• Emergent Processes
    • Michelene T H Chi
    • Michelene T H Chi: Influence Statistics

      Michelene T H Chi

      Michelene T H Chi

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      Mary Lou Fulton Teachers’ College, Arizona State University | Learning and Cognition Lab, Payne Hall 122, Arizona State University, Tempe, Arizona, USA | Arizona State ...

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      Michelene T H Chi:Expert Impact

      Concepts for whichMichelene T H Chihas direct influence:Emergent processes,Human tutoring,Tutor learning,Knowledge convergence,Memory development,Natural selection,Verbal data,Content knowledge.

      Michelene T H Chi:KOL impact

      Concepts related to the work of other authors for whichfor which Michelene T H Chi has influence:Problem solving,Prior knowledge,Active learning,Worked examples,Science education,Mental models,Conceptual understanding.

      KOL Resume for Michelene T H Chi


      Mary Lou Fulton Teachers’ College, Arizona State University


      Learning and Cognition Lab, Payne Hall 122, Arizona State University, Tempe, Arizona, USA


      Arizona State University, United States


      Mary Lou Fulton Teachers College, Arizona State University


      Learning Sciences Institute, Mary Lou Fulton Teachers College, Arizona State University


      Arizona State University


      Department of Psychology, Arizona State University, United States


      Department of Psychology, Arizona State University


      Arizona State University, Tempe, AZ, USA


      Learning Research and Development Center, University of Pittsburgh

      Psychology in Education, Arizona State University


      Department of Psychology and the Learning Research and Development Center, University of Pittsburgh


      University of Pittsburgh


      University of Pittsburgh, Pittsburgh, USA


      Learning Research and Development Center, University of Pittsburgh, USA


      Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA 15260, USA


      Learning Research and Development Center, University of Pittsburgh, 3939 O'Hara Street, Pittsburgh, PA 15260, USA


      University of Pittsburgh, USA


      821 Learning Research and Development Centre 3939 O'Hara Street, Pittsburgh, PA 15260


      Professor of Psychology at the University of Pittsburgh and a Senior Scientist at the Learning Research and Development Center. Her research focuses on learning and conceptual change in science domains.


      Learning Research and Development Center, University of Pittsburgh, 15260, Pittsburgh, Pennsylvania, USA


      Learning, Research and Development Center, University of Pittsburgh, Pittsburgh, Pennsylvania 15260


      University of Pittsburgh, U.S.A


      U Pittsburgh, Learning Research & Development Ctr


      University of Pittsburgh, Pittsburgh, Pennsylvania, USA


      University of Pittsburgh USA


      Learning Research and Development Center, University of Pittsburgh, 3939 O’Hara Street, 15260, Pittsburgh, Pennsylvania


      Carnegie-Mellon University USA


      Carnegie-Mellon U

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      Sample of concepts for which Michelene T H Chi is among the top experts in the world.
      Concept World rank
      explicit surface features #1
      theory active learning #1
      observing students #1
      current domain knowledge #1
      lack piaget #1
      conceptual physics novices #1
      tutoring tutees #1
      held misconceptions #1
      interactive style tutoring #1
      simply instantiating #1
      keywords scientific discovery #1
      participants simulation condition #1
      kinds conceptual #1
      talkaloud protocols #1
      science ontology training #1
      icap framework #1
      tutees knowledge #1
      data tification studies #1
      cascade domain knowledge #1
      conceptual physics problem #1
      constructs ideas #1
      constructive questions #1
      students understanding article #1
      passive activities studies #1
      verbal analyses #1
      utterance discourse moves #1
      gpa median #1
      ontological categories examples #1
      knowledge cognitive performances #1
      processes misconceptions #1
      observing videos andes #1
      expert model instruction #1
      schema understand #1
      holistic confrontation #1
      frequency semantic comparisons #1
      expert performance novices #1
      1on1 human tutoring #1
      paper favor #1
      explanations jhd #1
      reading learned #1
      skills patient case #1
      ontological categories matter #1
      generated studying #1
      unknown dinosaurs #1
      Sign-in to see all concepts, it's free!

      Prominent publications by Michelene T H Chi

      KOL-Index: 8231

      The representation of physics problems in relation to the organization of physics knowledge is investigated in experts and novices. Four experiments examine (a) the existence of problem categories as a basis for representation; (b) differences in the categories used by experts and novices; (c) differences in the knowledge associated with the categories; and (d) features in the problems that contribute to problem categorization and representation. Results from sorting tasks and protocols ...

      Known for Physics Problems | Experts Novices | Problem Representation | Knowledge Categories | Sorting Tasks
      KOL-Index: 7564

      The goals of this study are to evaluate a relatively novel learning environment, as well as to seek greater understanding of why human tutoring is so effective. This alternative learning environment consists of pairs of students collaboratively observing a videotape of another student being tutored. Comparing this collaboratively observing environment to four other instructional methods-one-on-one human tutoring, observing tutoring individually, collaborating without observing, and ...

      Known for Human Tutoring | Vicarious Learning | Tutorial Dialogues | Collaboratively Observing | Instructional Methods
      KOL-Index: 7015

      Prior research has established that peer tutors can benefit academically from their tutoring experiences. However, although tutor learning has been observed across diverse settings, the magnitude of these gains is often underwhelming. In this review, the authors consider how analyses of tutors’ actual behaviors may help to account for variation in learning outcomes and how typical tutoring behaviors may create or undermine opportunities for learning. The authors examine two tutoring ...

