Insights into cognitive mechanics from education, developmental psychology and cognitive science


Abstract

Humans reason implicitly and explicitly about the physical world, which enables them to successfully interact with and manipulate objects in their environment. This reasoning is studied under different names across three main literatures: education, developmental psychology and cognitive science. At a high level, education researchers examine the acquisition of formal scientific knowledge, developmental psychologists explore children’s emerging understanding of their physical surroundings and cognitive scientists analyse the structure of the mind. These different disciplines have reached divergent conclusions about what children and adults know about ‘cognitive mechanics’ and developed parallel scientific theories of these phenomena. In this Review, we describe the findings of these three literatures and conclude that each literature contributes robust and reliable findings that must be taken seriously even when they seem to be contradictory. We suggest that further progress requires reconciling these literatures; one avenue is to consider multiple interlocking cognitive mechanisms that are differentially engaged across scenarios and across development. Finally, we outline a research programme to further reconcile these literatures.

This is a preview of subscription content, access via your institution

Access options

/* style specs start */

/* style specs end */

Buy this article

Buy now

Prices may be subject to local taxes which are calculated during checkout

/* style specs start */
style {
display: none !important;
}
.LiveAreaSection * {
align-content: stretch;
align-items: stretch;
align-self: auto;
animation-delay: 0s;
animation-direction: normal;
animation-duration: 0s;
animation-fill-mode: none;
animation-iteration-count: 1;
animation-name: none;
animation-play-state: running;
animation-timing-function: ease;
azimuth: center;
backface-visibility: visible;
background-attachment: scroll;
background-blend-mode: normal;
background-clip: borderBox;
background-color: transparent;
background-image: none;
background-origin: paddingBox;
background-position: 0 0;
background-repeat: repeat;
background-size: auto auto;
block-size: auto;
border-block-end-color: currentcolor;
border-block-end-style: none;
border-block-end-width: medium;
border-block-start-color: currentcolor;
border-block-start-style: none;
border-block-start-width: medium;
border-bottom-color: currentcolor;
border-bottom-left-radius: 0;
border-bottom-right-radius: 0;
border-bottom-style: none;
border-bottom-width: medium;
border-collapse: separate;
border-image-outset: 0s;
border-image-repeat: stretch;
border-image-slice: 100%;
border-image-source: none;
border-image-width: 1;
border-inline-end-color: currentcolor;
border-inline-end-style: none;
border-inline-end-width: medium;
border-inline-start-color: currentcolor;
border-inline-start-style: none;
border-inline-start-width: medium;
border-left-color: currentcolor;
border-left-style: none;
border-left-width: medium;
border-right-color: currentcolor;
border-right-style: none;
border-right-width: medium;
border-spacing: 0;
border-top-color: currentcolor;
border-top-left-radius: 0;
border-top-right-radius: 0;
border-top-style: none;
border-top-width: medium;
bottom: auto;
box-decoration-break: slice;
box-shadow: none;
box-sizing: border-box;
break-after: auto;
break-before: auto;
break-inside: auto;
caption-side: top;
caret-color: auto;
clear: none;
clip: auto;
clip-path: none;
color: initial;
column-count: auto;
column-fill: balance;
column-gap: normal;
column-rule-color: currentcolor;
column-rule-style: none;
column-rule-width: medium;
column-span: none;
column-width: auto;
content: normal;
counter-increment: none;
counter-reset: none;
cursor: auto;
display: inline;
empty-cells: show;
filter: none;
flex-basis: auto;
flex-direction: row;
flex-grow: 0;
flex-shrink: 1;
flex-wrap: nowrap;
float: none;
font-family: initial;
font-feature-settings: normal;
font-kerning: auto;
font-language-override: normal;
font-size: medium;
font-size-adjust: none;
font-stretch: normal;
font-style: normal;
font-synthesis: weight style;
font-variant: normal;
font-variant-alternates: normal;
font-variant-caps: normal;
font-variant-east-asian: normal;
font-variant-ligatures: normal;
font-variant-numeric: normal;
font-variant-position: normal;
font-weight: 400;
grid-auto-columns: auto;
grid-auto-flow: row;
grid-auto-rows: auto;
grid-column-end: auto;
grid-column-gap: 0;
grid-column-start: auto;
grid-row-end: auto;
grid-row-gap: 0;
grid-row-start: auto;
grid-template-areas: none;
grid-template-columns: none;
grid-template-rows: none;
height: auto;
hyphens: manual;
image-orientation: 0deg;
image-rendering: auto;
image-resolution: 1dppx;
ime-mode: auto;
inline-size: auto;
isolation: auto;
justify-content: flexStart;
left: auto;
letter-spacing: normal;
line-break: auto;
line-height: normal;
list-style-image: none;
list-style-position: outside;
list-style-type: disc;
margin-block-end: 0;
margin-block-start: 0;
margin-bottom: 0;
margin-inline-end: 0;
margin-inline-start: 0;
margin-left: 0;
margin-right: 0;
margin-top: 0;
mask-clip: borderBox;
mask-composite: add;
mask-image: none;
mask-mode: matchSource;
mask-origin: borderBox;
mask-position: 0 0;
mask-repeat: repeat;
mask-size: auto;
mask-type: luminance;
max-height: none;
max-width: none;
min-block-size: 0;
min-height: 0;
min-inline-size: 0;
min-width: 0;
mix-blend-mode: normal;
object-fit: fill;
object-position: 50% 50%;
offset-block-end: auto;
offset-block-start: auto;
offset-inline-end: auto;
offset-inline-start: auto;
opacity: 1;
order: 0;
orphans: 2;
outline-color: initial;
outline-offset: 0;
outline-style: none;
outline-width: medium;
overflow: visible;
overflow-wrap: normal;
overflow-x: visible;
overflow-y: visible;
padding-block-end: 0;
padding-block-start: 0;
padding-bottom: 0;
padding-inline-end: 0;
padding-inline-start: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
page-break-after: auto;
page-break-before: auto;
page-break-inside: auto;
perspective: none;
perspective-origin: 50% 50%;
pointer-events: auto;
position: static;
quotes: initial;
resize: none;
right: auto;
ruby-align: spaceAround;
ruby-merge: separate;
ruby-position: over;
scroll-behavior: auto;
scroll-snap-coordinate: none;
scroll-snap-destination: 0 0;
scroll-snap-points-x: none;
scroll-snap-points-y: none;
scroll-snap-type: none;
shape-image-threshold: 0;
shape-margin: 0;
shape-outside: none;
tab-size: 8;
table-layout: auto;
text-align: initial;
text-align-last: auto;
text-combine-upright: none;
text-decoration-color: currentcolor;
text-decoration-line: none;
text-decoration-style: solid;
text-emphasis-color: currentcolor;
text-emphasis-position: over right;
text-emphasis-style: none;
text-indent: 0;
text-justify: auto;
text-orientation: mixed;
text-overflow: clip;
text-rendering: auto;
text-shadow: none;
text-transform: none;
text-underline-position: auto;
top: auto;
touch-action: auto;
transform: none;
transform-box: borderBox;
transform-origin: 50% 50%0;
transform-style: flat;
