DOCSLIB.ORG

Learning to Program from Interactive Example Code (With and Without Intentional Bugs)

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Learning to Program from Interactive Example Code (With and Without Intentional Bugs) LEARNING TO PROGRAM FROM INTERACTIVE EXAMPLE CODE (WITH AND WITHOUT INTENTIONAL BUGS) A Dissertation Submitted to the Temple University Graduate Board In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY by Jean M. Griffin May 2018 Dissertation Advisory Committee Members: Dr. Kristie Newton, Advisory Chair, Teaching and Learning Dr. Catherine Schifter, Psychological Studies in Education (Emerita) Dr. Julie Booth, Psychological Studies in Education External Advisor: Dr. John Dougherty, Haverford College Computer Science ABSTRACT Computing education for learning to program has made great strides in the current century. Exciting educational technologies are now available and active learning pedagogies are increasingly used. Interest is strong, but the longstanding problem remains: learning to program as an analytical endeavor is quite frustrating for many. The purpose of this study is to discover ways to mitigate this frustration. It researches ways to help students comprehend code by guiding them to take it apart (through reading, tracing, completing, and debugging) as they learn to write code on their own. This study contributes to the understanding of learning from errors. It also builds upon and further develops the emergent pedagogy of de-constructionism. The de- constructionist approach involves taking things apart, practice, and learning from errors. This study applies a de-constructionist approach in an experiment with ~80 undergraduates learning Python in an introductory programming class. During weekly lab periods, students engaged with web-based interactive practice problems that emphasize reading, tracing, completing, and in some cases, debugging code. Students also wrote code for lab and homework assignments. Approximately half of the students were given some that involved learning from bugs that were intentionally placed in the provided code, while the others were not. Learning gains were assessed using pre/post tests and exams. Surveys were used to measure attitudes. Learning gains and attitudes were compared according to condition (Bugs, NoBugs), prior experience, gender, minority status, and class size. This study demonstrates that bugs can be intentionally incorporated into practice problems that students like to solve, without detrimental effects on learning or attitudes about computing. It also contributes to the literature on code comprehension. ii ACKNOWLEDGEMENTS I am grateful to the Temple College of Education community, especially to my committee members. My advisors Dr. Catherine Schifter and Dr. Kristie Newton encouraged me to conduct computer science education research that I found meaningful; Dr. Julie Booth provided valuable advice about my study’s research design and analysis. My external advisor Dr. John Dougherty provided subject matter expertise in CS education. I am thankful for my research apprenticeship with Carol Brandt and my interdisciplinary cohort of fellow graduate students. I am also grateful to my University of Pennsylvania masters of engineering advisor, Dr. Norm Badler, and my computer science teachers at Mills College. I was fortunate to have the cooperation of the teacher participants in my study and their department chair, and to have the opportunity to attend the 2015 International Computing Education Research (ICER) doctoral consortium. I am grateful to the Runestone Interactive development team for their education technology and to Barbara Ericson who encouraged me to use it. I appreciate all the teaching assistants and colleagues who worked with me over the years to find ways to make introductory programming more accessible and fun. I am very grateful for the support of my family including my parents, children, and siblings. I am lucky that many dear friends encouraged me on this journey. iii TABLE OF CONTENTS Page ABSTRACT ........................................................................................................................ ii ACKNOWLEDGEMENTS ............................................................................................... iv LIST OF FIGURES .......................................................................................................... vii LIST OF TABLES ........................................................................................................... viii CHAPTER 1. INTRODUCTION ...............................................................................................................1 Purpose ............................................................................................................................5 Significance of Study ......................................................................................................5 Definitions of Terms .......................................................................................................6 Organization ....................................................................................................................7 2. LITERATURE REVIEW ....................................................................................................8 Introduction .....................................................................................................................8 Theoretical Framework ..........................................................................................8 My Professional Experience ................................................................................10 Publications Included in This Review ..................................................................10 Learning by Taking Apart .............................................................................................11 Taking Apart Computer Programs ........................................................................11 Taking Apart the Invisible Notional Machine ................................................11 Reading and Completing Example Code .......................................................14 Pedagogies and Curricula ...............................................................................17 Interactive Practice Problems .........................................................................27 Summary .......................................................................................................39 Taking Apart Physical Machines .........................................................................40 Formal Education: Mechanical Dissection and Product Dissection .............41 Informal Education: Tod Phod Jod ................................................................44 Reverse Engineering .......................................................................................46 Summary ........................................................................................................50 Techniques for Taking Apart Examples ................................................................51 Learning Through Practice ............................................................................................64 Learning from Intentional Errors ..................................................................................69 Controversy and Culture .......................................................................................70 Theories .................................................................................................................71 Usage of Common Misconceptions and Errors .....................................................76 Intentional Errors for Learning Mathematics ........................................................78 Intentional Errors for Learning to Program ...........................................................88 Wisdom from Early Research .........................................................................90 Curricula and Educational Technologies ........................................................92 Summary .......................................................................................................106 Emotions ...............................................................................................................109 Learning by De-Constructing ......................................................................................111 A Model for Learning by De-Constructing ........................................................112 De-Constructionism & Constructionism ............................................................115 iv Gaps in the Literature ..................................................................................................116 Research Questions .....................................................................................................118 3. METHODS ......................................................................................................................119 Research Design ..........................................................................................................119 Context and Participants ..............................................................................................120 Practice Problems Created with Runestone Interactive .....................................122 Timeline .......................................................................................................................125 Fall 2015: Classroom Observations ...................................................................125 Spring 2016: Usability Study .............................................................................126 Spring 2016: Pilot
Load more

Recommended publications
  • CV 10 October 2012
    CURRICULUM VITAE (12 October 2012) NAME: FERRARI, Michel WORK ADDRESS: Department of Human Development and Applied Psychology Ontario Institute for Studies in Education University of Toronto 252 Bloor Street West, Room 9-132 Toronto, Ontario, M5S 1V6 Tel: (416) 978-1070 Fax: (416) 926-4713 Email: [email protected] HOME ADDRESS: 102 Glendale Avenue Toronto, ON M6R 2T2 Tel (416) 531-4825 EMAIL: [email protected] BIRTH DATE AND PLACE: 23 June 1959, Montréal CITIZENSHIP: Canadian citizen LANGUAGES: Fluent in English and French; Some German Michel Ferrari, Vita 2 DEGREES Concordia University Western Society & Culture B.A. 1983 Université du Québec à Montréal (UQAM) Psychology B.A (Core courses) 1986 Université du Québec à Montréal (UQAM) Psychology Master's 1989 Université du Québec à Montréal (UQAM) Psychology Doctorate 1994 THESES Ferrari, M (1989). Rôle de l'autorégulation dans la performance motrice d'experts et de novices (The role of self-regulation in expert and novice motor performance). Unpublished master's thesis. Université du Québec à Montréal (UQAM), Montréal. Ferrari, M (1994). L’amélioration de l’autorégulation durant l’apprentissage d’une tâche motrice (Improving self-regulation during motor learning). Unpublished doctoral dissertation. Université du Québec à Montréal (UQAM), Montréal. EXPERIENCE Research Positions Research Assistant at the Laboratory of Human Ethology. (06/88 to 12/88, and 09/ 89 to 12/89, under the supervision of Fred Strayer). Participation in all aspects of a study concerning mother- child socio-affective relations. Tasks included: filming and coding videotaped data; developing a coding scheme to observe cognitive and affective mother-child interactions; statistical analyses; preparing scientific communications.
    [Show full text]
  • Ironpython in Action
    IronPytho IN ACTION Michael J. Foord Christian Muirhead FOREWORD BY JIM HUGUNIN MANNING IronPython in Action Download at Boykma.Com Licensed to Deborah Christiansen <[email protected]> Download at Boykma.Com Licensed to Deborah Christiansen <[email protected]> IronPython in Action MICHAEL J. FOORD CHRISTIAN MUIRHEAD MANNING Greenwich (74° w. long.) Download at Boykma.Com Licensed to Deborah Christiansen <[email protected]> For online information and ordering of this and other Manning books, please visit www.manning.com. The publisher offers discounts on this book when ordered in quantity. For more information, please contact Special Sales Department Manning Publications Co. Sound View Court 3B fax: (609) 877-8256 Greenwich, CT 06830 email: [email protected] ©2009 by Manning Publications Co. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by means electronic, mechanical, photocopying, or otherwise, without prior written permission of the publisher. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in the book, and Manning Publications was aware of a trademark claim, the designations have been printed in initial caps or all caps. Recognizing the importance of preserving what has been written, it is Manning’s policy to have the books we publish printed on acid-free paper, and we exert our best efforts to that end. Recognizing also our responsibility to conserve the resources of our planet, Manning books are printed on paper that is at least 15% recycled and processed without the use of elemental chlorine.
