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249
Index
AAbelson, H., 23, 34Abhiram, 191Abstract data types, 9, 237Abstraction, 9, 23, 42, 43, 48, 65, 102,
125, 148levels of, 34
Academia, viiACM Inroads magazine, 52ACM K–12 Education Task Force, 2ACM K–12 Task Force Curriculum
Committee, 218, 239ACM Task Force, 22ACM Transactions
on Computing Education, 52Action research, 248Active learning, 4, 6, 13, 251
in the MTCS course, 14Active-learning-based teaching methods, 95Active-learning-based teaching model,
13, 14, 16Active-learning teaching approach, 220Activity, open-end, 17Aharoni, D., 244, 245Alan Turing, 28Algorithm, 8, 42
correctness, 67, 154development, 67efficiently, 67visualization, 137
Algorithmic patterns, 74, 214, 237Algorithmic problems, 48Alice, 49, 140Almstrum, V., 135, 136Alon, A.J.D., 135Alternative conceptions, 7, 11, 57, 83, 170
learners, 83, 109Alternative consideration, 66Ambler, A.L., 34Analogies, 65, 113, 234Anderson, R., 14
Animation, 8, 17, 129Animation-based IDEs, 237AP, 1, 174Armoni, M., 48, 244, 245Armstrong, J., 34, 49Array, 153, 161, 237
of accumulators, 189boundaries, 189cell content, 189cell index, 189of counters, 189merge, 189of objects, 189one-dimensional, 188–193scans, 189search, 189sort, 189
Art, 199Arter, J., 183Artificial inelegance, 28Assessment
formative, 175peer, 175portfolio, 180summative, 175
Assignment, 42Association for Computing Machinery
(ACM), 28, 52Astrachan, O., 73Automata
push-down, 238theory, 164
Automatonfinite, 164push down, 164
Averbuch, H., 73, 74, 210
BBaecker, R., 134Baloian, N., 49Barak, M., 117
O. Hazzan et al., Guide to Teaching Computer Science: An Activity-Based Approach,DOI 10.1007/978-0-85729-443-2, © Springer-Verlag London Limited 2011
250 Index
Barg, M., 117Barnes, T., 191Bashford, M., 49Batory, D., 72Beck, W., 73Bednarik, R., 136Beeri, C., 240Ben-Ari, M., 15, 49, 70, 135, 227Ben-Bassat Levy, R., 49, 135Ben-David Kollikant, Y., 87Bents, M., 84Bents, R., 84Berger, C., 117Berne, J., 217Berry, G., 73Bethel, L.J., 210Binary tree, 211, 237Biology, 125Bischof, E., 49Blank, G.D., 49Blog, 191Bloom, B.S., 167BlueJ, 49Blue, J., 140Blumenfeld, P.C., 117Blum, L., 4, 49, 239, 240BNF grammar, 164Boolean
expressions, 103functions, 103
Borko, H., 217Bottom-up methodology, 72Brainstorming, 65Branching, 42Brandes, O., 49, 244Bridging gaps, 16Brooks, J., 17Brooks, M.G., 17Bruce, K.B., 191Brunching strategies, 103Bubble sort, 189, 224Burnett, M.M., 34Business issues, 30
CC++, 27Cañas, A.J., 107Carey, T., 34Caristi, J., 183Chaffin, A., 48Chamillard, A.T., 183Chemistry, 125Choosing an approach, 66Clancy, M.J., 74
Class, 42demography, 32
Classification, 96, 198activity, 42, 199–201, 237page, 200–201question, 159of recursive phenomena, 197task, 110
Classmate cooperation, 117Class organization, 7, 95, 134
methods, 237Clinical conversation, 90Closed questions, 162Cognition, 148Cognitive diversity, 84Cognitive skills, 8, 148Cognitive tool, 65Colors, 211Comer, D.E., 22Complexity, 238Comprehension, 148Computability, 28Computational machines,
history of, 28Computational models, 27, 237
deterministic, 238finite, 238
Computer, 23architecture, 136the history of, 27lab/laboratory, 5, 8, 124, 186, 236
Computerised DNA sequence databases, 25
Computerized tools, 49Computer science
curriculum, 4, 6, 9discipline of, 7heuristics, 43high school curricula, 23history of, 5, 7, 21, 22, 26, 214name of, 23nature of, 23, 238and other sciences, 25social issues of, 7, 21, 22, 29soft ideas, 7, 21, 38what is, 3, 7, 22, 236
Computer science educationcommunity, 51, 187content aspect, 222ethics in, 30journal, 52pedagogical aspect, 224research conducted on, 4research in, 47–60
251Index
social issues, viiteaching methods in, 7
Computer science education research, 86, 248