transition-delay: 0s;
transition-duration: 0s;
transition-property: all;
transition-timing-function: ease;
vertical-align: baseline;
visibility: visible;
white-space: normal;
widows: 2;
width: auto;
will-change: auto;
word-break: normal;
word-spacing: normal;
word-wrap: normal;
writing-mode: horizontalTb;
z-index: auto;
-webkit-appearance: none;
-moz-appearance: none;
-ms-appearance: none;
appearance: none;
margin: 0;
}
.LiveAreaSection {
width: 100%;
}
.LiveAreaSection .login-option-buybox {
display: block;
width: 100%;
font-size: 17px;
line-height: 30px;
color: #222;
padding-top: 30px;
font-family: Harding, Palatino, serif;
}
.LiveAreaSection .additional-access-options {
display: block;
font-weight: 700;
font-size: 17px;
line-height: 30px;
color: #222;
font-family: Harding, Palatino, serif;
}
.LiveAreaSection .additional-login > li:not(:first-child)::before {
transform: translateY(-50%);
content: “”;
height: 1rem;
position: absolute;
top: 50%;
left: 0;
border-left: 2px solid #999;
}
.LiveAreaSection .additional-login > li:not(:first-child) {
padding-left: 10px;
}
.LiveAreaSection .additional-login > li {
display: inline-block;
position: relative;
vertical-align: middle;
padding-right: 10px;
}
.BuyBoxSection {
display: flex;
flex-wrap: wrap;
flex: 1;
flex-direction: row-reverse;
margin: -30px -15px 0;
}
.BuyBoxSection .box-inner {
width: 100%;
height: 100%;
padding: 30px 5px;
display: flex;
flex-direction: column;
justify-content: space-between;
}
.BuyBoxSection p {
margin: 0;
}
.BuyBoxSection .readcube-buybox {
background-color: #f3f3f3;
flex-shrink: 1;
flex-grow: 1;
flex-basis: 255px;
background-clip: content-box;
padding: 0 15px;
margin-top: 30px;
}
.BuyBoxSection .subscribe-buybox {
background-color: #f3f3f3;
flex-shrink: 1;
flex-grow: 4;
flex-basis: 300px;
background-clip: content-box;
padding: 0 15px;
margin-top: 30px;
}
.BuyBoxSection .subscribe-buybox-nature-plus {
background-color: #f3f3f3;
flex-shrink: 1;
flex-grow: 4;
flex-basis: 100%;
background-clip: content-box;
padding: 0 15px;
margin-top: 30px;
}
.BuyBoxSection .title-readcube,
.BuyBoxSection .title-buybox {
display: block;
margin: 0;
margin-right: 10%;
margin-left: 10%;
font-size: 24px;
line-height: 32px;
color: #222;
text-align: center;
font-family: Harding, Palatino, serif;
}
.BuyBoxSection .title-asia-buybox {
display: block;
margin: 0;
margin-right: 5%;
margin-left: 5%;
font-size: 24px;
line-height: 32px;
color: #222;
text-align: center;
font-family: Harding, Palatino, serif;
}
.BuyBoxSection .asia-link,
.Link-328123652,
.Link-2926870917,
.Link-2291679238,
.Link-595459207 {
color: #069;
cursor: pointer;
text-decoration: none;
font-size: 1.05em;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
line-height: 1.05em6;
}
.BuyBoxSection .access-readcube {
display: block;
margin: 0;
margin-right: 10%;
margin-left: 10%;
font-size: 14px;
color: #222;
padding-top: 10px;
text-align: center;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
line-height: 20px;
}
.BuyBoxSection ul {
margin: 0;
}
.BuyBoxSection .link-usp {
display: list-item;
margin: 0;
margin-left: 20px;
padding-top: 6px;
list-style-position: inside;
}
.BuyBoxSection .link-usp span {
font-size: 14px;
color: #222;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
line-height: 20px;
}
.BuyBoxSection .access-asia-buybox {
display: block;
margin: 0;
margin-right: 5%;
margin-left: 5%;
font-size: 14px;
color: #222;
padding-top: 10px;
text-align: center;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
line-height: 20px;
}
.BuyBoxSection .access-buybox {
display: block;
margin: 0;
margin-right: 10%;
margin-left: 10%;
font-size: 14px;
color: #222;
opacity: 0.8px;
padding-top: 10px;
text-align: center;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
line-height: 20px;
}
.BuyBoxSection .price-buybox {
display: block;
font-size: 30px;
color: #222;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
padding-top: 30px;
text-align: center;
}
.BuyBoxSection .price-buybox-to {
display: block;
font-size: 30px;
color: #222;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
text-align: center;
}
.BuyBoxSection .price-info-text {
font-size: 16px;
padding-right: 10px;
color: #222;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
}
.BuyBoxSection .price-value {
font-size: 30px;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
}
.BuyBoxSection .price-per-period {
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
}
.BuyBoxSection .price-from {
font-size: 14px;
padding-right: 10px;
color: #222;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
line-height: 20px;
}
.BuyBoxSection .issue-buybox {
display: block;
font-size: 13px;
text-align: center;
color: #222;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
line-height: 19px;
}
.BuyBoxSection .no-price-buybox {
display: block;
font-size: 13px;
line-height: 18px;
text-align: center;
padding-right: 10%;
padding-left: 10%;
padding-bottom: 20px;
padding-top: 30px;
color: #222;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
}
.BuyBoxSection .vat-buybox {
display: block;
margin-top: 5px;
margin-right: 20%;
margin-left: 20%;
font-size: 11px;
color: #222;
padding-top: 10px;
padding-bottom: 15px;
text-align: center;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
line-height: 17px;
}
.BuyBoxSection .tax-buybox {
display: block;
width: 100%;
color: #222;
padding: 20px 16px;
text-align: center;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
line-height: NaNpx;
}
.BuyBoxSection .button-container {
display: flex;
padding-right: 20px;
padding-left: 20px;
justify-content: center;
}
.BuyBoxSection .button-container > * {
flex: 1px;
}
.BuyBoxSection .button-container > a:hover,
.Button-505204839:hover,
.Button-1078489254:hover,
.Button-2737859108:hover {
text-decoration: none;
}
.BuyBoxSection .btn-secondary {
background: #fff;
}
.BuyBoxSection .button-asia {
background: #069;
border: 1px solid #069;
border-radius: 0;
cursor: pointer;
display: block;
padding: 9px;
outline: 0;
text-align: center;
text-decoration: none;
min-width: 80px;
margin-top: 75px;
}
.BuyBoxSection .button-label-asia,
.ButtonLabel-3869432492,
.ButtonLabel-3296148077,
.ButtonLabel-1636778223 {
display: block;
color: #fff;
font-size: 17px;
line-height: 20px;
font-family: -apple-system, BlinkMacSystemFont, “Segoe UI”, Roboto,
Oxygen-Sans, Ubuntu, Cantarell, “Helvetica Neue”, sans-serif;
text-align: center;
text-decoration: none;
cursor: pointer;
}
.Button-505204839,
.Button-1078489254,
.Button-2737859108 {
background: #069;
border: 1px solid #069;
border-radius: 0;
cursor: pointer;
display: block;
padding: 9px;
outline: 0;
text-align: center;
text-decoration: none;
min-width: 80px;
max-width: 320px;
margin-top: 20px;
}
.Button-505204839 .btn-secondary-label,
.Button-1078489254 .btn-secondary-label,
.Button-2737859108 .btn-secondary-label {
color: #069;
}
.uList-2102244549 {
list-style: none;
padding: 0;
margin: 0;
}
/* style specs end */

Fig. 1: Examples of cognitive mechanics problems and common misconceptions.
Fig. 2: Developmental timelines for children’s understanding of torque.
Fig. 3: A simulation-based approach to action planning.
Fig. 4: Physical illusions.

