lifelong learning; decision-making; approach-avoidance motivation; Expected Value of Control (EVC)
Résumé :
[en] Background: Individual differences in commitment to lifelong learning, a process aimed at seizing opportunities for self-development, have not been extensively studied. Objective: Our aim is to provide a comprehensive understanding of the decision-making mechanisms involved in pursuing learning for self-development. Method: We conducted a literature review on the taxing nature of cognitive exertion and its impact on the inclination to engage in cognitively demanding tasks for learning, as well as individual differences in sensitivity to aversive or rewarding outcomes inherent in the learning process. Results: Our findings indicate that the Expected Value of Control (EVC) theory can elucidate the former, while research on approach-avoidance motivation can shed light on the latter. Conclusion: We propose and develop an integrated framework that incorporates both lines of research. This framework holds relevance for neuropsychology, experimental psychology, and education psychology, offering theoretical guidance for tailoring learning experiences to enhance engagement and commitment to self-development.
Disciplines :
Neurosciences & comportement
Auteur, co-auteur :
MENDES, Angelica ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS) > Cognitive Science and Assessment
GREIFF, Samuel ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences > Department of Behavioural and Cognitive Sciences > Team Samuel GREIFF
BOBROWICZ, Katarzyna ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS) > Cognitive Science and Assessment
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Approaching lifelong learning: An integrated framework for explaining decision-making processes in personal and professional development
Hassabis, D., Kumaran, D., Summerfield, C., Botvinick, M., Neuroscience-Inspired Artificial Intelligence. Neuron 95 (2017), 245–258, 10.1016/j.neuron.2017.06.011.
Parisi, G.I., Kemker, R., Part, J.L., Kanan, C., Wermter, S., Continual lifelong learning with neural networks: A review. Neural Netw. 113 (2019), 54–71, 10.1016/j.neunet.2019.01.012.
De Houwer, J., Barnes-Holmes, D., Moors, A., What is learning? On the nature and merits of a functional definition of learning. Psychon. Bull. Rev. 20 (2013), 631–642, 10.3758/s13423-013-0386-3.
Agrawal, M., Mattar, M.G., Cohen, J.D., Daw, N.D., The Temporal Dynamics of Opportunity Costs: A Normative Account of Cognitive Fatigue and Boredom. J. Educ. Psychol. Hum. Percept. Perform., 48(6), 2022, 665.
Shenhav, A., Botvinick, M.M., Cohen, J.D., The Expected Value of Control: An Integrative Theory of Anterior Cingulate Cortex Function. Neuron 79 (2013), 217–240, 10.1016/j.neuron.2013.07.007.
Shenhav, A., Musslick, S., Lieder, F., Kool, W., Griffiths, T.L., Cohen, J.D., Botvinick, M.M., Toward a Rational and Mechanistic Account of Mental Effort. Annu. Rev. Neurosci. 40 (2017), 99–124, 10.1146/annurev-neuro-072116-031526.
Leng, X., Yee, D., Ritz, H., Shenhav, A., Dissociable influences of reward and punishment on adaptive cognitive control. PLOS Comput. Biol, 17, 2021, e1009737, 10.1371/journal.pcbi.1009737.
Lieder, F., Shenhav, A., Musslick, S., Griffiths, T.L., Rational metareasoning and the plasticity of cognitive control. PLOS Comput. Biol., 14, 2018, e1006043, 10.1371/journal.pcbi.1006043.
Masís, J.A., Musslick, S., Cohen, J., The Value of Learning and Cognitive Control Allocation. Proc. Annu. Meet. Cogn. Sci. Soc., 2021 https://escholarship.org/uc/item/7w0223v0 accessed April 3, 2024.
Musslick, S., Cohen, J.D., Shenhav, A., Decomposing Individual Differences in Cognitive Control: A Model-Based Approach. Cogsci., 2019, 2427–2433.
Musslick, S., Botvinick, M.M., Shenhav, A., Cohen, J.D., A computational model of control allocation based on the Expected Value of Control. Reinf. Learn. Decis. Mak. Conf., 2015.