    [Show full text]
  • Python Programming
    Python Programming Wikibooks.org June 22, 2012 On the 28th of April 2012 the contents of the English as well as German Wikibooks and Wikipedia projects were licensed under Creative Commons Attribution-ShareAlike 3.0 Unported license. An URI to this license is given in the list of figures on page 149. If this document is a derived work from the contents of one of these projects and the content was still licensed by the project under this license at the time of derivation this document has to be licensed under the same, a similar or a compatible license, as stated in section 4b of the license. The list of contributors is included in chapter Contributors on page 143. The licenses GPL, LGPL and GFDL are included in chapter Licenses on page 153, since this book and/or parts of it may or may not be licensed under one or more of these licenses, and thus require inclusion of these licenses. The licenses of the figures are given in the list of figures on page 149. This PDF was generated by the LATEX typesetting software. The LATEX source code is included as an attachment (source.7z.txt) in this PDF file. To extract the source from the PDF file, we recommend the use of http://www.pdflabs.com/tools/pdftk-the-pdf-toolkit/ utility or clicking the paper clip attachment symbol on the lower left of your PDF Viewer, selecting Save Attachment. After extracting it from the PDF file you have to rename it to source.7z. To uncompress the resulting archive we recommend the use of http://www.7-zip.org/.
    [Show full text]
  • Conference Proceedings from the Annual Carnegie Cognition Symposium (10Th, Vail, Colorado, June 2-8, 1974)
    DOCUMENT RESUME ED 123 584 CS 002 668 AUTHOR Klahr, David, Ed. TITLE Cognition and Instruction; Conference Proceedings from the Annual Carnegie Cognition Symposium (10th, Vail, Colorado, June 2-8, 1974). INSTITUTION Carnegie-Mellon Univ., Pittsburgh, Pa. Dept. of Psychology. SPONS AGENCY Office of Naval Research, Washington, D.C. Personnel and Training Research Programs Office. PUB DATE May 76 CONTRACT N00014-73-C-04^5 NOTE 356p.; Some parts of text may not reproduce clearly due to smallness of type* ' EDRS PRICE *MF-$0.83 HC-$19.41 Plus Postage. DESCPIPTOES *Cognitive Development; *Cognitive Processes; Comprehension; Conference Reports; Educational Psychology; *Instruction; *Instructional Design; *Learning; Memory; Problem Solving; *Research ABSTRACT This book, containing conference papers and a summary of activities, focuses on the contributions which current research in cognitive psychology can make to the solution of problems in instructional design. The first three parts of the book include sets of research contributions followed by discussions: part one deals with different strategies for instructional research, part two concerns process and structure in learning, and part three concentrates on the processes that underlie the comprehension of verbal instructions. The fourth part contains three Chapters that offer critiques, syntheses, and evaluations of various aspects of the preceding chapters. A list of references and author and subject indexes are included. (JM) *********************************************************************** Documents acquired by ERIC include many informal unpublished * materials not available from other sources. ERIC makes,every effort * * to obtain the best copy available. Nevertheless, items of marginal * * reproducibility are often encountered and this affects the quality * * of the microfiche and hardcopy reproddctions ERIC makes available * * via, the ERIC Document Reproduction Service (EDRS).