References

  1. Chung, T. H., Orekhov, V. & Maio, A. Into the robotic depths: analysis and insights from the DARPA Subterranean Challenge. Annu. Rev. Control Robot. Auton. Syst. 6, 477–502 (2023).

    Article 

    Google Scholar 

  2. Garrett, C. R. et al. Integrated task and motion planning. Annu. Rev. Control Robot. Auton. Syst. 4, 265–293 (2021).

    Article 

    Google Scholar 

  3. Riochet, R. et al. Intphys 2019: a benchmark for visual intuitive physics understanding. IEEE Trans. Pattern Anal. Mach. Intell. 44, 5016–5025 (2021).

    Article 

    Google Scholar 

  4. Kubricht, J. R., Holyoak, K. J. & Lu, H. Intuitive physics: current research and controversies. Trends Cogn. Sci. 21, 749–759 (2017).

    Article 
    PubMed 

    Google Scholar 

  5. McCloskey, M. Intuitive physics. Sci. Am. 248, 122–131 (1983). A seminal paper that kicked off research on cognitive mechanics.

    Article 

    Google Scholar 

  6. Inhelder, B. & Piaget, J. The Growth of Logical Thinking From Childhood To Adolescence: An Essay On The Construction of Formal Operational Structures. (Psychology Press, 1958).

  7. Karmiloff-Smith, A. & Inhelder, B. If you want to get ahead, get a theory. Cognition 3, 195–212 (1974). An early and compelling proposal within the theory-change framework.

    Article 

    Google Scholar 

  8. McCloskey, M., Caramazza, A. & Green, B. Curvilinear motion in the absence of external forces: naive beliefs about the motion of objects. Science 210, 1139–1141 (1980).

    Article 
    PubMed 

    Google Scholar 

  9. Shanon, B. Aristotelianism, Newtonianism and the physics of the layman. Perception 5, 241–243 (1976).

    Article 
    PubMed 

    Google Scholar 

  10. Clement, J. Students’ preconceptions in introductory mechanics. Am. J. Phys. 50, 66–71 (1982).

    Article 

    Google Scholar 

  11. Driver, R. & Easley, J. Pupils and paradigms: a review of literature related to concept development in adolescent science students. https://doi.org/10.1080/03057267808559857 (1978).

  12. Minstrell, J. Explaining the ‘at rest’ condition of an object. Phys. Teach. 20, 10–14 (1982).

    Article 

    Google Scholar 

  13. Viennot, L. Spontaneous reasoning in elementary dynamics. Eur. J. Sci. Educ. 1, 205–221 (1979).

    Article 

    Google Scholar 

  14. Siegler, R. S. Three aspects of cognitive development. Cogn. Psychol. 8, 481–520 (1976).

    Article 

    Google Scholar 

  15. Ullman, T. D., Spelke, E., Battaglia, P. & Tenenbaum, J. B. Mind games: game engines as an architecture for intuitive physics. Trends Cogn. Sci. 21, 649–665 (2017).

    Article 
    PubMed 

    Google Scholar 

  16. Zago, M. & Lacquaniti, F. Visual perception and interception of falling objects: a review of evidence for an internal model of gravity. J. Neural Eng. 2, 198 (2005).

    Article 

    Google Scholar 

  17. Vicovaro, M. Intuitive physics and cognitive algebra: a review. Eur. Rev. Appl. Psychol. 71, 100610 (2021). One of the most compelling expositions of the information integration theory, a proposal that deserves careful consideration.

    Article 

    Google Scholar 

  18. Hast, M. & Howe, C. Children’s predictions and recognition of fall: the role of object mass. Cogn. Dev. 36, 103–110 (2015).

    Article 

    Google Scholar 

  19. Lin, Y., Stavans, M. & Baillargeon, R. in Cambridge Handbook of Cognitive Development (eds Houdé, O. & Borst, G.) 168–194 (Cambridge Univ. Press, 2022). A review of the literature on cognitive mechanics in infants.

  20. Baillargeon, R. Innate ideas revisited: for a principle of persistence in infants’ physical reasoning. Perspect. Psychol. Sci. 3, 2–13 (2008).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

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

    Article 

    Google Scholar 

  22. Xu, F. Towards a rational constructivist theory of cognitive development. Psychol. Rev. 126, 841 (2019). A proposal in the theory-change tradition that deserves careful consideration.

    Article 
    PubMed 

    Google Scholar 

  23. Vosniadou, S. The development of students’ understanding of science. Front. Educ. 4, 32 (2019).

    Article 

    Google Scholar 

  24. Stoen, S. M. et al. Force concept inventory: more than just conceptual understanding. Phys. Rev. Phys. Educ. Res. 16, 010105 (2020).

    Article 

    Google Scholar 

  25. Laverty, J. T. & Caballero, M. D. Analysis of the most common concept inventories in physics: what are we assessing? Phys. Rev. Phys. Educ. Res. 14, 010123 (2018).

    Article 

    Google Scholar 

  26. Crouch, C. H. & Mazur, E. Peer instruction: ten years of experience and results. Am. J. Phys. 69, 970–977 (2001). This paper illustrates just how profound an impact concept inventories have had in physics education.

    Article 

    Google Scholar 

  27. Resbiantoro, G. et al. A review of misconception in physics: the diagnosis, causes, and remediation. J. Turk. Sci. Educ. 19, 2 (2022).

    Google Scholar 

  28. Brown, D. E. & Hammer, D. in International Handbook of Research on Conceptual Change 1st edn (ed. Vosniadou, S.) 155–182 (Routledge, 2009). A helpful review of the knowledge-in-pieces framework.

  29. Hammer, D. in Converging Perspectives on Conceptual Change: Mapping an Emerging Paradigm in the Learning Sciences 1st edn (eds Amin, T. G. & Levrini, O.) 245–252 (Routledge, 2017).

  30. Chi, M. T. in International Handbook of Research on Conceptual Change 2nd edn (ed. Vosniadou, S.) 49–70 (Routledge, 2013).

  31. Muller, D. A., Bewes, J., Sharma, M. D. & Reimann, P. Saying the wrong thing: improving learning with multimedia by including misconceptions. J. Comput. Assist. Learn. 24, 144–155 (2008).

    Article 

    Google Scholar 

  32. diSessa, A. A. in The Cambridge Handbook of the Learning Sciences (ed. Sawyer, R.K.) 88–108 (Cambridge Univ. Press, 2014).

  33. Vicovaro, M. Grounding intuitive physics in perceptual experience. J. Intell. 11, 187 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  34. Hubbard, T. L. The possibility of an impetus heuristic. Psychon. Bull. Rev. 29, 2015–2033 (2022).

    Article 
    PubMed 

    Google Scholar 

  35. Brown, D. E. Students’ conceptions — coherent or fragmented? And what difference does it make. In Annual International Conf. National Association for Research in Science Teaching (Philadelphia, 2010).

  36. Brown, D. E. Students’ conceptions as dynamically emergent structures. Sci. Educ. 23, 1463–1483 (2014).

    Article 

    Google Scholar 

  37. Hegarty, M. Mechanical reasoning by mental simulation. Trends Cogn. Sci. 8, 280–285 (2004).

    Article 
    PubMed 

    Google Scholar 

  38. Battaglia, P. W., Hamrick, J. B. & Tenenbaum, J. B. Simulation as an engine of physical scene understanding. Proc. Natl Acad. Sci. USA 110, 18327–18332 (2013). This seminal paper introduced the video game engine in the head approach.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  39. Mitko, A. & Fischer, J. Do striking biases in mass inference reflect a flawed mental model of physics? J. Exp. Psychol. Gen. 152, 2636 (2023).

