research findings about human development

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• Published: 26 April 2024

The development of human causal learning and reasoning

• Mariel K. Goddu   ORCID: orcid.org/0000-0003-4969-7948 1 , 2 , 3 &
• Alison Gopnik 4 , 5  

Nature Reviews Psychology volume  3 ,  pages 319–339 ( 2024 ) Cite this article

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Causal understanding is a defining characteristic of human cognition. Like many animals, human children learn to control their bodily movements and act effectively in the environment. Like a smaller subset of animals, children intervene: they learn to change the environment in targeted ways. Unlike other animals, children grow into adults with the causal reasoning skills to develop abstract theories, invent sophisticated technologies and imagine alternate pasts, distant futures and fictional worlds. In this Review, we explore the development of human-unique causal learning and reasoning from evolutionary and ontogenetic perspectives. We frame our discussion using an ‘interventionist’ approach. First, we situate causal understanding in relation to cognitive abilities shared with non-human animals. We argue that human causal understanding is distinguished by its depersonalized (objective) and decontextualized (general) representations. Using this framework, we next review empirical findings on early human causal learning and reasoning and consider the naturalistic contexts that support its development. Then we explore connections to related abilities. We conclude with suggestions for ongoing collaboration between developmental, cross-cultural, computational, neural and evolutionary approaches to causal understanding.

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Prüfer, K. et al. The bonobo genome compared with the chimpanzee and human genomes. Nature 486 , 527–531 (2012).

PubMed   PubMed Central   Google Scholar  

Gopnik, A. & Wellman, H. M. Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory. Psychol. Bull. 138 , 1085–1108 (2012). This paper provides an introduction to the interventionist approach formalized in terms of causal Bayes nets.

Gopnik, A. & Schulz, L. (eds.) Causal Learning: Psychology, Philosophy and Computation (Oxford Univ. Press, 2007). This edited volume provides an interdisciplinary overview of the interventionist approach.

Pearl, J. Causality (Cambridge Univ. Press, 2009).

Penn, D. C. & Povinelli, D. J. Causal cognition in human and nonhuman animals: a comparative, critical review. Annu. Rev. Psychol. 58 , 97–118 (2007).

PubMed   Google Scholar  

Schölkopf, B. et al. Toward causal representation learning. Proc. IEEE 109 , 612–634 (2021).

Google Scholar  

Spirtes, P., Glymour, C. & Scheines, R. in Causation, Prediction, and Search Lecture Notes in Statistics Vol 81, 103–162 (Springer, 1993).

Gopnik, A. et al. A theory of causal learning in children: causal maps and Bayes nets. Psychol. Rev. 111 , 3–32 (2004). This seminal paper reviews the causal Bayes nets approach to causal reasoning and suggests that children construct mental models that help them understand and predict causal relations.

Pearl, J. & Mackenzie, D. The Book of Why: The New Science of Cause and Effect (Basic Books, 2018). This book provides a high-level overview of approaches to causal inference from theoretical computer science for a general audience.

Lombrozo, T. & Vasil, N. in Oxford Handbook of Causal Reasoning (ed. Waldmann, M.) 415–432 (Oxford Univ. Press, 2017).

Woodward, J. Making Things Happen: A Theory of Causal Explanation (Oxford Univ. Press, 2005). This book outlines the ‘interventionist’ approach to causation and causal explanation in philosophy.

Shanks, D. R. & Dickinson, A. Associative accounts of causality judgment. Psychol. Learn. Motiv. 21 , 229–261 (Elsevier, 1988).

Carey, S. The Origin of Concepts (Oxford Univ. Press, 2009).

Michotte, A. The Perception of Causality (Routledge, 2017).

Leslie, A. M. The perception of causality in infants. Perception 11 , 173–186 (1982). This canonical study shows that 4.5-month-old and 8-month-old infants are sensitive to spatiotemporal event configurations and contingencies that adults also construe as causal.

Leslie, A. M. Spatiotemporal continuity and the perception of causality in infants. Perception 13 , 287–305 (1984).

Danks, D. Unifying the Mind: Cognitive Representations as Graphical Models (MIT Press, 2014).

Godfrey‐Smith, P. in The Oxford Handbook of Causation (eds Beebee, H., Hitchcock, C. & Menzies, P.) 326–338 (Oxford Academic, 2009).

Gweon, H. & Schulz, L. 16-month-olds rationally infer causes of failed actions. Science 332 , 1524–1524 (2011).

Woodward, J. Causation with a Human Face: Normative Theory and Descriptive Psychology (Oxford Univ. Press, 2021). This book integrates philosophical and psychological literatures on causal reasoning to provide both normative and descriptive accounts of causal reasoning.

Rozenblit, L. & Keil, F. The misunderstood limits of folk science: an illusion of explanatory depth. Cogn. Sci . 26 , 521–562 (2002).

Ismael, J. How Physics Makes us Free (Oxford Univ. Press, 2016).

Woodward, J. in Causal Learning: Psychology, Philosophy, and Computation (eds Gopnik, A. & Schulz, L.) Oxford Series in Cognitive Development 19–36 (Oxford Academic, 2007).

Godfrey-Smith, P. Other Minds: The Octopus, the Sea, and the Deep Origins of Consciousness (Farrar, Straus and Giroux, 2016).

Körding, K. P. et al. Causal inference in multisensory perception. PLoS One 2 , e943 (2007).

Wei, K. & Körding, K. P. in Sensory Cue Integration (eds Trommershäuser, J., Kording, K. & Landy, M. S.) Computational Neuroscience Series 30–45 (Oxford Academic, 2011).

Haith, A. M. & Krakauer, J. W. in Progress in Motor Control: Neural, Computational and Dynamic Approaches (eds Richardson, M. J., Riley, M. A. & Shockley, K.) 1–21 (Springer, 2013).

Krakauer, J. W. & Mazzoni, P. Human sensorimotor learning: adaptation, skill, and beyond. Curr. Opin. Neurobiol. 21 , 636–644 (2011).

Adolph, K. E. An ecological approach to learning in (not and) development. Hum. Dev. 63 , 180–201 (2020).

Adolph, K. E., Hoch, J. E. & Ossmy, O. in Perception as Information Detection (eds Wagman, J. B. & Blau, J. J. C.) 222–236 (Routledge, 2019).

Riesen, A. H. The development of visual perception in man and chimpanzee. Science 106 , 107–108 (1947).

Spelke, E. S. What Babies Know: Core Knowledge and Composition Vol. 1 (Oxford Univ. Press, 2022).

Pearce, J. M. & Bouton, M. E. Theories of associative learning in animals. Annu. Rev. Psychol. 52 , 111–139 (2001).

Wasserman, E. A. & Miller, R. R. What’s elementary about associative learning? Annu. Rev. Psychol. 48 , 573–607 (1997).

Sutton, R. S. & Barto, A. G. Reinforcement learning: an introduction. Robotica 17 , 229–235 (1999).

Gershman, S. J., Markman, A. B. & Otto, A. R. Retrospective revaluation in sequential decision making: a tale of two systems. J. Exp. Psychol. Gen. 143 , 182–194 (2014).

Gershman, S. J. Reinforcement learning and causal models. In Oxford Handbook of Causal Reasoning (ed. Waldmann, M.) 295 (Oxford Univ. Press, 2017).

Taylor, A. H. et al. Of babies and birds: complex tool behaviours are not sufficient for the evolution of the ability to create a novel causal intervention. Proc. R. Soc. B 281 , 20140837 (2014). This study shows that complex tool use does not entail the ability to understand and create novel causal interventions: crows do not learn causal interventions from observing the effects of their own accidental behaviours.

Povinelli, D. J. & Penn, D. C. in Tool Use and Causal Cognition (eds McCormack, T., Hoerl, C. & Butterfill, S.) 69–88 (Oxford Univ. Press, 2011).

Povinelli, D. J. & Henley, T. More rope tricks reveal why more task variants will never lead to strong inferences about higher-order causal reasoning in chimpanzees. Anim. Behav. Cogn. 7 , 392–418 (2020).

Tomasello, M. & Call, J. Primate Cognition (Oxford Univ. Press, 1997).

Visalberghi, E. & Tomasello, M. Primate causal understanding in the physical and psychological domains. Behav. Process. 42 , 189–203 (1998).

Völter, C. J., Sentís, I. & Call, J. Great apes and children infer causal relations from patterns of variation and covariation. Cognition 155 , 30–43 (2016).

Tennie, C., Call, J. & Tomasello, M. Untrained chimpanzees ( Pan troglodytes schweinfurthii ) fail to imitate novel actions. Plos One 7 , e41548 (2012).

Whiten, A., Horner, V., Litchfield, C. A. & Marshall-Pescini, S. How do apes ape? Anim. Learn. Behav. 32 , 36–52 (2004).

Moore, R. Imitation and conventional communication. Biol. Phil. 28 , 481–500 (2013).

Meltzoff, A. N. & Marshall, P. J. Human infant imitation as a social survival circuit. Curr. Opin. Behav. Sci. 24 , 130–136 (2018).

Boesch, C. & Boesch, H. Optimisation of nut-cracking with natural hammers by wild chimpanzees. Behaviour 83 , 265–286 (1983).

Chappell, J. & Kacelnik, A. Tool selectivity in a non-primate, the New Caledonian crow ( Corvus moneduloides ). Anim. Cogn. 5 , 71–78 (2002).

Weir, A. A., Chappell, J. & Kacelnik, A. Shaping of hooks in New Caledonian crows. Science 297 , 981–981 (2002).

Wimpenny, J. H., Weir, A. A., Clayton, L., Rutz, C. & Kacelnik, A. Cognitive processes associated with sequential tool use in New Caledonian crows. PLoS One 4 , e6471 (2009).

Manrique, H. M., Gross, A. N.-M. & Call, J. Great apes select tools on the basis of their rigidity. J. Exp. Psychol. Anim. Behav. Process. 36 , 409–422 (2010).

Mulcahy, N. J., Call, J. & Dunbar, R. I. Gorillas ( Gorilla gorilla ) and orangutans ( Pongo pygmaeus ) encode relevant problem features in a tool-using task. J. Comp. Psychol. 119 , 23–32 (2005).

Sanz, C., Call, J. & Morgan, D. Design complexity in termite-fishing tools of chimpanzees ( Pan troglodytes ). Biol. Lett. 5 , 293–296 (2009).

Visalberghi, E. et al. Selection of effective stone tools by wild bearded capuchin monkeys. Curr. Biol. 19 , 213–217 (2009).

Seed, A., Hanus, D. & Call, J. in Tool Use and Causal Cognition (eds McCormack, T., Hoerl, C. & Butterfill, S.) 89–110 (Oxford Univ. Press, 2011).

Völter, C. J. & Call, J. in APA Handbook of Comparative Psychology: Perception, Learning, and Cognition (eds Call, J. et al.) 643–671 (American Psychological Association, 2017). This chapter provides a comprehensive overview of causal and inferential reasoning in non-human animals, highlighting (1) the difference between prediction versus causal knowledge and (2) the organization of non-human animals’ knowledge (stimulus- and/or context-specific versus general and structured).

Völter, C. J., Lambert, M. L. & Huber, L. Do nonhumans seek explanations? Anim. Behav. Cogn. 7 , 445–451 (2020).

Call, J. Inferences about the location of food in the great apes ( Pan paniscus , Pan troglodytes , Gorilla gorilla , and Pongo pygmaeus ). J. Comp. Psychol. 118 , 232–241 (2004).

Call, J. Apes know that hidden objects can affect the orientation of other objects. Cognition 105 , 1–25 (2007).

Hanus, D. & Call, J. Chimpanzees infer the location of a reward on the basis of the effect of its weight. Curr. Biol. 18 , R370–R372 (2008).

Hanus, D. & Call, J. Chimpanzee problem-solving: contrasting the use of causal and arbitrary cues. Anim. Cogn. 14 , 871–878 (2011).

Petit, O. et al. Inferences about food location in three cercopithecine species: an insight into the socioecological cognition of primates. Anim. Cogn. 18 , 821–830 (2015).

Heimbauer, L. A., Antworth, R. L. & Owren, M. J. Capuchin monkeys ( Cebus apella ) use positive, but not negative, auditory cues to infer food location. Anim. Cogn. 15 , 45–55 (2012).

Schloegl, C., Schmidt, J., Boeckle, M., Weiß, B. M. & Kotrschal, K. Grey parrots use inferential reasoning based on acoustic cues alone. Proc. R. Soc. B 279 , 4135–4142 (2012).

Schloegl, C., Waldmann, M. R. & Fischer, J. Understanding of and reasoning about object–object relationships in long-tailed macaques? Anim. Cogn. 16 , 493–507 (2013).

Schmitt, V., Pankau, B. & Fischer, J. Old world monkeys compare to apes in the primate cognition test battery. PLoS One 7 , e32024 (2012).

Völter, C. J. & Call, J. Great apes ( Pan paniscus , Pan troglodytes , Gorilla gorilla , Pongo abelii ) follow visual trails to locate hidden food. J. Comp. Psychol. 128 , 199–208 (2014).

Blaisdell, A. P., Sawa, K., Leising, K. J. & Waldmann, M. R. Causal reasoning in rats. Science 311 , 1020–1022 (2006).

Leising, K. J., Wong, J., Waldmann, M. R. & Blaisdell, A. P. The special status of actions in causal reasoning in rats. J. Exp. Psychol. Gen. 137 , 514–527 (2008).

Flavell, J. H. The Developmental Psychology Of Jean Piaget (Van Nostrand, 1963).

Piaget, J. The Construction of Reality in the Child (Routledge, 2013).

Henrich, J., Heine, S. J. & Norenzayan, A. Most people are not WEIRD. Nature 466 , 29–29 (2010).

Ayzenberg, V. & Behrmann, M. Development of visual object recognition. Nat. Rev. Psychol. 3 , 73–90 (2023).

Bronson, G. W. Changes in infants’ visual scanning across the 2- to 14-week age period. J. Exp. Child. Psychol. 49 , 101–125 (1990).

Aslin, R. Ν. in Eye Movements . Cognition and Visual Perception (eds Fisher, D. F., Monty, R. A. & Senders, J. W.) 31–51 (Routledge, 2017).

Miranda, S. B. Visual abilities and pattern preferences of premature infants and full-term neonates. J. Exp. Child. Psychol. 10 , 189–205 (1970).

Haith, M. M., Hazan, C. & Goodman, G. S. Expectation and anticipation of dynamic visual events by 3.5-month-old babies. Child Dev. 59 , 467–479 (1988).

Harris, P. & MacFarlane, A. The growth of the effective visual field from birth to seven weeks. J. Exp. Child. Psychol. 18 , 340–348 (1974).

Cohen, L. B. & Amsel, G. Precursors to infants’ perception of the causality of a simple event. Infant. Behav. Dev. 21 , 713–731 (1998).

Leslie, A. M. & Keeble, S. Do six-month-old infants perceive causality? Cognition 25 , 265–288 (1987).

Oakes, L. M. & Cohen, L. B. Infant perception of a causal event. Cogn. Dev. 5 , 193–207 (1990). This canonical study shows that 10-month-olds, but not 6-month-olds, discriminate between causal versus non-causal events.

Kotovsky, L. & Baillargeon, R. Calibration-based reasoning about collision events in 11-month-old infants. Cognition 51 , 107–129 (1994).

Kominsky, J. F. et al. Categories and constraints in causal perception. Psychol. Sci. 28 , 1649–1662 (2017).

Spelke, E. S., Breinlinger, K., Macomber, J. & Jacobson, K. Origins of knowledge. Psychol. Rev. 99 , 605 (1992).

Baillargeon, R. in Language, Brain, and Cognitive Development: Essays in Honor of Jacques Mehler (ed. Dupoux, E.) 341–361 (MIT Press, 2001).

Hespos, S. J. & Baillargeon, R. Infants’ knowledge about occlusion and containment events: a surprising discrepancy. Psychol. Sci. 12 , 141–147 (2001).

Spelke, E. S. Principles of object perception. Cogn. Sci. 14 , 29–56 (1990).

Sobel, D. M. & Kirkham, N. Z. Blickets and babies: the development of causal reasoning in toddlers and infants. Dev. Psychol. 42 , 1103–1115 (2006).

Sobel, D. M. & Kirkham, N. Z. Bayes nets and babies: infants’ developing statistical reasoning abilities and their representation of causal knowledge. Dev. Sci. 10 , 298–306 (2007).

Bell, S. M. & Ainsworth, M. D. S. Infant crying and maternal responsiveness. Child Dev . 43 , 1171–1190 (1972).

Jordan, G. J., Arbeau, K., McFarland, D., Ireland, K. & Richardson, A. Elimination communication contributes to a reduction in unexplained infant crying. Med. Hypotheses 142 , 109811 (2020).

Nakayama, H. Emergence of amae crying in early infancy as a possible social communication tool between infants and mothers. Infant. Behav. Dev. 40 , 122–130 (2015).

Meltzoff, A. N. & Moore, M. K. in The Body and the Self (eds Bermúdez, J. L., Marcel, A. J. & Eilan, N.) 3–69 (MIT Press, 1995).

Rovee, C. K. & Rovee, D. T. Conjugate reinforcement of infant exploratory behavior. J. Exp. Child. Psychol. 8 , 33–39 (1969).

Hillman, D. & Bruner, J. S. Infant sucking in response to variations in schedules of feeding reinforcement. J. Exp. Child. Psychol. 13 , 240–247 (1972).

DeCasper, A. J. & Spence, M. J. Prenatal maternal speech influences newborns’ perception of speech sounds. Infant. Behav. Dev. 9 , 133–150 (1986).

Watson, J. S. & Ramey, C. T. Reactions to response-contingent stimulation in early infancy. Merrill-Palmer Q. Behav. Dev. 18 , 219–227 (1972).

Rovee-Collier, C. in Handbook of Infant Development 2nd edn (ed. Osofsky, J. D.) 98–148 (John Wiley & Sons, 1987).

Twitchell, T. E. The automatic grasping responses of infants. Neuropsychologia 3 , 247–259 (1965).

Wallace, P. S. & Whishaw, I. Q. Independent digit movements and precision grip patterns in 1–5-month-old human infants: hand-babbling, including vacuous then self-directed hand and digit movements, precedes targeted reaching. Neuropsychologia 41 , 1912–1918 (2003).

Von Hofsten, C. Mastering reaching and grasping: the development of manual skills in infancy. Adv. Psychol . 61 , 223–258 (1989).

Witherington, D. C. The development of prospective grasping control between 5 and 7 months: a longitudinal study. Infancy 7 , 143–161 (2005).

Needham, A., Barrett, T. & Peterman, K. A pick-me-up for infants’ exploratory skills: early simulated experiences reaching for objects using ‘sticky mittens’ enhances young infants’ object exploration skills. Infant. Behav. Dev. 25 , 279–295 (2002).

van den Berg, L. & Gredebäck, G. The sticky mittens paradigm: a critical appraisal of current results and explanations. Dev. Sci. 24 , e13036 (2021).

