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Open Access Publications from the University of California

Scholarly Works (13 results)

  • Article
  • Peer Reviewed
Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 42 (2020)
Previous work has used pairwisesimilarityjudgments among numerals to reveal development in conceptions ofnumber,from exclusively attending to magnitude in kindergarten to including properties likeparityin middle school. In adulthood,these representations appear to settle on more advanced number properties. We extend this work with the goal of observingindividual rather than group-level number representations by administering pairwise similarity tasks at two separate timepoints to determine individual consistency. Specifically, we use two 10-item number (and kinship term for comparison)sets exemplifying a variety of mathematical concepts (e.g., primeness) to 48 students across grades 3-7. Multidimensionalscaling analyses reveal magnitude as the most pervasive feature and reflect differences in attended numerical featuresrelative to score on a math assessment. Analyses are ongoing, but the consistency of this measure in a short time-framewill validate its usability as a subtle pre- and post-test surrounding concept-specific education or interventions.
    Cover page: Similarity judgments determine consistency of implicit number conceptions acrossages
    • Article
    • Peer Reviewed
    UC Berkeley Previously Published Works (2023)
    Small GTPases act as molecular switches and control numerous cellular processes by their binding and hydrolysis of guanosine triphosphate (GTP). The activity of small GTPases is coordinated by guanine nucleotide exchange factors (GEFs) and GTPase activating proteins (GAPs). Recent structural and functional studies have characterized a subset of GAPs whose catalytic units consist of longin domains. Longin domain containing GAPs regulate small GTPases that facilitate nutrient signalling, autophagy, vesicular trafficking and lysosome homeostasis. All known examples in this GAP family function as part of larger multiprotein complexes. The three characterized mammalian protein complexes in this class are FLCN:FNIP, GATOR1 and C9orf72:SMCR8. Each complex carries out a unique cellular function by regulating distinct small GTPases. In this article, we explore the roles of longin domain GAPs in nutrient sensing, membrane dynamic, vesicular trafficking and disease. Through a structural lens, we examine the mechanism of each longin domain GAP and highlight potential therapeutic applications.
      Cover page: Longin domain GAP complexes in nutrient signalling, membrane traffic and neurodegeneration
      • Article
      Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 40 (2018)
      How are numbers represented in peoples minds? Previous work has used pairwise similarity judgments among numeralsto reveal development in individuals conceptions of number, from exclusively encoding magnitude in elementary schoolto including properties like shared factors in adulthood (Miller & Gelman, 1983). We extend this observation to develop anew, expanded measure comprised of two 10-item sets exemplifying multiple mathematical concepts (e.g., squares, prime-ness), which can ultimately be used as a subtle pre- and post-test surrounding concept-specific education or interventions.Initial multidimensional scaling analyses reveal individual differences in clustering of numerals based on mathematicalproperties that are not necessarily concordant with the individuals explicit knowledge of the same properties, which wealso solicited. We thus see this as a promising way to measure implicit number conceptions and track the salience of richmathematical properties in individuals representations of number.
        Cover page: A new similarity measure to reveal individual differences and growth in implicitnumber conceptions
        • Article
        • Peer Reviewed
        Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 41 (2019)
        Fraction arithmetic is a challenging topic for students. Past work has found that many errors can be accounted for by alimited number of malrules, reflecting both execution errors and incorrect strategies (Braithwaite, Pyke, and Siegler 2017).We develop an inverse planning model for fraction arithmetic that computes students’ affinity for particular malrulesbased on their problem solutions. Inverse planning models people’s choices when solving problems, and has been used tomodel data from solving algebraic equations and playing educational games. The output of the fraction arithmetic inverseplanning model gives a more detailed assessment of a student’s knowledge than the number of problems she answerscorrectly, and does not require human interpretation of students’ solutions. Applying the model to the two datasets inBraithwaite et al. (2017) and inferring tendencies to use two specific malrules shows that its output is consistent withmanual annotations of students’ strategies.
          Cover page: Modeling students’ fraction arithmetic strategies using inverse planning
          • Article
          • Peer Reviewed
          Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 39 (2017)
          What do people think of when they think of “math?” We pro-pose that individuals may have very different working defini-tions of the category of math, and that those with broader mathconceptions may have less math anxiety. In Study 1, we intro-duce a method for indexing the “breadth” of individuals’ mathconceptions, and show that there is an inverse relation betweenconception breadth and math anxiety. These results suggestthat math anxiety is related both to how expansive individualsperceive math to be, and how skillful they feel at the activitiesthey think it could involve. Study 2 attempts an intervention onstudents’ conceptions of math with a sample of middle schoolstudents. We find the same inverse relationship in students be-tween math conception breadth and math anxiety as found inadults. We discuss ongoing work that further explores quali-tative variation in math conceptions, and the lessons this mayhold for intervening on math anxiety.
            Cover page: What counts as math?Relating conceptions of math with anxiety about math
            • Thesis
            • Peer Reviewed
            UC Berkeley Electronic Theses and Dissertations (2024)