    Article 
    PubMed 

    Google Scholar 

  40. Hamrick, J. B., Battaglia, P. W., Griffiths, T. L. & Tenenbaum, J. B. Inferring mass in complex scenes by mental simulation. Cognition 157, 61–76 (2016).

    Article 
    PubMed 

    Google Scholar 

  41. Sanborn, A. N., Mansinghka, V. K. & Griffiths, T. L. Reconciling intuitive physics and Newtonian mechanics for colliding objects. Psychol. Rev. 120, 411 (2013). This paper was instrumental in prompting researchers in cognitive science to consider the possibility that adult humans do not have mechanics misconceptions.

    Article 
    PubMed 

    Google Scholar 

  42. Smith, K., Battaglia, P. & Tenenbaum, J. Integrating heuristic and simulation-based reasoning in intuitive physics. Preprint at PsyArXiv https://doi.org/10.31234/osf.io/bckes (2023).

  43. Ludwin-Peery, E., Bramley, N. R., Davis, E. & Gureckis, T. M. Broken physics: a conjunction-fallacy effect in intuitive physical reasoning. Psychol. Sci. 31, 1602–1611 (2020). This paper provides an excellent exposition on the theoretical and empirical debates in the contemporary cognitive science literature.

    Article 
    PubMed 

    Google Scholar 

  44. Smith, K. A., Battaglia, P. W. & Vul, E. Different physical intuitions exist between tasks, not domains. Comput. Brain Behav. 1, 101–118 (2018). One of the most systematic investigations of task effects, which suggests that the nature of the task has large effects on cognitive mechanics judgements.

    Article 

    Google Scholar 

  45. Neupärtl, N., Tatai, F. & Rothkopf, C. A. Naturalistic embodied interactions elicit intuitive physical behaviour in accordance with Newtonian physics. Cogn. Neuropsychol. 38, 440–454 (2021).

    Article 
    PubMed 

    Google Scholar 

  46. Davis, E. & Marcus, G. The scope and limits of simulation in automated reasoning. Artif. Intell. 233, 60–72 (2016).

    Article 

    Google Scholar 

  47. Hespos, S. J. & VanMarle, K. Physics for infants: characterizing the origins of knowledge about objects, substances, and number. Wiley Interdiscip. Rev. Cogn. Sci. 3, 19–27 (2012).

    Article 
    PubMed 

    Google Scholar 

  48. Proffitt, D. R., Kaiser, M. K. & Whelan, S. M. Understanding wheel dynamics. Cogn. Psychol. 22, 342–373 (1990).

    Article 
    PubMed 

    Google Scholar 

  49. Hestenes, D., Wells, M. & Swackhamer, G. Force concept inventory. Phys. Teach. 30, 141–158 (1992). Seminal paper that introduced the most widely used concept inventory.

    Article 

    Google Scholar 

  50. Eaton, P. & Willoughby, S. D. Confirmatory factor analysis applied to the force concept inventory. Phys. Rev. Phys. Educ. Res. 14, 010124 (2018).

    Article 

    Google Scholar 

  51. Scott, T. F., Schumayer, D. & Gray, A. R. Exploratory factor analysis of a force concept inventory data set. Phys. Rev. Spec. Top. Phys. Educ. Res. 8, 020105 (2012).

    Article 

    Google Scholar 

  52. Sands, D., Parker, M., Hedgeland, H., Jordan, S. & Galloway, R. Using concept inventories to measure understanding. High. Educ. Pedagog. 3, 173–182 (2018).

    Article 

    Google Scholar 

  53. Libarkin, J. Concept inventories in higher education science. In BOSE Conf. 1–10 (2008).

  54. Madsen, A., McKagan, S. B. & Sayre, E. C. Best practices for administering concept inventories. Phys. Teach. 55, 530–536 (2017).

    Article 

    Google Scholar 

  55. Scott, T. F. & Schumayer, D. Conceptual coherence of non-Newtonian worldviews in force concept inventory data. Phys. Rev. Phys. Educ. Res. 13, 010126 (2017).

    Article 

    Google Scholar 

  56. Caballero, M. D. et al. Comparing large lecture mechanics curricula using the force concept inventory: a five thousand student study. Am. J. Phys. 80, 638–644 (2012).

    Article 

    Google Scholar 

  57. Pinker, S. The Stuff of Thought: Language as a Window into Human Nature (Penguin, 2007).

  58. Piaget, J. La Représentation du Monde Chez L’enfant. Vol. 3 (Payot, 1926).

  59. Kuhn, T. S. The Structure of Scientific Revolutions 1st edn (Univ. Chicago Press, 1962).

  60. Halloun, I. A. & Hestenes, D. The initial knowledge state of college physics students. Am. J. Phys. 53, 1043–1055 (1985).

    Article 

    Google Scholar 

  61. Gunstone, R. & Watts, M. in Children’s Ideas in Science (eds Driver, R. et al.) 85–104 (Open Univ. Press, 1985).

  62. Carey, S. Conceptual Change in Childhood (MIT Press, 1985).

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

  64. Carey, S. & Spelke, E. in Mapping the Mind: Domain Specificity in Cognition and Culture (eds Hirschfeld, L. A. & Gelman, S. A.) 169–200 (Cambridge Univ. Press, 1994).

  65. Maclin, D., Grosslight, L. & Davis, H. Teaching for understanding: a study of students’ preinstruction theories of matter and a comparison of the effectiveness of two approaches to teaching about matter and density. Cogn. Instr. 15, 317–393 (1997).

    Article 

    Google Scholar 

  66. Wiser, M. in Software Goes to School: Teaching for Understanding with New Technologies (eds Perkins, D. N. e al.) 23–38 (Oxford Univ. Press, 1995).

  67. Bascandziev, I. Thought experiments as an error detection and correction tool. Cogn. Sci. 48, 13401 (2024). Compelling for its large sample size and careful experimental design, this paper suggests that not all intuitive physics simulations are the same.

    Article 

    Google Scholar 

  68. Kelemen, D., Rottman, J. & Seston, R. Professional physical scientists display tenacious teleological tendencies: purpose-based reasoning as a cognitive default. J. Exp. Psychol. Gen. 142, 1074 (2013).

    Article 
    PubMed 

    Google Scholar 

  69. Thornton, R. K., Kuhl, D., Cummings, K. & Marx, J. Comparing the force and motion conceptual evaluation and the force concept inventory. Phys. Rev. Spec. Top. Phys. Educ. Res. 5, 010105 (2009).

    Article 

    Google Scholar 

  70. Rosenblatt, R. & Heckler, A. F. Systematic study of student understanding of the relationships between the directions of force, velocity, and acceleration in one dimension. Phys. Rev. Phys. Educ. Res. 7, 020112 (2011).

    Article 

    Google Scholar 

  71. Morley, A., Nissen, J. M. & Van Dusen, B. Measurement invariance across race and gender for the force concept inventory. Phys. Rev. Phys. Educ. Res. 19, 020102 (2023).

    Article 

    Google Scholar 

  72. Yang, J., Zabriskie, C. & Stewart, J. Multidimensional item response theory and the force and motion conceptual evaluation. Phys. Rev. Phys. Educ. Res. 15, 020141 (2019).

    Article 

    Google Scholar 

  73. Hake, R. R. Interactive-engagement versus traditional methods: a six-thousand-student survey of mechanics test data for introductory physics courses. Am. J. Phys. 66, 64–74 (1998).

