The Relationship Between Children's Approximate Number Certainty and Symbolic Mathematics
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The Integrated Nature of Metamemory and Memory
The Integrated Nature of Metamemory and Memory John Dunlosky and Robert A. Bjork Introduction Memory has been of interest to scholars and laypeople alike for over 2,000 years. In a rather gruesome example from antiquity, Cicero tells the story of Simonides (557– 468 BC), who discovered the method of loci, which is a powerful mental mnemonic for enhancing one’s memory. Simonides was at a banquet of a nobleman, Scopas. To honor him, Simonides sang a poem, but to Scopas’s chagrin, the poem also honored two young men, Castor and Pollux. Being upset, Scopas told Simonides that he was to receive only half his wage. Simonides was later called from the banquet, and legend has it that the banquet room collapsed, and all those inside were crushed. To help bereaved families identify the victims, Simonides reportedly was able to name every- one according to the place where they sat at the table, which gave him the idea that order brings strength to our memories and that to employ this ability people “should choose localities, then form mental images of things they wanted to store in their memory, and place these in the localities” (Cicero, 2001). Tis example highlights an early discovery that has had important applied impli- cations for improving the functioning of memory (see, e.g., Yates, 1997). Memory theory was soon to follow. Aristotle (385–322 BC) claimed that memory arises from three processes: Events are associated (1) through their relative similarity or (2) rela- tive dissimilarity and (3) when they co-occur together in space and time. -
The Effects of a Suggested Encoding Strategies on Achievement
The Effects of Metacognition 17 The Effects of Metacognition and Concrete Encoding Strategies on Depth of Understanding in Educational Psychology Suzanne Schellenberg, Meiko Negishi, & Paul Eggen, University of North Florida The study compared the academic achievement, as measured by final examination scores, of an experimental group of undergraduate educational psychology students who were provided with concrete mechanisms designed to promote metacognition and the use of specific encoding strategies to the achievement of a control group of similar students who were not provided with the same concrete mechanisms. The two groups were taught by the same instructor, who used the same teaching methods and identical class activities, homework, quizzes, and tests. The results indicated a statistically significant difference between the two groups, favoring the experimental group. Implications of the study for instruction and suggestions for further research are included. This study explored instructional capacity working memory that designs that encourage learners to consciously organizes information into become responsible for their own conceptual structures that make sense to learning. Responsible learners are the individual, a long-term memory that metacognitive, strategic, and high stores knowledge and skills in a achievers. Therefore, researchers have relatively permanent fashion, and become interested in investigating ways metacognitive monitoring that regulates to foster learners’ metacognition and this processing (Atkinson & Shiffrin, strategy use. 1968; Chandler & Sweller, 1990; Mayer The purpose of the study was to & Chandler, 2001; Paas, Renkl, & examine the impact of concrete Sweller, 2004; Sweller, 2003; Sweller, mechanisms for promoting van Merrienboer, & Paas, 1998). The metacognition and the conscious use of way knowledge is stored in long-term encoding strategies on the achievement memory has an important impact on of undergraduate educational learners’ ability to retrieve that psychology students. -
Impact of Feedback on Perception and Metacognition 1
IMPACT OF FEEDBACK ON PERCEPTION AND METACOGNITION 1 The impact of feedback on perceptual decision making and metacognition: Reduction in bias but no change in sensitivity Nadia Haddara & Dobromir Rahnev School of Psychology, Georgia Institute of Technology, Atlanta, GA, USA Keywords: perceptual decision maKing, metacognition, criterion, bias, sensitivity, confidence calibration. Corresponding authors: Nadia Haddara Dobromir Rahnev Georgia Institute of Technology Georgia Institute of Technology 831 Marietta St NW 654 Cherry St NW Atlanta, GA 30318 Atlanta, GA 30332 [email protected] [email protected] IMPACT OF FEEDBACK ON PERCEPTION AND METACOGNITION 2 Abstract It is widely believed that feedbacK improves behavior but the mechanisms behind this improvement remain unclear. Different theories postulate that feedback has either a direct effect on performance through automatic reinforcement mechanisms or only an indirect effect mediated by a deliberate change in strategy. To adjudicate between these competing accounts, we performed two large studies (total N = 518) with approximately half the subjects receiving trial-by-trial feedback on a perceptual task, while the other half not receiving any feedback. We found that feedback had no effect on either perceptual or metacognitive sensitivity even after seven days of training. On the other hand, feedback significantly affected subjects’ response strategies by reducing response bias and improving confidence calibration. These results strongly support the view that feedback does not improve behavior through direct reinforcement mechanisms but that its beneficial effects stem from allowing people to adjust their strategies for performing the tasK. Word count: 149/150 IMPACT OF FEEDBACK ON PERCEPTION AND METACOGNITION 3 Statement of relevance How can we help people improve their performance? It is often thought that across a variety of domains from education to worK settings to sports achievements to various cognitive tasks, performance can be improved by simply providing feedbacK. -