Keen, R. The development of problem solving in young children: a critical cognitive skill. Annu. Rev. Psychol. 62 , 1–21 (2011). This paper provides an overview of the developmental trajectory of ‘problem-solving’skills in young children, integrating findings from perception and motor development studies with cognitive problem-solving studies.

Claxton, L. J., McCarty, M. E. & Keen, R. Self-directed action affects planning in tool-use tasks with toddlers. Infant. Behav. Dev. 32 , 230–233 (2009).

McCarty, M. E., Clifton, R. K. & Collard, R. R. The beginnings of tool use by infants and toddlers. Infancy 2 , 233–256 (2001).

Gopnik, A. & Meltzoff, A. N. Semantic and cognitive development in 15- to 21-month-old children. J. Child. Lang. 11 , 495–513 (1984).

Gopnik, A. & Meltzoff, A. N. in The Development of Word Meaning: Progress in Cognitive Development Research (eds Kuczaj, S. A. & Barrett, M. D.) 199–223 (Springer, 1986).

Gopnik, A. & Meltzoff, A. N. Words, Thoughts, and Theories (Mit Press, 1997).

Tomasello, M. in Early Social Cognition: Understanding Others in the First Months of Life (ed. Rochat, P.) 301–314 (Lawrence Erlbaum Associates, 1999).

Tomasello, M. & Farrar, M. J. Joint attention and early language. Child Dev . 57 , 1454–1463 (1986).

Gopnik, A. Words and plans: early language and the development of intelligent action. J. Child. Lang. 9 , 303–318 (1982). This paper proposes that language acquisition tracks with conceptual developments in infants’ and toddlers’ abilities in goal-directed action and planning.

Meltzoff, A. N. Infant imitation and memory: nine-month-olds in immediate and deferred tests. Child. Dev. 59 , 217–225 (1988).

Meltzoff, A. N. Infant imitation after a 1-week delay: long-term memory for novel acts and multiple stimuli. Dev. Psychol. 24 , 470–476 (1988).

Gergely, G., Bekkering, H. & Király, I. Rational imitation in preverbal infants. Nature 415 , 755–755 (2002).

Meltzoff, A. N., Waismeyer, A. & Gopnik, A. Learning about causes from people: observational causal learning in 24-month-old infants. Dev. Psychol. 48 , 1215–1228 (2012). This study demonstrates that 2-year-old and 3-year-old children learn novel causal relations from observing other agents’ interventions (observational causal learning).

Waismeyer, A., Meltzoff, A. N. & Gopnik, A. Causal learning from probabilistic events in 24‐month‐olds: an action measure. Dev. Sci. 18 , 175–182 (2015).

Stahl, A. E. & Feigenson, L. Observing the unexpected enhances infants’ learning and exploration. Science 348 , 91–94 (2015). This study demonstrates that 11-month-old children pay special visual and exploratory attention to objects that appear to violate the laws of physics as the result of an agent’s intervention.

Perfors, A., Tenenbaum, J. B., Griffiths, T. L. & Xu, F. A tutorial introduction to Bayesian models of cognitive development. Cognition 120 , 302–321 (2011).

Gopnik, A. & Bonawitz, E. Bayesian models of child development. Wiley Interdiscip. Rev. Cognit. Sci. 6 , 75–86 (2015). This paper is a technical introduction and tutorial in the Bayesian framework.

Gopnik, A., Sobel, D. M., Schulz, L. E. & Glymour, C. Causal learning mechanisms in very young children: two-, three-, and four-year-olds infer causal relations from patterns of variation and covariation. Dev. Psychol. 37 , 620–629 (2001).

Schulz, L. E. & Bonawitz, E. B. Serious fun: preschoolers engage in more exploratory play when evidence is confounded. Dev. Psychol. 43 , 1045–1050 (2007).

Gopnik, A. & Sobel, D. M. Detecting blickets: how young children use information about novel causal powers in categorization and induction. Child. Dev. 71 , 1205–1222 (2000).

Schulz, L. E., Gopnik, A. & Glymour, C. Preschool children learn about causal structure from conditional interventions. Dev. Sci. 10 , 322–332 (2007).

Walker, C. M., Gopnik, A. & Ganea, P. A. Learning to learn from stories: children’s developing sensitivity to the causal structure of fictional worlds. Child. Dev. 86 , 310–318 (2015).

Schulz, L. E., Bonawitz, E. B. & Griffiths, T. L. Can being scared cause tummy aches? Naive theories, ambiguous evidence, and preschoolers’ causal inferences. Dev. Psychol. 43 , 1124–1139 (2007).

Kushnir, T. & Gopnik, A. Young children infer causal strength from probabilities and interventions. Psychol. Sci. 16 , 678–683 (2005).

Walker, C. M. & Gopnik, A. Toddlers infer higher-order relational principles in causal learning. Psychol. Sci. 25 , 161–169 (2014). This paper shows that 18–30-month-old infants can learn relational causal rules and generalize them to novel stimuli.

Sobel, D. M., Yoachim, C. M., Gopnik, A., Meltzoff, A. N. & Blumenthal, E. J. The blicket within: preschoolers’ inferences about insides and causes. J. Cogn. Dev. 8 , 159–182 (2007).

Schulz, L. E. & Sommerville, J. God does not play dice: causal determinism and preschoolers’ causal inferences. Child. Dev. 77 , 427–442 (2006).

Schulz, L. E. & Gopnik, A. Causal learning across domains. Dev. Psychol. 40 , 162–176 (2004).

Seiver, E., Gopnik, A. & Goodman, N. D. Did she jump because she was the big sister or because the trampoline was safe? Causal inference and the development of social attribution. Child. Dev. 84 , 443–454 (2013).

Vasilyeva, N., Gopnik, A. & Lombrozo, T. The development of structural thinking about social categories. Dev. Psychol. 54 , 1735–1744 (2018).

Kushnir, T., Xu, F. & Wellman, H. M. Young children use statistical sampling to infer the preferences of other people. Psychol. Sci. 21 , 1134–1140 (2010).

Kushnir, T. & Gopnik, A. Conditional probability versus spatial contiguity in causal learning: preschoolers use new contingency evidence to overcome prior spatial assumptions. Dev. Psychol. 43 , 186–196 (2007).

Kimura, K. & Gopnik, A. Rational higher‐order belief revision in young children. Child. Dev. 90 , 91–97 (2019).

Goddu, M. K. & Gopnik, A. Learning what to change: young children use “difference-making” to identify causally relevant variables. Dev. Psychol. 56 , 275–284 (2020).

Gopnik, A. et al. Changes in cognitive flexibility and hypothesis search across human life history from childhood to adolescence to adulthood. Proc. Natl Acad. Sci. USA 114 , 7892–7899 (2017).

Lucas, C. G., Bridgers, S., Griffiths, T. L. & Gopnik, A. When children are better (or at least more open-minded) learners than adults: developmental differences in learning the forms of causal relationships. Cognition 131 , 284–299 (2014). This paper shows that young children learn and generalize unusual causal relationships more readily than adults do.

Goddu, M. K., Lombrozo, T. & Gopnik, A. Transformations and transfer: preschool children understand abstract relations and reason analogically in a causal task. Child. Dev. 91 , 1898–1915 (2020).

Magid, R. W., Sheskin, M. & Schulz, L. E. Imagination and the generation of new ideas. Cogn. Dev. 34 , 99–110 (2015).

Liquin, E. G. & Gopnik, A. Children are more exploratory and learn more than adults in an approach–avoid task. Cognition 218 , 104940 (2022).

Erickson, J. E., Keil, F. C. & Lockhart, K. L. Sensing the coherence of biology in contrast to psychology: young children’s use of causal relations to distinguish two foundational domains. Child Dev. 81 , 390–409 (2010).

Keil, F. C. Concepts, Kinds, and Cognitive Development (MIT Press, 1992).

Carey, S. Conceptual Change in Childhood (MIT Press, 1987).

Gelman, S. A. The Essential Child: Origins of Essentialism in Everyday Thought (Oxford Univ. Press, 2003).

Ahl, R. E., DeAngelis, E. & Keil, F. C. “I know it’s complicated”: children detect relevant information about object complexity. J. Exp. Child. Psychol. 222 , 105465 (2022).

Chuey, A. et al. No guts, no glory: underestimating the benefits of providing children with mechanistic details. npj Sci. Learn. 6 , 30 (2021).

Keil, F. C. & Lockhart, K. L. Beyond cause: the development of clockwork cognition. Curr. Dir. Psychol. Sci. 30 , 167–173 (2021).

Chuey, A., Lockhart, K., Sheskin, M. & Keil, F. Children and adults selectively generalize mechanistic knowledge. Cognition 199 , 104231 (2020).

Lockhart, K. L., Chuey, A., Kerr, S. & Keil, F. C. The privileged status of knowing mechanistic information: an early epistemic bias. Child Dev. 90 , 1772–1788 (2019).

Kominsky, J. F., Zamm, A. P. & Keil, F. C. Knowing when help is needed: a developing sense of causal complexity. Cogn. Sci. 42 , 491–523 (2018).

Mills, C. M. & Keil, F. C. Knowing the limits of one’s understanding: the development of an awareness of an illusion of explanatory depth. J. Exp. Child Psychol. 87 , 1–32 (2004).

Goldwater, M. B. & Gentner, D. On the acquisition of abstract knowledge: structural alignment and explication in learning causal system categories. Cognition 137 , 137–153 (2015).

Rottman, B. M., Gentner, D. & Goldwater, M. B. Causal systems categories: differences in novice and expert categorization of causal phenomena. Cogn. Sci. 36 , 919–932 (2012).

Bonawitz, E. B. et al. Just do it? Investigating the gap between prediction and action in toddlers’ causal inferences. Cognition 115 , 104–117 (2010). This study demonstrates that the ability to infer causal relations from observations of correlational information without an agent’s involvement or the use of causal language develops at around the age of four years.

Herrmann, E., Call, J., Hernández-Lloreda, M. V., Hare, B. & Tomasello, M. Humans have evolved specialized skills of social cognition: the cultural intelligence hypothesis. Science 317 , 1360–1366 (2007).

Tomasello, M. Becoming Human: A Theory of Ontogeny (Harvard Univ. Press, 2019).

Henrich, J. The Secret of our Success (Princeton Univ. Press, 2015).

Hesslow, G. in Contemporary Science and Natural Explanation: Commonsense Conceptions of Causality (ed. Hilton, D. J.) 11–32 (New York Univ. Press, 1988).

Woodward, J. The problem of variable choice. Synthese 193 , 1047–1072 (2016).

Khalid, S., Khalil, T. & Nasreen, S. A survey of feature selection and feature extraction techniques in machine learning. In 2014 Science and Information Conf . 372–378 (IEEE, 1988).

Bonawitz, E., Denison, S., Griffiths, T. L. & Gopnik, A. Probabilistic models, learning algorithms, and response variability: sampling in cognitive development. Trends Cogn. Sci. 18 , 497–500 (2014).

Bonawitz, E., Denison, S., Gopnik, A. & Griffiths, T. L. Win–stay, lose–sample: a simple sequential algorithm for approximating Bayesian inference. Cogn. Psychol. 74 , 35–65 (2014).

Denison, S., Bonawitz, E., Gopnik, A. & Griffiths, T. L. Rational variability in children’s causal inferences: the sampling hypothesis. Cognition 126 , 285–300 (2013).

Samland, J., Josephs, M., Waldmann, M. R. & Rakoczy, H. The role of prescriptive norms and knowledge in children’s and adults’ causal selection. J. Exp. Psychol. Gen. 145 , 125–130 (2016).

Samland, J. & Waldmann, M. R. How prescriptive norms influence causal inferences. Cognition 156 , 164–176 (2016).

Phillips, J., Morris, A. & Cushman, F. How we know what not to think. Trends Cogn. Sci. 23 , 1026–1040 (2019).

Gureckis, T. M. & Markant, D. B. Self-directed learning: a cognitive and computational perspective. Perspect. Psychol. Sci. 7 , 464–481 (2012).

Saylor, M. & Ganea, P. Active Learning from Infancy to Childhood (Springer, 2018).

Goddu, M. K. & Gopnik, A. in The Cambridge Handbook of Cognitive Development (eds Houdé, O. & Borst, G.) 299–317 (Cambridge Univ. Press, 2022).

Gopnik, A. Scientific thinking in young children: theoretical advances, empirical research, and policy implications. Science 337 , 1623–1627 (2012).

Weisberg, D. S. & Sobel, D. M. Constructing Science: Connecting Causal Reasoning to Scientific Thinking in Young Children (MIT Press, 2022).

Xu, F. Towards a rational constructivist theory of cognitive development. Psychol. Rev. 126 , 841 (2019).

Xu, F. & Kushnir, T. Infants are rational constructivist learners. Curr. Dir. Psychol. Sci. 22 , 28–32 (2013).

Lapidow, E. & Bonawitz, E. What’s in the box? Preschoolers consider ambiguity, expected value, and information for future decisions in explore-exploit tasks. Open. Mind 7 , 855–878 (2023).

Kidd, C., Piantadosi, S. T. & Aslin, R. N. The Goldilocks effect: human infants allocate attention to visual sequences that are neither too simple nor too complex. PLoS One 7 , e36399 (2012).

Ruggeri, A., Swaboda, N., Sim, Z. L. & Gopnik, A. Shake it baby, but only when needed: preschoolers adapt their exploratory strategies to the information structure of the task. Cognition 193 , 104013 (2019).

Sim, Z. L. & Xu, F. Another look at looking time: surprise as rational statistical inference. Top. Cogn. Sci. 11 , 154–163 (2019).

Sim, Z. L. & Xu, F. Infants preferentially approach and explore the unexpected. Br. J. Dev. Psychol. 35 , 596–608 (2017).

Siegel, M. H., Magid, R. W., Pelz, M., Tenenbaum, J. B. & Schulz, L. E. Children’s exploratory play tracks the discriminability of hypotheses. Nat. Commun. 12 , 3598 (2021).

Schulz, E., Wu, C. M., Ruggeri, A. & Meder, B. Searching for rewards like a child means less generalization and more directed exploration. Psychol. Sci. 30 , 1561–1572 (2019).

Schulz, L. Infants explore the unexpected. Science 348 , 42–43 (2015).

Perez, J. & Feigenson, L. Violations of expectation trigger infants to search for explanations. Cognition 218 , 104942 (2022).

Cook, C., Goodman, N. D. & Schulz, L. E. Where science starts: spontaneous experiments in preschoolers’ exploratory play. Cognition 120 , 341–349 (2011). This study demonstrates that preschoolers spontaneously perform causal interventions that are relevant to disambiguating multiple possible causal structures in their free play.

Lapidow, E. & Walker, C. M. Learners’ causal intuitions explain behavior in control of variables tasks. Dev. Psychol. (in the press).

Lapidow, E. & Walker, C. M. Rethinking the “gap”: self‐directed learning in cognitive development and scientific reasoning. Wiley Interdiscip. Rev. Cogn. Sci. 13 , e1580 (2022). This theory paper provides a complementary viewpoint to ‘child-as-scientist’, or Bayesian ‘rational constructivist’, account, arguing that children seek to identify and generate evidence for causal relations that are robust across contexts (and thus will be reliable for causal intervention).

Lapidow, E. & Walker, C. M. Informative experimentation in intuitive science: children select and learn from their own causal interventions. Cognition 201 , 104315 (2020).

Moeller, A., Sodian, B. & Sobel, D. M. Developmental trajectories in diagnostic reasoning: understanding data are confounded develops independently of choosing informative interventions to resolve confounded data. Front. Psychol. 13 , 800226 (2022).

Fernbach, P. M., Macris, D. M. & Sobel, D. M. Which one made it go? The emergence of diagnostic reasoning in preschoolers. Cogn. Dev. 27 , 39–53 (2012).

Buchanan, D. W. & Sobel, D. M. Mechanism‐based causal reasoning in young children. Child. Dev. 82 , 2053–2066 (2011).

Sobel, D. M., Benton, D., Finiasz, Z., Taylor, Y. & Weisberg, D. S. The influence of children’s first action when learning causal structure from exploratory play. Cogn. Dev. 63 , 101194 (2022).

Lapidow, E. & Walker, C. M. The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning (Springer, 2020).

Klayman, J. Varieties of confirmation bias. Psychol. Learn. Motiv. 32 , 385–418 (1995).

Zimmerman, C. The development of scientific thinking skills in elementary and middle school. Dev. Rev. 27 , 172–223 (2007).

Rule, J. S., Tenenbaum, J. B. & Piantadosi, S. T. The child as hacker. Trends Cogn. Sci. 24 , 900–915 (2020).

Burghardt, G. M. The Genesis of Animal Play: Testing the Limits (MIT Press, 2005).

Chu, J. & Schulz, L. E. Play, curiosity, and cognition. Annu. Rev. Dev. Psychol. 2 , 317–343 (2020).

Schulz, L. The origins of inquiry: inductive inference and exploration in early childhood. Trends Cogn. Sci. 16 , 382–389 (2012).

Harris, P. L., Kavanaugh, R. D., Wellman, H. M. & Hickling, A. K. in Monographs of the Society for Research in Child Development https://doi.org/10.2307/1166074 (Society for Research in Child Development, 1993).

Weisberg, D. S. in The Oxford Handbook of the Development of Imagination (ed. Taylor, M.) 75–93 (Oxford Univ. Press, 2013).

Gopnik, A. & Walker, C. M. Considering counterfactuals: the relationship between causal learning and pretend play. Am. J. Play. 6 , 15–28 (2013).

Weisberg, D. S. & Gopnik, A. Pretense, counterfactuals, and Bayesian causal models: why what is not real really matters. Cogn. Sci. 37 , 1368–1381 (2013).

Root-Bernstein, M. M. in The Oxford Handbook of the Development of Imagination (ed. Taylor, M.) 417–437 (Oxford Univ. Press, 2013).

Buchsbaum, D., Bridgers, S., Skolnick Weisberg, D. & Gopnik, A. The power of possibility: causal learning, counterfactual reasoning, and pretend play. Phil. Trans. R. Soc. B 367 , 2202–2212 (2012).

Wente, A., Gopnik, A., Fernández Flecha, M., Garcia, T. & Buchsbaum, D. Causal learning, counterfactual reasoning and pretend play: a cross-cultural comparison of Peruvian, mixed-and low-socioeconomic status US children. Phil. Trans. R. Soc. B 377 , 20210345 (2022).

Buchsbaum, D., Gopnik, A., Griffiths, T. L. & Shafto, P. Children’s imitation of causal action sequences is influenced by statistical and pedagogical evidence. Cognition 120 , 331–340 (2011).

Csibra, G. & Gergely, G. ‘Obsessed with goals’: functions and mechanisms of teleological interpretation of actions in humans. Acta Psychol. 124 , 60–78 (2007).

Kelemen, D. The scope of teleological thinking in preschool children. Cognition 70 , 241–272 (1999).

Casler, K. & Kelemen, D. Young children’s rapid learning about artifacts. Dev. Sci. 8 , 472–480 (2005).