categories of, 48–49the learner’s perspective, 50resources for, 48, 52the teacher’s perspective, 51–52world of, 53
Computer science instructors, in the university, 11
Computer science lens, 143Computer science teacher preparation
program, 246construction of, 246structure of, 247, 248
Computer science teachers, 49high school, vii, 1, 2, 11in-service, vii, 4, 11leading, 49preparation programs, 9professional conception, 19professional identity, 4prospective, vii, 13, 16
Computer science teaching, 1, 2, 4, 5, 8, 11
certificate, 2license, 9, 239, 241, 244social issues in, 49
Computer scientists, 5, 7, 9, 22, 28Computing as a Discipline report, 22Computing Curricula 2001, 24, 29The Computing Research Association, 27Concept map, 18, 96, 107, 110, 237
construction, 109evaluation, 110
Conceptual teaching, 224Concept understanding, 48Conclusions, intermediate, 133Concretization, 148Concurrent paradigm, 34Conditional expressions, 236Conditional statement, 103, 129Conditional-statement-bingo game, 98Confrey, J., 14Confucius, 14Considerations
external-to-the-class, 186internal-to-the-class, 186
Constructivism, 14Constructivist approach, 13, 111, 124Constructivist educators, 14Constructivist perspective, 107Constructivist teachers, 32
Constructivist teaching methods, 13Control structures, 9, 10, 42,
112, 237Cooper, M.L., 135Corder, C., 34Correctness, 42Cortina, T.J., 49Course-summary exam, 174Cox, L., 73CSTA, 2, 12CS-unplugged, 95, 237Curriculum, 7–10, 13, 239Customer stories, 176Czerniak, C., 117
DDale, N.B., 210Daniels, M., 14, 17, 49Danyluk, A., 191Dark, M.J., 49Darling-Hammond, L., 230Data representation, 42Data structures, 100Data types, 103Davis, K.M., 14Davis, R.B., 14, 15Debugging, 17, 42, 48, 75Decision making, 148Decker, A., 191Deek, F., 2, 218, 233, 239Defined curriculum, 240Denier, S., 48Denning, P.J., 22de Raadt, M., 48Design, 23Diagnostic exercises, 85Dijkstra, E.W., 23, 28, 39, 72Disciplinary knowledge, 229The discipline of computer science, 21Discovery learning, 70diSessa, A.A., 15, 50Distance learning, 143Diversity, 32, 49, 236
cognitive, 84Divide and conquer, 65Divisors, 150Doppelt, Y., 117Doran, K., 48Double recursion, 215Drake, J., 73Dreyfus, T., 136Dry lab, 127Dubinsky, Y., 183, 244Dyck, L., 49
252 Index
EEagle, M., 191East, J.P., 48, 73Edsger Dijkstra, 28Educators, computer science, viiEdwards, S.H., 48Efficiency, 42, 103, 155, 189Egert, C., 191Eick, C.J., 218, 230Engagement taxonomy, 135
changing, 136constructing, 136controlled viewing, 136entering input, 136modifying, 136no viewing, 135presenting, 136responding, 136reviewing, 136viewing, 135
Engelhart, M.D., 167Engineering, 23ePortfolio, 180Erlwanger, S.H., 50Ernest, P., 117Ethical dilemmas, analysis of, 31Ethics, 4, 13, 49, 238
code of, 30Evaluation, 8, 10, 43, 86, 109, 169, 197, 198,
212–213project, 169, 174rubric, 170, 172of the students enrolled in the MTCS
course, 170the students in the MTCS course, 182teacher, 175
Evaluation rubric, software projects, 177
Examcourse-summary, 174how to evaluate, 236how to write, 236
Examples, 234Experience in computer science education,
217, 237Experimental process, 128Experimental scientific method, 23Experiments, 124
FFaulkner, X., 14, 17Fekete, A., 117Felleisen, M., 127
Fibonacci, 203, 208Filter, 214Fincher, S., 118, 183Finite automaton, 164The first lesson, teacher’s
conception about, 226Fitzgeraldb, S., 49Flag metaphor, 103Flatt, M., 34, 49Fleck, A., 49Floyd, R.W., 34Fluery, A.N., 54Ford, G., 210Forisek, M., 49For loop, 157Formal language, 42Formative assessment, 175, 179Formative evaluation, 190Fossum, T.V., 49Fractals, 198, 201, 211, 212Friedman, D.P., 127Fuller, F.F., 84Functional approach, 103Functional paradigm, 34Functions, 103Furlong, J., 230Furst, E.J., 167
GGal-Ezer, J., 3, 4, 59, 60, 218, 240,
242, 245Games, 96, 191, 237
advantages and disadvantages, 96
