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 knowledge-change processes that support the ICAP hypothesis and address the limitations and caveats of the hypothesis. In addition, empirical validation for the hypothesis is provided by examining laboratory and classroom studies that focus on three specific engagement activities: note taking, concept mapping and self-explaining. We also consider how ICAP can be used as a tool for explaining discrepant findings, dictate the proper choice of a control condition, and evaluate students’ outputs. Finally, we briefly compare ICAP to existing...

The ICAP Framework: Linking Cognitive Engagement to Active Learning Outcomes.

Contents: J. Gale, Preface. Part I:Radical Constructivism and Social Constructionism. E. von Glasersfeld, A Constructivist Approach to Teaching. K.J. Gergen, Social Construction and the Educational Process. J. Shotter, In Dialogue: Social Constructionism and Radical Constructivism. J. Richards, Construct[ion/iv]ism: Pick One of the Above. Part II:Information-Processing Constructivism and Cybernetic Systems. F. Steier, From Universing to Conversing: An Ecological Constructionist Approach to Learning and Multiple Description. R.J. Spiro, P.J. Feltovich, M.J. Jacobson, R.L. Coulson, Cognitive Flexibility, Constructivism, and Hypertext: Random Access Instruction for Advanced Knowledge Acquisition in Ill-Structured Domains. K. Tomm, Response to Chapters by Spiro et al. and Steier. P.W. Thompson, Constructivism, Cybernetics, and Information Processing: Implications for Technologies of Research on Learning. Part III:Social Constructivism and Sociocultural Approaches. H. Bauersfeld, The Structuring of the Structures: Development and Function of Mathematizing as a Social Practice. J.V. Wertsch, C. Toma, Discourse and Learning in the Classroom: A Sociocultural Approach. C. Konold, Social and Cultural Dimensions of Knowledge and Classroom Teaching. J. Confrey, How Compatible Are Radical Constructivism, Sociocultural Approaches, and Social Constructivism? Analysis and Synthesis I: Alternative Epistemologies. M.H. Bickhard, World Mirroring Versus World Making: There's Gotta Be a Better Way. Part IV:Alternative Epistemologies in Language, Mathematics, and Science Education. R. Duit, The Constructivist View: A Fashionable and Fruitful Paradigm for Science Education Research and Practice. G.B. Saxe, From the Field to the Classroom: Studies in Mathematical Understanding. N.N. Spivey, Written Discourse: A Constructivist Perspective. T. Wood, From Alternative Epistemologies to Practice in Education: Rethinking What It Means to Teach and Learn. E. Ackermann, Construction and Transference of Meaning Through Form. D. Rubin, Constructivism, Sexual Harassment, and Presupposition: A (Very) Loose Response to Duit, Saxe, and Spivey. Part V:Alternative Epistemologies in Clinical, Mathematics, and Science Education. E. von Glasersfeld, Sensory Experience, Abstraction, and Teaching. R. Driver, Constructivist Approaches to Science Teaching. T. Wood, P. Cobb, E. Yackel, Reflections on Learning and Teaching Mathematics in Elementary School. P. Lewin, The Social Already Inhabits the Epistemic: A Discussion of Driver Wood, Cobb, and Yackel and von Glasersfeld. J. Becker, M. Varelas, Assisting Construction: The Role of the Teacher in Assisting the Learner's Construction of Preexisting Cultural Knowledge. E.H. Auerswald, Shifting Paradigms: A Self-Reflective Critique. Analysis and Synthesis II: Epsitemologies in Education. P. Ernest, The One and the Many. Analysis and Synthesis III: Retrospective Comments and Future Prospects. L.P. Steffe, Alternative Epistemologies: An Educator's Perspective. J. Gale, Epilogue.

教育中的建构主义 = Constructivism in Education

http://repository.hyogo-u.ac.jp/dspace/bitstream/10132/3239/1/AN100700980160017.pdf

“Science for All Americans”が語る科学とは何か

A concise and factual abstract is required (of between 100-200 words). The abstract should state briefly the purpose of the research, the principal results and major conclusions. An abstract is often presented separately from the article, so it must be able to stand alone. For this reason, References should be avoided, but if essential, then cite the author(s) and year(s). Also, non-standard or uncommon abbreviations should be avoided, but if essential they must be defined at their first mention in the abstract itself. Graphical abstract Although a graphical abstract is optional, its use is encouraged as it draws more attention to the online article. The graphical abstract should summarize the contents of the article in a concise, pictorial form designed to capture the attention of a wide readership. Graphical abstracts should be submitted as a separate file in the online submission system. Image size: Please provide an image with a minimum

English for Specific Purposes

The Cognitive Tutor Authoring Tools (CTAT) support creation of a novel type of tutors called example-tracing tutors. Unlike other types of ITSs (e.g., model-tracing tutors, constraint-based tutors)...