Casler, K. & Kelemen, D. Reasoning about artifacts at 24 months: the developing teleo-functional stance. Cognition 103 , 120–130 (2007).

Ruiz, A. M. & Santos, L. R. 6. in Tool Use in Animals: Cognition and Ecology 119–133 (Cambridge Univ. Press, 2013).

Walker, C. M., Rett, A. & Bonawitz, E. Design drives discovery in causal learning. Psychol. Sci. 31 , 129–138 (2020).

Butler, L. P. & Markman, E. M. Finding the cause: verbal framing helps children extract causal evidence embedded in a complex scene. J. Cogn. Dev. 13 , 38–66 (2012).

Callanan, M. A. et al. Exploration, explanation, and parent–child interaction in museums. Monogr. Soc. Res. Child. Dev. 85 , 7–137 (2020).

McHugh, S. R., Callanan, M., Jaeger, G., Legare, C. H. & Sobel, D. M. Explaining and exploring the dynamics of parent–child interactions and children’s causal reasoning at a children’s museum exhibit. Child Dev . https://doi.org/10.1111/cdev.14035 (2023).

Sobel, D. M., Letourneau, S. M., Legare, C. H. & Callanan, M. Relations between parent–child interaction and children’s engagement and learning at a museum exhibit about electric circuits. Dev. Sci. 24 , e13057 (2021).

Willard, A. K. et al. Explain this, explore that: a study of parent–child interaction in a children’s museum. Child Dev. 90 , e598–e617 (2019).

Daubert, E. N., Yu, Y., Grados, M., Shafto, P. & Bonawitz, E. Pedagogical questions promote causal learning in preschoolers. Sci. Rep. 10 , 20700 (2020).

Yu, Y., Landrum, A. R., Bonawitz, E. & Shafto, P. Questioning supports effective transmission of knowledge and increased exploratory learning in pre‐kindergarten children. Dev. Sci. 21 , e12696 (2018).

Walker, C. M. & Nyhout, A. in The Questioning Child: Insights From Psychology and Education (eds Butler, L. P., Ronfard, S. & Corriveau, K. H.) 252–280 (Cambridge Univ. Press, 2020).

Weisberg, D. S. & Hopkins, E. J. Preschoolers’ extension and export of information from realistic and fantastical stories. Infant. Child. Dev. 29 , e2182 (2020).

Tillman, K. A. & Walker, C. M. You can’t change the past: children’s recognition of the causal asymmetry between past and future events. Child. Dev. 93 , 1270–1283 (2022).

Rottman, B. M., Kominsky, J. F. & Keil, F. C. Children use temporal cues to learn causal directionality. Cogn. Sci. 38 , 489–513 (2014).

Tecwyn, E. C., Mazumder, P. & Buchsbaum, D. One- and two-year-olds grasp that causes must precede their effects. Dev. Psychol. 59 , 1519–1531 (2023).

Liquin, E. G. & Lombrozo, T. Explanation-seeking curiosity in childhood. Curr. Opin. Behav. Sci. 35 , 14–20 (2020).

Mills, C. M., Legare, C. H., Bills, M. & Mejias, C. Preschoolers use questions as a tool to acquire knowledge from different sources. J. Cogn. Dev. 11 , 533–560 (2010).

Ruggeri, A., Sim, Z. L. & Xu, F. “Why is Toma late to school again?” Preschoolers identify the most informative questions. Dev. Psychol. 53 , 1620–1632 (2017).

Ruggeri, A. & Lombrozo, T. Children adapt their questions to achieve efficient search. Cognition 143 , 203–216 (2015).

Legare, C. H. & Lombrozo, T. Selective effects of explanation on learning during early childhood. J. Exp. Child. Psychol. 126 , 198–212 (2014).

Legare, C. H. Exploring explanation: explaining inconsistent evidence informs exploratory, hypothesis‐testing behavior in young children. Child Dev. 83 , 173–185 (2012).

Walker, C. M., Lombrozo, T., Legare, C. H. & Gopnik, A. Explaining prompts children to privilege inductively rich properties. Cognition 133 , 343–357 (2014).

Vasil, N., Ruggeri, A. & Lombrozo, T. When and how children use explanations to guide generalizations. Cogn. Dev. 61 , 101144 (2022).

Walker, C. M., Bonawitz, E. & Lombrozo, T. Effects of explaining on children’s preference for simpler hypotheses. Psychon. Bull. Rev. 24 , 1538–1547 (2017).

Walker, C. M. & Lombrozo, T. Explaining the moral of the story. Cognition 167 , 266–281 (2017).

Walker, C. M., Lombrozo, T., Williams, J. J., Rafferty, A. N. & Gopnik, A. Explaining constrains causal learning in childhood. Child. Dev. 88 , 229–246 (2017).

Gopnik, A. Childhood as a solution to explore–exploit tensions. Phil. Trans. R. Soc. B 375 , 20190502 (2020).

Wente, A. O. et al. Causal learning across culture and socioeconomic status. Child. Dev. 90 , 859–875 (2019).

Carstensen, A. et al. Context shapes early diversity in abstract thought. Proc. Natl Acad. Sci. USA 116 , 13891–13896 (2019). This study provides evidence for developmentally early emerging cross-cultural differences in learning ‘individual’ versus ‘relational’ causal rules in children from individualist versus collectivist societies.

Ross, N., Medin, D., Coley, J. D. & Atran, S. Cultural and experiential differences in the development of folkbiological induction. Cogn. Dev. 18 , 25–47 (2003).

Inagaki, K. The effects of raising animals on children’s biological knowledge. Br. J. Dev. Psychol. 8 , 119–129 (1990).

Cole, M. & Bruner, J. S. Cultural differences and inferences about psychological processes. Am. Psychol. 26 , 867–876 (1971).

Rogoff, B. & Morelli, G. Perspectives on children’s development from cultural psychology. Am. Psychol. 44 , 343–348 (1989).

Rogoff, B. Adults and peers as agents of socialization: a highland Guatemalan profile. Ethos 9 , 18–36 (1981).

Shneidman, L., Gaskins, S. & Woodward, A. Child‐directed teaching and social learning at 18 months of age: evidence from Yucatec Mayan and US infants. Dev. Sci. 19 , 372–381 (2016).

Callanan, M., Solis, G., Castañeda, C. & Jipson, J. in The Questioning Child: Insights From Psychology and Education (eds Butler, L. P., Ronfard, S. & Corriveau, K. H.) 73–88 (Cambridge Univ. Press, 2020).

Gauvain, M., Munroe, R. L. & Beebe, H. Children’s questions in cross-cultural perspective: a four-culture study. J. Cross-Cult. Psychol. 44 , 1148–1165 (2013).

Adolph, K. E. & Hoch, J. E. Motor development: embodied, embedded, enculturated, and enabling. Annu. Rev. Psychol. 70 , 141–164 (2019).

Schleihauf, H., Herrmann, E., Fischer, J. & Engelmann, J. M. How children revise their beliefs in light of reasons. Child. Dev. 93 , 1072–1089 (2022).

Vasil, N. et al. Structural explanations lead young children and adults to rectify resource inequalities. J. Exp. Child Psychol. 242 , 105896 (2024).

Koskuba, K., Gerstenberg, T., Gordon, H., Lagnado, D. & Schlottmann, A. What’s fair? How children assign reward to members of teams with differing causal structures. Cognition 177 , 234–248 (2018).

Bowlby, J. The Bowlby–Ainsworth attachment theory. Behav. Brain Sci. 2 , 637–638 (1979).

Tottenham, N., Shapiro, M., Flannery, J., Caldera, C. & Sullivan, R. M. Parental presence switches avoidance to attraction learning in children. Nat. Hum. Behav. 3 , 1070–1077 (2019).

Frankenhuis, W. E. & Gopnik, A. Early adversity and the development of explore–exploit tradeoffs. Trends Cogn. Sci. 27 , 616–630 (2023).

Van IJzendoorn, M. H. & Kroonenberg, P. M. Cross-cultural patterns of attachment: a meta-analysis of the strange situation. Child Dev. 59 , 147–156 (1988).

Gopnik, A. Explanation as orgasm. Minds Mach. 8 , 101–118 (1998).

Gottlieb, S., Keltner, D. & Lombrozo, T. Awe as a scientific emotion. Cogn. Sci. 42 , 2081–2094 (2018).

Valdesolo, P., Shtulman, A. & Baron, A. S. Science is awe-some: the emotional antecedents of science learning. Emot. Rev. 9 , 215–221 (2017).

Keil, F. C. Wonder: Childhood and the Lifelong Love of Science (MIT Press, 2022).

Perez, J. & Feigenson, L. Stable individual differences in infants’ responses to violations of intuitive physics. Proc. Natl Acad. Sci. USA 118 , e2103805118 (2021).

Goddu, M. K., Sullivan, J. N. & Walker, C. M. Toddlers learn and flexibly apply multiple possibilities. Child. Dev. 92 , 2244–2251 (2021).

Cisek, P. Resynthesizing behavior through phylogenetic refinement. Atten. Percept. Psychophys. 81 , 2265–2287 (2019).

Pezzulo, G. & Cisek, P. Navigating the affordance landscape: feedback control as a process model of behavior and cognition. Trends Cogn. Sci. 20 , 414–424 (2016).

Cisek, P. Cortical mechanisms of action selection: the affordance competition hypothesis. Phil. Trans. R. Soc. B 362 , 1585–1599 (2007).

Tomasello, M. The Evolution of Agency: Behavioral Organization From Lizards to Humans (MIT Press, 2022).

Beck, S. R., Robinson, E. J., Carroll, D. J. & Apperly, I. A. Children’s thinking about counterfactuals and future hypotheticals as possibilities. Child. Dev. 77 , 413–426 (2006).

Robinson, E. J., Rowley, M. G., Beck, S. R., Carroll, D. J. & Apperly, I. A. Children’s sensitivity to their own relative ignorance: handling of possibilities under epistemic and physical uncertainty. Child. Dev. 77 , 1642–1655 (2006).

Leahy, B. P. & Carey, S. E. The acquisition of modal concepts. Trends Cogn. Sci. 24 , 65–78 (2020).

Mody, S. & Carey, S. The emergence of reasoning by the disjunctive syllogism in early childhood. Cognition 154 , 40–48 (2016).

Shtulman, A. & Carey, S. Improbable or impossible? How children reason about the possibility of extraordinary events. Child Dev. 78 , 1015–1032 (2007).

Redshaw, J. & Suddendorf, T. Children’s and apes’ preparatory responses to two mutually exclusive possibilities. Curr. Biol. 26 , 1758–1762 (2016).

Phillips, J. S. & Kratzer, A. Decomposing modal thought. Psychol. Rev. (in the press).

Vetter, B. Abilities and the epistemology of ordinary modality. Mind (in the press).

Kahneman, D. & Tversky, A. Variants of uncertainty. Cognition 11 , 143–157 (1982).

Rafetseder, E., Schwitalla, M. & Perner, J. Counterfactual reasoning: from childhood to adulthood. J. Exp. Child Psychol. 114 , 389–404 (2013).

Beck, S. R. & Riggs, K. J. Developing thoughts about what might have been. Child Dev. Perspect. 8 , 175–179 (2014).

Kominsky, J. F. et al. The trajectory of counterfactual simulation in development. Dev. Psychol. 57 , 253 (2021). This study uses a physical collision paradigm to demonstrate that the content of children’s counterfactual judgements changes over development.

Gerstenberg, T. What would have happened? Counterfactuals, hypotheticals and causal judgements. Phil. Trans. R. Soc. B 377 , 20210339 (2022).

Gerstenberg, T., Goodman, N. D., Lagnado, D. A. & Tenenbaum, J. B. A counterfactual simulation model of causal judgments for physical events. Psychol. Rev. 128 , 936 (2021).

Nyhout, A. & Ganea, P. A. The development of the counterfactual imagination. Child Dev. Perspect. 13 , 254–259 (2019).

Nyhout, A. & Ganea, P. A. Mature counterfactual reasoning in 4- and 5-year-olds. Cognition 183 , 57–66 (2019).

Moll, H., Meltzoff, A. N., Merzsch, K. & Tomasello, M. Taking versus confronting visual perspectives in preschool children. Dev. Psychol. 49 , 646–654 (2013).

Moll, H. & Tomasello, M. Three-year-olds understand appearance and reality — just not about the same object at the same time. Dev. Psychol. 48 , 1124–1132 (2012).

Moll, H. & Meltzoff, A. N. How does it look? Level 2 perspective‐taking at 36 months of age. Child. Dev. 82 , 661–673 (2011).

Gopnik, A., Slaughter, V. & Meltzoff, A. in Children’s Early Understanding of Mind: Origins and Development (eds Lewis, C. & Mitchell, P.) 157–181 (Routledge, 1994).

Gopnik, A. & Astington, J. W. Children’s understanding of representational change and its relation to the understanding of false belief and the appearance–reality distinction. Child Dev. 59 , 26–37 (1988).

Doherty, M. & Perner, J. Metalinguistic awareness and theory of mind: just two words for the same thing? Cogn. Dev. 13 , 279–305 (1998).

Wimmer, H. & Perner, J. Beliefs about beliefs: representation and constraining function of wrong beliefs in young children’s understanding of deception. Cognition 13 , 103–128 (1983).

Flavell, J. H., Speer, J. R., Green, F. L., August, D. L. & Whitehurst, G. J. in Monographs of the Society for Research in Child Development 1–65 (Society for Research in Child Development, 1981).

Wellman, H. M., Cross, D. & Watson, J. Meta‐analysis of theory‐of‐mind development: the truth about false belief. Child. Dev. 72 , 655–684 (2001).

Kelemen, D. & DiYanni, C. Intuitions about origins: purpose and intelligent design in children’s reasoning about nature. J. Cogn. Dev. 6 , 3–31 (2005).

Kelemen, D. Why are rocks pointy? Children’s preference for teleological explanations of th natural world. Dev. Psychol. 35 , 1440 (1999).

Vihvelin, K. Causes, Laws, and Free Will: Why Determinism Doesn’t Matter (Oxford Univ. Press, 2013).

Yiu, E., Kosoy, E. & Gopnik, A. Transmission versus truth, imitation versus innovation: what children can do that large language and language-and-vision models cannot (yet). Persp. Psychol. Sci . https://doi.org/10.1177/17456916231201401 (2023).

Kosoy, E. et al. Towards understanding how machines can learn causal overhypotheses. Preprint at arXiv https://doi.org/10.48550/arXiv.2206.08353 (2022).

Frank, M. C. Baby steps in evaluating the capacities of large language models. Nat. Rev. Psychol. 2 , 451–452 (2023).

Frank, M. C. Bridging the data gap between children and large language models. Trends Cogn. Sci . 27 , https://doi.org/10.1016/j.tics.2023.08.007 (2023).

Schmidhuber, J. A possibility for implementing curiosity and boredom in model-building neural controllers. In Proc. Int. Conf. on Simulation of Adaptive Behavior: From Animals to Animats 222–227 (MIT Press, 1991).

Volpi, N. C. & Polani, D. Goal-directed empowerment: combining intrinsic motivation and task-oriented behaviour. IEEE Trans. Cogn. Dev. Syst. 15 , 361–372 (2020).

Salge, C., Glackin, C. & Polani, D. in Guided Self-Organization: Inception . Emergence, Complexity and Computation Vol. 9 (ed. Prokopenko, M.) 67–114 (Springer, 2014).

Klyubin, A. S., Polani, D. & Nehaniv, C. L. Empowerment: a universal agent-centric measure of control. In 2005 IEEE Congr. on Evolutionary Computation 128–135 (IEEE, 2005).

Gopnik, A. Empowerment as causal learning, causal learning as empowerment: a bridge between Bayesian causal hypothesis testing and reinforcement learning. Preprint at https://philsci-archive.pitt.edu/id/eprint/23268 (2024).

Rovee-Collier, C. K., Sullivan, M. W., Enright, M., Lucas, D. & Fagen, J. W. Reactivation of infant memory. Science 208 , 1159–1161 (1980).

Kominsky, J. F., Li, Y. & Carey, S. Infants’ attributions of insides and animacy in causal interactions. Cogn. Sci. 46 , e13087 (2022).

Lakusta, L. & Carey, S. Twelve-month-old infants’ encoding of goal and source paths in agentive and non-agentive motion events. Lang. Learn. Dev. 11 , 152–175 (2015).

Saxe, R., Tzelnic, T. & Carey, S. Knowing who dunnit: infants identify the causal agent in an unseen causal interaction. Dev. Psychol. 43 , 149–158 (2007).

Saxe, R., Tenenbaum, J. & Carey, S. Secret agents: inferences about hidden causes by 10- and 12-month-old infants. Psychol. Sci. 16 , 995–1001 (2005).

Liu, S., Brooks, N. B. & Spelke, E. S. Origins of the concepts cause, cost, and goal in prereaching infants. Proc. Natl Acad. Sci. USA 116 , 17747–17752 (2019).

Liu, S. & Spelke, E. S. Six-month-old infants expect agents to minimize the cost of their actions. Cognition 160 , 35–42 (2017).

Nyhout, A. & Ganea, P. A. What is and what never should have been: children’s causal and counterfactual judgments about the same events. J. Exp. Child. Psychol. 192 , 104773 (2020).

Legare, C. H. The contributions of explanation and exploration to children’s scientific reasoning. Child. Dev. Perspect. 8 , 101–106 (2014).

Denison, S. & Xu, F. Twelve‐to 14‐month‐old infants can predict single‐event probability with large set sizes. Dev. Sci. 13 , 798–803 (2010).

Denison, S., Reed, C. & Xu, F. The emergence of probabilistic reasoning in very young infants: evidence from 4.5-and 6-month-olds. Dev. Psychol. 49 , 243 (2013).

Alderete, S. & Xu, F. Three-year-old children’s reasoning about possibilities. Cognition 237 , 105472 (2023).

Scholl, B. J. & Tremoulet, P. D. Perceptual causality and animacy. Trends Cogn. Sci. 4 , 299–309 (2000).

Hood, B., Carey, S. & Prasada, S. Predicting the outcomes of physical events: two‐year‐olds fail to reveal knowledge of solidity and support. Child. Dev. 71 , 1540–1554 (2000).

Hood, B. M., Hauser, M. D., Anderson, L. & Santos, L. Gravity biases in a non‐human primate? Dev. Sci. 2 , 35–41 (1999).

Hood, B. M. Gravity does rule for falling events. Dev. Sci. 1 , 59–63 (1998).

Hood, B. M. Gravity rules for 2-to 4-year olds? Cognit. Dev. 10 , 577–598 (1995).

Woodward, A. L. Infants selectively encode the goal object of an actor’s reach. Cognition 69 , 1–34 (1998).

Woodward, A. L. Infants’ grasp of others’ intentions. Curr. Dir. Psychol. Sci. 18 , 53–57 (2009).

Woodward, A. L., Sommerville, J. A., Gerson, S., Henderson, A. M. & Buresh, J. The emergence of intention attribution in infancy. Psychol. Learn. Motiv. 51 , 187–222 (2009).