Musslick, S., Bizyaeva, A., Agaron, S., Leonard, N., Cohen, J.D., Stability-Flexibility Dilemma in Cognitive Control: A Dynamical System Perspective. Proc. 41st Annu. Meet. Cogn. Sci. Soc, 2019 https://par.nsf.gov/biblio/10125021-stability-flexibility-dilemma-cognitive-control-dynamical-system-perspective accessed April 3, 2024.
Musslick, S., Cohen, J.D., Rationalizing constraints on the capacity for cognitive control. Trends Cogn. Sci. 25 (2021), 757–775, 10.1016/j.tics.2021.06.001.
Silvestrini, N., Musslick, S., Berry, A.S., Vassena, E., An integrative effort: Bridging motivational intensity theory and recent neurocomputational and neuronal models of effort and control allocation. Psychol. Rev. 130 (2023), 1081–1103, 10.1037/rev0000372.
Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., Wager, T.D., The Unity and Diversity of Executive Functions and Their Contributions to Complex “Frontal Lobe” Tasks: A Latent Variable Analysis. Cognit. Psychol. 41 (2000), 49–100, 10.1006/cogp.1999.0734.
Cohen, J.D., Dunbar, K., McClelland, J.L., On the control of automatic processes: A parallel distributed processing account of the Stroop effect. Psychol. Rev. 97 (1990), 332–361, 10.1037/0033-295X.97.3.332.
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., Murayama, K., Pessoa, L., Samanez-Larkin, G.R., Somerville, L.H., for the MOMCAI group, Mechanisms of motivation–cognition interaction: challenges and opportunities. Cogn. Affect. Behav. Neurosci. 14 (2014), 443–472, 10.3758/s13415-014-0300-0.
Kool, W., McGuire, J.T., Rosen, Z.B., Botvinick, M.M., Decision making and the avoidance of cognitive demand. J. Exp. Psychol. Gen. 139 (2010), 665–682, 10.1037/a0020198.
Kool, W., Botvinick, M., The intrinsic cost of cognitive control. Behav. Brain Sci. 36 (2013), 697–698, 10.1017/S0140525X1300109X.
Kool, W., Botvinick, M., Mental labour. Nat. Hum. Behav 2 (2018), 899–908, 10.1038/s41562-018-0401-9.
Westbrook, A., Braver, T.S., Cognitive effort: A neuroeconomic approach. Cogn. Affect. Behav. Neurosci. 15 (2015), 395–415, 10.3758/s13415-015-0334-y.
Dunn, T.L., Lutes, D.J.C., Risko, E.F., Metacognitive evaluation in the avoidance of demand. J. Exp. Psychol. Hum. Percept. Perform. 42 (2016), 1372–1387, 10.1037/xhp0000236.
Chong, T.T.J., Apps, M., Giehl, K., Sillence, A., Grima, L.L., Husain, M., Neurocomputational mechanisms underlying subjective valuation of effort costs. PLoS. Biol., 15, 2017, e1002598, 10.1371/journal.pbio.1002598.
Westbrook, A., Kester, D., Braver, T.S., What Is the Subjective Cost of Cognitive Effort? Load, Trait, and Aging Effects Revealed by Economic Preference. PLoS. One, 8, 2013, e68210, 10.1371/journal.pone.0068210.
Huber, S.E., Cortez, R., Kiili, K., Lindstedt, A., Ninaus, M., Game elements enhance engagement and mitigate attrition in online learning tasks. Comput. Hum. Behav., 149, 2023, 107948, 10.1016/j.chb.2023.107948.
Spitzer, M.W.H., Kiesel, A., Dignath, D., Performance errors influence voluntary task choices. J. Exp. Psychol. Hum. Percept. Perform. 48 (2022), 665–688, 10.1037/xhp0000991.
Ryan, R.M., Deci, E.L., Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol., 55, 2000, 68.
Murayama, K., A reward-learning framework of knowledge acquisition: An integrated account of curiosity, interest, and intrinsic–extrinsic rewards. Psychol. Rev. 129 (2022), 175–198, 10.1037/rev0000349.
Kang, M.J., Hsu, M., Krajbich, I.M., Loewenstein, G., McClure, S.M., Wang, J.T., Camerer, C.F., The Wick in the Candle of Learning: Epistemic Curiosity Activates Reward Circuitry and Enhances Memory. Psychol. Sci. 20 (2009), 963–973, 10.1111/j.1467-9280.2009.02402.x.
