1999). Les mille effets de la musique. Cerveau et psycho, 22. 

2. Ho, Y. C., Cheung, M. C., & Chan, A. S. (2003). Music training improves verbal but not visual memory: cross-sectional and longitudinal explorations in children. Neuropsychology, 17(3), 439. 

3. Jaschke, A. C., Honing, H., & Scherder, E. J. (2018). Longitudinal analysis of music education on executive functions in primary school children. Frontiers in neuroscience, 103. 

4. Lee, Y. S., Lu, M. J., & Ko, H. P. (2007). Effects of skill training on working memory capacity. Learning and Instruction, 17(3), 336-344. 

5. Pietschnig, J., Voracek, M., & Formann, A. K. (2010). Mozart effect–Shmozart effect: A meta-analysis. Intelligence, 38(3), 314-323. 

6. Rauscher, F. H., Shaw, G. L., & Ky, C. N. (1993). Music and spatial task performance. Nature, 365(6447), 611-611.

7. Thompson, W. F., Geeves, A. M., & Olsen, K. N. (2019). Who enjoys listening to violent music and why?. Psychology of Popular Media Culture, 8(3), 218. 

Références :

1. Brown, C. (2001). Familiarity with the test environment improves escape responses in the crimson spotted rainbowfish, Melanotaenia duboulayi. Animal Cognition, 4(2), 109-113. 

2. Gee, P., Stephenson, D., & Wright, D. E. (1994). Temporal discrimination learning of operant feeding in goldfish (Carassius auratus). Journal of the experimental analysis of behavior, 62(1), 1-13. 

3. Zion, B., Barki, A., Grinshpon, J., Rosenfeld, L., & Karplus, I. (2011). Retention of acoustic conditioning in St Peter's fish Sarotherodon galilaeus. Journal of Fish Biology, 78(3), 838-847. 

Références :

1. Hulleman, C. S., & Harackiewicz, J. M. (2009). Promoting interest and performance in high school science classes. science, 326(5958), 1410-1412.

2. Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological science in the public interest, 9(3), 105-119.

3. Reber, R., Canning, E. A., & Harackiewicz, J. M. (2018). Personalized education to increase interest. Current directions in psychological science, 27(6), 449-454.

4. Riener, C., & Willingham, D. (2010). The myth of learning styles. Change: The magazine of higher learning, 42(5), 32-35.

5. Rousseau, L., & Brabant-Beaulieu, J. (2020). Le neuromythe des «styles d’apprentissage» VAK (visuel, auditif, kinesthésique): une tentative de démystification auprès d’apprentis enseignants franco-ontariens. Neuroeducation, 6(1), 65-91.

Références :

1. Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004). Changes in grey matter induced by training. Nature, 427(6972), 311-312. 

2. Gómez-Ocádiz, R., Trippa, M., Zhang, C. L., Posani, L., Cocco, S., Monasson, R., & Schmidt-Hieber, C. (2022). A synaptic signal for novelty processing in the hippocampus. Nature Communications, 13(1), 1-15.

3. Hebb, D. O. (1949). The first stage of perception: growth of the assembly. The Organization of Behavior, 4, 60-78.

4. Hebb, D. O. (2005). The organization of behavior: A neuropsychological theory. Psychology Press.

5. Kwok, V., Niu, Z., Kay, P., Zhou, K., Mo, L., Jin, Z., ... & Tan, L. H. (2011). Learning new color names produces rapid increase in gray matter in the intact adult human cortex. Proceedings of the National Academy of Sciences, 108(16), 6686-6688.

6. Maguire, E. A., Gadian, D. G., Johnsrude, I. S., Good, C. D., Ashburner, J., Frackowiak, R. S., & Frith, C. D. (2000). Navigation-related structural change in the hippocampi of taxi drivers. Proceedings of the National Academy of Sciences, 97(8), 4398-4403.

Références :

1. Azevedo, F. A., Carvalho, L. R., Grinberg, L. T., Farfel, J. M., Ferretti, R. E., Leite, R. E., ... & Herculano‐Houzel, S. (2009). Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled‐up primate brain. Journal of Comparative Neurology, 513(5), 532-541.

2. Toga, A. W., Clark, K. A., Thompson, P. M., Shattuck, D. W., & Van Horn, J. D. (2012). Mapping the human connectome. Neurosurgery, 71(1), 1-5.

Références :

1. MacLean, P. D., & Guyot, R. (1990). Les trois cerveaux de l'homme. R. Laffont.

2. Maclean, P. (2021). Brain evolution: The origins of social and cognitive behaviors. In A Child’s Brain (pp. 9-21). Routledge.

3. Newman, J. D., & Harris, J. C. (2009). The scientific contributions of Paul D. MacLean (1913–2007). The Journal of nervous and mental disease, 197(1), 3-5.