Meltzoff, A. N. ‘Like me’: a foundation for social cognition. Dev. Sci. 10 , 126–134 (2007).

Gerson, S. A. & Woodward, A. L. The joint role of trained, untrained, and observed actions at the origins of goal recognition. Infant. Behav. Dev. 37 , 94–104 (2014).

Gerson, S. A. & Woodward, A. L. Learning from their own actions: the unique effect of producing actions on infants’ action understanding. Child. Dev. 85 , 264–277 (2014).

Sommerville, J. A., Woodward, A. L. & Needham, A. Action experience alters 3-month-old infants’ perception of others’ actions. Cognition 96 , B1–B11 (2005).

Liu, S. & Almeida, M. Knowing before doing: review and mega-analysis of action understanding in prereaching infants. Psychol. Bull. 149 , 294–310 (2023).

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The authors acknowledge their funding sources: the Alexander von Humboldt Foundation, the Templeton World Charity Foundation (0434), the John Templeton Foundation (6145), the Defense Advanced Research Projects Agency (047498-002 Machine Common Sense), the Department of Defense Multidisciplinary University Initiative (Self-Learning perception Through Real World Interaction), and the Canadian Institute for Advanced Research Catalyst Award. For helpful discussions, comments, and other forms of support, the authors thank: S. Boardman, E. Bonawitz, B. Brast-McKie, D. Buchsbaum, M. Deigan, J. Engelmann, T. Friend, T. Gerstenberg, S. Kikkert, A. Kratzer, E. Lapidow, B. Leahy, T. Lombrozo, J. Phillips, H. Rakoczy, L. Schulz, D. Sobel, E. Spelke, H. Steward, B. Vetter, M. Waldmann and E. Yiu.

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Goddu, M.K., Gopnik, A. The development of human causal learning and reasoning. Nat Rev Psychol 3 , 319–339 (2024). https://doi.org/10.1038/s44159-024-00300-5

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Harvard study, almost 80 years old, has proved that embracing community helps us live longer, and be happier

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W hen scientists began tracking the health of 268 Harvard sophomores in 1938 during the Great Depression, they hoped the longitudinal study would reveal clues to leading healthy and happy lives.

They got more than they wanted.

After following the surviving Crimson men for nearly 80 years as part of the Harvard Study of Adult Development , one of the world’s longest studies of adult life, researchers have collected a cornucopia of data on their physical and mental health.

Of the original Harvard cohort recruited as part of the Grant Study, only 19 are still alive, all in their mid-90s. Among the original recruits were eventual President John F. Kennedy and longtime Washington Post editor Ben Bradlee. (Women weren’t in the original study because the College was still all male.)

In addition, scientists eventually expanded their research to include the men’s offspring, who now number 1,300 and are in their 50s and 60s, to find out how early-life experiences affect health and aging over time. Some participants went on to become successful businessmen, doctors, lawyers, and others ended up as schizophrenics or alcoholics, but not on inevitable tracks.

“Loneliness kills. It’s as powerful as smoking or alcoholism.” Robert Waldinger, psychiatrist, Massachusetts General Hospital

During the intervening decades, the control groups have expanded. In the 1970s, 456 Boston inner-city residents were enlisted as part of the Glueck Study, and 40 of them are still alive. More than a decade ago, researchers began including wives in the Grant and Glueck studies.

Over the years, researchers have studied the participants’ health trajectories and their broader lives, including their triumphs and failures in careers and marriage, and the finding have produced startling lessons, and not only for the researchers.

“The surprising finding is that our relationships and how happy we are in our relationships has a powerful influence on our health,” said Robert Waldinger , director of the study, a psychiatrist at Massachusetts General Hospital and a professor of psychiatry at Harvard Medical School . “Taking care of your body is important, but tending to your relationships is a form of self-care too. That, I think, is the revelation.”

Close relationships, more than money or fame, are what keep people happy throughout their lives, the study revealed. Those ties protect people from life’s discontents, help to delay mental and physical decline, and are better predictors of long and happy lives than social class, IQ, or even genes. That finding proved true across the board among both the Harvard men and the inner-city participants.

“The people who were the most satisfied in their relationships at age 50 were the healthiest at age 80,” said Robert Waldinger with his wife Jennifer Stone.

Rose Lincoln/Harvard Staff Photographer

The long-term research has received funding from private foundations, but has been financed largely by grants from the National Institutes of Health, first through the National Institute of Mental Health, and more recently through the National Institute on Aging.

Researchers who have pored through data, including vast medical records and hundreds of in-person interviews and questionnaires, found a strong correlation between men’s flourishing lives and their relationships with family, friends, and community. Several studies found that people’s level of satisfaction with their relationships at age 50 was a better predictor of physical health than their cholesterol levels were.

“When we gathered together everything we knew about them about at age 50, it wasn’t their middle-age cholesterol levels that predicted how they were going to grow old,” said Waldinger in a popular TED Talk . “It was how satisfied they were in their relationships. The people who were the most satisfied in their relationships at age 50 were the healthiest at age 80.”

He recorded his TED talk, titled “What Makes a Good Life? Lessons from the Longest Study on Happiness,” in 2015, and it has been viewed 13,000,000 times.

The researchers also found that marital satisfaction has a protective effect on people’s mental health. Part of a study found that people who had happy marriages in their 80s reported that their moods didn’t suffer even on the days when they had more physical pain. Those who had unhappy marriages felt both more emotional and physical pain.

Those who kept warm relationships got to live longer and happier, said Waldinger, and the loners often died earlier. “Loneliness kills,” he said. “It’s as powerful as smoking or alcoholism.”

According to the study, those who lived longer and enjoyed sound health avoided smoking and alcohol in excess. Researchers also found that those with strong social support experienced less mental deterioration as they aged.

In part of a recent study , researchers found that women who felt securely attached to their partners were less depressed and more happy in their relationships two-and-a-half years later, and also had better memory functions than those with frequent marital conflicts.

“When the study began, nobody cared about empathy or attachment. But the key to healthy aging is relationships, relationships, relationships.” George Vaillant, psychiatrist

“Good relationships don’t just protect our bodies; they protect our brains,” said Waldinger in his TED talk. “And those good relationships, they don’t have to be smooth all the time. Some of our octogenarian couples could bicker with each other day in and day out, but as long as they felt that they could really count on the other when the going got tough, those arguments didn’t take a toll on their memories.”

Since aging starts at birth, people should start taking care of themselves at every stage of life, the researchers say.

“Aging is a continuous process,” Waldinger said. “You can see how people can start to differ in their health trajectory in their 30s, so that by taking good care of yourself early in life you can set yourself on a better course for aging. The best advice I can give is ‘Take care of your body as though you were going to need it for 100 years,’ because you might.”

The study, like its remaining original subjects, has had a long life, spanning four directors, whose tenures reflected their medical interests and views of the time.

Under the first director, Clark Heath, who stayed from 1938 until 1954, the study mirrored the era’s dominant view of genetics and biological determinism. Early researchers believed that physical constitution, intellectual ability, and personality traits determined adult development. They made detailed anthropometric measurements of skulls, brow bridges, and moles, wrote in-depth notes on the functioning of major organs, examined brain activity through electroencephalograms, and even analyzed the men’s handwriting.

Now, researchers draw men’s blood for DNA testing and put them into MRI scanners to examine organs and tissues in their bodies, procedures that would have sounded like science fiction back in 1938. In that sense, the study itself represents a history of the changes that life brings.

6 factors predicting healthy aging According to George Vaillant’s book “Aging Well,” from observations of Harvard men in long-term aging study

Physically active.

Absence of alcohol abuse and smoking

Having mature mechanisms to cope with life’s ups and downs

Healthy weight

Stable marriage.

Psychiatrist George Vaillant, who joined the team as a researcher in 1966, led the study from 1972 until 2004. Trained as a psychoanalyst, Vaillant emphasized the role of relationships, and came to recognize the crucial role they played in people living long and pleasant lives.

In a book called “Aging Well,” Vaillant wrote that six factors predicted healthy aging for the Harvard men: physical activity, absence of alcohol abuse and smoking, having mature mechanisms to cope with life’s ups and downs, and enjoying both a healthy weight and a stable marriage. For the inner-city men, education was an additional factor. “The more education the inner city men obtained,” wrote Vaillant, “the more likely they were to stop smoking, eat sensibly, and use alcohol in moderation.”

Vaillant’s research highlighted the role of these protective factors in healthy aging. The more factors the subjects had in place, the better the odds they had for longer, happier lives.

“When the study began, nobody cared about empathy or attachment,” said Vaillant. “But the key to healthy aging is relationships, relationships, relationships.”

“We want to find out how it is that a difficult childhood reaches across decades to break down the body in middle age and later.” Robert Waldinger

The study showed that the role of genetics and long-lived ancestors proved less important to longevity than the level of satisfaction with relationships in midlife, now recognized as a good predictor of healthy aging. The research also debunked the idea that people’s personalities “set like plaster” by age 30 and cannot be changed.

“Those who were clearly train wrecks when they were in their 20s or 25s turned out to be wonderful octogenarians,” he said. “On the other hand, alcoholism and major depression could take people who started life as stars and leave them at the end of their lives as train wrecks.”

The study’s fourth director, Waldinger has expanded research to the wives and children of the original men. That is the second-generation study, and Waldinger hopes to expand it into the third and fourth generations. “It will probably never be replicated,” he said of the lengthy research, adding that there is yet more to learn.

“We’re trying to see how people manage stress, whether their bodies are in a sort of chronic ‘fight or flight’ mode,” Waldinger said. “We want to find out how it is that a difficult childhood reaches across decades to break down the body in middle age and later.”

Lara Tang ’18, a human and evolutionary biology concentrator who recently joined the team as a research assistant, relishes the opportunity to help find some of those answers. She joined the effort after coming across Waldinger’s TED talk in one of her classes.

“That motivated me to do more research on adult development,” said Tang. “I want to see how childhood experiences affect developments of physical health, mental health, and happiness later in life.”

Asked what lessons he has learned from the study, Waldinger, who is a Zen priest, said he practices meditation daily and invests time and energy in his relationships, more than before.

“It’s easy to get isolated, to get caught up in work and not remembering, ‘Oh, I haven’t seen these friends in a long time,’ ” Waldinger said. “So I try to pay more attention to my relationships than I used to.”

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Suggested citation: National Scientific Council on the Developing Child. (2024). A World of Differences: The Science of Human Variation Can Drive Early Childhood Policies and Programs to Bigger Impacts: Working Paper No. 17. Retrieved from www.developingchild.harvard.edu

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Impact of the circular economy on human development: evidence from Germany

• Published: 02 May 2024

Cite this article

• Naila Erum   ORCID: orcid.org/0000-0003-0806-2882 1 ,
• Kazi Musa   ORCID: orcid.org/0000-0002-6686-0199 1 ,
• Saira Tufail 2 ,
• Jamaliah Said   ORCID: orcid.org/0000-0003-1912-2529 1 &
• Nor Balkish Zakaria   ORCID: orcid.org/0000-0002-1795-9854 1  

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The circular economy has garnered significant consideration due to its ability to contribute to human development. This study presents a comprehensive analysis of the individual effects of four categories of circular economy, namely renewable energy consumption (REC), recycle, reuse, and repair, on human development. For this purpose, we collected time series data of Germany from 1990 to 2021 and applied a dynamic ARDL simulation technique to compile empirical results. The findings show that the REC has positive and significant impact on human development. Reuse and Recycle have an inverse and significant influence on human development in Germany. Whereas human development is neutral to repair. Additionally, the control variables, environmental tax and industrial employment also have negative impacts on human development. Based on the findings, the study suggests that policymakers should design suitable, efficient, and targeted measures to foster the role of each category of circular economy for human development in Germany.

Graphical abstract

We examined the impact of various categories of circular economy on human development in Germany. The findings indicate that REC is positively and significantly associated with human development. The repair has a neutral impact on human development as a category of circular economy. The study also finds that reuse and recycling negatively and significantly affect human development in Germany.

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Abbas, J., Al-Sulaiti, K., Lorente, D. B., Shah, S. A. R., & Shahzad, U. Reset the industry redux through corporate social responsibility: The COVID-19 tourism impact on hospitality firms through business model innovation. In Economic Growth and Environmental Quality in a Post-Pandemic World (pp. 177–201). Routledge (2022).

Abokersh, M. H., Norouzi, M., Boer, D., Cabeza, L. F., Casa, G., Prieto, C., Jiménez, L., & Valles, M. (2021). A framework for sustainable evaluation of thermal energy storage in circular economy. Renewable Energy, 175 , 686–701.

Adedoyin, F. F., Erum, N., Taşkin, D., & Chebab, D. (2023). Energy policy simulation in times of crisis: Revisiting the impact of renewable and non-renewable energy production on environmental quality in Germany. Energy Reports, 9 , 4749–4762.

Article   Google Scholar  

Alaerts, L., Van Acker, K., Rousseau, S., De Jaeger, S., Moraga, G., Dewulf, J., De Meester, S., Van Passel, S., Compernolle, T., Bachus, K., Vrancken, K., & Eyckmans, J. (2019). Towards a more direct policy feedback in circular economy monitoring via a societal needs perspective. Resources, Conservation and Recycling, 149 , 363–371.

Alnajem, M., Mostafa, M. M., & ElMelegy, A. R. (2021). Mapping the first decade of circular economy research: A bibliometric network analysis. Journal of Industrial and Production Engineering, 38 (1), 29–50.

Androniceanu, A., Kinnunen, J., & Georgescu, I. (2021). Circular economy as a strategic option to promote sustainable economic growth and effective human development. Journal of International Studies., 14 (1), 2071–8330.

Baars, J., Domenech, T., Bleischwitz, R., Melin, H. E., & Heidrich, O. (2021). Circular economy strategies for electric vehicle batteries reduce reliance on raw materials. Nature Sustainability, 4 (1), 71–79.

Balsalobre-Lorente, D., Abbas, J., He, C., Pilař, L., & Shah, S. A. R. (2023). Tourism, urbanization and natural resources rents matter for environmental sustainability: The leading role of AI and ICT on sustainable development goals in the digital era. Resources Policy, 82 , 103445.

Beccarello, M., & Di Foggia, G. (2018). Moving towards a circular economy: Economic impacts of higher material recycling targets. Materials Today Proceedings, 5 (1), 531–543.

Ben Mbarek, M., Saidi, K., & Rahman, M. M. (2018). Renewable and non-renewable energy consumption, environmental degradation and economic growth in Tunisia. Quality & Quantity, 52 , 1105–1119.

Brando, P., Macedo, M., Silvério, D., Rattis, L., Paolucci, L., Alencar, A., Coe, M., & Amorim, C. (2020). Amazon wildfires: Scenes from a foreseeable disaster. Flora, 268 , 151609.

Bracquene, E., Peeters, J. R., Burez, J., De Schepper, K., Duflou, J. R., & Dewulf, W. (2019). Repairability evaluation for energy-related products. Procedia CIRP, 80 , 536–541.

Chang, Q., & Goplerud, M. (2024). Generalized Kernel Regularized Least Squares. Political Analysis, 32 (2), 157–171.

Chauhan, A., Jakhar, S. K., & Chauhan, C. (2021). The interplay of circular economy with industry 4.0 enabled smart city drivers of healthcare waste disposal. Journal of Cleaner Production., 10 (279), 123854.

Chioatto, E., & Sospiro, P. (2023). Transition from waste management to circular economy: The European Union roadmap. Environment, Development and Sustainability, 25 (1), 249–276.

Chui, K. T., Lytras, M. D., & Visvizi, A. (2018). Energy sustainability in smart cities: Artificial intelligence, smart monitoring, and optimization of energy consumption. Energies 11, 2869. Energy, 158 , 1080–1091.

Google Scholar  

Corona, B., Shen, L., Reike, D., Carreón, J. R., & Worrell, E. (2019). Towards sustainable development through the circular economy—A review and critical assessment on current circularity metrics. Resources Conservation and Recycling, 151 , 104498.

Corvellec, H., Stowell, A. F., & Johansson, N. (2022). Critiques of the circular economy. Journal of Industrial Ecology, 26 (2), 421–432.

Daú, G., Scavarda, A., Scavarda, L. F., & Portugal, V. J. T. (2019). The healthcare sustainable supply chain 4.0: The circular economy transition conceptual framework with the corporate social responsibility mirror. Sustainability, 11 (12), 3259.

Deloitte (2016), Study on Socioeconomic Impacts of Increased Reparability of Increased Reparability: Final Report , Prepared for the European Commission, DG ENV. European Commission, Brussels.

Desing, H., Brunner, D., Takacs, F., Nahrath, S., Frankenberger, K., & Hischier, R. (2020). A circular economy within the planetary boundaries: Towards a resource-based, systemic approach. Resources Conservation and Recycling, 155 , 104673.

D'Urzo, M., & Campagnaro, C. (2023). Design-led repair & reuse: An approach for an equitable, bottom-up, innovation-driven circular economy. Journal of Cleaner Production, 387 , 135724.

Geissdoerfer, M., Savaget, P., Bocken, N. M., & Hultink, E. J. (2017). The Circular Economy–A new sustainability paradigm?. Journal of Cleaner Production, 143 , 757–768.

Hao, Y., Wang, Y., Wu, Q., Sun, S., Wang, W., & Cui, M. (2020). What affects residents’ participation in the circular economy for sustainable development? Evidence from China. Sustainable Development, 28 (5), 1251–1268.

Horbach, J., & Rammer, C. (2020). Circular economy innovations, growth and employment at the firm level: Empirical evidence from Germany. Journal of Industrial Ecology, 24 (3), 615–625.

International Energy Agency (2020). Germany 2020 - Energy Policy Review. Accessed from https://iea.blob.core.windows.net/assets/60434f12-7891-4469-b3e4-1e82ff898212/Germany_2020_Energy_Policy_Review.pdf . Accessed on 26-04-2024.

Islam, K. N., Sarker, T., Taghizadeh-Hesary, F., Atri, A. C., & Alam, M. S. (2021). Renewable energy generation from livestock waste for a sustainable circular economy in Bangladesh. Renewable and Sustainable Energy Reviews, 139 , 110695.

Article   CAS   Google Scholar  

Jaeger-Erben, M., Frick, V., & Hipp, T. (2021). Why do users (not) repair their devices? A study of the predictors of repair practices. Journal of Cleaner Production., 286 , 125382. https://doi.org/10.1016/j.jclepro.2020.125382

Jang, Y. C., Lee, G., Kwon, Y., Lim, J. H., & Jeong, J. H. (2020). Recycling and management practices of plastic packaging waste towards a circular economy in South Korea. Resources Conservation and Recycling, 158 , 104798.

Jordan, S., & Philips, A. Q. (2018). Cointegration testing and dynamic simulations of autoregressive distributed lag models. Symposium (international) on Combustion, 18 (4), 902–923.

Kazancoglu, I., Sagnak, M., Kumar Mangla, S., & Kazancoglu, Y. (2021). Circular economy and the policy: A framework for improving the corporate environmental management in supply chains. Business Strategy and the Environment, 30 (1), 590–608.