    Article 

    Google Scholar 

  74. Santoso, P. H. et al. Exploring gender differences in the force concept inventory using a random effects meta-analysis of international studies. Phys. Rev. Phys. Educ. Res. 20, 010601 (2024).

    Article 

    Google Scholar 

  75. Stewart, J. et al. Mediational effect of prior preparation on performance differences of students underrepresented in physics. Phys. Rev. Phys. Educ. Res. 17, 010107 (2021).

    Article 

    Google Scholar 

  76. Von Korff, J. et al. Secondary analysis of teaching methods in introductory physics: a 50 k-student study. Am. J. Phys. 84, 969–974 (2016).

    Article 

    Google Scholar 

  77. Hoellwarth, C., Moelter, M. J. & Knight, R. D. A direct comparison of conceptual learning and problem solving ability in traditional and studio style classrooms. Am. J. Phys. 73, 459–462 (2005).

    Article 

    Google Scholar 

  78. Semak, M., Dietz, R., Pearson, R. & Willis, C. Examining evolving performance on the force concept inventory using factor analysis. Phys. Rev. Phys. Educ. Res. 13, 010103 (2017).

    Article 

    Google Scholar 

  79. Stewart, J., Zabriskie, C., DeVore, S. & Stewart, G. Multidimensional item response theory and the force concept inventory. Phys. Rev. Phys. Educ. Res. 14, 010137 (2018).

    Article 

    Google Scholar 

  80. Eaton, P. & Willoughby, S. Identifying a preinstruction to postinstruction factor model for the force concept inventory within a multitrait item response theory framework. Phys. Rev. Phys. Educ. Res. 16, 010106 (2020).

    Article 

    Google Scholar 

  81. Stewart, J. et al. Examining the relation of correct knowledge and misconceptions using the nominal response model. Phys. Rev. Phys. Educ. Res. 17, 010122 (2021).

    Article 

    Google Scholar 

  82. Lasry, N., Rosenfield, S., Dedic, H., Dahan, A. & Reshef, O. The puzzling reliability of the force concept inventory. Am. J. Phys. 79, 909–912 (2011).

    Article 

    Google Scholar 

  83. Wang, J. & Bao, L. Analyzing force concept inventory with item response theory. Am. J. Phys. 78, 1064–1070 (2010).

    Article 

    Google Scholar 

  84. Huffman, D. & Heller, P. What does the force concept inventory actually measure? Phys. Teach. 33, 138–143 (1995).

    Article 

    Google Scholar 

  85. Henderson, C. Common concerns about the force concept inventory. Phys. Teach. 40, 542–547 (2002).

    Article 

    Google Scholar 

  86. Maries, A. & Singh, C. Teaching assistants’ performance at identifying common introductory student difficulties in mechanics revealed by the Force Concept Inventory. Phys. Rev. Phys. Educ. Res. 12, 010131 (2016).

    Article 

    Google Scholar 

  87. diSessa, A. A., Gillespie, N. M. & Esterly, J. B. Coherence versus fragmentation in the development of the concept of force. Cogn. Sci. 28, 843–900 (2004).

    Article 

    Google Scholar 

  88. diSessa, A. A. et al. in International Handbook of Research on Conceptual Change (ed. Vosniadou, S.) 31–48 (Routledge, 2008).

  89. Cooke, N. J. & Breedin, S. D. Naive misconceptions of Cooke and Breedin’s research: response to ranney. Mem. Cognit. 22, 503–507 (1994).

    Article 
    PubMed 

    Google Scholar 

  90. Kaiser, M. K., McCloskey, M. & Proffitt, D. R. Development of intuitive theories of motion: curvilinear motion in the absence of external forces. Dev. Psychol. 22, 67 (1986).

    Article 

    Google Scholar 

  91. Proffitt, D. R. & Gilden, D. L. Understanding natural dynamics. J. Exp. Psychol. Hum. Percept. Perform. 15, 384 (1989).

    Article 
    PubMed 

    Google Scholar 

  92. Rohrer, D. Misconceptions about incline speed for nonlinear slopes. J. Exp. Psychol. Hum. Percept. Perform. 28, 963 (2002).

    Article 
    PubMed 

    Google Scholar 

  93. Shtulman, A. & Lombrozo, T. in Core Knowledge and Conceptual Change (eds Barner, D. & Baron, A. S.) 53–72 (Oxford Univ. Press, 2016). This book provides compelling evidence that adults have both veridical and non-veridical cognitive mechanics.

  94. Vosniadou, S. in International Handbook of Research on Conceptual Change 2nd edn (ed. Vosniadou, S.) 11–30 (Routledge, 2013).

  95. Clark, D. B. & Linn, M. C. in International Handbook of Research on Conceptual Change 2nd edn (ed. Vosniadou, S.) 520–538 (Routledge, 2013).

  96. Panagiotaki, G., Nobes, G. & Banerjee, R. Children’s representations of the earth: a methodological comparison. Br. J. Dev. Psychol. 24, 353–372 (2006).

    Article 

    Google Scholar 

  97. diSessa, A. A. in Constructivism in the Computer Age (eds Forman, G. & Pufall, P. B.) 49–70 (Psychology Press, 1988).

  98. Hammer, D. Misconceptions or p-prims: how may alternative perspectives of cognitive structure influence instructional perceptions and intentions. J. Learn. Sci. 5, 97–127 (1996).

    Article 

    Google Scholar 

  99. Brown, D. E. Refocusing core intuitions: a concretizing role for analogy in conceptual change. J. Res. Sci. Teach. 30, 1273–1290 (1993).

    Article 

    Google Scholar 

  100. Conlin, L. D., Gupta, A. & Hammer, D. Framing and resource activation: bridging the cognitive-situative divide using a dynamic unit of cognitive analysis. In Proc. Annual Meeting of the Cognitive Science Society 32, (Cogn. Sci. 2010).

  101. Kahneman, D. Thinking, Fast and Slow (Macmillan, 2011).

  102. Heckler, A. F. in Psychology of Learning and Motivation: Cognition in Education (eds Mestre, J. P. & Ross, B. H.) 227–267 (Elsevier Academic Press, 2011).

  103. Heckler, A. F. & Bogdan, A. M. Reasoning with alternative explanations in physics: the cognitive accessibility rule. Phys. Rev. Phys. Educ. Res. 14, 010120 (2018).

    Article 

    Google Scholar 

  104. Gette, C. R., Kryjevskaia, M., Stetzer, M. R. & Heron, P. R. Probing student reasoning approaches through the lens of dual-process theories: a case study in buoyancy. Phys. Rev. Phys. Educ. Res. 14, 010113 (2018).

    Article 

    Google Scholar 

  105. Gette, C. R. & Kryjevskaia, M. Establishing a relationship between student cognitive reflection skills and performance on physics questions that elicit strong intuitive responses. Phys. Rev. Phys. Educ. Res. 15, 010118 (2019).

    Article 

    Google Scholar 

  106. Speirs, J. C., Stetzer, M. R., Lindsey, B. A. & Kryjevskaia, M. Exploring and supporting student reasoning in physics by leveraging dual-process theories of reasoning and decision making. Phys. Rev. Phys. Educ. Res. 17, 020137 (2021).

    Article 

    Google Scholar 

  107. Wood, A. K., Galloway, R. K. & Hardy, J. Can dual processing theory explain physics students’ performance on the force concept inventory? Phys. Rev. Phys. Educ. Res. 12, 023101 (2016).

