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

A dynamic cellular automaton model for evacuation process with obstacles

The reflective practitioner: How professionals think in action : Donald A. Schon, Basic Books, New York, 1983

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Cellular Automata And Complexity Collected Papers

Computation-based approaches in design have emerged in the last decades and rapidly became popular among architects and other designers. Design professionals and researchers adopted different terminologies to address these approaches. However, some terms are used ambiguously and inconsistently, and different terms are commonly used to express the same concept. This paper discusses computational design (CD) and proposes an improved and sound taxonomy for a set of key CD terms, namely, parametric, generative, and algorithmic design, based on an extensive literature review from which different definitions by various authors were collected, analyzed, and compared.

Computational design in architecture: Defining parametric, generative, and algorithmic design

BIM adoption across the Chinese AEC industries: An extended BIM adoption model

Generative design, which integrates multidisciplinary types of expertise in unconventional ways, was reserved just until recently to experienced and highly autodidactic designers. However, growing recognition of the importance of generative design methodologies have resulted in a need to introduce theories and applications of generative design to undergraduate students as part of their design studies. This emerging educational field of generative design teaching currently lacks methodologies, teaching experience and introductory study material. Available textbooks related to algorithmic form generation, discussing algorithmic growth, artificial life, fi-actal images, emergent behaviour and the like have originated in the field of mathematics. This resource provides an abundance of examples and generative approaches but when adapted to design education, it poses great interdisciplinary challenges which are addressed in this paper. Experiences in generative design teaching are presented, focusing on the relation between algorithmic reproduction of nature (as emphasized by authors in the mathematical field) and innovation (as commonly emphasized in design education). This discussion leads to a derivation of pedagogic suggestions as early steps on the way towards theories and curricula of generative design teaching, addressed to curriculum planners, generative design teachers as well as novices of the field such as undergraduate students.

Teaching Generative Design

Adapting cellular automata to support the architectural design process

Cellular automata in architectural design: From generic systems to specific design tools

During the past decades, complexity theory has evolved as a new discipline that provides a broad scientific perspective towards dynamic real-life phenomena, challenging the classical linear worldview as well as simple cause-and-effect-style Newtonian physics. For architects, the advent of this new science offers the challenge as well as the chance to reconsider common design approaches and to invent new strategies based on the new paradigms. The actual application of complexity theory to architectural design, however, results in a fundamental dilemma: How can a reflective, ultimately retrospective body of thought (complexity theory) be applied to prospective design challenges (architecture)? Being part of a current MArch thesis project, the proposed paper focuses on this general dilemma between architectural design and complexity theory and discusses actual as well as potential future generative architectural design approaches involving complexity theory. Generative design strategies commonly apply algorithmic methods and formalisms, which can conveniently produce and deal with high levels of complexity. Complexity describes general properties of a system and can be further dissected into several modes: epistemic, ontological and functional complexity. This taxonomy offers insights into generative design applications, which have mostly focused on a limited set of complexity modes. Besides complexity generated by sheer numbers, aspects like functional or hierarchical complexity offer further perspectives on generative systems, processes and output. Considering these aspects of complexity theory, future challenges to generative architectural design can be predicted.

Christiane M. Herr

Papers

BIM adoption across the Chinese AEC industries: An extended BIM adoption model

Teaching Generative Design

Adapting cellular automata to support the architectural design process

Cellular automata in architectural design: From generic systems to specific design tools

Generative Architectural Design and Complexity Theory