    [Show full text]
  • NOVEMBER 18 • WEDNESDAY Build Stuff'15 Lithuania
    Build Stuff'15 Lithuania NOVEMBER 18 • WEDNESDAY A Advanced B Beginner I Intermediate N Non­Technical 08:30 – 09:00 Registration 1. Alfa Speakers: Registration 09:00 – 09:15 Welcome talk 1. Alfa Speakers: Welcome talk 09:00 – 18:00 Open Space 6. Lobby Speakers: Open Space Sponsors: 4Finance, Devbridge, Storebrand, Visma Lietuva, WIX Lietuva 09:15 – 10:15 B Uncle Bob / Robert Martin @unclebobmartin ­ The Last Programming Language 1. Alfa Speakers: Uncle Bob / Robert Martin For the last 50 years we’ve been exploring language after language. Now many of the “new” languages are actually quite old. The latest fad is “functional programming” which got it’s roots back in the 50s. Have we come full circle? Have we explored all the different kinds of languages? Is it time for us to finally decide on a single language for all software development? In this talk Uncle Bob walks through some of the history of programming languages, and then prognosticates on the future of languages. 10:15 – 10:35 Coffee/tea break 1. Alfa Speakers: Coffee/tea break 10:35 – 11:30 I Dmytro Mindra @dmytromindra ­ Refactoring Legacy Code 5. Theta Speakers: Dmytro Mindra Every programmer has to face legacy code day after day. It might be ugly, it might look scary, it can make a grown man cry. Some will throw it away and try rewriting everything from scratch. Most of them will fail. Refactoring legacy code is a much better idea. It is not so scary when you take it in very small bites, introduce small changes, add unit tests.
    [Show full text]
  • The Best of Both Worlds?
    The Best of Both Worlds? Reimplementing an Object-Oriented System with Functional Programming on the .NET Platform and Comparing the Two Paradigms Erik Bugge Thesis submitted for the degree of Master in Informatics: Programming and Networks 60 credits Department of Informatics Faculty of mathematics and natural sciences UNIVERSITY OF OSLO Autumn 2019 The Best of Both Worlds? Reimplementing an Object-Oriented System with Functional Programming on the .NET Platform and Comparing the Two Paradigms Erik Bugge © 2019 Erik Bugge The Best of Both Worlds? http://www.duo.uio.no/ Printed: Reprosentralen, University of Oslo Abstract Programming paradigms are categories that classify languages based on their features. Each paradigm category contains rules about how the program is built. Comparing programming paradigms and languages is important, because it lets developers make more informed decisions when it comes to choosing the right technology for a system. Making meaningful comparisons between paradigms and languages is challenging, because the subjects of comparison are often so dissimilar that the process is not always straightforward, or does not always yield particularly valuable results. Therefore, multiple avenues of comparison must be explored in order to get meaningful information about the pros and cons of these technologies. This thesis looks at the difference between the object-oriented and functional programming paradigms on a higher level, before delving in detail into a development process that consisted of reimplementing parts of an object- oriented system into functional code. Using results from major comparative studies, exploring high-level differences between the two paradigms’ tools for modular programming and general program decompositions, and looking at the development process described in detail in this thesis in light of the aforementioned findings, a comparison on multiple levels was done.
    [Show full text]
  • Jupyter Tutorial Release 0.8.0
    Jupyter Tutorial Release 0.8.0 Veit Schiele Oct 01, 2021 CONTENTS 1 Introduction 3 1.1 Status...................................................3 1.2 Target group...............................................3 1.3 Structure of the Jupyter tutorial.....................................3 1.4 Why Jupyter?...............................................4 1.5 Jupyter infrastructure...........................................4 2 First steps 5 2.1 Install Jupyter Notebook.........................................5 2.2 Create notebook.............................................7 2.3 Example................................................. 10 2.4 Installation................................................ 13 2.5 Follow us................................................. 15 2.6 Pull-Requests............................................... 15 3 Workspace 17 3.1 IPython.................................................. 17 3.2 Jupyter.................................................. 50 4 Read, persist and provide data 143 4.1 Open data................................................. 143 4.2 Serialisation formats........................................... 144 4.3 Requests................................................. 154 4.4 BeautifulSoup.............................................. 159 4.5 Intake................................................... 160 4.6 PostgreSQL................................................ 174 4.7 NoSQL databases............................................ 199 4.8 Application Programming Interface (API)..............................