      Known for Tutor Learning | Knowledge Building | Support Peer | Process Data | Telling Bias
      KOL-Index: 6872

      This article offers a plausible domain-general explanation for why some concepts of processes are resistant to instructional remediation although other, apparently similar concepts are more easily understood. The explanation assumes that processes may differ in ontological ways: that some processes (such as the apparent flow in diffusion of dye in water) are emergent and other processes (such as the flow of blood in human circulation) are direct. Although precise definition of the two ...

      Known for Emergent Processes | Students Misconceptions | Blood Circulation | Correct Conception | Heat Temperature
      KOL-Index: 6817

      This paper operationalized the notion of knowledge convergence and assessed quantitatively how much knowledge convergence occurred during collaborative learning. Knowledge convergence was defined as an increase in common knowledge where common knowledge referred to the knowledge that all collaborating partners had. Twenty pairs of college students collaborated to learn a science text about the human circulatory system. Comparisons of individual pre-test and post-test performance revealed ...

      Known for Knowledge Convergence | Collaborative Learning | Mental Models | College Students | Human Circulatory
      KOL-Index: 6620

      A good deal of research has addressed the topic of naive physics knowledge, with a focus on the physics domain of classical mechanics. In particular, it has been proposed that novices enter into instruction with an existing, well-defined knowledge base that they have derived from their everyday experiences. Most relevant initial knowledge will be substance based, in the sense that it represents the novice's understanding of how material objects and other types of substances behave in the ...

      Known for Naive Physics | Material Substances | Article Discussion | Everyday Life | Conceptions Concepts
      KOL-Index: 6385

      This article describes the ICAP framework that defines cognitive engagement activities on the basis of students’ overt behaviors and proposes that engagement behaviors can be categorized and differentiated into one of four modes: Interactive, Constructive, Active, and Passive. The ICAP hypothesis predicts that as students become more engaged with the learning materials, from passive to active to constructive to interactive, their learning will increase. We suggest possible ...

      Known for Icap Framework | Cognitive Engagement | Active Learning | Control Condition | Concept Mapping
      KOL-Index: 6183

      This paper summarizes the results of our investigation of: 1) how students learn to solve simple mechanics problems; 2) what is learned when they study worked-out examples in the text; and 3) how they use what has been learned from the examples while solving problems. We also provide justifications for why mechanics problems were chosen, why we examined learning from examples, and how we can capture the understanding of examples by asking students to generate explanations. The underlying ...

      Known for Examples Students | Individual Differences | Relevant Knowledge | Principles Concepts | Solve Problems
      KOL-Index: 6157

      Similar to other domains, engineering education lacks a framework to classify active learning methods used in classrooms, which makes it difficult to evaluate when and why they are effective for learning. This study evaluated the effectiveness and applicability of the Differentiated Overt Learning Activities (DOLA) framework, which classifies learning activities as interactive, constructive, or active, for engineering classes. We tested the ICAP hypothesis that student learning is more ...

      Known for Learning Activities | Icap Hypothesis | Constructive Active | Differentiated Overt | Engineering Classes
      KOL-Index: 6013

      Conceptual change occurs when a concept is reassigned from one category to another. The theory of conceptual change in this article explains why some kinds of conceptual change, or category shifts, are more difficult than others. The theory assumes that entities in the world belong to different ontological categories, such as MATTER (things) and PROCESSES. Many scientific concepts, for example light, belong in a subcategory of PROCESSES, which we call constraint-based interactions. ...

      Known for Processes Conceptual | Scientific Concepts | Learning Science | Ontological Categories | Human Circulatory
      KOL-Index: 5942

      Active, constructive, and interactive are terms that are commonly used in the cognitive and learning sciences. They describe activities that can be undertaken by learners. However, the literature is actually not explicit about how these terms can be defined; whether they are distinct; and whether they refer to overt manifestations, learning processes, or learning outcomes. Thus, a framework is provided here that offers a way to differentiate active, constructive, and interactive in terms ...

      Known for Learning Activities | Conceptual Framework | Active Constructive | Studies Literature | Psychological Theory
      KOL-Index: 5797

      ICAP is a theory of active learning that differentiates students' engagement based on their behaviors. ICAP postulates that Interactive engagement, demonstrated by co-generative collaborative behaviors, is superior for learning to Constructive engagement, indicated by generative behaviors. Both kinds of engagement exceed the benefits of Active or Passive engagement, marked by manipulative and attentive behaviors, respectively. This paper discusses a 5-year project that attempted to ...

      Known for Icap Theory | Cognitive Engagement | Active Learning | Teachers Difficulty | Activities Students
      KOL-Index: 5717

      Abstract Learning in multimedia environments is hard because it requires learners to actively comprehend and integrate information across diverse sources and modalities. Self-explanation is an effective learning strategy that helps learners develop deep understanding of complex phenomena and could be used to support learning from multimedia. Researchers have established the benefits of self-explaining across many domains for a range of ages and learning contexts (including multimedia ...

      Known for Multimedia Learning | Deep Understanding | Additional Support | Explanation Principle | Single Media
      KOL-Index: 5537

      Children and adults quantified random patterns of dots, under unlimited exposure duration. For adults and children two distinct processes appear to operate. For adults the quantification of collections of from one to three dots is essentially errorless, and proceeds at the rate of 46 msec per item, while the quantification rate for from 4 to 10 dots is 307 msec per dot. For children the same operating ranges appear to hold, however children are much slower. The lower slope is 195 msec ...

      Known for Children Adults | Pattern Recognition | Reaction Time | Child Preschool | Form Perception

      Key People For Emergent Processes

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      Lauren B Resnick
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      Mary Lou Fulton Teachers’ College, Arizona State University | Learning and Cognition Lab, Payne Hall 122, Arizona State University, Tempe, Arizona, USA | Arizona State University, United States | Mary Lou Fulton Teachers College, Arizona State Univer

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