Düzel, E., Bunzeck, N., Guitart-Masip, M., Düzel, S., NOvelty-related Motivation of Anticipation and exploration by Dopamine (NOMAD): Implications for healthy aging. Neurosci. Biobehav. Rev. 34 (2010), 660–669, 10.1016/j.neubiorev.2009.08.006.
Law, E., Yin, M., Goh, J., Chen, K., Terry, M.A., Gajos, K.Z., Curiosity Killed the Cat, but Makes Crowdwork Better. Proc. 2016 CHI Conf. Hum. Factors Comput. Syst, 2016, Association for Computing Machinery, New York, NY, USA, 4098–4110, 10.1145/2858036.2858144.
Loewenstein, G., The psychology of curiosity: A review and reinterpretation. Psychol. Bull. 116 (1994), 75–98, 10.1037/0033-2909.116.1.75.
Tang, H., Houthooft, R., Foote, D., Stooke, A., Xi Chen, O., Duan, Y., Schulman, J., DeTurck, F., Abbeel, #Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning. Adv. Neural Inf. Process. Syst., 2017, Curran Associates, Inc. https://proceedings.neurips.cc/paper_files/paper/2017/hash/3a20f62a0af1aa152670bab3c602feed-Abstract.html accessed April 19, 2024.
Dubey, R., Griffiths, T.L., Reconciling novelty and complexity through a rational analysis of curiosity. Psychol. Rev. 127 (2020), 455–476, 10.1037/rev0000175.
Gottlieb, J., Oudeyer, P.Y., Towards a neuroscience of active sampling and curiosity. Nat. Rev. Neurosci. 19 (2018), 758–770, 10.1038/s41583-018-0078-0.
FitzGibbon, L., Komiya, A., Murayama, K., The Lure of Counterfactual Curiosity: People Incur a Cost to Experience Regret. Psychol. Sci. 32 (2021), 241–255, 10.1177/0956797620963615.
Behrens, T.E.J., Woolrich, M.W., Walton, M.E., Rushworth, M.F.S., Learning the value of information in an uncertain world. Nat. Neurosci. 10 (2007), 1214–1221, 10.1038/nn1954.
Frömer, R., Lin, H., Dean Wolf, C.K., Inzlicht, M., Shenhav, A., Expectations of reward and efficacy guide cognitive control allocation. Nat. Commun., 12, 2021, 1030, 10.1038/s41467-021-21315-z.
Fricke, K., Vogel, S., How interindividual differences shape approach-avoidance behavior: Relating self-report and diagnostic measures of interindividual differences to behavioral measurements of approach and avoidance. Neurosci. Biobehav. Rev. 111 (2020), 30–56, 10.1016/j.neubiorev.2020.01.008.
Cacioppo, J.T., Petty, R.E., The need for cognition. J. Pers. Soc. Psychol. 42 (1982), 116–131, 10.1037/0022-3514.42.1.116.
Cloninger, C.R., Svrakic, D.M., Przybeck, T.R., A Psychobiological Model of Temperament and Character. Arch. Gen. Psychiatry 50 (1993), 975–990, 10.1001/archpsyc.1993.01820240059008.
Freeston, M.H., Rhéaume, J., Letarte, H., Dugas, M.J., Ladouceur, R., Why do people worry?. Personal. Individ. Differ. 17 (1994), 791–802, 10.1016/0191-8869(94)90048-5.
Goldberg, L.R., The structure of phenotypic personality traits. Am. Psychol. 48 (1993), 26–34, 10.1037/0003-066X.48.1.26.
McCrae, R.R., John, O.P., An Introduction to the Five-Factor Model and Its Applications. J. Pers. 60 (1992), 175–215, 10.1111/j.1467-6494.1992.tb00970.x.
Atkinson, J.W., Feather, N.T., Others, A theory of Achievement Motivation. 1966, Wiley, New York.
Lewin, K., A dynamic theory of personality: Selected papers. J. Nerv. Ment. Dis. 84:5 (1936), 612–613.