    Article 

    Google Scholar 

  108. Friedman, W. J. Arrows of time in early childhood. Child Dev. 74, 155–167 (2003).

    Article 
    PubMed 

    Google Scholar 

  109. Hast, M. & Howe, C. Changing predictions, stable recognition: children’s representations of downward incline motion. Br. J. Dev. Psychol. 35, 516–530 (2017).

    Article 
    PubMed 

    Google Scholar 

  110. Hespos, S. J. & Baillargeon, R. Young infants’ actions reveal their developing knowledge of support variables: converging evidence for violation-of-expectation findings. Cognition 107, 304–316 (2008).

    Article 
    PubMed 

    Google Scholar 

  111. Kaiser, M. K. & Proffitt, D. R. The development of sensitivity to causally relevant dynamic information. Child Dev. 55, 1614–1624 (1984).

    Article 
    PubMed 

    Google Scholar 

  112. Kim, I.-K. & Spelke, E. S. Perception and understanding of effects of gravity and inertia on object motion. Dev. Sci. 2, 339–362 (1999).

    Article 

    Google Scholar 

  113. Larsen, N. E., Venkadasalam, V. P. & Ganea, P. A. Prompting children’s belief revision about balance through primary and secondary sources of evidence. Front. Psychol. 11, 541958 (2020).

    Article 

    Google Scholar 

  114. Luo, Y., Kaufman, L. & Baillargeon, R. Young infants’ reasoning about physical events involving inert and self-propelled objects. Cogn. Psychol. 58, 441–486 (2009).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  115. Halford, G. S. et al. Young children’s performance on the balance scale: the influence of relational complexity. J. Exp. Child Psychol. 81, 417–445 (2002).

    Article 
    PubMed 

    Google Scholar 

  116. Messer, D. J., Pine, K. J. & Butler, C. Children’s behaviour and cognitions across different balance tasks. Learn. Instr. 18, 42–53 (2008).

    Article 

    Google Scholar 

  117. Baillargeon, R. A model of physical reasoning in infancy. Adv. Infancy Res. 9, 305–371 (1995).

    Google Scholar 

  118. Baillargeon, R., Needham, A. & DeVos, J. The development of young infants’ intuitions about support. Early Dev. Parent. 1, 69–78 (1992).

    Article 

    Google Scholar 

  119. Krist, H. Development of intuitions about support beyond infancy. Dev. Psychol. 46, 266 (2010).

    Article 
    PubMed 

    Google Scholar 

  120. Krist, H., Atlas, C., Fischer, H. & Wiese, C. Development of basic intuitions about physical support during early childhood: evidence from a novel eye-tracking paradigm. Q. J. Exp. Psychol. 71, 1988–2004 (2018).

    Article 

    Google Scholar 

  121. Hofman, A. D., Visser, I., Jansen, B. R. & Maas, H. L. The balance-scale task revisited: a comparison of statistical models for rule-based and information-integration theories of proportional reasoning. PLoS ONE 10, e0136449 (2015). One of the several papers that use modern statistical analysis to characterize development on the balance-scale task in the contemporary developmental literature.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  122. Jansen, B. R. & Maas, H. L. The development of children’s rule use on the balance scale task. J. Exp. Child Psychol. 81, 383–416 (2002).

    Article 
    PubMed 

    Google Scholar 

  123. Siegler, R. S. & Chen, Z. Development of rules and strategies: balancing the old and the new. J. Exp. Child Psychol. 81, 446–457 (2002).

    Article 
    PubMed 

    Google Scholar 

  124. Boom, J. & ter Laak, J. Classes in the balance: latent class analysis and the balance scale task. Dev. Rev. 27, 127–149 (2007). One of the several papers that use modern statistical analysis to characterize development on the balance-scale task in the contemporary developmental literature.

    Article 

    Google Scholar 

  125. Shultz, T. R. & Takane, Y. Rule following and rule use in the balance-scale task. Cognition 103, 460–472 (2007).

    Article 
    PubMed 

    Google Scholar 

  126. Spelke, E. S. What Babies Know: Core Knowledge and Composition, Vol. 1 (Oxford Univ. Press, 2022). The first in a two-volume landmark synthesis of the core knowledge theory; although it covers much more than cognitive mechanics, it is worth reading in full.

  127. Schapiro, A. C. & McClelland, J. L. A connectionist model of a continuous developmental transition in the balance scale task. Cognition 110, 395–411 (2009).

    Article 
    PubMed 

    Google Scholar 

  128. Dandurand, F. & Shultz, T. R. A comprehensive model of development on the balance-scale task. Cogn. Syst. Res. 31, 1–25 (2014).

    Article 

    Google Scholar 

  129. Howe, C., Taylor Tavares, J. & Devine, A. Children’s conceptions of physical events: explicit and tacit understanding of horizontal motion. Br. J. Dev. Psychol. 32, 141–162 (2014).

    Article 
    PubMed 

    Google Scholar 

  130. Mitko, A., Navarro-Cebrián, A., Cormiea, S. & Fischer, J. A dedicated mental resource for intuitive physics. iScience 27, 108607 (2024).

    Article 
    PubMed 

    Google Scholar 

  131. Kaiser, M. K., Proffitt, D. R., Whelan, S. M. & Hecht, H. Influence of animation on dynamical judgments. J. Exp. Psychol. Hum. Percept. Perform. 18, 669 (1992).

    Article 
    PubMed 

    Google Scholar 

  132. Hecht, H. Beyond illusions: on the limitations of perceiving relational properties. in Open MIND Vol. 18 (MIND Group, 2015).

  133. Ludwin-Peery, E., Bramley, N. R., Davis, E. & Gureckis, T. M. Limits on simulation approaches in intuitive physics. Cogn. Psychol. 127, 101396 (2021).

    Article 
    PubMed 

    Google Scholar 

  134. Smith, K. A. & Vul, E. Sources of uncertainty in intuitive physics. Top. Cogn. Sci. 5, 185–199 (2013).

    Article 
    PubMed 

    Google Scholar 

  135. Lau, J. S.-H. & Brady, T. F. Noisy perceptual expectations: multiple object tracking benefits when objects obey features of realistic physics. J. Exp. Psychol. Hum. Percept. Perform. 46, 1280 (2020).

    Article 
    PubMed 

    Google Scholar 

  136. Li, Y. et al. An approximate representation of objects underlies physical reasoning. J. Exp. Psychol. Gen. 152, 3074–3086 (2023). This paper provides a rich exposition of and evidence for the current resource-rational video game engine in the head account.

    Article 
    PubMed 

    Google Scholar 

  137. Bass, I., Smith, K. A., Bonawitz, E. & Ullman, T. D. Partial mental simulation explains fallacies in physical reasoning. Cogn. Neuropsychol. 38, 413–424 (2021). This paper provides an excellent exposition on the theoretical and empirical debates in the contemporary cognitive science literature.

    Article 
    PubMed 

    Google Scholar 

  138. Kosslyn, S. M., Thompson, W. L. & Ganis, G. The Case for Mental Imagery (Oxford Univ. Press, 2006).

  139. Shepard, S. & Metzler, D. Mental rotation: effects of dimensionality of objects and type of task. J. Exp. Psychol. Hum. Percept. Perform. 14, 3 (1988).

    Article 
    PubMed 

    Google Scholar 

  140. Hartshorne, J. The video game engine in your head. Sci. Am. https://www.scientificamerican.com/article/the-video-game-engine-in-your-head/ (2014).