    [Show full text]
  • On the Cognitive Prerequisites of Learning Computer Programming
    On the Cognitive Prerequisites of Learning Computer Programming Roy D. Pea D. Midian Kurland Technical Report No. 18 ON THE COGNITIVE PREREQUISITES OF LEARNING COMPUTER PROGRAMMING* Roy D. Pea and D. Midian Kurland Introduction Training in computer literacy of some form, much of which will consist of training in computer programming, is likely to involve $3 billion of the $14 billion to be spent on personal computers by 1986 (Harmon, 1983). Who will do the training? "hardware and software manu- facturers, management consultants, -retailers, independent computer instruction centers, corporations' in-house training programs, public and private schools and universities, and a variety of consultants1' (ibid.,- p. 27). To date, very little is known about what one needs to know in order to learn to program, and the ways in which edu- cators might provide optimal learning conditions. The ultimate suc- cess of these vast training programs in programming--especially toward the goal of providing a basic computer programming compe- tency for all individuals--will depend to a great degree on an ade- quate understanding of the developmental psychology of programming skills, a field currently in its infancy. In the absence of such a theory, training will continue, guided--or to express it more aptly, misguided--by the tacit Volk theories1' of programming development that until now have served as the underpinnings of programming instruction. Our paper begins to explore the complex agenda of issues, promise, and problems that building a developmental science of programming entails. Microcomputer Use in Schools The National Center for Education Statistics has recently released figures revealing that the use of micros in schools tripled from Fall 1980 to Spring 1983.
    [Show full text]
  • Handout 16: J Dictionary
    J Dictionary Roger K.W. Hui Kenneth E. Iverson Copyright © 1991-2002 Jsoftware Inc. All Rights Reserved. Last updated: 2002-09-10 www.jsoftware.com . Table of Contents 1 Introduction 2 Mnemonics 3 Ambivalence 4 Verbs and Adverbs 5 Punctuation 6 Forks 7 Programs 8 Bond Conjunction 9 Atop Conjunction 10 Vocabulary 11 Housekeeping 12 Power and Inverse 13 Reading and Writing 14 Format 15 Partitions 16 Defined Adverbs 17 Word Formation 18 Names and Displays 19 Explicit Definition 20 Tacit Equivalents 21 Rank 22 Gerund and Agenda 23 Recursion 24 Iteration 25 Trains 26 Permutations 27 Linear Functions 28 Obverse and Under 29 Identity Functions and Neutrals 30 Secondaries 31 Sample Topics 32 Spelling 33 Alphabet and Numbers 34 Grammar 35 Function Tables 36 Bordering a Table 37 Tables (Letter Frequency) 38 Tables 39 Classification 40 Disjoint Classification (Graphs) 41 Classification I 42 Classification II 43 Sorting 44 Compositions I 45 Compositions II 46 Junctions 47 Partitions I 48 Partitions II 49 Geometry 50 Symbolic Functions 51 Directed Graphs 52 Closure 53 Distance 54 Polynomials 55 Polynomials (Continued) 56 Polynomials in Terms of Roots 57 Polynomial Roots I 58 Polynomial Roots II 59 Polynomials: Stopes 60 Dictionary 61 I. Alphabet and Words 62 II. Grammar 63 A. Nouns 64 B. Verbs 65 C. Adverbs and Conjunctions 66 D. Comparatives 67 E. Parsing and Execution 68 F. Trains 69 G. Extended and Rational Arithmeti 70 H. Frets and Scripts 71 I. Locatives 72 J. Errors and Suspensions 73 III. Definitions 74 Vocabulary 75 = Self-Classify - Equal 76 =. Is (Local) 77 < Box - Less Than 78 <.
    [Show full text]
  • Introduction to Summit Learning
    -~ -~ -~ ThE ReSeArCh tHaT SUPPOrTS SUMMit LeArNiNg Summit Learning was developed by Summit Public Schools over the course of 15 years, in partnership with nationally acclaimed learning f!~ PERTS • BEFUTURE - READY scientists, researchers, and academics. 00 LEARNING POLICY III !~..~! 1I~}:~ Center for Education PolicyResearch NAT I O NAL EQUITY HARVARD UNIVERSITY :fJ.. .-P R O J EC T ' MINDSET Yale SCHOLARS S<;.Q~t~ NETWORK Op portunity Policy in Educat ion Centerfor Emotio11c1I lntclligmcc Dig into the research with the BUCK IKSTITUTE FOR EDUCATION ••a ~l m".UMSRI Education ~ Science of Summit white paper: I mREDESIGN UCHICAGO Consortium Making Education Marr Relevant on School Research summitleaming.org/research ': ' DESiGninG FOr STUDENT SUCCESS STUDENT SUMMIT LEARNING SCHOOL OUTCOMES COMPONENTS DESIGN Mentoring Projects - --- -- -- Self-Direction The student experience is defined by specific design choices that help students achieve three key outcomes. -~ -~ Students demonstrate proficiency in the following three outcomes • ~,e I Essential and Understanding and Mindsets and behaviors transferable application of complex, that support academic lifelong skills challenging facts and achievement and concepts well-being ., ThE coMrOnEnTS OF SUMW\It LeArNiNg • Mentoring elf-Di e tio Students meet 1:1 with a Students are guided through a dedicated mentor who knows learning cycle that develops them deeply and supports them self-direction by teaching them how in setting and achieving their to set goals, make plans, short- and long-term goals. Projects demonstrate their skills and Students apply their acquired knowledge, and reflect. knowledge, skills and habits to projects that prepare them for the real-world scenarios they'll encounter in life after school.
