It is said that there’s nothing so practical as good theory. It may also be said that there’s nothing so theoretically interesting as good practice 1 . This is particularly true of efforts to relate constructivism as a theory of learning to the practice of instruction. Our goal in this paper is to provide a clear link between the theoretical principles of constructivism, the practice of instructional design, and the practice of teaching. We will begin with a basic characterization of constructivism identifying what we believe to be the central principles in learning and understanding. We will then identify and elaborate on eight instructional principles for the design of a constructivist learning environment. Finally, we will examine what we consider to be one of the best exemplars of a constructivist learning environment -- Problem Based Learning as described by Barrows (1985, 1986, 1992).

/pdf/problem-based-learning-an-instructional-model-and-its-2r69iz9pwj.pdf

Problem Based Learning: An instructional model and its constructivist framework

In Search of Understanding. The Case for Constructivist Classrooms. [Revised.].

Reasoning is generally seen as a means to improve knowledge and make better decisions. However, much evidence shows that reasoning often leads to epistemic distortions and poor decisions. This suggests that the function of reasoning should be rethought. Our hypothesis is that the function of reasoning is argumentative. It is to devise and evaluate arguments intended to persuade. Reasoning so conceived is adaptive given the exceptional dependence of humans on communication and their vulnerability to misinformation. A wide range of evidence in the psychology of reasoning and decision making can be reinterpreted and better explained in the light of this hypothesis. Poor performance in standard reasoning tasks is explained by the lack of argumentative context. When the same problems are placed in a proper argumentative setting, people turn out to be skilled arguers. Skilled arguers, however, are not after the truth but after arguments supporting their views. This explains the notorious confirmation bias. This bias is apparent not only when people are actually arguing, but also when they are reasoning proactively from the perspective of having to defend their opinions. Reasoning so motivated can distort evaluations and attitudes and allow erroneous beliefs to persist. Proactively used reasoning also favors decisions that are easy to justify but not necessarily better. In all these instances traditionally described as failures or flaws, reasoning does exactly what can be expected of an argumentative device: Look for arguments that support a given conclusion, and, ceteris paribus, favor conclusions for which arguments can be found.

/pdf/why-do-humans-reason-arguments-for-an-argumentative-theory-19genwgdwy.pdf

Why Do Humans Reason? Arguments for an Argumentative Theory

Este articulo analiza el desarrollo y la validacion de una medida de la pertenencia percibida o la pertenencia psicologica de los estudiantes adolescentes al entorno escolar.

The psychological sense of school membership among adolescents: scale development and educational correlates.

Recent calls for instructional innovation in undergraduate science, mathematics, engineering, and technology (SMET) courses and programs highlight the need for a solid foundation of education research at the undergraduate level on which to base policy and practice. We report herein the results of a meta-analysis that integrates research on undergraduate SMET education since 1980. The meta-analysis demonstrates that various forms of small-group learning are effective in promoting greater academic achievement, more favorable attitudes toward learning, and increased persistence through SMET courses and programs. The magnitude of the effects reported in this study exceeds most findings in comparable reviews of research on educational innovations and supports more widespread implementation of small-group learning in undergraduate SMET.

Effects of Small-Group Learning on Undergraduates in Science, Mathematics, Engineering, and Technology: A Meta-Analysis:

Preface. I. COOPERATIVE LEARNING THEORY. 1. An Introduction to Cooperative Learning. 2. Cooperative Learning and Student Achievement. 3. Cooperative Learning and Outcomes Other Than Achievement. II. PRACTICAL GUIDES TO COOPERATIVE LEARNING METHODS. 4. STAD and TGT. 5. TAI and CIRC. 6. Task Specialization Methods. 7. Other Cooperative Learning Methods and Resources. References. Appendixes. Index.

Cooperative Learning: Theory, Research and Practice

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Cooperative Learning: Theory, Research and Practice