Khajuria, A., Atienza, V. A., Chavanich, S., Henning, W., Islam, I., Kral, U., & Li, J. (2022). Accelerating circular economy solutions to achieve the 2030 agenda for sustainable development goals. Circular Economy, 1 (1), 100001.

Kirchherr, J., Reike, D., & Hekkert, M. (2017). Conceptualizing the circular economy: An analysis of 114 definitions. Resources Conservation and Recycling, 127 , 221–232.

Knäble, D., de Quevedo Puente, E., Pérez-Cornejo, C., & Baumgärtler, T. (2022). The impact of the circular economy on sustainable development: A European panel data approach. Sustainable Production and Consumption, 34 , 233–243.

Laitala, K., Klepp, I. G., Haugrønning, V., Throne-Holst, H., & Strandbakken, P. (2021). Increasing repair of household appliances, mobile phones and clothing: Experiences from consumers and the repair industry. Journal of Cleaner Production., 282 , 125349. https://doi.org/10.1016/j.jclepro.2020.125349

Lederer, J., Gassner, A., Kleemann, F., & Fellner, J. (2020). Potentials for a circular economy of mineral construction materials and demolition waste in urban areas: A case study from Vienna. Resources, Conservation and Recycling, 161 , 104942.

Lee, J. W. (2019). Long-run dynamics of renewable energy consumption on carbon emissions and economic growth in the European Union. International Journal of Sustainable Development & World Ecology, 26 (1), 69–78.

Llorente-González, L. J., & Vence, X. (2020). How labour-intensive is the circular economy? A policy-orientated structural analysis of the repair, reuse and recycling activities in the European Union. Resources, Conservation and Recycling, 162 , 105033.

Luttenberger, L. R. (2020). Waste management challenges in transition to circular economy–case of Croatia. Journal of Cleaner Production, 256 , 120495.

Marrucci, L., Daddi, T., & Iraldo, F. (2021). The contribution of green human resource management to the circular economy and performance of environmental certified organisations. Journal of Cleaner Production, 319 , 128859.

Maslyuk, S. Energy Consumption Transition and Human Development. In  Institutions, Efficiency and Evolving Energy Technologies, 34th IAEE International Conference, June 19–23, 2011 . International Association for Energy Economics. (2011)

Mavropoulos, A., & Nilsen, A. W. (2020). Industry 40 and circular economy: Towards a wasteless future or a wasteful planet? John Wiley & Sons.

Mauss, N. A., Bühner, D., & Fottner, J. (2023). Applicability and limitations of change management for circular economy in manufacturing companies. Procedia Computer Science, 217 , 998–1007.

McLaren, D., Niskanen, J., & Anshelm, J. (2020). Reconfiguring repair: Contested politics and values of repair challenge instrumental discourses found in circular economies literature. Resources Conservation Recycling X, 8 , 100046.

McVeigh, M. K., Dalhammar, C., & Richter, J. L. Planned obsolescence–Built not to last. Stockholm: European Liberal Forum and Fores. (2019).

Mendonça, A.Kd.S., de Andrade Conradi Barni, G., Moro, M.F., Bornia, A.C., Kupek, E., Fernandes, L., 2020. Hierarchical modeling of the 50 largest economies to verify the

Micah, A. E., Bhangdia, K., Cogswell, I. E., Lasher, D., Lidral-Porter, B., Maddison, E. R., & Hlongwa, M. M. (2023). Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026. The Lancet Global Health, 11 (3), e385–e413.

Mies, A., & Gold, S. (2021). Mapping the social dimension of the circular economy. Journal of Cleaner Production, 321 , 128960.

Moraga, G., Huysveld, S., Mathieux, F., Blengini, G. A., Alaerts, L., Van Acker, K., & Dewulf, J. (2019). Circular economy indicators: What do they measure? Resources Conservation and Recycling, 146 , 452–461.

Morseletto, P. (2020). Targets for a circular economy. Resources Conservation and Recycling, 153 , 104553.

Mukoro, V., Gallego-Schmid, A., & Sharmina, M. (2021). Life cycle assessment of renewable energy in Africa. Sustainable Production and Consumption, 28 , 1314–1332.

Murray, A., Skene, K., & Haynes, K. (2017). The circular economy: An interdisciplinary exploration of the concept and application in a global context. Journal of Business Ethics, 140 , 369–380.

Neligan, A., Baumgartner, R. J., Geissdoerfer, M., & Schöggl, J. P. (2023). Circular disruption: Digitalisation as a driver of circular economy business models. Business Strategy and the Environment, 32 (3), 1175–1188.

Nelson, A., & Neguriță, O. (2020). Big data-driven smart cities: Internet of things devices and environmentally sustainable urban development. Geopolitics History and International Relations, 12 (2), 37–43. https://doi.org/10.22381/GHIR12220205

Neumayer, E. (2016). Human development and sustainability. The Capability Approach and Sustainability , 154–172.

Neumann, J., Petranikova, M., Meeus, M., Gamarra, J. D., Younesi, R., Winter, M., & Nowak, S. (2022). Recycling of lithium-ion batteries—current state of the art, circular economy, and next generation recycling. Advanced Energy Materials, 12 (17), 2102917.

NY State Senate, Bill S149 Establishes the right to repair act. [Online]. Available https://www.nysenate.gov/legislation/bills/2021/s149 . Accessed 01 Oct 2022 (2020)

Ofori, D., & Opoku Mensah, A. (2022). Sustainable electronic waste management among households: A circular economy perspective from a developing economy. Management of Environmental Quality: An International Journal, 33 (1), 64–85.

Ogunmakinde, O. E., Egbelakin, T., & Sher, W. (2022). Contributions of the circular economy to the UN sustainable development goals through sustainable construction. Resources Conservation and Recycling, 178 , 106023.

Ouedraogo, N. S. (2013). Energy consumption and human development: Evidence from a panel cointegration and error correction model. Energy, 63 , 28–41.

Pahunang, R. R., Buonerba, A., Senatore, V., Oliva, G., Ouda, M., Zarra, T., & Naddeo, V. (2021). Advances in technological control of greenhouse gas emissions from wastewater in the context of circular economy. Science of the Total Environment, 792 , 148479.

Pajunen, N., & Holuszko, M. E. (2022). Circular economy in electronics and the future of e-waste. Electronic Waste: Recycling and Reprocessing for a Sustainable Future., 10 , 299–314.

Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16 (3), 289–326.

Puntillo, P. (2023). Circular economy business models: Towards achieving sustainable development goals in the waste management sector—Empirical evidence and theoretical implications. Corporate Social Responsibility and Environmental Management, 30 (2), 941–954.

Reike, D., Vermeulen, W. J., & Witjes, S. (2018). The circular economy: New or refurbished as CE 3.0?—exploring controversies in the conceptualization of the circular economy through a focus on history and resource value retention options. Resources, Conservation and Recycling, 135 , 246–264.

Sabbaghi, M., Cade, W., Behdad, S., & Bisantz, A. M. (2017). The current status of the consumer electronics repair industry in the US: A survey-based study. Resources, Conservation and Recycling, 116 , 137–151.

Sanchez-Loor, D. A., & Zambrano-Monserrate, M. A. (2015). Causality analysis between electricity consumption, real GDP, foreign direct investment, human development and remittances in Colombia, Ecuador and Mexico. International Journal of Energy Economics and Policy, 5 (3), 746–753.

Sarkodie, S. A., & Owusu, P. A. (2020). How to apply the novel dynamic ARDL simulations (dynardl) and Kernel-based regularized least squares (krls). MethodsX, 7 , 101160.

Sasmaz, M. U., Sakar, E., Yayla, Y. E., & Akkucuk, U. (2020). The relationship between renewable energy and human development in OECD countries: A panel data analysis. Sustainability, 12 (18), 7450.

Schäfer, P., & Schmidt, M. (2021). Model-based analysis of the limits of recycling for its contribution to climate change mitigation. Nachhaltigkeits Management Forum, 29 (2), 65–75.

Schröder, P., Lemille, A., & Desmond, P. (2020). Making the circular economy work for human development. Resources Conservation and Recycling, 156 , 104686.

Scotland, Z. W. (2015). Circular economy evidence building programme: Remanufacturing study.

Shah, S. A. R., Zhang, Q., Abbas, J., Tang, H., & Al-Sulaiti, K. I. (2023). Waste management, quality of life and natural resources utilization matter for renewable electricity generation: The main and moderate role of environmental policy. Utilities Policy, 82 , 101584.

Shamsuyeva, M., & Endres, H. J. (2021). Plastics in the context of the circular economy and sustainable plastics recycling: Comprehensive review on research development, standardization and market. Composites Part C Open Access, 6 , 100168.

Shanmugam, V., Das, O., Neisiany, R. E., Babu, K., Singh, S., Hedenqvist, M. S., & Ramakrishna, S. (2020). Polymer recycling in additive manufacturing: An opportunity for the circular economy. Materials Circular Economy, 2 , 1–11.

Sharma, N. K., Govindan, K., Lai, K. K., Chen, W. K., & Kumar, V. (2021). The transition from linear economy to circular economy for sustainability among SMEs: A study on prospects, impediments, and prerequisites. Business Strategy and the Environment, 30 (4), 1803–1822.

Shishegar, S., Duchesne, S., Pelletier, G., & Ghorbani, R. (2021). A smart predictive framework for system-level storm water management optimization. Journal of Environmental Management, 278 , 111505.

Silva, V. U., Nascimento, M. F., Oliveira, P. R., Panzera, T. H., Rezende, M. O., Silva, D. A. L., & Christoforo, A. L. (2021). Circular vs. linear economy of building materials: A case study for particleboards made of recycled wood and biopolymer vs. conventional particleboards. Construction and Building Materials, 285 , 122906.

Simoens, M. C., & Leipold, S. (2021). Trading radical for incremental change: The politics of a circular economy transition in the German packaging sector. Journal of Environmental Policy Planning, 23 (6), 822–836.

Sinha, E. (2022). Circular economy—A way forward to sustainable development: Identifying conceptual overlaps and contingency factors at the microlevel. Sustainable Development, 30 (4), 771–783.

Spencer, G., Corbin, J. H., & Miedema, E. (2019). Sustainable development goals for health promotion: A critical frame analysis. Health Promotion International, 34 (4), 847–858.

Steffen, W., Richardson, K., Rockström, J., Cornell, S. E., Fetzer, I., Bennett, E. M., Biggs, R., Carpenter, S. R., De Vries, W., De Wit, C. A., & Folke, C. (2015). Planetary boundaries: Guiding human development on a changing planet. Science, 347 (6223), 1259855. https://doi.org/10.1126/science.1259855

Strielkowski, W., Streimikiene, D., Fomina, A., & Semenova, E. (2019). Internet of energy (IoE) and high-renewables electricity system market design. Energies, 12 (24), 4790.

Svensson-Hoglund, S., Russell, J. D., & Richter, J. L. (2023). A process approach to product repair from the perspective of the individual. Circular Economy and Sustainability., 3 (3), 1327–1359.

Sverko Grdic, Z., Krstinic Nizic, M., & Rudan, E. (2020). Circular economy concept in the context of economic development in EU countries. Sustainability, 12 (7), 3060.

Ul-Durar, S., Awan, U., Varma, A., Memon, S., & Mention, A. L. (2023). Integrating knowledge management and orientation dynamics for organization transition from eco-innovation to circular economy. Journal of Knowledge Management., 27 (8), 2217–2248.

Valencia, A., Zhang, W., & Chang, N. B. (2022). Sustainability transitions of urban food-energy-water-waste infrastructure: A living laboratory approach for circular economy. Resources Conservation and Recycling, 177 , 105991.

Velasco-Muñoz, J. F., Mendoza, J. M. F., Aznar-Sánchez, J. A., & Gallego-Schmid, A. (2021). Circular economy implementation in the agricultural sector: Definition, strategies and indicators. Resources Conservation and Recycling, 170 , 105618.

Wang, S., Abbas, J., Al-Sulati, K. I., & Shah, S. A. (2024b). The impact of economic corridor and tourism on local community’s quality of life under one belt one road context. Evaluation Review, 48 (2), 312–345.

Wang, X., Li, Y., Liu, N., & Zhang, Y. (2023a). An urban material flow analysis framework and measurement method from the perspective of urban metabolism. Journal of Cleaner Production, 257 , 120564.

Wu, C., Chen, B., Huang, X., & Wei, Y. D. (2020). Effect of land-use change and optimization on the ecosystem service values of Jiangsu province. China. Ecological Indicators, 117 , 106507.

Wuni, I. Y. (2023). A systematic review of the critical success factors for implementing circular economy in construction projects. Sustainable Development, 31 (3), 1195–1213.

Yang, Y., Pilanci, M., & Wainwright, M. J. (2017). Randomized sketches for kernels: Fast and optimal nonparametric regression.

Zhang, X., Husnain, M., Yang, H., Ullah, S., Abbas, J., & Zhang, R. (2022). Corporate business strategy and tax avoidance culture: Moderating role of gender diversity in an emerging economy. Frontiers in Psychology, 13 , 827553.

Zhang, X., & Liu, Y. (2022). Circular economy is game-changing municipal wastewater treatment technology towards energy and carbon neutrality. Chemical Engineering Journal, 429 , 132114.

Zhuang, G. L., Shih, S. G., & Wagiri, F. (2023). Circular economy and sustainable development goals: Exploring the potentials of reusable modular components in circular economy business model. Journal of Cleaner Production, 414 , 137503.

Zink, T., & Geyer, R. (2017). Circular economy rebound. Journal of Industrial Ecology, 21 (3), 593–602.

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Erum, N., Musa, K., Tufail, S. et al. Impact of the circular economy on human development: evidence from Germany. Environ Dev Sustain (2024). https://doi.org/10.1007/s10668-024-04918-6

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What is Development?

Human Development or Lifespan Development is the scientific study of the ways in which people change, as well as remain the same, from conception to death. You will discover that the field, known more broadly as developmental science , examines changes and stability across multiple domains of psychological and social functioning. These include physical and neurophysiological processes, cognition, language, emotion, personality, moral, and psychosocial development, including our relationships with others.

Originally concerned with infants and children, the field has expanded to include adolescence and more recently, aging and the entire life span. Previously, the message was once you are 25, your development is essentially completed. Our academic knowledge of the lifespan has changed, and although there is still less research on adulthood than on childhood, adulthood is gaining increasing attention. This is particularly true now that the large cohort known as the “baby boomers” are beginning to enter late adulthood. The assumption that early childhood experiences dictate our future is also being called into question. Instead, we have come to appreciate that growth and change continues throughout life and experience continues to have an impact on who we are and how we relate to others. We now recognize that adulthood is a dynamic period of life marked by continued cognitive, social, and psychological development.

You will also discover that developmental psychologists investigate key questions, such as whether children are qualitatively different from adults or simply lack the experience that adults draw upon. Other issues they consider include the question of whether development occurs through the gradual accumulation of knowledge or through qualitative shifts from one stage of thinking to another, or if children are born with innate knowledge or figure things out through experience, and whether development is driven by the social context or something inside each child. From these questions, you may already be thinking that developmental psychology is related to other applied fields. You are right. Developmental science informs many applied fields, including, educational psychology, developmental psychopathology, and intervention science. It also complements several other basic research fields in psychology including social psychology, cognitive psychology, and cross-cultural psychology. Lastly, it draws from the theories and research of several scientific fields including biology, sociology, health care, nutrition, and anthropology.

Learning Objectives: Lifespan Perspective

• Explain the lifespan perspective and its assumptions about development
• Differentiate periods of human development
• Identify key assumptions and major meta-theories underlying lifespan development 
• Identify major historical and contemporary theories focusing on lifespan development

Lifespan Perspective

Paul Baltes identified several underlying principles of the lifespan perspective (Baltes, 1987; Baltes, Lindenberger, & Staudinger, 2006).

• Development is lifelong . Lifespan theorists believe that development is life-long, and change is apparent across the lifespan. No single age period is more crucial, characterizes, or dominates human development. Consequently, the term lifespan development will be used throughout the textbook.
• Development is multidirectional and multidimensional.  Lifespan researchers hold that different people follow different developmental pathways, and proceed along pathways at different rates. Even within the same person, different dimensions or domains of development can change in different ways.
• Development includes both gains and losses . Lifespan theorists do not agree with the traditional view of development that childhood is a period characterized by developmental gains, whereas old age is a time of loss. Instead, the lifespan approach holds that at every age, we may show gains in some areas of development, while showing losses in other areas. Every change, whether it is finishing high school, getting married, or becoming a parent, entails both growth and loss.
• Development is characterized by plasticity. Plasticity is about malleability , or our potential to change and to follow a wide range of developmental pathways.  For instance, plasticity is illustrated in the brain’s ability to learn from experience and the many ways it can recover from injury.
• Development is embedded in historical and cultural contexts. Lifespan researchers believe that d evelopment is influenced by the many social contexts in which it unfolds. How  people develop will depend on their societal and cultural contexts, and on the historical period during which their development takes place.
•   Development is multiply determined. Lifespan theorists argue that development is caused by multiple factors, and is always shaped by  both biological and environmental factors. In addition, the individual plays an active role in their own development.
• Development is multidisciplinary. As mentioned at the start of the chapter, human development is such a vast topic of study that it requires the theories, research methods, and knowledge bases of many academic disciplines.

Contextualism as paradigm.  Baltes (1987) identified three specific developmental systems of influence, all of which include biological and environmental forces.

• Normative age-graded influences: An age-grade is a specific age group, such as toddler, adolescent, or senior . Humans experience particular age-graded social experiences (e.g., starting school) and biological changes (e.g., puberty).
• Normative history-graded influences: The time period in which you are born (see Table 1.1) shapes your experiences. A cohort is a group of people who are born at roughly the same period in a particular society. These people travel through life often experiencing similar historical changes at similar ages. History-graded influences include both environmental determinants (e.g., historical changes in the job market) and biological determinants (e.g., historical changes in life expectancy).
• Non-normative influences : People’s development is also shaped by specific influences that are not organized by age or historical time, such as immigration, accidents, or the death of a parent. These can be environmental (e.g., parental mental health issues) or biological (e.g., life threatening illness).

Table 1.1. Which generation (cohort) are you?

adapted from Lally & Valentine-French, 2019

Domains of development. We change across three general domains/dimensions; physical, cognitive, and psychosocial. The physical domain includes changes in height and weight, sensory capabilities, the nervous system, as well as the propensity for disease and illness . The cognitive domain encompasses the changes in intelligence, wisdom, perception, problem-solving, memory, and language. The psychosocial domain focuses on changes in emotion, self-perception and interpersonal relationships with families, peers, and friends. All three domains influence each other. It is also important to note that a change in one domain may cascade and prompt changes in the other domains. For instance, an infant who has started to crawl or walk will encounter more objects and people, thus fostering developmental change in the child’s understanding of the physical and social world.