Systems Neuroscience of Mathematical Cognition and Learning
CHAPTER 15 Systems Neuroscience of Mathematical Cognition and Learning: Basic Organization and Neural Sources of Heterogeneity in Typical and Atypical Development Teresa Iuculano, Aarthi Padmanabhan, Vinod Menon Stanford University, Stanford, CA, United States OUTLINE Introduction 288 Ventral and Dorsal Visual Streams: Neural Building Blocks of Mathematical Cognition 292 Basic Organization 292 Heterogeneity in Typical and Atypical Development 295 Parietal-Frontal Systems: Short-Term and Working Memory 296 Basic Organization 296 Heterogeneity in Typical and Atypical Development 299 Lateral Frontotemporal Cortices: Language-Mediated Systems 302 Basic Organization 302 Heterogeneity in Typical and Atypical Development 302 Heterogeneity of Function in Numerical Cognition 287 https://doi.org/10.1016/B978-0-12-811529-9.00015-7 © 2018 Elsevier Inc. All rights reserved. 288 15. SYSTEMS NEUROSCIENCE OF MATHEMATICAL COGNITION AND LEARNING The Medial Temporal Lobe: Declarative Memory 306 Basic Organization 306 Heterogeneity in Typical and Atypical Development 306 The Circuit View: Attention and Control Processes and Dynamic Circuits Orchestrating Mathematical Learning 310 Basic Organization 310 Heterogeneity in Typical and Atypical Development 312 Plasticity in Multiple Brain Systems: Relation to Learning 314 Basic Organization 314 Heterogeneity in Typical and Atypical Development 315 Conclusions and Future Directions 320 References 324 INTRODUCTION Mathematical skill acquisition is hierarchical in nature, and each iteration of increased proficiency builds on knowledge of a lower-level primitive. For example, learning to solve arithmetical operations such as “3 + 4” requires first an understanding of what numbers mean and rep- resent (e.g., the symbol “3” refers to the quantity of three items, which derives from the ability to attend to discrete items in the environment). -
Metacognitive Awareness Inventory
Metacognitive Awareness Inventory What is Metacognition? The simplest definition of metacognition is “thinking about thinking.” This refers to the “self-regulation” effective learners exhibit, meaning they are aware of their learning process and can measure how efficiently they are learning as they study. Essentially, metacognition involves two simultaneous levels of thought: the first level is the student’s thinking/learning about the specific subject content and the second level is the student’s thinking about his/her learning. A student practicing metacognition would ask him/herself “How am I thinking?” or “Where am I in the learning process? Am I learning/understanding this topic? How could I learn more effectively?” These two levels are: knowledge and regulation. Students who are metacognitively aware demonstrate self-knowledge: They know what strategies and conditions work best for them while they are learning. Declarative, procedural, and conditional knowledge are essential for developing conceptual knowledge (content knowledge). Regulation refers to students’ knowledge about the implementation of strategies and the ability to monitor the effectiveness of their strategies. When students regulate, they are continually developing and monitoring their learning strategies based on their evolving self-knowledge. Complete the Metacognitive Awareness Inventory to assess your metacognitive processes. The Inventory Check True or False for each statement below. After you complete the inventory, use the scoring guide. Contact an Academic Coach at the Academic Support Center at (856) 681-6250 to discuss your results and strategies to increase your metacognitive awareness. True False 1. I ask myself periodically if I am meeting my goals. 2. I consider several alternatives to a problem before I answer. -
Assessing Metacognition As a Learning Outcome in a Postsecondary Strategic Learning Course
Journal of Postsecondary Education and Disability, 27(1), 51 - 62 51 Assessing Metacognition as a Learning Outcome in a Postsecondary Strategic Learning Course Patricia Mytkowicz Diane Goss Bruce Steinberg Curry College Abstract While metacognition is an important component of the learning process for college students, development of meta- cognitive knowledge and regulation is particularly important for students with LD and/or ADHD. The research- ers used Schraw and Dennison’s (1994) Metacognitive Awareness Inventory (MAI) to assess first year college students’ baseline and follow-up levels of metacognitive awareness during a strategic learning course for students with LD and/or ADHD. Over their first year in college, the students showed significant improvements in a number of metacognitive subprocesses. Several subprocess scores were also found to be positively correlated with GPA. This study’s findings can be helpful to practitioners in the postsecondary LD support field. This approach may also be an appropriate way to evaluate the effectiveness of LD support programs when used as part of a broader programmatic review. Keywords: Metacognition, learning outcomes, learning disability, postsecondary Students with learning disabilities (LD) and/or At- must have adequate self-awareness in order to recognize tention Defi cit Hyperactivity Disorder (ADHD) have and articulate their need for accommodations or other particular learning needs that may place them at risk support services to appropriate personnel. Students with for academic failure. Indeed, in comparison to peers ADHD also face challenges to college success. Blase et without LD, they have lower rates of persistence to al., (2009) found that students with current diagnoses of graduation. -