            The mechanistic target of rapamycin complex 1 (mTORC1) regulates cell growth andcatabolism by phosphorylating key substrates in response to nutrient fluctuations. Recruitment of mTORC1 to the lysosomal membrane by the Rag-Ragulator complex is important for activation of its kinase activity and interaction with select substrates. The Rag-Ragulator complex is comprised of two small GTPases, Rag A/B and Rag C/D, and the pentameric scaffold protein complex Ragulator. The Rags GTPases exist predominately in an active (RagAGTP:RagCGDP) or inactive (RagAGDP:RagCGTP) state, with mTORC1 binding to the active state. The Rag GTPase's nucleotide state and activity are modulated by two GAPs, FLCN and GATOR1, transitioning the complex between active and inactive forms. Additional protein complexes (KICSTOR, GATOR2) and nutrient sensors (SLC38A9, Castor1, Sestrin2 and Samtor) regulate the activity of these GAPs in response to nutrient levels ultimately regulating the activity of mTORC1. In this work, structural analysis and in vitro reconstitution were used to elucidate the mechanisms of FLCN and GATOR1 regulation. The network of GATOR1 regulation was dissected to understand how the KICSTOR complex regulates GATOR1 and how nutrient sensors Castor1 and Sestrin2 relay information to the GATOR2 complex.

              • Thesis
              • Peer Reviewed
              UC Berkeley Electronic Theses and Dissertations (2021)

              What does the word "math" evoke? It is in many ways a fraught term eliciting negative reactions and unpleasant memories. In this dissertation, I explore the variety of ways we humans perceive this concept, starting with the internal (perceptions of ability), then the personal journey (perceptions of belonging), and finally the external (perceptions of conception). I employ a mixture of experiments and computational modeling in order to develop a more holistic understanding of how people perceive math and reinforce human studies with data collected from naturalistic settings - specifically, the internet, to explore word usage and how discussions of math seem to dier from mentions of other concepts.

                Cover page: The ABC's of Mathematics Perceptions
                • Article
                • Peer Reviewed
                Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 42 (2020)
                People’s assessment of their ability varies in whether it is mea-sured once following a task or sequentially via confidencejudgments recorded throughout. Multiple models have beendeveloped to predict one-off judgments of performance, whichhave often distinguished between peoples’ biases about theirgeneral ability in a domain and their sensitivity to correctness.We propose a rational model of sequential self-assessmentwhich allows us to make predictions about each individualseparately—unlike in the one-off case which looks exclusivelyat the population level—and to identify, in addition to bias andsensitivity, the extent to which individuals’ beliefs are respon-sive to their most recent evidence over the course of a task. Wefit our model to data where participants solve algebraic equa-tions and show that bias, sensitivity, and responsiveness varymeaningfully across participants.
                  Cover page: A rational model of sequential self-assessment
                  • Article
                  Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 40 (2018)
                  Self-assessment, or the evaluation of one’s ability on a task, is widely perceived as a fundamental skill, yet in most studies, people are found to be poorly calibrated to their own abilities. Some results seem to show poorer calibration for low perform- ers than for high performers. This effect has been explained in multiple ways: it could indicate worse metacognitive abil- ity among the low performers (the “Dunning-Kruger” effect), or simply regression to the mean. To tease apart these expla- nations we develop a Bayesian model of self-assessment and evaluate its predictions in two experiments. Our results suggest that poor self-assessment is caused by the influence of prior be- liefs and imperfect skill at determining whether a problem was solved correctly or not, and offer only weak support for of a relationship between metacognitive ability and performance.
                    Cover page: Modeling the Dunning-Kruger Effect: A Rational Account of Inaccurate Self-Assessment
                    • Article
                    • Peer Reviewed
                    Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 39 (2017)
                    Appraising one’s own performance after a task, known as self-assessment, has been studied from a cognitive science perspec-tive in domains such as humor, trivia, and logic. Previous stud-ies have found that participants are systematically poor at judg-ing their own performance, though sometimes self-assessmentvaries based on actual performance. We explored calibrationof self-assessment on algebra problems, a domain where peo-ple have typically received explicit instruction. In this domain,we found that people do not behave as they do in other do-mains previously studied: they are generally well-calibrated injudging their algebra performance. This suggests that in thecourse of learning to solve algebra problems, people have alsolearned to accurately judge their performance, both absolutelyand relative to others.
                      Cover page: Algebra is not like trivia:Evaluating self-assessment in an online math tutor
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