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1

Björck, Ulric. Distributed problem-based learning: Studies of a pedagogical model in practice. Acta Universitatis Gothoburgensis, 2004.

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2

Sally, Glen, and Wilkie Kay, eds. Problem-based learning in nursing: A new model for a new context? Macmillan, 2000.

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3

Fogarty, Robin. Problem-based learning and other curriculum models for the multiple intelligences classroom. IRI/Skylight Training and Publishing, 1997.

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4

Xin, Yan Ping, ed. Conceptual Model-Based Problem Solving. SensePublishers, 2012. http://dx.doi.org/10.1007/978-94-6209-104-7.

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5

Hsu, Yayun. Partition-based Model Representation Learning. [publisher not identified], 2020.

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6

Glen, Sally, and Kay Wilkie, eds. Problem-based Learning in Nursing. Macmillan Education UK, 2000. http://dx.doi.org/10.1007/978-0-333-98240-2.

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7

1955-, Beaumont Chris, ed. Technology and problem-based learning. Information Science Pub., 2006.

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8

Eng, Chen Swee, and Australian Problem Based Learning Network., eds. Reflections on problem based learning. Australian Problem Based Learning Network, 1994.

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9

1946-, Rankin Jocelyn Anne, and Medical Library Association, eds. Handbook on problem-based learning. Forbes Custom Pub., 1999.

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10

S, Relvas Monica, Shanley Thomas P. 1963-, and Society of Critical Care Medicine., eds. Pediatric problem-based learning discussions. Society of Critical Care Medicine, 2007.

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11

Bohland, Mark A. Problem based learning: Mystery disease. Dandy Lion Publications, 2003.

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12

J, David T., ed. Problem-based learning in medicine. Royal Society of Medicine Press, 1999.

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13

Bridges, Edwin M. Problem-based learning for administrators. ERIC, 1992.

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14

E, Szalados James, Rehm Christina G, and Society of Critical Care Medicine., eds. Adult problem-based learning discussions. Society of Critical Care Medicine, 2007.

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15

Walton, Henry. Essentials of problem-based learning. Association for the Study of Medical Education, 1989.

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16

1946-, Rankin Jocelyn Anne, and Medical Library Association, eds. Handbook on problem-based learning. Forbes Custom Pub., 1999.

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17

Szalados, James E. Adult problem-based learning discussions. Edited by Society of Critical Care Medicine. Society of Critical Care Medicine, 2009.

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18

S, Relvas Monica, Shanley Thomas P. 1963-, and Society of Critical Care Medicine., eds. Pediatric problem-based learning discussions. Society of Critical Care Medicine, 2007.

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19

Chandy, Rithi John, Rima I. Ghamrawi, Veronica Emmerich, Courtney E. Heron, Steven R. Feldman, and William W. Huang. Problem Based Learning in Dermatology. CRC Press, 2024. http://dx.doi.org/10.1201/9781003437987.

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20

Alderman, Belle Y. A model for work-based learning. Scarecrow Press, 2005.

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21

David, Boud, and Feletti Grahame, eds. The Challenge of problem based learning. St. Martin's Press, 1991.

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22

Reed, Samantha S., Carol A. Mullen, and Emily T. Boyles. Problem-Based Learning in Elementary School. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70598-5.

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23

Anette Kolmos; Flemming K. Fink; Lone Krogh (eds.). The Aalborg PBL Model: Progress, Diversity and Challenges. Aalborg University Press, 2005.

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24

Wilkie, Kay, and Sally Glen. Problem-Based Learning in Nursing: A New Model for a New Context. Palgrave Macmillan, 2000.

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25

Anitescu, Magdalena. Neuroanesthesia: A Problem-Based Learning Approach. Edited by David E. Traul and Irene P. Osborn. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190850036.001.0001.

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Neuroanesthesia: A Problem-Based Learning Approach provides a comprehensive review of the field of neuroanesthesia. Its format, inspired by the American Society of Anesthesiologists model of Problem-Based Learning Discussions, incorporates a pool of practical, ABA board-exam-style multiple choice questions for self-assessment. Each of its 29 case-based chapters start with a case description, usually a compilation of several actual cases; it then branches out through case-based questions to increasingly complex situations. The structure is designed to create an authentic experience that mirrors that of an oral board examination. The discussion sections that follow offer a comprehensive approach to the chapter’s subject matter, thus creating a modern, complete, and up-to-date review of the topic. This book is equally a solid reference compendium of neuronesthesia topics and a comprehensive review to assist the general anesthesiologist both in day-to-day practice and during preparation for certification exams.
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26

Xin, Yan Ping. Conceptual Model-Based Problem Solving: Teach Students with Learning Difficulties to Solve Math Problems. BRILL, 2012.

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27

Xin, Yan Ping. Conceptual Model-Based Problem Solving: Teach Students with Learning Difficulties to Solve Math Problems. BRILL, 2012.