Using Metacognitive Strategies to Support Student Self-Regulation
Professional Practice Note 14 Teaching students metacognitive strategies1 offers students USING tools to “drive their brains”2. WHO BENEFITS FROM THE USE OF METACOGNITIVE METACOGNITIVE STRATEGIES? ‘Explicit attention to and application of thinking STRATEGIES TO skills enables students to develop an increasingly sophisticated understanding of the processes SUPPORT STUDENT they can employ whenever they encounter both the familiar and unfamiliar, to break ineffective habits and build on successful ones, building a SELF-REGULATION capacity to manage their thinking.’ AND EMPOWERMENT Victorian Curriculum and Assessment Authority All students, regardless of their age, background or ‘Where students have developed strong metacognitive skills, we see them evaluating and achievement level, benefit from the use of metacognitive sharing evidence about their thinking.’ strategies. This journey, which starts in early childhood and continues through primary school, secondary school and Dean Bush, Assistant Principal, Seymour College beyond, is mapped in the Critical and Creative Thinking OVERVIEW capability of the Victorian Curriculum F-10 (the Curriculum). Teaching metacognitive strategies can greatly enhance The sophistication of the metacognitive skills students can learning for all students in all subject areas. master increases as they progress through education. This professional practice note provides advice to support Students can start with the ability to monitor progress school leaders and teachers in the integration of towards the achievement of learning goals negotiated with metacognitive strategies in everyday teaching. the teacher. This negotiation and monitoring plays an important role in the learning of all students, regardless of In addition, it includes examples of how schools can their background or previous achievement. implement metacognitive strategies to assist students to build self-regulation and develop a strong sense of agency Metacognitive strategies can also be differentiated to bolster in their learning. -
True Numerical Cognition in the Wild Research-Article6868622017
PSSXXX10.1177/0956797616686862Piantadosi, CantlonTrue Numerical Cognition in the Wild 686862research-article2017 Research Article Psychological Science 2017, Vol. 28(4) 462 –469 True Numerical Cognition in the Wild © The Author(s) 2017 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI:https://doi.org/10.1177/0956797616686862 10.1177/0956797616686862 www.psychologicalscience.org/PS Steven T. Piantadosi and Jessica F. Cantlon Department of Brain and Cognitive Sciences, University of Rochester Abstract Cognitive and neural research over the past few decades has produced sophisticated models of the representations and algorithms underlying numerical reasoning in humans and other animals. These models make precise predictions for how humans and other animals should behave when faced with quantitative decisions, yet primarily have been tested only in laboratory tasks. We used data from wild baboons’ troop movements recently reported by Strandburg-Peshkin, Farine, Couzin, and Crofoot (2015) to compare a variety of models of quantitative decision making. We found that the decisions made by these naturally behaving wild animals rely specifically on numerical representations that have key homologies with the psychophysics of human number representations. These findings provide important new data on the types of problems human numerical cognition was designed to solve and constitute the first robust evidence of true numerical reasoning in wild animals. Keywords numerosity, evolution, numerical cognition, animal cognition Received 1/11/16; Revision accepted 12/8/16 Over the past half century, laboratory work on numerical who are able to follow a consensus group vote rather processing has advanced considerably in psychology, than an experienced leader or despot will face fewer fit- neuroscience, and comparative cognition. -
The Development of Numerical Cognition in Children and Artificial
The development of numerical cognition in children and artificial systems: a review of the current knowledge and proposals for multi-disciplinary research DI NUOVO, Alessandro <http://orcid.org/0000-0003-2677-2650> and JAY, Tim Available from Sheffield Hallam University Research Archive (SHURA) at: http://shura.shu.ac.uk/23767/ This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it. Published version DI NUOVO, Alessandro and JAY, Tim (2019). The development of numerical cognition in children and artificial systems: a review of the current knowledge and proposals for multi-disciplinary research. Cognitive Computation and Systems. Copyright and re-use policy See http://shura.shu.ac.uk/information.html Sheffield Hallam University Research Archive http://shura.shu.ac.uk Cognitive Computation and Systems Review Article eISSN 2517-7567 Development of numerical cognition in Received on 28th September 2018 Revised 10th December 2018 children and artificial systems: a review of the Accepted on 2nd January 2019 doi: 10.1049/ccs.2018.0004 current knowledge and proposals for multi- www.ietdl.org disciplinary research Alessandro Di Nuovo1 , Tim Jay2 1Sheffield Robotics, Department of Computing, Sheffield Hallam University, Howard Street, Sheffield, UK 2Sheffield Institute of Education, Sheffield Hallam University, Howard Street, Sheffield, UK E-mail: [email protected] Abstract: Numerical cognition is a distinctive component of human intelligence such that the observation of its practice provides a window in high-level brain function. The modelling of numerical abilities in artificial cognitive systems can help to confirm existing child development hypotheses and define new ones by means of computational simulations. -