4. Lemerle, S. (2021). Le cerveau reptilien. Sur la popularité d'une erreur scientifique. Cnrs.

5. BONUS : Lemerle, S. (2021). Le cerveau reptilien. Sur la popularité d'une erreur scientifique. CNRS éditions. 

Références :

1. Rutten, G. J. (2022). Broca-Wernicke theories: A historical perspective. Handbook of Clinical Neurology, 185, 25-34.

2. Sperry, R. W. (1961). Cerebral Organization and Behavior: The split brain behaves in many respects like two separate brains, providing new research possibilities. Science, 133(3466), 1749-1757.

3. Gazzaniga, M. S. (2014). The split-brain: Rooting consciousness in biology. Proceedings of the National Academy of Sciences, 111(51), 18093-18094.

4. Kong, X. Z., Mathias, S. R., Guadalupe, T., ENIGMA Laterality Working Group, Glahn, D. C., Franke, B., ... & Karolinska Schizophrenia Project (KaSP) consortium. (2018). Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium. Proceedings of the National Academy of Sciences, 115(22), E5154-E5163.

5. Guadalupe, T., Mathias, S. R., Vanerp, T. G., Whelan, C. D., Zwiers, M. P., Abe, Y., ... & Wolfers, T. (2017). Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex. Brain imaging and behavior, 11(5), 1497-1514.

6. Karolis, V. R., Corbetta, M., & Thiebaut de Schotten, M. (2019). The architecture of functional lateralisation and its relationship to callosal connectivity in the human brain. Nature communications, 10(1), 1-9.

7. Ringo, J. L., Doty, R. W., Demeter, S., & Simard, P. Y. (1994). Time is of the essence: a conjecture that hemispheric specialization arises from interhemispheric conduction delay. Cerebral Cortex, 4(4), 331-343.

8. Amalric, M., & Dehaene, S. (2016). Origins of the brain networks for advanced mathematics in expert mathematicians. Proceedings of the National Academy of Sciences, 113(18), 4909-4917.

Références :

1. Nielsen, J. A., Zielinski, B. A., Ferguson, M. A., Lainhart, J. E., & Anderson, J. S. (2013). An evaluation of the left-brain vs. right-brain hypothesis with resting state functional connectivity magnetic resonance imaging. PloS one, 8(8), e71275.  

2. Hall, J. A. (1978). Gender effects in decoding nonverbal cues. Psychological bulletin, 85(4), 845. 

3. Huguet, P., & Regner, I. (2007). Stereotype threat among schoolgirls in quasi-ordinary classroom circumstances. Journal of educational psychology, 99(3), 545. 

4. Merton, R. K. (2016). The self-fulfilling prophecy. The Antioch Review, 74(3), 504-521. 

5. Rosenthal, R., & Jacobson, L. (1968). Pygmalion in the classroom. The urban review, 3(1), 16-20. 

Références :

1. Dennison, P. E., & Dennison, G. E. (1986). Brain Gym. Simple Activities for Whole Brain Learning.

2. Spaulding, L. S., Mostert, M. P., & Beam, A. P. (2010). Is Brain Gym® an effective educational intervention?. Exceptionality, 18(1), 18-30.

1. Hyatt, K. J. (2007). Brain Gym®: Building stronger brains or wishful thinking?. Remedial and special education, 28(2), 117-124.

2. Maskell, B., Shapiro, D. R., & Ridley, C. (2004). Effects of Brain Gym on overhand throwing in first grade students: A preliminary investigation. Physical Educator, 61(1), 14-22.

3. Stephenson, J. (2009). Best practice? Advice provided to teachers about the use of Brain Gym® in Australian schools. Australian Journal of Education, 53(2), 109-124.

Références :

1. Rivera, S. M., Reiss, A. L., Eckert, M. A., & Menon, V. (2005). Developmental changes in mental arithmetic: evidence for increased functional specialization in the left inferior parietal cortex. Cerebral cortex, 15(11), 1779-1790.

2. Shaywitz, B. A., Skudlarski, P., Holahan, J. M., Marchione, K. E., Constable, R. T., Fulbright, R. K., ... & Shaywitz, S. E. (2007). Age‐related changes in reading systems of dyslexic children. Annals of neurology, 61(4), 363-370.

3. Chein, J. M., & Schneider, W. (2005). Neuroimaging studies of practice-related change: fMRI and meta-analytic evidence of a domain-general control network for learning. Cognitive Brain Research, 25(3), 607-623.

4. Callan, D. E., & Schweighofer, N. (2010). Neural correlates of the spacing effect in explicit verbal semantic encoding support the deficient‐processing theory. Human brain mapping, 31(4), 645-659.

