Curvilinear motion in the absence of external forces: naive beliefs about the motion of objects.

By M. McCloskey, Alfonso Caramazza, B. Green. 1980

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Citations in the corpus

Flexible Neural Representation for Physics Prediction (2018, background): “Finally, it will be of great interest to evaluate to what extent HRN-type models describe patterns of human intuitive physical knowledge observed by cognitive scientists [32, 35, 38].”
COPHY: Counterfactual Learning of Physical Dynamics (2019, background): “…studies on cognitive psychology have shown that humans perform poorly when asked to reason about expected outcomes of a physics based event, demonstrating striking deviations from Newtonian physics in their intuitions (McCloskey & Kohl, 1983; McClooskey et al., 1980; 1983; Kubricht et al., 2017).”
Situated Cognition and the Culture of Learning (1989, unknown): “We know from an extensive literature (diSessa, 1982, 1983, 1986; McCloskey, Caramazza, & Green, 1980; White, 1983) that students have many mis-conceptions about qualitative phenomena in physics.”
Mind Games: Game Engines as an Architecture for Intuitive Physics. (2017, background): “Early research on intuitive physics suggested that people’s reasoning about object motion fails to accord with Newtonian principles, and is subject to surprising errors, even on simple motion prediction tasks [77, 78].”
PHYRE: A New Benchmark for Physical Reasoning (2019, background): “Foundational work in cognitive psychology suggests that people reason about the physical world using simplified intuitive theories [31–33].”
Reconciling intuitive physics and Newtonian mechanics for colliding objects. (2013, background): “While people are poor at reasoning about a ball that has followed a curved path (McCloskey et al., 1980), they are much more accurate at reasoning about water that has passed through a curved hose (Kaiser, Jonides, & Alexander, 1986) or about videos of balls traveling through tubes (Kaiser, Proffitt”
Should Science be Taught in Early Childhood? (2005, background): “Such conceptions of students have been labeled by a wide variety of terms in the literature, including misconceptions, preconceptions (Clement, 1982), alternative conceptions (Hewson and Hewson, 1984), and naı̈ve beliefs (McCloskey et al., 1980).”
The neuroscience of conceptual learning in science and mathematics (2016, background): “In this approach, the goal is often to describe and uncover the mechanisms underlying conceptual change as a function of new learning [13,20,21] in, for example, domains such as biology [22], physics [23], or evolution [24].”
Developmental Continuity in Teleo-Functional Explanation: Reasoning about Nature Among Romanian Romani Adults (2008, result): “These findings—taken together with education research indicating the difficulties of effecting theory change through instruction (Brumby, 1984 ; McCloskey, Caramazza, & Green, 1980 ) and neuropsychological work revealing the inhibitory activation even as schooled individuals offer scientifically “”
Understanding Natural Selection: Essential Concepts and Common Misconceptions (2009, background): “Misconceptions are well known to be common with many (perhaps most) aspects of science, including much simpler and more commonly encountered phenomena such as the physics of motion (e.g., McCloskey et al. 1980; Halloun and Hestenes 1985; Bloom and Weisberg 2007).”
Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense (2020, background): “namic event based on a static image representing the situation at a single point in time [161, 160, 162].”