Contextual perspectives , like the lifespan approach, highlight societal contexts that influence our development. An important societal factor is our social standing, socioeconomic status, or social class. Socioeconomic status (SES) is a way to identify families and households based on their shared levels of education, income, and occupation. While there is certainly individual variation, members of a social class tend to share similar privileges, opportunities, lifestyles, patterns of consumption, parenting styles, stressors, religious preferences, and other aspects of daily life. All of us born into a class system are socially located, and we may move up or down depending on a combination of both socially and individually created limits and opportunities.

Families with higher socioeconomic status usually are in occupations (e.g., attorneys, physicians, executives) that not only pay better, but also grant them a certain degree of freedom and control over their job. Having a sense of autonomy or control is a key factor in experiencing job satisfaction, personal happiness, and ultimately health and well-being (Weitz, 2007). Those families with lower socioeconomic status are typically in occupations that are more routine, more heavily supervised, and require less formal education. These occupations are also more subject to job disruptions, including lay-offs and lower wages.

Poverty level is an income amount established by the federal government that is based on a set of thresholds that vary by family size (United States Census Bureau, 2016). If a family’s income is less than the government threshold, that family is considered in poverty. Those living at or near poverty level may find it extremely difficult to sustain a household with this amount of income. Poverty is associated with poorer health and a lower life expectancy due to poorer diet, less healthcare, greater stress, working in more dangerous occupations, higher infant mortality rates, poorer prenatal care, greater iron deficiencies, greater difficulty in school, and many other problems. Members of higher income status may fear losing that status, but the poor may have greater concerns over losing housing.

Today we are more aware of the variations in development and the impact that culture and the environment have on shaping our lives. Culture is the totality of our shared language, knowledge, material objects, and behavior. It includes ideas about what is right and wrong, what to strive for, what to eat, how to speak, what is valued, as well as what kinds of emotions are called for in certain situations. Culture teaches us how to live in a society and allows us to advance because each new generation can benefit from the solutions found and passed down from previous generations. Culture is learned from parents, schools, houses of worship, media, friends and others throughout a lifetime. The kinds of traditions and values that evolve in a particular culture serve to help members function and value their own society. We tend to believe that our own culture’s practices and expectations are the right ones. This belief that our own culture is superior is called ethnocentrism and is a normal by-product of growing up in a culture. It becomes a roadblock, however, when it inhibits understanding of cultural practices from other societies. Cultural relativity is an appreciation for cultural differences and the understanding that cultural practices are best understood from the standpoint of that particular culture.

Culture is an extremely important context for human development and understanding development requires being able to identify which features of development are culturally based. This understanding is somewhat new and still being explored. Much of what developmental theorists have described in the past has been culturally bound and difficult to apply to various cultural contexts. The reader should keep this in mind and realize that there is still much that is unknown when comparing development across cultures.

Lifespan vs. Life expectancy: At this point you must be wondering what the difference between lifespan and life expectancy is, according to developmentalists. Lifespan , or longevity, refers to the maximum age any member of a species can reach under optimal conditions . For instance, the grey wolf can live up to 20 years in captivity, the bald eagle up to 50 years, and the Galapagos tortoise over 150 years (Smithsonian National Zoo, 2016). The longest recorded lifespan for a human was Jean Calment who died in 1994 at the age of 122 years, 5 months, and 14 days (Guinness World Records, 2016). Life expectancy is the average number of years a person born in a particular time period can typically expect to live (Vogt & Johnson, 2016).

Conceptions of Age

How old are you? Chances are you would answer that question based on the number of years since your birth, or what is called your chronological age . Ever felt older than your chronological age? Some days we might “feel” like we are older, especially if we are not feeling well, are tired, or are stressed out. We might notice that a peer seems more emotionally mature than we are, or that they are physically more capable. So years since birth is not the only way we can conceptualize age.

Biological age: Another way developmental researchers can think about the concept of age is to examine how quickly the body is aging , this is your biological age . Several factors determine the rate at which our body ages. Our nutrition, level of physical activity, sleeping habits, smoking, alcohol consumption, how we mentally handle stress, and the genetic history of our ancestors, to name but a few.

Psychological age: Our psychologically adaptive capacity compared to others of our chronological age is our psychological age . This includes our cognitive capacity along with our emotional beliefs about how old we are. An individual who has cognitive impairments might be 20 years of age, yet has the mental capacity of an 8-year-old. A 70- year-old might be travelling to new countries, taking courses at college, or starting a new business. Compared to others of our age group, we may be more or less active and excited to meet new challenges. Remember you are as young or old as you feel.

Social age: Our social age is based on the social norms of our culture and the expectations our culture has for people of our age group . Our culture often reminds us whether we are “on target” or “off target” for reaching certain social milestones, such as completing our education, moving away from home, having children, or retiring from work. However, there have been arguments that social age is becoming less relevant in the 21st century (Neugarten, 1979; 1996). If you look around at your fellow students at college you might notice more people who are older than traditional aged college students, those 18 to 25. Similarly, the age at which people are moving away from the home of their parents, starting their careers, getting married or having children, or even whether they get married or have children at all, is changing.

Those who study lifespan development recognize that chronological age does not completely capture a person’s age. Our age profile is much more complex than this. A person may be physically more competent than others in their age group, while being psychologically immature. So, how old are you?

Table 1.2 Age Periods of Development

Table 1.2 shows the developmental periods that will be explored in this book, starting with prenatal development and continuing thought late adulthood to death. Both childhood and adulthood are divided into multiple developmental periods. So, while both an 8-month old and an 8-year-old are considered children, they have very different motor abilities, social relationships, and cognitive skills. Their nutritional needs are different and their primary psychological concerns are also distinctive. The same is true of an 18-year-old and an 80-year-old, even though both are considered adults.

Prenatal Development : Conception occurs and development begins. All of the major structures of the body are forming, and the health of the mother is of primary concern. Understanding nutrition, teratogens , or environmental factors that can lead to birth defects , and labor and delivery are primary concerns.

Infancy and Toddlerhood : The first two years of life are ones of dramatic growth and change. A newborn, with a keen sense of hearing but very poor vision, is transformed into a walking, talking toddler within a relatively short period of time. Caregivers are also transformed from someone who manages feeding and sleep schedules to a constantly moving guide and safety inspector for a mobile, energetic child.

Early Childhood: This period is also referred to as the preschool years and consists of the years that follow toddlerhood and precede formal schooling. As a two to six-year-old, the child is busy learning language, gaining a sense of self and greater independence, and  beginning to understand the workings of the physical world.

Middle and Late Childhood: The ages of six to the onset of puberty comprise middle and late childhood, and much of what children experience at this age is connected to their involvement in the early grades of school. Now the world becomes one of learning and testing new academic skills, and assessing one’s abilities and accomplishments by making comparisons between self and others.

Adolescence : Adolescence is a period of dramatic physical change marked by an overall growth spurt and sexual maturation, known as puberty . It is also a time of cognitive change as the adolescent begins to think of new possibilities and to consider abstract concepts such as love, fear, and freedom. At the same time, adolescents have a sense of invincibility that puts them at greater risk of accidents or contracting sexually transmitted infections that can have lifelong consequences.

Emerging Adulthood: The period of emerging adulthood is a transitional time between the end of adolescence and before individuals acquire all the benchmarks of adulthood. Continued identity exploration and preparation for full independence from parents are negotiated. Although at one’s physiological peak, emerging adults are most at risk for involvement in violent crimes and substance abuse.

Early Adulthood : The twenties and thirties are identified as early adulthood. Intimate relationships, establishing families (of all shapes and sizes), and work are primary concerns at this stage of life.  For adults with children, developmental changes can become organized around the family life cycle.

Middle Adulthood : The forties through the mid-sixties are referred to as middle adulthood. This is a period in which aging becomes more noticeable and when many people are at their peak of productivity in love and work.  At this age, some people are negotiating adolescent children and aging parents at the same time.

Late Adulthood : Late adulthood is sometimes subdivided into two categories: The young-old who are from 65-84 years and the oldest-old who are 85 years and older. One of the primary differences between these groups is that the young-old are still relatively healthy, productive, active, and the majority continue to live independently. With both age groups the risks of diseases such as arteriosclerosis, cancer, and cerebral vascular disease increase substantially.

Meta-theories of Human Development

The study of development is guided by the assumptions researchers hold about the nature of humans and their development. These assumptions are called meta-theories . “Meta” means “above” or “beyond,” like “meta-physics.” Other terms used to describe meta-theories are “world views,” “cosmologies,” “perspectives,” or “paradigms,” as in “paradigm shifts.” Explicit discussions of meta-theories are found most often in philosophy.

What are meta-theories of human development?

Meta-theories (or world views or paradigms) of human development are sets of assumptions people hold about the nature of humans and the meaning of development — what it looks like, how it happens, what causes it. These assumptions are important because everyone has them, including researchers, but they are often implicit, meaning we are not always consciously aware of them. In the study of development, such assumptions influence everything about how research is conducted: the questions we ask, the measures and methods that are used, and the interpretation of data. For example, if researchers assume that development ends at 18, they do not look for developmental changes after that age. Or, if researchers assume that aging is a process of decline, then they never look for characteristics that might improve as people get older.

All researchers have meta-theories, since assumptions are baked into the theories and methodologies they use. But researchers are often unaware of them, and so these assumptions are rarely acknowledged. It is important to note that meta-theories are not just cold cognitions. They are often deeply held convictions that researchers will fiercely defend. Typically researchers think that their assumptions are self-evident truths. They are often convinced that their assumptions are right and everyone else’s are wrong.

Researchers holding different meta-theories can have difficulty communicating with each other. Since they are asking different questions and using different truth criteria for research, they often argue past each other or misunderstand each other. One group of researchers will offer what they consider to be irrefutable proof of their ideas, which other researchers then dismiss as irrelevant. Discrepancies, inconsistencies, arguments, and furor often characterize an area of study in which researchers from multiple meta-theories are working.

What kinds of assumptions guide the study of human development?

We consider six key assumptions. You may have heard of many of them, since they are perennial issues in the study of development. They include:

• Assumptions about human nature : whether people are born as blank slates ( tabula rasa ) or whether people are inherently good or inherently bad.
• Assumptions about the causes of development : whether development is determined by nature (genes, biology) or determined by nurture (environment, learning).
• Assumptions about the role of the individual in his or her own development: whether people are passive participants, reacting to external forces or whether they are active in choosing and shaping their own development.
• Assumptions about stability vs. change : whether traits, characteristics, and experiences early in life have permanent effects or whether people are malleable and open to change throughout life.
• Assumptions about continuity vs. discontinuity : whether development involves quantitative incremental change or qualitative shifts.
• Assumptions about universality vs. context specificity : whether development follows a universal pathway or depends more on specific experiences and environmental contexts.

Nature of humans. What is the nature of humans? These assumptions refer to beliefs about the underlying qualities of our species– whether humans are born as blank slates ( tabula rasa ) or whether we all bring intrinsic human characteristics with us into the world. For example, these different assumptions are readily apparent in alternative conceptualizations of motivation—some theories assume that motives and motivation are all acquired, whereas others assume that all humans come with intrinsic motivations.

Nature and Nurture: Why are you the way you are? As you consider some of your features (height, weight, personality, being diabetic, etc.), ask yourself whether these features are a result of heredity or environmental factors, or both. Chances are, you can see the ways in which both heredity and environmental factors (such as lifestyle, diet, and so on) have contributed to these features. For decades, scholars have carried on the “nature/nurture” debate. For any particular feature, those on the side of nature would argue that heredity plays the most important role in bringing about that feature. Those on the side of nurture would argue that one’s environment is most significant in shaping the way we are. This debate continues in all aspects of human development, and most scholars agree that there is a constant interplay between the two forces. It is difficult to isolate the root of any single behavior as a result solely of nature or nurture.

Active versus Passive: How much do you play a role in your own developmental path? Are you at the whim of your genetic inheritance or the environment that surrounds you? Some theorists see humans as playing a much more active role in their own development. Piaget, for instance believed that children actively explore their world and construct new ways of thinking to explain the things they experience. In contrast, many behaviorists view humans as being more passive in the developmental process.

Stability versus Change: How similar are you to how you were as a child? Were you always as out-going or reserved as you are now? Some theorists argue that the personality traits of adults are rooted in the behavioral and emotional tendencies of the infant and young child. Others disagree, and believe that these initial tendencies are modified by social and cultural forces over time.

Continuity versus Discontinuity: Is human development best characterized as a slow, gradual process, or is it best viewed as one of more abrupt change? The answer to that question often depends on which developmental theorist you ask and what topic is being studied. The theories of Freud, Erikson, Piaget, and Kohlberg are called stage theories. Stage theories or discontinuous development assume that developmental change occurs in distinct stages that are qualitatively different from each other, and that unfold in a set, universal sequence . At each stage of development, children and adults have different qualities and characteristics. Thus, stage theorists assume development is discontinuous. Others, such as the behaviorists, Vygotsky, and information processing theorists, assume development is a more slow and gradual process known as continuous development . For instance, they would see the adult as not possessing new skills, but as using more advanced skills that were already present in some form in the child. Brain development and environmental experiences contribute to the acquisition of more developed skills.

Universal vs. context specific . A final assumption focuses on whether pathways of development are presumed to be (1) normative and universal, meaning that all people pass through them in the same sequence, or (2) differential and specific, meaning that a variety of different patterns and pathways of developmental change are possible depending on the individual and the context. Some theorists, like Piaget or Erickson, assume that everyone progresses through the same stages of cognitive development in the same order, or that everyone negotiates the same set of developmental tasks at about the same ages. Other theorists, who endorse lifespan or ecological systems approaches, believe that development can take on a wide variety of patterns and pathways, depending on the specific cultural, historical, and societal under which it unfolds.

What are the guiding meta-theories in human development?

These six basic assumptions are clustered into “packages” that go together. Clusters are organized around metaphors, which are at the root of meta-theories of humans and their development. We consider four meta-theories, each with its own metaphor: (1) humans as seeds , as depicted by Maturational meta-theories; (2) humans as machines , as depicted in Mechanistic meta-theories (3) humans as butterflies , as depicted in Organismic meta-theories; and (4) humans as participants in a tennis game, conversation, or dance , as depicted by Contextualist meta-theories. For an overview of these guiding meta-theories, see this chart [pdf] .

• Maturational meta-theory : Maturational meta-theories can be understood using the plant as a metaphor. It is as if humans develop the same way as plants. The important thing to study is people’s “seeds,” that is, their genetic make-up. People are assumed to be passive, the product of their genes. The environment can provide support and nutrition (rain, sun, and soil), but can’t change a person’s nature (poppy seeds will always produce poppies). The role of the person is to be reactive—to their genes. The course of development will be continuous or discontinuous depending on the genetic program, although acorns always grow into oak trees.
• Mechanistic meta-theory : Mechanistic meta-theories can be understood using the machine as a metaphor. It is as if humans change the same way as machines. People are assumed to be made up of pieces that can be studied apart from the rest of them. They are passive, with the energy coming from outside (like gasoline for a car). Development is continuous and people do not develop into something else (a car stays a car). The person can only react to the environment that is controlling them (like a car responding to the gas pedal or the brake). All causes for development come from the outside, from environmental forces.
• Organismic meta-theory : Organismic meta-theories can be understood using the butterfly as a metaphor. It is as if humans develop the same way as butterflies. People are assumed to be made up of structured wholes. Their nature is to be curious, interested, and open to growth. They are active and develop through discontinuous qualitatively different stages (like the caterpillar, chrysalis, and butterfly). People construct their own next steps in development based on the affordances and opportunities provided by the environment. Development is caused by imbalances that lead to structural reorganizations. Development is progressive (gets better) and only goes in one direction (from caterpillar toward butterfly) and not the reverse.
• Contextual meta-theory : Contextual meta-theories can be understood using the tennis game (or dance) as a metaphor. It is as if humans’ development is like a game of tennis or a dance. The important thing to study is the back and forth between the person and his or her context, both of which are assumed to be proactive and acting on their own agendas. Development can be continuous or discontinuous depending on how the game is played. Both person and environment are active partners in the system, which can lead to transformations in both.

What are examples of theories that fall within each meta-theory?

Nested within each higher-order meta-theory are sets of lower-level approaches or theories called “families” of perspectives or theories to denote that they share common properties, based on their similarity to the root metaphors and characteristics of the guiding meta-theories. This table contains several examples of “big” theories of development and provides an analysis of their defining features according to the meta-theoretical assumptions we have been discussing [pdf]. Based on this analysis, we indicate the higher-order family to which we think each big theory or approach belongs.

Although maturational meta-theories were prevalent in the beginning of the 20th century, their popularity has waxed and waned since then, and they have taken on many different forms. These include some formulations of behavioral genetics, sociobiology, evolutionary, ethological, neuroscience, temperament, and personality theories. Maturational assumptions are signaled by concepts such as “trait,” the search for “the aggression gene,” the discovery of the brain system, hormone, or neurotransmitter responsible for a specific condition, or any other terms that suggest development is solely the product of innate or immutable characteristics of individuals. Although they are not typically referred to as “maturational,” there are many kinds of theories that place all the active ingredients of behavior or development inside the head (or more specifically the social cognitions) of the person. Even if they are not direct descendants, these theories can be considered cousins of Maturational meta-theories because they are exclusively focused on the role of the individual.

The prototypic Mechanistic theories are behaviorist, operant, and classical conditioning learning theories, like social learning theory. This family of theories dominated psychology from the early to the mid-20th century, but Mechanistic theories are still alive and well in many areas, such as learning and motivation, and especially in many theories that have been adapted for use in educational systems. New kinds of machines serve as prototypes for mechanistic theories of memory, learning, and automatic functioning—focusing on the computer, the robot, and the automaton. Such assumptions have even pervaded our understanding of biological systems, as seen in metaphors like “the brain is a computer.” And although the “cognitive revolution” was supposed to have overthrown behaviorist assumptions, some cognitivistic theories treat humans as if they were information processing machines.

Perhaps surprisingly, there are also mechanistic assumptions embedded in certain progressive analyses of the effects of societal and social conditions, such as poverty, oppression, racism, and discrimination, which sometimes seem to imply that these external forces are the sole determinants of the development of stereotypes or implicit attitudes. In this case, because all people are presumed to passively internalize these societal prejudices, psychological phenomena are modeled after the metaphor of the “Xerox machine.” Just as in Maturational meta-theories, where humans could be seen as “hosts” to their genes, who were really running the show, in Mechanistic meta-theories, humans can be seen as “hosts” to their own behaviors, which are automatically reflexively produced based on previous social programming.

The prototypical Organismic theory is Piaget’s constructivist theory of cognitive and affective development, and the several neo-constructivist theories that were inspired by Piaget, for example, Kohlberg’s theory of the development of moral reasoning. Other theories living under the Organismic umbrella include Werner’s comparative psychology, focusing on the orthogenetic principle of differentiation and integration, and Erikson, who posited universal age-graded developmental tasks. Other theories that claim kinship with Organismic meta-theories (e.g., theories of intrinsic motivation) do not typically include notions of universal stages or tasks, but focus instead on Organismic assumptions about the nature of humans, specifically, that humans are innately active, curious, and interested, and inherently desire to explore, understand, and fit in with their social and physical environments. With the rise of radical contextualism and cultural relativism in psychology, theories of “universal” anything (e.g., psychological needs, stages, developmental tasks) have come increasingly under attack.