5. Bradley, M. M., Costa, V. D., Ferrari, V., Codispoti, M., Fitzsimmons, J. R., & Lang, P. J. (2015). Imaging distributed and massed repetitions of natural scenes: Spontaneous retrieval and maintenance. Human Brain Mapping, 36(4), 1381-1392.

6. Zhao, X., Wang, C., Liu, Q., Xiao, X., Jiang, T., Chen, C., & Xue, G. (2015). Neural mechanisms of the spacing effect in episodic memory: A parallel EEG and fMRI study. Cortex, 69, 76-92.

7. Xue, G., Mei, L., Chen, C., Lu, Z. L., Poldrack, R., & Dong, Q. (2011). Spaced learning enhances subsequent recognition memory by reducing neural repetition suppression. Journal of cognitive neuroscience, 23(7), 1624-1633.

8. Rasch, B., & Born, J. (2013). About sleep's role in memory. Physiological reviews.

9. Smolen, P., Zhang, Y., & Byrne, J. H. (2016). The right time to learn: mechanisms and optimization of spaced learning. Nature Reviews Neuroscience, 17(2), 77-88.

10. Cepeda, N. J., Vul, E., Rohrer, D., Wixted, J. T., & Pashler, H. (2008). Spacing effects in learning: A temporal ridgeline of optimal retention. Psychological science, 19(11), 1095-1102.

11. Kang, S. H., Lindsey, R. V., Mozer, M. C., & Pashler, H. (2014). Retrieval practice over the long term: Should spacing be expanding or equal-interval?. Psychonomic bulletin & review, 21(6), 1544-1550.

Références :

1. Dale, E. (1946). Effective learning. From Chapter 1 in audio-visual methods in teaching. New York: Dryden Press (Holt, Rinehart, and Winston). Retrieved April, 3, 2006.

2. Dale, E. (1969). Audiovisual methods in teaching (3rd ed.). New York: Dryden Press.

3. Subramony, D. P., Molenda, M., Betrus, A. K., & Thalheimer, W. (2014). Timeline of the Mythical Retention Chart and Corrupted Dale's Cone. Educational Technology, 31-34.

4. Treichler, D. G. (1967). Are you missing the boat in training aids. Film and AV Communication, 1, 14-16.

5. Bauman, A. R. (1978). Training of trainers (Vol. 1). National Institute on Drug Abuse, Division of Research Development, Manpower and Training Branch.

6. Letrud, K., & Hernes, S. (2016). The diffusion of the learning pyramid myths in academia: an exploratory study. Journal of Curriculum Studies, 48(3), 291-302.

7. Lee, S. J., & Reeves, T. C. (2007). Edgar Dale: A significant contributor to the field of educational technology. Educational Technology, 47(6), 56.

Références :

1. McCabe, D. P., & Castel, A. D. (2008). Seeing is believing: The effect of brain images on judgments of scientific reasoning. Cognition, 107(1), 343-352.

2. Weisberg, D. S., Keil, F. C., Goodstein, J., Rawson, E., & Gray, J. R. (2008). The seductive allure of neuroscience explanations. Journal of cognitive neuroscience, 20(3), 470-477.

3. Gentaz, É. (2022). Éditorial - Un nouveau neuromythe ? Les apports des neurosciences à l'enseignement. A.N.A.E., 179,445-447.

4. Gentaz, É. (2022). Les neurosciences à l'école: leur véritable apport. Odile Jacob. 

Références :

1. Gardner, H. E. (2011). Frames of mind: The theory of multiple intelligences. Hachette Uk.

2. Willingham, D. T. (2004). Reframing the mind. Education Next, 4(3), 19-24. 

3. Spearman, C. (1961). " General Intelligence" Objectively Determined and Measured.

4. Guilford, J. P. (1967). The nature of human intelligence.

5. Cattell, R. B. (1971). Abilities: Their structure, growth, and action.

6. Carroll, J. B. (1993). Human cognitive abilities: A survey of factor-analytic studies (No. 1). Cambridge University Press.

7. Larivée, S., & Senéchal, C. (2012). Que dit la science à propos des intelligences multiples?. Revue québécoise de psychologie, 33(1), 23-45.

8. Gardner, H. (1997). Les formes de l’intelligence. Paris : Odile Jacob.

9. Kornhaber, M. L., & Gardner, H. (1993). Réflexion critique et formes multiples de l’intelligence. Apprendre à penser, penser pour apprendre, 185-218.