Carver, C.S., White, T.L., Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS Scales. J. Pers. Soc. Psychol. 67 (1994), 319–333, 10.1037/0022-3514.67.2.319.
Gray, J.A., McNaughton, N., The neuropsychology of anxiety: Reprise. Neb. Symp. Motiv. 1995 Perspect. Anxiety Panic Fear, 1996, University of Nebraska Press, Lincoln, NE, US, 61–134.
Corr, P.J., Reinforcement sensitivity theory and personality. Neurosci. Biobehav. Rev. 28 (2004), 317–332, 10.1016/j.neubiorev.2004.01.005.
Corr, P.J., Approach and Avoidance Behaviour: Multiple Systems and their Interactions. Emot. Rev. 5 (2013), 285–290, 10.1177/1754073913477507.
Corr, P.J., Reinforcement Sensitivity Theory of Personality Questionnaires: Structural survey with recommendations. Personal. Individ. Differ. 89 (2016), 60–64, 10.1016/j.paid.2015.09.045.
Ratcliff, R., Smith, P.L., Brown, S.D., McKoon, G., Diffusion Decision Model: Current Issues and History. Trends Cogn. Sci. 20 (2016), 260–281, 10.1016/j.tics.2016.01.007.
Ratcliff, R., McKoon, G., The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks. Neural Comput. 20 (2008), 873–922, 10.1162/neco.2008.12-06-420.
Aupperle, R.L., Sullivan, S., Melrose, A.J., Paulus, M.P., Stein, M.B., A reverse translational approach to quantify approach-avoidance conflict in humans. Behav. Brain Res. 225 (2011), 455–463, 10.1016/j.bbr.2011.08.003.
Schlund, M.W., Brewer, A.T., Magee, S.K., Richman, D.M., Solomon, S., Ludlum, M., Dymond, S., The tipping point: Value differences and parallel dorsal–ventral frontal circuits gating human approach–avoidance behavior. Neuroimage 136 (2016), 94–105, 10.1016/j.neuroimage.2016.04.070.
Talmi, D., Dayan, P., Kiebel, S.J., Frith, C.D., Dolan, R.J., How Humans Integrate the Prospects of Pain and Reward during Choice. J. Neurosci. 29 (2009), 14617–14626, 10.1523/JNEUROSCI.2026-09.2009.
Yee, D.M., Leng, X., Shenhav, A., Braver, T.S., Aversive motivation and cognitive control. Neurosci. Biobehav. Rev., 133, 2022, 104493, 10.1016/j.neubiorev.2021.12.016.
R.F. Baumeister, E. Bratslavsky, M. Muraven, D.M. Tice, Ego Depletion: Is the Active Self a Limited Resource?, (2018).
Baumeister, R.F., Muraven, M., Tice, D.M., Ego Depletion: A Resource Model of Volition, Self-Regulation, and Controlled Processing. Soc. Cogn. 18 (2000), 130–150, 10.1521/soco.2000.18.2.130.
Gailliot, M.T., Baumeister, R.F., DeWall, C.N., Maner, J.K., Plant, E.A., Tice, D.M., Brewer, L.E., Schmeichel, B.J., Self-control relies on glucose as a limited energy source: Willpower is more than a metaphor. J. Pers. Soc. Psychol. 92 (2007), 325–336, 10.1037/0022-3514.92.2.325.
Carter, E.C., Kofler, L.M., Forster, D.E., McCullough, M.E., A series of meta-analytic tests of the depletion effect: Self-control does not seem to rely on a limited resource. J. Exp. Psychol. Gen. 144 (2015), 796–815, 10.1037/xge0000083.
B. Blain, G. Hollard, M. Pessiglione, Neural mechanisms underlying the impact of daylong cognitive work on economic decisions, Proc. Natl. Acad. Sci. 113 (2016) 6967–6972. https://doi.org/10.1073/pnas.1520527113.
Tanaka, M., Ishii, A., Watanabe, Y., Neural effects of mental fatigue caused by continuous attention load: A magnetoencephalography study. Brain Res. 1561 (2014), 60–66, 10.1016/j.brainres.2014.03.009.
Thorndike, E.L., The Law of Effect. Am. J. Psychol. 39 (1927), 212–222, 10.2307/1415413.