A New Paradigm for Intelligent Tutoring Systems: Example-Tracing Tutors

taught out contexts utility draw connections to core ideas they can appear as a disconnected bag ( 1). The ChemCollective (www.chemcollect ive. org) is a library of online activities for general chemistry instruction that engages students problem-solving activities than those found textbooks. Our goal activities that allow stu- abstract concepts to experiments panel pro- vides multiple representations of the contents of the selected including the perature and pH, cies amounts shown grams, or molar concentrations. These quantities are the in the computational of the so this provides explicit link between the paper-and-pencil calculations of the course and chemical the performs on the workbench. The virtual lab supports new forms of problem-solving. Consider of limiting reagents reaction is usually taught. A student s practice with concept typically centers a standard computational for predicting fi nal reagents, the initial amounts. Our unknown reaction

https://science.sciencemag.org/content/sci/328/5978/584.full.pdf

The ChemCollective—Virtual Labs for Introductory Chemistry Courses

The efficiency of worked examples compared to erroneous examples, tutored problem solving, and problem solving in computer-based learning environments

An important question for teachers and developers of instructional software is how much guidance or assistance should be provided to help students learn. This question has been framed within the field of educational technology as the ‘assistance dilemma’ and has been the subject of a variety of studies. In the study reported in this paper, we explore the learning benefits of four types of computer-based instructional materials, which span from highly assistive (worked examples) to no assistance (conventional problems to solve), with support levels in between these two extremes (tutored problems to solve, erroneous examples). In this never-before conducted comparison of the four instructional materials, we found that worked examples are the most efficient instructional material in terms of time and mental effort spent on the intervention problems, but we did not find that the materials differentially benefitted learners of high and low prior knowledge levels. We conjecture why this somewhat surprising result was found and propose a follow-up study to investigate this issue.

/pdf/exploring-the-assistance-dilemma-comparing-instructional-2thsmezpgv.pdf

Exploring the assistance dilemma: Comparing instructional support in examples and problems

How much help helps in discovery learning? This question is one instance of the assistance dilemma , an important issue in the learning sciences and educational technology research. To explore this question, we conducted a study involving 87 college students solving problems in a virtual chemistry laboratory (VLab), testing three points along an assistance continuum: (1) a minimal assistance, inquiry-learning approach, in which students used the VLab with no hints and minimal feedback; (2) a mid-level assistance, tutored approach, in which students received intelligent tutoring hints and feedback while using the VLab (i.e., help given on request and feedback on incorrect steps); and (3) a high assistance, direct-instruction approach, in which students were coaxed to follow a specific set of steps in the VLab. Although there was no difference in learning results between conditions on near transfer posttest questions, students in the tutored condition did significantly better on conceptual posttest questions than students in the other two conditions. Furthermore, the more advanced students in the tutored condition, those who performed better on a pretest, did significantly better on the conceptual posttest than their counterparts in the other two conditions. Thus, it appears that students in the tutored condition had just the right amount of assistance, and that the better students in that condition used their superior metacognitive skills and/or motivation to decide when to use the available assistance to their best advantage.

/pdf/how-much-assistance-is-helpful-to-students-in-discovery-34rnn0eexg.pdf

How Much Assistance Is Helpful to Students in Discovery Learning

We present an analysis of the affect that precedes, follows, and cooccurs with students' choices to go off-task or engage in on-task conversation within two versions of a virtual laboratory for chemistry. This analysis is conducted using field observation data collected within undergraduate classes using the virtual laboratory software as part of their regular chemistry classes. We find that off-task behavior co-occurs with boredom, but appears to relieve boredom, leading to significantly lower probability of later boredom. We also find that on-task conversation leads to greater future probability of engaged concentration. These results help to clarify the role that behavior outside of educational software plays in students' affect during use of that software.

http://www.columbia.edu/~rsb2162/ACII-AffectOT-2011-v27-BAL.pdf

Michael Karabinos

Papers

The ChemCollective—Virtual Labs for Introductory Chemistry Courses

The efficiency of worked examples compared to erroneous examples, tutored problem solving, and problem solving in computer-based learning environments

Exploring the assistance dilemma: Comparing instructional support in examples and problems

How Much Assistance Is Helpful to Students in Discovery Learning

The dynamics between student affect and behavior occurring outside of educational software