Some of the better-known members of the Contextualist family include Bronfenbrenner’s bio-ecological model and the lifespan approach, both of which arose in reaction to dominant meta-theories of their day (experimental child psychology and Piagetian psychology, respectively), with their almost exclusive focus on the child as a developing individual. The “contextualist” moniker reflects these perspectives’ insistence that development unfolds within and is shaped by higher-order multi-level ecological or contextual forces outside the individual, such as microsystem settings, and societal, cultural, and historical contexts.

Does the field of psychology have meta-theories?

During different historical periods, specific meta-theories dominated the field of psychology. For example, during the 1940s and 1950s, behaviorism held sway. In the 1960s, Piaget’s theories were introduced to the United States and captured the field’s attention. Some fierce theoretical and empirical battles were fought between behaviorists and Piagetians.

When a specific meta-theory governs the field, it becomes very difficult for researchers from opposing meta-theories to work—they have trouble getting funding, they have trouble getting their research findings published, and they are marginalized by other researchers. For example, when the area of motivation was dominated by behaviorists (who believed that all behavior was motivated by rewards and punishments), it was very difficult for researchers to study and publish research on intrinsic motivation.

What is the dominant meta-theory in the field today?

“Cognitivism” is a guiding meta-theory in the field of psychology today. “Cognitivism” is the assumption that all the causal factors that shape human behavior and development are inside the mind or belief system of the person. You can hear the assumptions in the theories of the field: self-efficacy, self-esteem, attributions, perceived social support, values, sense of purpose, goal orientations, internal working model, identity, and so on.

The paradigm that is currently taking over the field of psychology is neuroscience . That is, the brain is in charge of behavior, and neurobiology is destiny. Some branches of neuroscience are predominantly Maturational , as seen in discussions of the brain systems responsible for certain actions, predilections, and characteristics. Other branches are more Contextual , for example, research on neuroplasticity, which examines the way that social contexts and interactions shape the developing brain.

News flash : In the field of psychology outside developmental, most researchers assume that people don’t develop. In personality, social, cognitive, and industrial-organizational psychology, researchers largely examine individual differences as indicators of people’s permanent characteristics.

Who else has meta-theories?

Everyone has meta-theories about human nature and development: parents, teachers, nurses, social workers, doctors, business people, artists, politicians, and so on.

For example,

• doctors assume that weight loss is all about diet and exercise (nurture), so no one can do research on physiological differences in metabolism (nature).
• teachers have assumptions about whether students come with motivation (nature) or have to be motivated from the outside (nurture), and organize their classrooms accordingly.
• parents often argue about the nature of children’s development, whether it’s just the child’s personality (maturational), or the child is going through a normal stage (organismic), or if they are rewarding the wrong behavior (mechanistic).

What is the meta-theory that guides our class and this book?

Our class endorses a life-span perspective on human development, a contextualist perspective that fought its way through the dominant perspectives in child psychology (e.g., development ends at age 18), starting in the 1980s to become one of the dominant meta-theories governing the field of developmental science today. Note that your instructors chose your book, so their meta-theory is influencing the meta-theoretical filter through which you are learning about development.

What is the correct meta-theory?

There is no single correct definition of development or meta-theory. Really. Even the lifespan approach has its drawbacks.

However, as research accumulates, many theories derived from certain meta-theories have been found to be incomplete—so far researchers have not found any significant aspect of development that is caused only by nature or only by nurture. Therefore, most researchers currently say they favor interactionist metatheories, like contextualist or systems meta-theories. However, it is important to look carefully at researchers’ actual work, because sometimes they say that they have one meta-theory, but their work seems to be guided by assumptions from a different meta-theory.

Do I have a meta-theory about development?

Yes, you do. And you can figure out what it is. Although it’s not easy, you can discern your own assumptions about development—by thinking about which assumptions make the most sense to you. You can also see which kinds of theories you prefer and what kinds of recommendations you would make about how to structure development, like how people should parent, teach, or make policies. The hardest part about discovering your own meta-theory is realizing that it is made up of assumptions you have (based on your experiences and messages from society)—that aren’t necessarily true. Our meta-theories sure seem true to each of us!

How do I get rid of my meta-theory?

It’s not really possible to get rid of all of our assumptions. It is our goal to be aware of our own assumptions or meta-theories, to realize that they are not the truth but are our current working models of how the world operates and people develop. The most important thing is to be explicit about our assumptions and to be cognizant of how they are guiding our actions. It is a goal of this class to help students figure out their own assumptions and to help them become (or remain) open to alternative viewpoints.

Adapted from : Ellen Skinner, Glen Richardson, Jennifer Pitzer, and Cynthia Taylor. Portland State University. July 2011.

Historical Theories of Development

Preformationist View : Well into the 18th century, children were merely thought of as little adults. Preformationism , or the belief that a tiny, fully formed human is implanted in the sperm or egg at conception and then grows in size until birth, was the predominant early theory. Children were believed to possess all their sensory capabilities, emotions, and mental aptitude at birth, and as they developed these abilities unfolded on a predetermined schedule (Thomas, 1979). The environment was thought to play no role in determining development .

John Locke (1632-1704): Locke, a British philosopher, refuted the idea of innate knowledge and instead proposed that children are largely shaped by their social environments, especially their education as adults teach them important knowledge. He believed that through education a child learns socialization, or what is needed to be an appropriate member of society. Locke advocated thinking of a child’s mind as a tabula rasa or blank slate , and whatever comes into the child’s mind comes from the environment. Locke emphasized that the environment is especially powerful in the child’s early life because he considered the mind the most pliable then. Locke indicated that the environment exerts its effects through associations between thoughts and feelings, behavioral repetition, imitation, and rewards and punishments (Crain, 2005). Locke’s ideas laid the groundwork for the behavioral perspective and subsequent learning theories of Pavlov, Skinner and Bandura.

Jean-Jacques Rousseau (1712-1778): Like Locke, Rousseau also believed that children were not just little adults. However, he did not believe they were blank slates, but instead developed according to a natural plan which unfolded in different stages (Crain, 2005). He did not believe in teaching them the correct way to think, but believed children should be allowed to think by themselves according to their own ways and an inner, biological timetable. This focus on biological maturation resulted in Rousseau being considered the father of developmental psychology. Followers of Rousseau’s developmental perspective include Gesell, Montessori, and Piaget.

Arnold Gesell (1880-1961): Gesell spent 50 years at the Yale Clinic of Child Development, and with his colleagues he studied the neuromotor development of children. Gesell believed that the child’s development was activated by genes and he called this process maturation (Crain, 2005). Further, he believed that development unfolded in fixed sequences, and he opposed efforts to teach children ahead of schedule as he believed they will engage in behaviors when their nervous systems had sufficiently matured.

Sigmund Freud (1856-1939): Freud was a very influential figure in the area of development. Freud emphasized the importance of early childhood experiences in shaping our personality and behavior. In our natural state, we are biological beings and are driven primarily by instincts. During childhood, however, we begin to become social beings as we learn how to manage our instincts and transform them into socially acceptable behaviors. His assumptions were that personality formed during the first few years of life. The ways in which parents or other caregivers interacted with children were assumed to have a long-lasting impact on children’s emotional states. His beliefs formed the psychodynamic perspective and his theories of psychosexual development and psychopathology dominated the field of psychiatry until the growth of behaviorism in the 1950s.

However, Freud’s theory has been heavily criticized for several reasons. One is that it is very difficult to test scientifically (Crews, 1998). Freud suggested that much of what determines our actions were unknown to us, and as scientists we cannot measure these unconscious concepts. A second criticism is that Freud’s case studies were not validated and cannot be used as evidence for his theories. Many later theories, particularly behaviorism and humanism, came about as challenges to Freud’s views.

Contemporary Theories on Development

Erikson (1902-1994) and Psychosocial Theory: Now, let’s turn to a less controversial psychodynamic theorist, Erik Erikson. Erikson presents eight developmental stages that encompass the entire lifespan. For that reason, Erikson’s psychosocial theory forms the foundation for much of our discussion of psychosocial development.

Erikson (1950) proposed a model of lifespan development that provides a useful guideline for thinking about the changes we experience throughout life. Erikson broke with Freud’s emphasis on sexuality as the cornerstone of social-emotional development and instead suggested that social relationships fostered development. Erikson proposed that each period of life has a unique challenge or crisis that the person who reaches it must face, referred to as psychosocial crises . According to Erikson, successful development involves dealing with and resolving the goals and demands of each of these psychosocial crises in a positive way. These crises are usually called stages, although that is not the term Erikson used. If a person does not resolve a stage successfully, it may hinder their ability to deal with later stages. For example, the person who does not develop a sense of trust (Erikson’s first stage) may find it challenging as an adult to form a positive intimate relationship (Erikson’s sixth stage). Or an individual who does not develop a clear sense of purpose and identity (Erikson’s fifth stage) may become self-absorbed and stagnate rather than work toward the betterment of others (Erikson’s seventh stage).

However, most individuals are able to successfully complete the eight stages of his theory (See Table 1.3).

Table 1.3 Erikson's Psychosocial Stages

Erikson’s theory has been criticized for focusing so heavily on crises and assuming that the completion of one crisis is a prerequisite for the next crisis of development. His theory also focused on the social expectations that are found in certain cultures, but not in all. For instance, the idea that adolescence is a time of searching for identity might translate well in the middle-class culture of the United States, but not as well in cultures where the transition into adulthood coincides with puberty through rites of passage and where adult roles offer fewer choices.

Learning Theory: Also known as Behaviorism , is based on the premise that it is not possible to objectively study the mind, and therefore psychologists should limit their attention to the study of behavior itself. The most famous behaviorist was Burrhus Frederick (B. F.) Skinner (1904–1990), who expanded the principles of behaviorism and also brought them to the attention of the public at large. Skinner used the ideas of stimulus and response, along with the application of rewards or reinforcements, to train pigeons and other animals. In addition, he used the general principles of behaviorism to develop theories about how best to teach children and how to create societies that were peaceful and productive (Skinner, 1957, 1968, 1972).

The behaviorists made substantial contributions to psychology by identifying the principles of learning. Although the behaviorists were incorrect in their beliefs that it was not possible to measure thoughts and feelings, their ideas provided new insights that helped further our understanding regarding the nature-nurture debate as well as the question of free will. The ideas of behaviorism are fundamental to psychology and have been developed to help us better understand the role of prior experiences in a variety of areas of psychology.

Social Learning Theory , or learning by watching others , was developed by Albert Bandura (1977). His theory calls our attention to the ways in which many of our actions are not learned through conditioning, as suggested by Skinner . Young children frequently learn behaviors through imitation. Especially when children do not know what else to do, they learn by modeling or copying the behavior of others.

Bandura (1986) suggests that there is interplay between the environment and the individual. We are not just the product of our surroundings, rather we influence our surroundings. There is interplay between our personality and the way we interpret events and how they influence us. This concept is called reciprocal determinism . An example of this might be the interplay between parents and children. Parents not only influence their child’s environment, perhaps intentionally through the use of reinforcement, etc., but children influence parents as well. Parents may respond differently with their first child than with their fourth. Perhaps they try to be the perfect parents with their firstborn, but by the time their last child comes along they have very different expectations, both of themselves and their child. Our environment creates us and we create our environment.

Other social influences: TV or not TV? Bandura, Ross and Ross (1963) began a series of studies to look at the impact of television on the behavior of children. Bandura began by conducting an experiment in which he showed children a film of a woman hitting an inflatable clown or “bobo” doll. Then the children were allowed in the room, where they found the doll and during their play they began to hit it. The children also demonstrated novel ways of being aggressive toward the doll that were not demonstrated by those children who did not see the aggressive model. Bandura’s research raised concerns about the impact of violence on young children. Since then, considerable research has been conducted on the impact of violent media on children’s aggression including playing video games.

Cognitive Theory: The cognitive theories focus on how our mental processes or cognitions change over time . Three important theories are Jean Piaget’s, Lev Vygotsky’s, and Information-processing.

Jean Piaget (1896-1980) was one of the most influential cognitive theorists in development. He was inspired to explore children’s ability to think and reason by watching his own children’s development. He was one of the first to recognize and map out the ways in which children’s intelligence differs from that of adults (Piaget, 1929). He became interested in this area when he was asked to test the IQ of children and began to notice that there was a pattern in their wrong answers. He believed that children’s intellectual skills change over time and that maturation, rather than training, brings about that change. Children of differing ages interpret the world differently. Piaget theorized that children progressed through four stages of cognitive development (see Table 1.4).

Table 1.4 Piaget's Stages of Cognitive Development

Piaget has been criticized for overemphasizing the role that physical maturation plays in cognitive development and in underestimating the role that culture and experience plays. Looking across cultures reveals considerable variation in what children are able to do at various ages. Research has shown considerable overlap among the four stages and that development is more continuous.

Lev Vygotsky (1896-1934) was a Russian psychologist who wrote in the early 1900s, but whose work was not discovered by researchers in the United States until the 1960s and became more widely known in the 1980s (Crain, 2005). His sociocultural theory emphasizes the importance of culture and interaction in the development of cognitive abilities . Vygotsky differed with Piaget in that he believed that a person not only has a set of abilities, but also a set of potential abilities that can be realized if given the proper guidance from others. Vygotsky developed theories on teaching that have been adopted by educators today.

Information Processing is not the work of a single theorist, but based on the ideas and research of several cognitive scientists studying how individuals perceive, analyze, manipulate, use, and remember information . This approach assumes that humans gradually improve in their processing skills; that is, cognitive development is continuous rather than stage-like. The more complex mental skills of adults are built from the primitive abilities of children. We are born with the ability to notice stimuli, store, and retrieve information. Brain maturation enables advancements in our information processing system. At the same time, interactions with the environment also aid in our development of more effective strategies for processing information.

Urie Bronfenbrenner (1917-2005) developed the Ecological Systems Theory , which provides a framework for understanding and studying the many influences on human development (Bronfenbrenner, 1979). Bronfenbrenner recognized that human interaction is influenced by larger social forces and that an understanding of these forces is essential for understanding an individual. The individual is impacted by several systems including:

• Microsystem includes the individual’s setting and those who have direct, significant contact with the person, such as parents or siblings . The input of those is modified by the cognitive and biological state of the individual as well. These influence the person’s actions, which in turn influence systems operating on him or her.
• Mesosystem includes the larger organizational structures, such as school, the family, or religion. These institutions impact the microsystems just described. The philosophy of the school system, daily routine, assessment methods, and other characteristics can affect the child’s self-image, growth, sense of accomplishment, and schedule thereby impacting the child, physically, cognitively, and emotionally.
• Exosystem includes the larger contexts of community . A community’s values, history, and economy can impact the organizational structures it houses. Mesosystems both influence and are influenced by the exosystem.
• Macrosystem includes the cultural elements, such as global economic conditions, war, technological trends, values, philosophies, and a society’s responses to the global community.
• Chronosystem is the historical context in which these experiences occur. This relates to the different generational time periods previously discussed, such as the baby boomers and millennials.

In sum, a child’s experiences are shaped by larger forces, such as the family, schools, religion, culture, and time period. Bronfenbrenner’s model helps us understand all of the different environments that impact each one of us simultaneously. Despite its comprehensiveness, Bronfenbrenner’s ecological system’s theory is not easy to use. Taking into consideration all the different influences makes it difficult to research and determine the impact of all the different variables (Dixon, 2003). Consequently, psychologists have not fully adopted this approach, although they recognize the importance of the ecology of the individual. Figure 1.9 is a model of Bronfenbrenner’s Ecological Systems Theory.

Figure 1.9. Bronfenbrenner’s Ecological Systems Theory

Supplemental Materials

• This article discusses the importance of critical reflection on the underlying assumptions of developmental psychology as a science.

Teo, T. (1997). Developmental Psychology and the Relevance of a Critical Metatheoretical Reflection. Human Development, 40 (4), 195–210. https://doi.org/10.1159/000278723

Baltes, P. B. (1987). Theoretical propositions of life span developmental psychology: On the dynamics between growth and decline. Developmental Psychology, 23, 611-626.

Baltes, P. B., Lindenberger, U., & Staudinger, U. M. (2006). Life span theory in developmental psychology. In W. Damon, & R. M. Lerner (Eds.), Handbook of child psychology , 6th edition (pp. 569-664). Hoboken, NJ: John Wiley & Sons.

Bandura, A. (1977). Social learning theory . New York: General Learning Press.

Bandura, A. (1986). Social foundations of thought and action: A social-cognitive theory . Upper Saddle River, NJ: Prentice Hall.

Bandura, A, Ross, D. &. Ross S. (1963). Imitation of film-mediated aggressive models. Journal of Abnormal and Social Psychology, 66 , 3-11.

Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design . Cambridge, MA: Harvard University Press.

Crain, W. (2005). Theories of development concepts and applications (5th ed.). New Jersey: Pearson.

Crews, F. C. (1998). Unauthorized Freud: Doubters confront a legend . New York, NY: Viking Press.

Dixon, W. E. (2003). Twenty studies that revolutionized child psy chology. Upper Saddle River, NJ: Prentice Hall.

Erikson, E. H. (1950). Childhood and society . New York: Norton.

Guinness World Records. (2016). Oldest person (ever). Retrieved from http://www.guinnessworldrecords.com/search?term=oldest+person+%28ever%29

Neugarten, B. L. (1979). Policy for the 1980s: Age or need entitlement? In J. P. Hubbard (Ed.), Aging: Agenda for the eighties, a national journal issues book (pp. 48-52). Washington, DC: Government Research Corporation.

Neugarten, D. A. (Ed.) (1996). The meanings of age . Chicago, IL: The University of Chicago Press.

Piaget, J. (1929). The child’s conception of the world . NY: Harcourt, Brace Jovanovich.

Smithsonian National Zoo. (2016). Retrieved from http://nationalzoo.si.edu/

Skinner, B. (1957). Verbal behavior . Acton, MA: Copley.

Skinner, B. (1968). The technology of teaching . New York, NY: Appleton-Century-Crofts.

Skinner, B. (1972). Beyond freedom and dignity . New York, NY: Vintage Books.

Thomas, R. M. (1979). Comparing theories of child development . Santa Barbara, CA: Wadsworth.

United States Census Bureau. (2016). Povert y. Retrieved from http://www.census.gov/topics/income-poverty/poverty/about/glossary.html

Vogt, W.P., & Johnson, R.B. (2016). The SAGE dictionary of statistics and methodology . Los Angeles, CA: Sage

Webb, S. J., Dawson, G., Bernier, R., & Panagiotides, H. (2006). ERP evidence of atypical face processing in young children with autism. Journal of Autism and Developmental Disorders, 36 , 884-890. doi: 10.1007/s10803-006-0126-x

Weitz, R. (2007). The sociology of health, illness, and health care: A critical approach, (4th ed.). Belmont, CA: Thomson.