Dixon, M.L., Christoff, K., The Decision to Engage Cognitive Control Is Driven by Expected Reward-Value: Neural and Behavioral Evidence. PLoS. One, 7, 2012, e51637, 10.1371/journal.pone.0051637.
Dunn, T.J., Kennedy, M., Technology Enhanced Learning in higher education; motivations, engagement and academic achievement. Comput. Educ. 137 (2019), 104–113, 10.1016/j.compedu.2019.04.004.
Shenhav, A., Straccia, M.A., Cohen, J.D., Botvinick, M.M., Anterior cingulate engagement in a foraging context reflects choice difficulty, not foraging value. Nat. Neurosci. 17 (2014), 1249–1254, 10.1038/nn.3771.
Spielberg, J.M., Miller, G.A., Warren, S.L., Engels, A.S., Crocker, L.D., Banich, M.T., Sutton, B.P., Heller, W., A Brain Network Instantiating Approach and Avoidance Motivation. Psychophysiology. 49 (2012), 1200–1214, 10.1111/j.1469-8986.2012.01443.x.
Kawai, R., Markman, T., Poddar, R., Ko, R., Fantana, A.L., Dhawale, A.K., Kampff, A.R., Ölveczky, B.P., Motor Cortex Is Required for Learning but Not for Executing a Motor Skill. Neuron 86 (2015), 800–812, 10.1016/j.neuron.2015.03.024.
Arias-Carrión, O., Stamelou, M., Murillo-Rodríguez, E., Menéndez-González, M., Pöppel, E., Dopaminergic reward system: a short integrative review. Int. Arch. Med, 3, 2010, 24, 10.1186/1755-7682-3-24.
Floresco, S.B., Magyar, O., Mesocortical dopamine modulation of executive functions: beyond working memory. Psychopharmacology (Berl.) 188 (2006), 567–585, 10.1007/s00213-006-0404-5.
Crockett, M., Cools, R., Serotonin and aversive processing in affective and social decision-making. Curr. Opin. Behav. Sci. 5 (2015), 64–70, 10.1016/j.cobeha.2015.08.005.
Geurts, D.E.M., Huys, Q.J.M., den Ouden, H.E.M., Cools, R., Serotonin and Aversive Pavlovian Control of Instrumental Behavior in Humans. J. Neurosci. 33 (2013), 18932–18939, 10.1523/JNEUROSCI.2749-13.2013.
Kirlic, N., Young, J., Aupperle, R.L., Animal to human translational paradigms relevant for approach avoidance conflict decision making. Behav. Res. Ther. 96 (2017), 14–29, 10.1016/j.brat.2017.04.010.
Hartikainen, K.M., Emotion-Attention Interaction in the Right Hemisphere. Brain Sci., 11, 2021, 1006, 10.3390/brainsci11081006.
Pigott, T.A., Gender Differences in the Epidemiology and Treatment of Anxiety Disorders. J. Clin. Psychiatry, 1999.
Bullimore, M.A., Gilmartin, B., The accommodative response, refractive error and mental effort: 1. The sympathetic nervous system. Doc. Ophthalmol. 69 (1988), 385–397, 10.1007/BF00162751.
G.H. Gendolla, Wright, Richter R.A, M., Effort intensity: Some insights from the cardiovascular system. Oxf. Handb. Hum. Motiv., 2012, 420–438.
Silvestrini, N., Psychological and neural mechanisms associated with effort-related cardiovascular reactivity and cognitive control: An integrative approach. Int. J. Psychophysiol. 119 (2017), 11–18, 10.1016/j.ijpsycho.2016.12.009.
Van Der Wel, P., Van Steenbergen, H., Pupil dilation as an index of effort in cognitive control tasks: A review. Psychon. Bull. Rev. 25 (2018), 2005–2015, 10.3758/s13423-018-1432-y.
Bernacki, M.L., Greene, M.J., Lobczowski, N.G., A Systematic Review of Research on Personalized Learning: Personalized by Whom, to What, How, and for What Purpose(s)?. Educ. Psychol. Rev. 33 (2021), 1675–1715, 10.1007/s10648-021-09615-8.