Appendix for "Perceptual Variation and Relativism"

In "Perceptual Variation and Relativism" I criticized two proposals for combining perceptual relativism with perceptual atomism. In this appendix I consider and reject several other proposals. I conclude that perceptual relativism should not be combined with perceptual atomism

Visual Noise Due to Quantum Indeterminacies

We establish that, due to certain quantum indeterminacies, there must be foundational colours that do not reliably cause any particular experience. This report functions as an appendix to Morrison's "Colour in a Physical World.

Appendix for "Perceptual Variation and Ignorance"

In "Perceptual Variation and Ignorance" I make a claims about evidence and perceptual justification that might sound controversial, but aren't. In this appendix I distinguish them from more controversial claims

Resilience, science, technology, engineering, and mathematics (STEM), and anger: A linguistic inquiry into the psychological processes associated with resilience in secondary school STEM learning.

AIM: To examine resilience in Science, Technology, Engineering, and Mathematics (STEM) learning within an ecological model, identifying the psychological processes associated with resilient, and non-resilient learning to develop a framework for promoting STEM resilience. SAMPLE AND METHOD: From a sample of secondary-school students (n = 4,936), 1,577 students who found their STEM lesson difficult were identified. Students were assessed on three resilience capabilities and asked to write a commentary on how they responded to the lesson. RESULTS: Factor analysis revealed that resilience in STEM learning could be positioned within the ecological systems model, with students' resilience being comprised of three capabilities; the ability to quickly and easily recover (Recovery), remain focussed on goals (Ecological), and naturally adjust (Adaptive capacity). Using a linguistic analysis programme, we identified the prevalence of words within the student commentaries which related to seven psychological processes. Greater ability to recover was negatively related to negative emotional processes. To increase the specificity of this relationship, we identified high and low resilient students and compared their commentaries. Low resilient students used significantly more anger words. Qualitative analysis revealed interpersonal sources of anger (anger at teacher due to lack of support) and intrapersonal sources of anger (including rumination, expression and control, and seeking distraction). CONCLUSIONS: Anger is a key process that distinguishes students who struggle to recover from a difficult STEM lesson. An ecological systems model may prove useful for understanding STEM resilience and developing intervention pathways. Implications for teacher education include the importance of students' perceptions of teacher support

Resilience, science, technology, engineering, and mathematics (STEM), and anger: A linguistic inquiry into the psychological processes associated with resilience in secondary school STEM learning

Aim: To examine resilience in Science, Technology, Engineering, and Mathematics (STEM) learning within an ecological model, identifying the psychological processes associated with resilient, and non-resilient learning to develop a framework for promoting STEM resilience. Sample and method: From a sample of secondary-school students (n = 4,936), 1,577 students who found their STEM lesson difficult were identified. Students were assessed on three resilience capabilities and asked to write a commentary on how they responded to the lesson. Results: Factor analysis revealed that resilience in STEM learning could be positioned within the ecological systems model, with students’ resilience being comprised of three capabilities; the ability to quickly and easily recover (Recovery), remain focussed on goals (Ecological), and naturally adjust (Adaptive capacity). Using a linguistic analysis programme, we identified the prevalence of words within the student commentaries which related to seven psychological processes. Greater ability to recover was negatively related to negative emotional processes. To increase the specificity of this relationship, we identified high and low resilient students and compared their commentaries. Low resilient students used significantly more anger words. Qualitative analysis revealed interpersonal sources of anger (anger at teacher due to lack of support) and intrapersonal sources of anger (including rumination, expression and control, and seeking distraction). Conclusions: Anger is a key process that distinguishes students who struggle to recover from a difficult STEM lesson. An ecological systems model may prove useful for understanding STEM resilience and developing intervention pathways. Implications for teacher education include the importance of students’ perceptions of teacher support

Resilience, science, technology, engineering, and mathematics (STEM), and anger: A linguistic inquiry into the psychological processes associated with resilience in secondary school STEM learning.

AIM: To examine resilience in Science, Technology, Engineering, and Mathematics (STEM) learning within an ecological model, identifying the psychological processes associated with resilient, and non-resilient learning to develop a framework for promoting STEM resilience. SAMPLE AND METHOD: From a sample of secondary-school students (n = 4,936), 1,577 students who found their STEM lesson difficult were identified. Students were assessed on three resilience capabilities and asked to write a commentary on how they responded to the lesson. RESULTS: Factor analysis revealed that resilience in STEM learning could be positioned within the ecological systems model, with students' resilience being comprised of three capabilities; the ability to quickly and easily recover (Recovery), remain focussed on goals (Ecological), and naturally adjust (Adaptive capacity). Using a linguistic analysis programme, we identified the prevalence of words within the student commentaries which related to seven psychological processes. Greater ability to recover was negatively related to negative emotional processes. To increase the specificity of this relationship, we identified high and low resilient students and compared their commentaries. Low resilient students used significantly more anger words. Qualitative analysis revealed interpersonal sources of anger (anger at teacher due to lack of support) and intrapersonal sources of anger (including rumination, expression and control, and seeking distraction). CONCLUSIONS: Anger is a key process that distinguishes students who struggle to recover from a difficult STEM lesson. An ecological systems model may prove useful for understanding STEM resilience and developing intervention pathways. Implications for teacher education include the importance of students' perceptions of teacher support

The Grizzly, February 15, 1980

J-Board Hears USGA Controversy • Victory Over Swarthmore: Men\u27s Basketball Captures Title • Reber Spends Semester In England • USGA Notes • Letters to the Editor • Basketball Downs K-town • MAC Championships • Lacrosse Looking Good • Spider Wrestler Line-up • The FUNdamentals of Freestyle Skiinghttps://digitalcommons.ursinus.edu/grizzlynews/1033/thumbnail.jp

Comparison and Mapping Facilitate Relation Discovery and Predication

Relational concepts play a central role in human perception and cognition, but little is known about how they are acquired. For example, how do we come to understand that physical force is a higher-order multiplicative relation between mass and acceleration, or that two circles are the same-shape in the same way that two squares are? A recent model of relational learning, DORA (Discovery of Relations by Analogy; Doumas, Hummel & Sandhofer, 2008), predicts that comparison and analogical mapping play a central role in the discovery and predication of novel higher-order relations. We report two experiments testing and confirming this prediction