OER Attribution: “Lifespan Development: A Psychological Perspective, Second Edition” by Martha Lally and Suzanne Valentine-French is licensed under a CC-BY-NC-SA-3.0

Additional written material (Meta-theories of Human Development) by Ellen Skinner, Glen Richardson, Jennifer Pitzer, and Cynthia Taylor, Portland State University is licensed under a CC BY-NC-SA 4.0 .

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Lessons from the longest study on human development - helen pearson.

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For the past 70 years, scientists in Britain have been studying thousands of children through their lives to find out why some end up happy and healthy while others struggle - in fact, it's the longest-running study of human development in the world. Reviewing this remarkable research, science journalist Helen Pearson shares some important findings and simple truths about life and good parenting.

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What the Longest Study on Human Happiness Found Is the Key to a Good Life

The Harvard Study of Adult Development has established a strong correlation between deep relationships and well-being. The question is, how does a person nurture those deep relationships?

This article was featured in One Story to Read Today, a newsletter in which our editors recommend a single must-read from The Atlantic , Monday through Friday. Sign up for it here.       

T urn your mind for a moment to a friend or family member you cherish but don’t spend as much time with as you would like. This needn’t be your most significant relationship, just someone who makes you feel energized when you’re with them, and whom you’d like to see more regularly.

How often do you see that person? Every day? Once a month? Once a year? Do the math and project how many hours annually you spend with them. Write this number down and hang on to it.

For us, Bob and Marc, though we work closely together and meet every week by phone or video call, we see each other in person for only a total of about two days (48 hours) every year.

How does this add up for the coming years? Bob is 71 years old. Marc is 60. Let’s be (very) generous and say we will both be around to celebrate Bob’s 100th birthday. At two days a year for 29 years, that’s 58 days that we have left to spend together in our lifetimes.

Fifty-eight out of 10,585 days.

Of course, this is assuming a lot of good fortune, and the real number is almost certainly going to be lower.

Since 1938, the Harvard Study of Adult Development has been investigating what makes people flourish. After starting with 724 participants—boys from disadvantaged and troubled families in Boston, and Harvard undergraduates—the study incorporated the spouses of the original men and, more recently, more than 1,300 descendants of the initial group. Researchers periodically interview participants, ask them to fill out questionnaires, and collect information about their physical health. As the study’s director (Bob) and associate director (Marc), we’ve been able to watch participants fall in and out of relationships, find success and failure at their jobs, become mothers and fathers. It’s the longest in-depth longitudinal study on human life ever done, and it’s brought us to a simple and profound conclusion: Good relationships lead to health and happiness. The trick is that those relationships must be nurtured.

From the June 2009 issue: What makes us happy?

We don’t always put our relationships first. Consider the fact that the average American in 2018 spent 11 hours every day on solitary activities such as watching television and listening to the radio. Spending 58 days over 29 years with a friend is infinitesimal compared with the 4,851 days that Americans will spend interacting with media during that same time period. Distractions are hard to avoid.

Thinking about these numbers can help us put our own relationships in perspective. Try figuring out how much time you spend with a good friend or family member. We don’t have to spend every hour with our friends, and some relationships work because they’re exercised sparingly. But nearly all of us have people in our lives whom we’d like to see more. Are you spending time with the people you most care about? Is there a relationship in your life that would benefit both of you if you could spend more time together? Many of these are untapped resources, waiting for us to put them to use. And, enriching these relationships can in turn nourish our minds and bodies.

Y ou don’t have to examine scientific findings to recognize that relationships affect you physically. All you have to do is notice the invigoration you feel when you believe that someone has really understood you during a good conversation, or the tension and distress you feel after an argument, or how little sleep you get during a period of romantic strife.

In this sense, having healthy, fulfilling relationships is its own kind of fitness—social fitness—and like physical fitness, it takes work to maintain. Unlike stepping on the scale, taking a quick look in the mirror, or getting readouts for blood pressure and cholesterol, assessing our social fitness requires a bit more sustained self-reflection. It requires stepping back from the crush of modern life, taking stock of our relationships, and being honest with ourselves about where we’re devoting our time and whether we are tending to the connections that help us thrive. Finding the time for this type of reflection can be hard, and sometimes it’s uncomfortable. But it can yield enormous benefits.

Many of our Harvard Study participants have told us that filling out questionnaires every two years and being interviewed regularly have given them a welcome perspective on their life and relationships. We ask them to really think about themselves and the people they love, and that process of self-reflection helps some of them.

Read: 10 practical ways to improve happiness

This is a practice that could help anyone. Looking in the mirror and thinking honestly about where your life stands is a first step in trying to live a good life. Noticing where you are can help put into relief where you would like to be. Having some reservations about this kind of self-reflection is understandable. Our study participants were not always keen on filling out our questionnaires, or eager to consider the larger picture of their life. Some would skip difficult questions or leave entire pages blank, and some would just not return certain surveys. Some even wrote comments in the margins of their questionnaires about what they thought of our requests. “What kinds of questions are these!?” is a response we received occasionally, often from participants who preferred not to think about difficulties in their life. The experiences of the people who skipped questions or entire questionnaires were also important, though—they were just as crucial in understanding adult development as the experiences of people eager to share. A lot of useful data and gems of experience were buried in the shadowed corners of their lives. We just had to go through a little extra effort to excavate them.

One of these people was a man we’ll call Sterling Ainsley. (We are using a pseudonym to protect his confidentiality as a study participant.)

S terling Ainsley was a hopeful guy. He graduated from Harvard in the 1940s and then served in World War II. After he left the service, he got a job as a scientist and retired in his 60s. When asked to describe his philosophy for getting through hard times, he said, “You try not to let life get to you. You remember your victories and take a positive attitude.”

The year was 1986. George Vaillant, the then-director of the study, was on a long interview trek, driving through the Rocky Mountains to visit the study’s participants who lived in Colorado, Utah, Idaho, and Montana. Sterling had not returned the most recent survey, and there was some catching up to do. He met Vaillant at a hotel to give him a ride to the diner where Sterling wanted to do his scheduled interview. When Vaillant buckled himself into the passenger seat of Sterling’s car, the seat belt left a stripe of dust across his chest. “I was left to wonder,” he wrote, “the last time somebody had used it.”

Sterling was technically married, but his wife lived far away, and they hadn’t slept in the same room in years. They spoke only every few months.

Read: The six forces that fuel friendship

When asked why they had not gotten a divorce, he said, “I wouldn’t want to do that to the children,” even though his kids were grown and had children of their own. Sterling was proud of his kids and beamed when he spoke of them, saying they were the most important thing in his life. But he rarely saw them and seemed to prefer to keep his relationships with them thriving mostly in his imagination. Vaillant noted that Sterling seemed to be using optimism to push away some of his fears and avoid challenges in his life. Putting a positive spin on every matter and then pushing it out of his mind made it possible for him to believe that nothing was wrong, he was fine, he was happy, his kids didn’t need him.

He didn’t travel to see his son’s new home abroad, because he didn’t “want to be a burden”—even though he’d been learning a new language to prepare for the trip. He had another child who lived closer, but he hadn’t visited in more than a year. He didn’t have a relationship with his grandchildren, and he wasn’t in contact with any friends.

When asked about his older sister, Sterling seemed startled. “My sister?” he said.

Yes, the sister he had told the study so much about when he was younger.

Sterling thought about it for a long time, and then told Vaillant that it must have been decades since he last spoke with her. A frightened expression came over his face. “Would she still be living?” he said.

Sterling tried not to think about his relationships, and he was even less inclined to talk about them. This is a common experience. We don’t always know why we do things or why we don’t do things, and we may not understand what is holding us at a distance from the people in our life. Taking some time to look in the mirror can help. Sometimes there are needs inside of us that are looking for a voice, a way to get out. They might be things that we have never seen or articulated to ourselves.

This seemed to be the case with Sterling. Asked how he spent his evenings, he said he spent time with an elderly woman who lived in a nearby trailer. Each night he would walk over, and they’d watch TV and talk. Eventually she would fall asleep, and he would help her into bed and wash her dishes and close the shades before walking home. She was the closest thing he had to a confidant.

“I don’t know what I’ll do if she dies,” he said.

Listen to Robert Waldinger in conversation with Arthur Brooks and Rebecca Rashid on "How to Build a Happy Life":

L oneliness has a physical effect on the body. It can render people more sensitive to pain, suppress their immune system, diminish brain function, and disrupt sleep, which in turn can make an already lonely person even more tired and irritable. Research has found that, for older adults, loneliness is far more dangerous than obesity. Ongoing loneliness raises a person’s odds of death by 26 percent in any given year. A study in the U.K., the Environmental Risk (E-Risk) Longitudinal Twin Study, recently reported on the connections between loneliness and poorer health and self-care in young adults. This ongoing study includes more than 2,200 people born in England and Wales in 1994 and 1995. When they were 18, the researchers asked them how lonely they were. Those who reported being lonelier had a greater chance of facing mental-health issues, partaking in unsafe physical-health behaviors, and coping with stress in negative ways. Add to this the fact that a tide of loneliness is flooding through modern societies, and we have a serious problem. Recent stats should make us take notice.

In a study conducted online that sampled 55,000 respondents from across the world, one out of every three people of all ages reported that they often feel lonely. Among these, the loneliest group were 16-to-24-year-olds, 40 percent of whom reported feeling lonely “often or very often.” In the U.K., the economic cost of this loneliness—because lonely people are less productive and more prone to employment turnover—is estimated at more than £2.5 billion (about $3.1 billion) annually and helped lead to the establishment of a U.K. Ministry of Loneliness.

Read: Why do we look down on lonely people?

In Japan, 32 percent of adults expected to feel lonely most of the time during 2020. In the United States, a 2019 study suggested that three out of four adults felt moderate to high levels of loneliness. As of this writing, the long-term effects of the coronavirus pandemic, which separated us from one another on a massive scale and left many feeling more isolated than ever, are still being studied.

Alleviating this epidemic of loneliness is difficult because what makes one person feel lonely might have no effect on someone else. We can’t rely entirely on easily observed indicators such as whether or not one lives alone, because loneliness is a subjective experience. One person might have a significant other and too many friends to count and yet feel lonely, while another person might live alone and have a few close contacts and yet feel very connected. The objective facts of a person’s life are not enough to explain why someone is lonely. Regardless of your race or class or gender, the feeling resides in the difference between the kind of social contact you want and the social contact you actually have.

I t never hurts —especially if you’ve been feeling low—to take a minute to reflect on how your relationships are faring and what you wish could be different about them. If you’re the scheduling type, you could make it a regular thing; perhaps every year on New Year’s Day or the morning of your birthday, take a few moments to draw up your current social universe, and consider what you’re receiving, what you’re giving, and where you would like to be in another year. You could keep your chart or relationships assessment in a special place, so you know where to look the next time you want to peek at it to see how things have changed.

If nothing else, doing this reminds us of what’s most important. Repeatedly, when the participants in our study reached old age, they would make a point to say that what they treasured most were their relationships. Sterling Ainsley himself made that point. He loved his older sister deeply—but he lost touch with her. Some of his fondest memories were of his friends—whom he never contacted. There was nothing he cared more about than his children—whom he rarely saw. From the outside it might look like he didn’t care. That was not the case. Sterling was quite emotional in his recounting of his most cherished relationships, and his reluctance to answer certain study questions was clearly connected to the pain that keeping his distance had caused him over the years. Sterling never sat down to really think about how he might conduct his relationships or what he might do to properly care for the people he loved most.

Sterling’s life reminds us of the fragility of our connections, and it echoes the lessons of science: Relationships keep us happier and healthier throughout our life spans. We neglect our connections with others at our peril. Investing in our social fitness is possible each day, each week of our lives. Even small investments today in our relationships with others can create long-term ripples of well-being.

This article is adapted from Robert Waldinger and Marc Schulz’s new book, The Good Life: Lessons From the World’s Longest Scientific Study of Happiness .

When you buy a book using a link on this page, we receive a commission. Thank you for supporting The Atlantic.

​When you buy a book using a link on this page, we receive a commission. Thank you for supporting The Atlantic.

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The beginning of becoming a human—insights from researchers

by Impact Journals LLC

A new review paper was published in advance by Aging , titled " The beginning of becoming a human ."

According to birth certificates, the life of a child begins once their body comes out of the mother's womb. In this new review, researchers Polina A. Loseva and Vadim N. Gladyshev from Harvard Medical School pose the controversial question: when does their organismal life begin? Science holds a palette of answers—depending on how one defines a human life.

"Debates on when human life begins are rooted deep in philosophical history. However, until recently they have been limited by the state of technology," write Loseva and Gladyshev.

In 1984, a commission on the regulatory framework for human embryo experimentation opted not to answer this question, instead setting a boundary, 14 days post-fertilization, beyond which any experiments were forbidden. Recently, as the reproductive technologies developed and the demand for experimentation grew stronger, this boundary may be set aside leaving the ultimate decision to local oversight committees.

While science has not come closer to setting a zero point for human life, there has been significant progress in our understanding of early mammalian embryogenesis. It has become clear that the 14-day stage does in fact possess features, which make it a foundational time point for a developing human. Importantly, this stage defines the separation of soma from the germline and marks the boundary between rejuvenation and aging.

"We explore how different levels of life organization emerge during human development and suggest a new meaning for the 14-day stage in organismal life that is grounded in recent mechanistic advances and insights from aging studies," say Loseva and Gladyshev.

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BRIEF RESEARCH REPORT article

This article is part of the research topic.

Early Media Exposure

Social interactions offset the detrimental effects of digital media use on children's vocabulary Provisionally Accepted

• 1 Psychology, Southern Methodist University, United States
• 2 Louisiana State University, United States

The final, formatted version of the article will be published soon.

Young children’s rapid vocabulary growth during the first few years is supported by input during social interactions with caregivers and, increasingly, from digital media. However, the amount of exposure to both sources can vary substantially across socioeconomic classes, and little is known about how social interactions and digital media use together predict vocabulary in the first few years of life. The current study takes a first step toward examining whether increased social interactions with other individuals may buffer the potentially detrimental effects of digital media use on language among a socioeconomically diverse sample. 305 caregivers of children between 17-30-months completed questionnaires about their family demographics, their child’s technology use, and the child’s daily routines and social interactions. Findings suggest children who experience fewer human interactions and greater technology exposure have smaller vocabularies than their peers who socialize more and use less technology, and this disparity becomes greater as children get older. Moreover, the number of social interactions moderates the link between SES, digital media, and vocabulary such that the negative impact of digital media on vocabulary for children from low SES households can be offset with increased social interactions. Together, this suggests that increasing the amount of human interactions may serve as a protective factor for vocabulary outcomes in a world where digital media use is prominent.

Keywords: Digital Media, Social Interactions, vocabulary, Socioeconomic status, language development

Received: 15 Mar 2024; Accepted: 09 May 2024.

Copyright: © 2024 Kucker and Schneider. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Sarah C. Kucker, Southern Methodist University, Psychology, Dallas, United States

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College of Education and Human Development

Coehd faculty, students present innovative research at annual neero conference.

Several students and faculty members from the University of Maine College of Education and Human Development attended the recent New England Educational Research Organization (NEERO) Conference in Portsmouth, New Hampshire. The three-day conference featured researchers, practitioners, activists, policymakers, students and teachers exploring the theme “Empowering the Pursuit of Educational Justice by Looking Back and Imagining Forward.”

Here’s a look at some of the presentations featuring members of the UMaine College of Education and Human Development community:

• Emily Hamby , a child development and family relations major, presented a project titled “Teacher Perspectives Post-Covid Amidst Anti-Woke Policies” at a roundtable session on “Improving Student and Teacher Support Systems in Diversity, Equity, and Inclusion.” Hamby also participated in a presentation on “Integrating Social Justice Into Instructional Planning: An Analysis of Teacher Educator Feedback” at a roundtable session on “Research Topics on Teacher Perceptions and Underrepresented Populations.” Hamby, of Andover, Massachusetts, is the recipient of 2023-24 fellowship from the University of Maine Center for Undergraduate Research , and has been working with faculty mentor Rebecca Buchanan , associate professor of curriculum, assessment and instruction.
• Melissa Lyons-Vitalone , a Doctor of Education (Ed.D.) student in educational leadership, presented on her dissertation research, “Breaking Down Barriers to Inclusion for Students.”
• Nicole Hatch , an Ed.D. student in educational leadership, presented on her dissertation research, “Enhancing Teacher Supervision Through a Therapeutic Lens: A Holistic Approach to Professional Development.”
• Ben Greenlaw , an Ed.D. student in educational leadership, presented on his dissertation research, “What Makes a Constructive Relationship Between a Principal and Superintendent?”
• Steffany Tribou , an Ed.D. student in educational leadership, presented on her dissertation research, “Motivating the Future Workforce: High School Extended Learning Opportunities.”
• Sue Sydnor , an Ed.D. student in educational leadership, presented on her dissertation research, “School Exclusionary Practices: Why Are We Still Suspending Kids?”
• Janet Hicks , an Ed.D. student in educational leadership, presented on her dissertation research, “Supporting Students of Color in a Predominantly White, Rural School System: Support and Facilitation of an Affinity Group for Students of Color.”
• Kim Andersson , an Ed.D. student in educational leadership, presented on her dissertation research, “How Top-Down Reform Efforts Impact Teachers as Adult Learners.”
• Janet Corcoran , an Ed.D. student in educational leadership, presented on her dissertation research, “Paraprofessional Supports and Student Outcomes.”
• Amy Sullivan , an Ed.D. student in educational leadership, presented on her dissertation research, “SEL Initiative Implementation and Teacher Buy-In.”
• Heather Mitchell , an Ed.D. student in educational leadership, presented on her dissertation research, “Supporting Teachers to Support Students: Studying the Impact of Staff Professional Development in the Engagement, Satisfaction, and Retention of Students in Rural Public Schools.”
• Orlina Boteva , a doctoral student in higher education and director of the Office of International Programs at UMaine, along with associate professor of higher education Leah Hakkola , presented a study titled “Addressing Secondary Trauma and Burnout in Higher Education Through an Embodied Social Justice Approach,” part of a roundtable session on “Higher Education Journeys: Mentoring, SEL and CAO Stories.”
• Assistant professor of special education Melissa Cuba , Buchanan and Hakkola presented on “Supporting DEIB Endeavors Through a Research-Practice Partnership.” The session covered both the process of developing a research-practice partnership (RPP) between the College of Education and Human Development and a school district in Maine, as well as the emerging findings of the project. The RPP was established to strengthen the district’s diversity, equity, inclusion, and belonging (DEIB) efforts. Cuba, Buchanan and Hakkola are leading a collaborative equity review that provides meaningful analysis of qualitative and quantitative data to inform future DEIB efforts within the school district. In addition, the researchers offer a series of professional development opportunities that explore aspects of intercultural competence, culturally sustaining practices and equity-oriented advocacy.
• Assistant professor of educational leadership Esther Enright participated in the presentation of a study titled “Herding Cats: Learning About Shared Governance From Faculty Senate Presidents,” part of a session on “Agency and Impacts, Governance and Belonging, the Human Side of Higher Education.”