  141. Weitnauer, E., Goldstone, R. L. & Ritter, H. Perception and simulation during concept learning. Psychol. Rev. 130, 1203–1238 (2023).

    Article 
    PubMed 

    Google Scholar 

  142. Ahuja, A., Desrochers, T. M. & Sheinberg, D. L. A role for visual areas in physics simulations. Cogn. Neuropsychol. 38, 425–439 (2021).

    Article 
    PubMed 

    Google Scholar 

  143. Fischer, J. The Building Blocks of Intuitive Physics in the Mind and Brain (Taylor & Francis, 2021).

  144. Masin, S. C. The cognitive and perceptual laws of the inclined plane. Am. J. Psychol. 129, 221–234 (2016).

    Article 
    PubMed 

    Google Scholar 

  145. Gregory, J. Game Engine Architecture (AK Peters/CRC Press, 2018).

  146. Lieder, F. & Griffiths, T. L. Resource-rational analysis: understanding human cognition as the optimal use of limited computational resources. Behav. Brain Sci. 43, e1 (2020).

    Article 

    Google Scholar 

  147. Ho, M. K. et al. People construct simplified mental representations to plan. Nature 606, 129–136 (2022).

    Article 
    PubMed 

    Google Scholar 

  148. Kozhevnikov, M. & Hegarty, M. Impetus beliefs as default heuristics: dissociation between explicit and implicit knowledge about motion. Psychon. Bull. Rev. 8, 439–453 (2001).

    Article 
    PubMed 

    Google Scholar 

  149. Ullman, T. D. & Tenenbaum, J. B. Bayesian models of conceptual development: learning as building models of the world. Annu. Rev. Dev. Psychol. 2, 533–558 (2020).

    Article 

    Google Scholar 

  150. Xu, K. et al. A Bayesian-symbolic approach to reasoning and learning in intuitive physics. In Advances in Neural Information Processing Systems 34, 2478–2490 (NeurIPS, 2021).

  151. Wu, J. et al. Galileo: perceiving physical object properties by integrating a physics engine with deep learning. In Advances in Neural Information Processing Systems 28, 127–135 (NeurIPS, 2015).

  152. Chen, T. et al. ‘Just In Time’ representations for mental simulation in intuitive physics. Proc. Annu. Meet. Cogn. Sci. Soc. 45, 2484–2491 (2023).

    Google Scholar 

  153. Hartshorne, J. K. & Schachner, A. Tracking replicability as a method of postpublication open evaluation. Front. Comput. Neurosci. 6, 8 (2012).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  154. Open Science Collaboration. Estimating the reproducibility of psychological science. Science 349, 4716 (2015).

    Article 

    Google Scholar 

  155. Cohen, A. D. Test-taking strategies. Lang. Assess. Q. 3, 307–331 (2006).

    Article 

    Google Scholar 

  156. Xie, Q. Does test preparation work? Implications for score validity. Lang. Assess. Q. 10, 196–218 (2013).

    Article 

    Google Scholar 

  157. Stenlund, T., Eklöf, H. & Lyrén, P. E. Group differences in test-taking behaviour: an example from a high-stakes testing program. Assess. Educ. Princ. Policy Pract. 24, 4–20 (2017).

    Google Scholar 

  158. Stenlund, T., Lyrén, P. E. & Eklöf, H. The successful test taker: exploring test-taking behavior profiles through cluster analysis. Eur. J. Psychol. Educ. 33, 403–417 (2018).

    Article 

    Google Scholar 

  159. Zago, M. & Lacquaniti, F. Cognitive, perceptual and action-oriented representations of falling objects. Neuropsychologia 43, 178–188 (2005).

    Article 
    PubMed 

    Google Scholar 

  160. Huber, S. & Krist, H. When is the ball going to hit the ground? Duration estimates, eye movements, and mental imagery of object motion. J. Exp. Psychol. Hum. Percept. Perform. 30, 431 (2004).

    Article 
    PubMed 

    Google Scholar 

  161. Vicovaro, M., Noventa, S. & Battaglini, L. Intuitive physics of gravitational motion as shown by perceptual judgment and prediction-motion tasks. Acta Psychol. 194, 51–62 (2019).

    Article 

    Google Scholar 

  162. Friedman, W. J. Arrows of time in infancy: the representation of temporal-causal invariances. Cogn. Psychol. 44, 252–296 (2002).

    Article 
    PubMed 

    Google Scholar 

  163. Masin, S. C., Crivellaro, F. & Varotto, D. The intuitive physics of the equilibrium of the lever and of the hydraulic pressures: implications for the teaching of elementary physics. Psicológica 35, 441–461 (2014).

    Google Scholar 

  164. Howard, I. P. & Rogers, B. in Stevens Handbook of Experimental Psychology: Sensation and Perception 3rd edn (eds Pashler, H. & Yantis, S.) 77–120 (Wiley, 2002).

  165. Eichenbaum, H. Memory systems. WIREs Cogn. Sci. 1, 478–490 (2010).

    Article 

    Google Scholar 

  166. Frank, M. J., Cohen, M. X. & Sanfey, A. G. Multiple systems in decision making: a neurocomputational perspective. Curr. Dir. Psychol. Sci. 18, 73–77 (2009).

    Article 

    Google Scholar 

  167. Oved, I., Krishnaswamy, N., Pustejovsky, J. & Hartshorne, J. K. Neither neural networks nor the language-of-thought alone make a complete game. Behav. Brain Sci. 46, e1 (2023).

    Article 

    Google Scholar 

  168. Duan, J., Dasgupta, A., Fischer, J. & Tan, C. A survey on machine learning approaches for modelling intuitive physics. In Proc. 31st Int. Joint Conf. Artif. Intell. (IJCAI-22) 5444–5452 (2022).

  169. McCoy, R. T., Yao, S., Friedman, D., Hardy, M. D. & Griffiths, T. L. Embers of autoregression show how large language models are shaped by the problem they are trained to solve. Proc. Natl Acad. Sci. USA 121, e2322420121 (2024).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  170. Marcus, G. F. The Algebraic Mind: Integrating Connectionism and Cognitive Science (MIT Press, 2003).

  171. Tenenbaum, J. B., Kemp, C., Griffiths, T. L. & Goodman, N. D. How to grow a mind: statistics, structure, and abstraction. Science 331, 1279–1285 (2011).

    Article 
    PubMed 

    Google Scholar 

  172. Goodman, N. D. & Frank, M. C. Pragmatic language interpretation as probabilistic inference. Trends Cogn. Sci. 20, 818–829 (2016).

    Article 
    PubMed 

    Google Scholar 

  173. Griffiths, T. L. Manifesto for a new (computational) cognitive revolution. Cognition 135, 21–23 (2015).

    Article 
    PubMed 

    Google Scholar 

  174. Kriegeskorte, N. & Douglas, P. K. Cognitive computational neuroscience. Nat. Neurosci. 21, 1148–1160 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  175. Gershman, S. J., Horvitz, E. J. & Tenenbaum, J. B. Computational rationality: a converging paradigm for intelligence in brains, minds, and machines. Science 349, 273–278 (2015).

    Article 
    PubMed 

    Google Scholar 

  176. Bhui, R., Lai, L. & Gershman, S. J. Resource-rational decision making. Curr. Opin. Behav. Sci. 41, 15–21 (2021).

    Article 

    Google Scholar 

  177. Goodman, N. D., Tenenbaum, J. B. & ProbMods Contributors. Probabilistic Models of Cognition. https://probmods.org (2024).