Predicting Biases in Very Highly Educated Samples: Numeracy and Metacognition
Judgment and Decision Making, Vol. 9, No. 1, January 2014, pp. 15–34 Predicting biases in very highly educated samples: Numeracy and metacognition Saima Ghazal∗ Edward T. Cokely,∗ † Rocio Garcia-Retamero†‡ Abstract We investigated the relations between numeracy and superior judgment and decision making in two large community outreach studies in Holland (n=5408). In these very highly educated samples (e.g., 30–50% held graduate degrees), the Berlin Numeracy Test was a robust predictor of financial, medical, and metacognitive task performance (i.e., lotteries, intertemporal choice, denominator neglect, and confidence judgments), independent of education, gender, age, and another numeracy assessment. Metacognitive processes partially mediated the link between numeracy and superior performance. More numerate participants performed better because they deliberated more during decision making and more accurately evaluated their judgments (e.g., less overconfidence). Results suggest that well-designed numeracy tests tend to be robust predictors of superior judgment and decision making because they simultaneously assess (1) mathematical competency and (2) metacognitive and self-regulated learning skills. Keywords: numeracy, risk literacy, individual differences, cognitive abilities, superior decision making, judgment bias, metacognition, confidence, dual systems. 1 Introduction Furlan, Stein, & Pardo, 2012; Lindberg, & Friborg, 2013; Schapira et al., 2012; Weller, Dieckmann, Tusler, Mertz, Statistical numeracy—i.e., one’s practical understanding Burns, -
Teaching Implications of Information Processing Theory and Evaluation Approach of Learning Strategies Using LVQ Neural Network
WSEAS TRANSACTIONS on Andreas G. Kandarakis and Marios S. Poulos ADVANCES in ENGINEERING EDUCATION Teaching Implications of Information Processing Theory and Evaluation Approach of learning Strategies using LVQ Neural Network 1ANDREAS G. KANDARAKIS and 2MARIOS S. POULOS 1Department of Special Education and Psychology University of Athens Greece [email protected] 2Department of Archives and Library Sciences Ionian University, Corfu, Greece [email protected] Abstract: - In terms of information processing model, learning represents the process of gathering information, and organizing it into mental schemata. Information-processing theory has definite educational implications for students with learning and behavior problems. Teachers with a greater understanding of the theory and how it is formed to, select learning strategies in order to improve the retention and retrieval of learning. But it must also be taken into consideration that the learning environment has specific effects on academic achievement. Socialization alters the levels of stress, confidence, and even the content knowledge. Social support provides encouragement, stress reduction, feedback, and communication factors which enable learning. Furthermore, an evaluation of 4 learning strategies attempted via a well-formed LVQ Neural Network. Key-Words: - information processing, memory, matacognition, learning strategies, general education classroom, learning, behavioral problems and neural networks. 1. Introduction 2. The information-processing While behaviorists talk about learning as the result of theory the interactions between an organism and its At a first glance, the gathering and storage of environment or changes in responses, the cognitive information may seem less efficient as a approach focuses on the knowledge which guides those learning system compared to the behaviorist responses. -
Language-Specific Numerical Estimation in Bilingual Children
BILINGUAL ESTIMATION 1 Language-specific numerical estimation in bilingual children Elisabeth Marchand1, Shirlene Wade2,3, Jessica Sullivan4, & David Barner1 1University of California, San Diego 2University of Rochester 3University of California, Berkeley 4Skidmore College CONTACT: Elisabeth Marchand Department of Psychology, UCSD 9500 Gilman Drive, La Jolla CA 92093 [email protected] BILINGUAL ESTIMATION 2 Abstract We tested 5- to 7-year-old bilingual learners of French and English (N = 91) to investigate how language-specific knowledge of verbal numerals affects numerical estimation. Participants made verbal estimates for rapidly presented random dot arrays in each of their two languages. Estimation accuracy differed across children’s two languages, an effect which remained when controlling for children’s familiarity with number words across their two languages. Also, children’s estimates were equivalently well ordered in their two languages, suggesting that differences in accuracy were due to how children represented the relative distance between number words in each language. Overall, these results suggest that bilingual children have different mappings between their verbal and non-verbal counting systems across their two languages and that those differences in mappings are likely driven by an asymmetry in their knowledge of the structure of the count list across their languages. Implications for bilingual math education are discussed. Keywords: Numerical cognition, number estimation, bilingualism, cognitive development BILINGUAL