    [Show full text]
  • Bassok, Miriam Learning from Examples Via Self-Explanations
    DOCUMENT RESUME ED 296 879 SE 049 405 AUTHOR Chi, Michelene T. H.; Bassok, Miriam TITLE Learning from Examples via Self-Explanations. Technical Report No. 11. INSTITUTION Pittsburgh Univ., ra. Learning Research and Development Center. SPONS AGENCY Office of Naval Research, Arlington, Va. Personnel and Training Research Programs Office. PUB DATE 13 Jul 88 CONTRACT N00014-84-K-0542 NOTE 56p.; Drawings may not reproduce well. PUB TYPE Reports Research/Technical (143) EDRS PRICE MF°1/PC03 Plus Postage. DESCRIPTORS *Cognitive Style; *Concept Formation; Educational Research; *Learning Strategies; Logical Thinking; *Mechanics (Physics); *Problem Solving; Schemata (Cognition); Science Education; Secondary Education; Secondary School Science ABSTRACT One approach to the study of problem solving is to observe how people with different skills (novices and experts) solve problems by collecting and analyzing protocols and formulating models to obtain solution processes. Individual differences are subsequently explained by the differences in the knowledge possessed, as embodied by the sets of production rules or programs. The intention of the models was to derive the knowledge of the skilled solver from the knowledge of the unskilled solver. Inferences about the transition have not been straightforward. An alternative approach is to determine what students acquire from studying, to represent the knowledge underlying the generation of the solution procedures for the skilled and less skilled students. This paper summarizes a stuciy 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.
    [Show full text]
  • Celebrating 50 Years of LRDC (PDF)
    UNIVERSITY OF PITTSBURGH Celebrating 50 Years of LRDC This report was published in 2014 by the University of Pittsburgh Learning Research and Development Center. THIS REPORT CELEBRATES THE UNIVERSITY OF PITTSBURGH LEARNING RESEARCH AND DEVELOPMENT CENTER’S (LRDC) 50 YEARS AS A LEADING INTERDISCIPLINARY CENTER FOR RESEARCH ON LEARNING AND EDUCATION. IT PROVIDES GLIMPSES OF LRDC OVER THE YEARS AND HIGHLIGHTS SOME OF THE EXCITING WORK THAT OCCUPIES OUR CURRENT RESEARCH AND DEVELOPMENT AGENDA. The Center’s interconnected programs of research and development have reflected its mission of stimulating interaction between research and practice across a broad spectrum of problems, from the neural basis of learning to the development of intelligent tutors to educational policy. Among research institutions in learning and education, this interconnected breadth is unique. The Center’s research has been equally wide-ranging in the domains of learning it has studied. Reading, mathematics, and science—staples of education—have been a continuing focus over much of LRDC’s 50 years. However, the Center also has addressed less-studied learning domains (e.g., history, geography, avionics, and law) as well as the reasoning and intellectual abilities that serve learning across domains. Moreover, social settings for learning, including those outside schools; teaching effectiveness; and technol- ogy for learning are all part of LRDC’s research story. LRDC’s ability to sustain research programs across these diverse, intersecting problems owes much to the cooperation of its partnering schools and depart- ments in the University. The leadership of the University of Pittsburgh has made possible what is often very difficult: a research center that has been able to effectively pursue truly cross-disciplinary research programs.
    [Show full text]