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

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  179. Ritchie, D., Horsfall, P. & Goodman, N.D. Deep amortized inference for probabilistic programs. Preprint at https://doi.org/10.48550/arXiv.1610.05735 (2016).

  180. Christiansen, M. H. & Chater, N. The now-or-never bottleneck: a fundamental constraint on language. Behav. Brain Sci. 39, 62 (2016).

    Article 

    Google Scholar 

  181. O’Donnell, T. J. Productivity and Reuse in Language: A Theory of Linguistic Computation and Storage (MIT Press, 2015).

  182. Vul, E., Goodman, N., Griffiths, T. L. & Tenenbaum, J. B. One and done? optimal decisions from very few samples. Cogn. Sci. 38, 599–637 (2014).

    Article 
    PubMed 

    Google Scholar 

  183. Griffiths, T. L., Lieder, F. & Goodman, N. D. Rational use of cognitive resources: levels of analysis between the computational and the algorithmic. Top. Cogn. Sci. 7, 217–229 (2015).

    Article 
    PubMed 

    Google Scholar 

  184. Ellis, K. et al. Dreamcoder: bootstrapping inductive program synthesis with wake-sleep library learning. In Proc. 42nd ACM Sigplan International Conference on Programming Language Design and Implementation, 835–850 (ACM, 2021).

  185. Allen, K. R. et al. Lifelong learning of cognitive styles for physical problem-solving: the effect of embodied experience. Psychon. Bull. Rev. 31, 1364–1375 (2024).

    Article 
    PubMed 

    Google Scholar 

  186. Yen, W. M. & Fitzpatrick, A. R. in Educational Measurement 4th edn (ed. Brennan, R. L.) 111–153 (Praeger, 2006).

  187. Mulaik, S. A. Foundations of Factor Analysis (CRC Press, 2009).

  188. Passonneau, R. J. & Carpenter, B. The benefits of a model of annotation. Trans. Assoc. Comput. Linguist. 2, 311–326 (2014).

    Article 

    Google Scholar 

  189. Gershman, S. J. & Blei, D. M. A tutorial on Bayesian nonparametric models. J. Math. Psychol. 56, 1–12 (2012).

    Article 

    Google Scholar 

  190. Erb, C. D., Germine, L. & Hartshorne, J. K. Cognitive control across the lifespan: congruency effects reveal divergent developmental trajectories. J. Exp. Psychol. Gen. 152, 3285–3291 (2023).

    Article 
    PubMed 

    Google Scholar 

  191. Hartshorne, J. K. & Germine, L. T. When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the life span. Psychol. Sci. 26, 433–443 (2015).

    Article 
    PubMed 

    Google Scholar 

  192. Hampshire, A., Highfield, R. R., Parkin, B. L. & Owen, A. M. Fractionating human intelligence. Neuron 76, 1225–1237 (2012).

    Article 
    PubMed 

    Google Scholar 

  193. Ullman, M. T. in Theories in Second Language Acquisition 2nd edn (eds VanPatten, B. & Williams, J.) 128–161 (Routledge, 2020).

  194. Dreher, J.-C. & Berman, K. F. Fractionating the neural substrate of cognitive control processes. Proc. Natl Acad. Sci. USA 99, 14595–14600 (2002).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  195. Aglinskas, A., Hartshorne, J. K. & Anzellotti, S. Contrastive machine learning reveals the structure of neuroanatomical variation within autism. Science 376, 1070–1074 (2022).

    Article 
    PubMed 

    Google Scholar 

  196. Fischer, J. & Mahon, B. Z. What tool representation, intuitive physics, and action have in common: the brain’s first-person physics engine. Cogn. Neuropsychol. 38, 455–467 (2021).

    Article 
    PubMed 

    Google Scholar 

  197. Pramod, R., Cohen, M. A., Tenenbaum, J. B. & Kanwisher, N. Invariant representation of physical stability in the human brain. eLife 11, e71736 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  198. Fischer, J., Mikhael, J. G., Tenenbaum, J. B. & Kanwisher, N. Functional neuroanatomy of intuitive physical inference. Proc. Natl Acad. Sci. USA 113, 5072–5081 (2016).

    Article 

    Google Scholar 

  199. Schwettmann, S., Tenenbaum, J. B. & Kanwisher, N. Invariant representations of mass in the human brain. eLife 8, e46619 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  200. Schwartenbeck, P. et al. Generative replay underlies compositional inference in the hippocampal–prefrontal circuit. Cell 186, 4885–4897 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  201. Hecht, H. & Bertamini, M. Understanding projectile acceleration. J. Exp. Psychol. Hum. Percept. Perform. 26, 730 (2000).

    Article 
    PubMed 

    Google Scholar 

  202. Hecht, H. Regularities of the physical world and the absence of their internalization. Behav. Brain Sci. 24, 608–617 (2001).

    Article 
    PubMed 

    Google Scholar 

  203. Hartshorne, J. K. et al. A thousand studies for the price of one: accelerating psychological science with pushkin. Behav. Res. Methods 51, 1782–1803 (2019).

    Article 
    PubMed 

    Google Scholar 

  204. Fedorov, V. Optimal experimental design. WIREs Comput. Stat. 2, 581–589 (2010).

    Article 

    Google Scholar 

  205. Foster, A. et al. Variational Bayesian optimal experimental design. In Advances in Neural Information Processing Systems 32 (eds Wallach, H. et al.) 14036–14047 (NeurIPS, 2019).

  206. Golan, T., Raju, P. C. & Kriegeskorte, N. Controversial stimuli: pitting neural networks against each other as models of human cognition. Proc. Natl Acad. Sci. USA 117, 29330–29337 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  207. Kuczmann, I. The structure of knowledge and students’ misconceptions in physics. In AIP Conf. Proc. 1916 (AIP, 2017).

  208. Dan, N., Omori, T. & Tomiyasu, Y. Development of infants’ intuitions about support relations: sensitivity to stability. Dev. Sci. 3, 171–180 (2000).

    Article 

    Google Scholar 

  209. Needham, A. & Baillargeon, R. Intuitions about support in 4.5-month-old infants. Cognition 47, 121–148 (1993).

    Article 
    PubMed 

    Google Scholar 

  210. Baillargeon, R. & Hanko-Summers, S. Is the top object adequately supported by the bottom object? Young infants’ understanding of support relations. Cognit. Dev. 5, 29–53 (1990).

    Article 

    Google Scholar 

  211. Baillargeon, R. in The Cognitive Neurosciences (ed. Gazzaniga, M. S.) 181–204 (MIT Press, 1995).

Download references

Acknowledgements

The authors thank A. Eisenkraft, E. Bonawitz, D. Hammer, K. Smith and T. Ullman for commentary and feedback. Funding was provided by NSF No. 2238912 and No. 2033938 to J.K.H.

Author information

Authors and Affiliations

Authors

Contributions

The authors contributed equally to all aspects of the article.

Corresponding author

Correspondence to
Joshua K. Hartshorne.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Reviews Psychology thanks Igor Bascandziev, Michele Vicovaro and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hartshorne, J.K., Jing, M. Insights into cognitive mechanics from education, developmental psychology and cognitive science.
Nat Rev Psychol (2025). https://doi.org/10.1038/s44159-025-00412-6

Download citation

  • Accepted: 14 January 2025

  • Published: 28 February 2025

  • DOI: https://doi.org/10.1038/s44159-025-00412-6


Leave a Reply

Your email address will not be published. Required fields are marked *