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28

Xin, Yan Ping. Conceptual Model-Based Problem Solving: Teach Students with Learning Difficulties to Solve Math Problems. BRILL, 2013.

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29

nerapan Model Problem Based Learning untuk Meningkatkan Partisipasi Belajar dan Hasil Belajar. Suci, 2008.

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30

Loggerenberg, Annemarie Van. Implementing a problem-based learning model in the training of teachers for an outcomes-based technology curriculum. 2000.

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31

Problem-based Learning: Welcome to the "Real World": A Teaching Model for Adult Learners. BookSurge Publishing, 2007.

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32

Experiential Student Team Consulting Process: A Problem-Based Model for Consulting and Service-Learning. CENGAGE Learning Custom Publishing, 2012.

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33

The Experiential Student Team Consulting Process: A Problem-Based Model for Consulting and Service-Learning. Cengage Learning, 2016.

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34

Model-Based Approaches to Learning: Using Systems Models and Simulations to Improve Understanding and Problem Solving in Complex Domains. BRILL, 2009.

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35

Bjorck, Ulroc. Distributed Problem-based Learning: Studies of a Pedagogical Model in Practice (Goteborg Studies in Educational Sciences). ACTA Universitatis Gothoburgensis, 2004.

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36

How to design a problem-based curriculum for the preclinical years. Springer Pub. Co., 1985.

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37

Boland, Lawrence A. Recognizing knowledge and learning in equilibrium models. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190274320.003.0007.

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This chapter introduces Part II, discussing the limits of equilibrium models. This chapter discusses how the recognition of time and information within models results in the need to deal with expectations explicitly. This leads to the problem of explaining nature of a decision maker’s knowledge – is it quantity-based or quality based. That is, is knowledge like wealth or like health. The chapter also provides a discussion of the main property that every neoclassical equilibrium must provide. Specifically, an equilibrium model’s explanation of economic events must not violate methodological individualism. The chapter criticizes the presumption that methodological individualism must be compatibility with a psychology-based model of the individual decision maker. Using a psychology-based model of the individual can undermine the idea of completely free choice, which was the original appeal of the equilibrium models.
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38

Gershman, Samuel J. Reinforcement Learning and Causal Models. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.20.

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This chapter reviews the diverse roles that causal knowledge plays in reinforcement learning. The first half of the chapter contrasts a “model-free” system that learns to repeat actions that lead to reward with a “model-based” system that learns a probabilistic causal model of the environment, which it then uses to plan action sequences. Evidence suggests that these two systems coexist in the brain, both competing and cooperating with each other. The interplay of two systems allows the brain to negotiate a balance between cognitively cheap but inaccurate model-free algorithms and accurate but expensive model-based algorithms. The second half of the chapter reviews research on hidden state inference in reinforcement learning. The problem of inferring hidden states can be construed in terms of inferring the latent causes that give rise to sensory data and rewards. Because hidden state inference affects both model-based and model-free reinforcement learning, causal knowledge impinges upon both systems.
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39

College of William & Mary. Animal Populations: A Study of Physical, Conceptual, and Mathematical Models. Kendall Hunt Pub Co, 2007.

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40

Schwartz, Peter. Problem-based Learning. Routledge, 2013. http://dx.doi.org/10.4324/9781315042541.

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41

Evensen, Dorothy H. Problem-based Learning. Routledge, 2000. http://dx.doi.org/10.4324/9781410604989.

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42

Problem-Based Learning. Routledge, 2013.

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43

Problem-Based Learning. A S M E Press, 2007.

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44

Hmelo‐Silver, Cindy E. Problem-based Learning. Taylor & Francis, Inc., 2000.

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45

Schwartz, Peter. Problem-Based Learning. Taylor & Francis Group, 2013.

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46

Wilkie, Kay, and Iain Burns. Problem Based Learning. Palgrave Macmillan, 2002.

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47

Moust/Schmidt. Problem-Based Learning. Taylor & Francis Group, 2010.

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48

Schwartz, Peter. Problem-Based Learning. Taylor & Francis Group, 2013.

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49

Schwartz, Peter. Problem-Based Learning. Taylor & Francis Group, 2013.

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50

Olmedo Torre, Noelia, Oscar Farrerons Vidal, and Anna Pujol Ferran. Constructivist learning models in training programs. OmniaScience, 2021. http://dx.doi.org/10.3926/oms.407.

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With more than 25 years of university teaching in technical careers behind them, book’s authors have been observing for a long time Constructivism. It is an essential part in training students process and how interaction between them and Instruction are decisive in learning, being equal or greater importance than the content or the way information is presented. The authors carry out their teaching activities involved with GOMS, Learning by Doing and Situated Learning models, as well as Problem Based Learning and the Case Method. All have led them to reach high levels of performance among their students. The reader can discover numerous publications made in prestigious magazines in this book. The book you are holding makes a review of the most important theories and constructivism’s models, attempting to shed light on the wide range of methodological proposals. Everything to achieve and develop higher quality teaching.
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