10. Gardner, H. (2016). 35 Multiple Intelligences: Prelude, Theory, and Aftermath. Scientists making a difference: One hundred eminent behavioral and brain scientists talk about their most important contributions, 167.Gardner, H. (2020). “Neuromyths”: A critical consideration. Mind, Brain, and Education, 14(1), 2-4

11. Gardner, H. (2020). “Neuromyths”: A critical consideration. Mind, Brain, and Education, 14(1), 2-4.

12. Rousseau, L. (2021). “Neuromyths” and Multiple Intelligences (MI) Theory: A Comment on Gardner, 2020. Frontiers in Psychology, 12.

Références :

1. Howard-Jones, P. A. (2014). Neuroscience and education: myths and messages. Nature Reviews Neuroscience, 15(12), 817-824.

2. Meyers, S. M., R. Tam, J. S. Lee, S. H. Kolind, I. M. Vavasour, E. Mackie, et al. 2016. Does hydration status affect MRI measures of brain volume or water content? J. Magn. Reson. Imaging 44:296–304.  https://doi.org/10.1002/jmri.25168.

3. Watson, Phillip, et al. "Effect of exercise and heat-induced hypohydration on brain volume." (2010).

4. Kempton, M. J., Ettinger, U., Foster, R., Williams, S. C., Calvert, G. A., Hampshire, A., ... & Smith, M. S. (2011). Dehydration affects brain structure and function in healthy adolescents. Human brain mapping, 32(1), 71-79.

5. Kempton, Matthew J., et al. "Effects of acute dehydration on brain morphology in healthy humans." Human brain mapping 30.1 (2009): 291-298.

6. Wittbrodt, M. T., Sawka, M. N., Mizelle, J. C., Wheaton, L. A., & Millard‐Stafford, M. L. (2018). Exercise‐heat stress with and without water replacement alters brain structures and impairs visuomotor performance. Physiological reports, 6(16), e13805.

Références :

1. Rasch, B., & Born, J. (2013). About sleep's role in memory. Physiological reviews.

2. Peigneux P, Laureys S, Delbeuck X, Maquet P. Sleeping brain, learning brain. The role of sleep for memory systems. Neuroreport. 2001;12(18):A111-124

3. Ngo, H. V. V., Martinetz, T., Born, J., & Mölle, M. (2013). Auditory closed-loop stimulation of the sleep slow oscillation enhances memory. Neuron, 78(3), 545-553.

4. Rudoy, J. D., Voss, J. L., Westerberg, C. E., & Paller, K. A. (2009). Strengthening individual memories by reactivating them during sleep. Science, 326(5956), 1079-1079.

5. Züst, M. A., Ruch, S., Wiest, R., & Henke, K. (2019). Implicit vocabulary learning during sleep is bound to slow-wave peaks. Current biology, 29(4), 541-553.

6. Antony, J. W., Gobel, E. W., O'hare, J. K., Reber, P. J., & Paller, K. A. (2012). Cued memory reactivation during sleep influences skill learning. Nature neuroscience, 15(8), 1114-1116.

7. Strauss, M., Griffon, L., Van Beers, P., Elbaz, M., Bouziotis, J., Sauvet, F., ... & Peigneux, P. (2022). Order matters: sleep spindles contribute to memory consolidation only when followed by rapid-eye-movement sleep. Sleep, 45(4), zsac022.

Références :

1. Burnette, J. L., Billingsley, J., Banks, G. C., Knouse, L. E., Hoyt, C. L., Pollack, J. M., & Simon, S. (2022). A systematic review and meta-analysis of growth mindset interventions: For whom, how, and why might such interventions work? Psychological Bulletin, 149, 174–205.

2. Burnette, J. L., Russell, M. V., Hoyt, C. L., Orvidas, K., & Widman, L. (2018). An online growth mindset intervention in a sample of rural adolescent girls. British Journal of Educational Psychology, 88(3), 428–445

3. Dweck, C. S. (2000). Self-theories: Their role in motivation, personality, and development. Psychology press.

4. Gazmuri, C. (2025). Can growth mindset interventions improve academic achievement? A structured review of the existing evidence. Review of Education, 13 (2), e70066.

5. Gorard, S. (2024). Judging the relative trustworthiness of research results: How to do it and why it matters. Review of Education, 12(1), e3448. 

6. Howell, D. C. (2024). Méthodes statistiques en sciences humaines. De Boeck Supérieur.

7. Macnamara, B. N., & Burgoyne, A. P. (2022). Do growth mindset interventions impact students' academic achievement? A systematic review and meta-analysis with recommendations for best practices. Psychological Bulletin, 149(3-4), 133–173. 

8. Masson, S. (2020). Activer ses neurones: pour mieux apprendre et enseigner. Odile Jacob.

9. 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.

10. Sisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. L., & Macnamara, B. N. (2018). To what extent and under which circumstances are growth mind-setsimportant to academic achievement? Two meta-analyses. Psychological Science, 29(4), 549–571.