Garner, S., 48Gehringer, E.F., 14Gender, diversity, 33Generalization, 42, 148George, C.E., 201Gersting, J.L., 198Ginat, D., 73, 74Grading policy, 176, 179Graph algorithms, 28Green, A.M., 117Greenfoot, 140Gries, D., 22Guide
chapter description, 6how to use, 9motivation for writing, 2structure and organization, 5
Guiding software projects development, 236, 237
253Index
HHaberman, B., 2, 34, 49, 54, 73, 74, 87, 210,
218, 245Haden, P., 48Haller, S.M., 49Halting problem, 163Hands-on experience, 125Hanks, B., 49Harel, D., 3, 59, 60, 240, 242Haridi, S., 34Harland, J., 167Harvey, B., 201, 205Hauer, A., 49Hayes, E., 183Haynes, S.M., 210Hazzan, O., 2, 4, 13, 16, 26, 29–33, 38, 43, 49,
88, 117, 139, 167, 183, 195, 211, 218, 219, 226, 227, 229, 233, 234, 240, 244, 246, 248
Heap, 38Hebetim - Journal of the Israeli National
Center for Computer Science Teachers, 54, 94, 97
Hicks, D., 48High school, vii, 1, 3, 4, 7, 9–12
practicum, 248High school computer science curricula,
designers of, 246High school computer science curriculum,
235, 236, 244High school computer science teacher
preparation programs, 239History
of computational machines, 28of computer science, 22, 26,
214, 236of computing, 29of object-oriented software
development, 27Hodnigg, K., 49Hofstadter, D., 198Howland, J.E., 191Human Genome Project, 25Hypothesis testing, 65
IIDEs, visualization- and
animation-based, 140IEEE-CS/ACM Joint Task Force, 30Illustrations, 234Imperative approach, 103Individual work, 103Inference, 148
Informatics in Secondary Schools: Evolution and Perspective (ISSEP), 52
Information resource, 143Inheritance, 48Innovation and Technology in Computer
Science (ITiCSE), 52Input-output, 42Inroads - ACM SIGCSE Bulletin, 52Inroads - The SIGCSE Bulletin, 32In-school mentor, 218In-service training, 248The instructor, role of, 18Integrative understanding, 117Intellectual property, 29Interactivity, 97Intermediate conclusions, 131Internet, 8, 123, 194, 236, 237
exploration, 24Interview, 91Introduction to computer
science course, 117Israeli high-school computer science
curriculum, 239Israeli National Center for Computer Science
Teachers, 54, 94, 97, 238, 246
JJava, 6, 27, 49, 203, 211
development environments, 236
Jeliot, 49, 140Jigsaw, 116Johnson, D.S., 114Johnson, M., 113The Joint Task Force on Computing
Curricula of the IEEE Computer Society and the Association for Computing Machinery, 24
Jones, J., 2, 218, 233, 239Jones, K.O., 167Jones, M.T., 218, 230Joni, S.A., 54Joyce, D., 126
KKaczmarczyk, L.C., 48Kahney, H., 204, 210Kaila, E., 75Karel, 49Karel J. Robot, 140Karel the robot, 237Kay, J., 117Kessler, R., 115
254 Index
Kilpatrick, J., 14Kimmel, H., 2Kinds of questions, 138, 160Kinds of task, 133Knowledge
construction, 14pedagogical/pedagogical content, 3subject matter, 3
Knox, D., 126Kolikant Ben-David, Y., 245Kölling, M., 49Korhonen, A., 75Krajcik, J.S., 117Kuhn, T.S., 33
LLaakso, M. J., 75Lab
dry, 127experience, 186
Lab-based teaching, 8, 10, 123, 170, 215, 237, 251
Lab-first activity, 127Lab-first approach, 236, 237Lab-first teaching approach, 8
advantages and disadvantages, 129
Laboratory, 124instruction, 13work, 49
Lakoff, G., 113Langly, D., 245Languages, 238Lapidot, T., 3, 13, 26, 29, 32, 43, 54, 88,
101, 139, 199, 202, 203, 211, 218, 222, 233, 245
Lateral thinking, 65Lave, J., 227Lawhead, P.B., 183Leap of faith, 197, 198, 201–203Learner(s)
alternative conception, 169alternative conceptions, 7, 83cognitive abilities, 47conceptions, 48, 209difficulties, 47, 229, 234difficulties and conceptions, 10misconceptions, 50mistakes, 5, 58project grading, 47understanding, 53ways of thinking, 7
Learning processes, viiLearning rhythm, 133
Learning skills, 48Learning style, 117Learning/teaching recursion, research on,
209–210Learning theories, 13Leron, U., 201, 203Lesson planning, 215Lesson preparation, 47Lev, E., 245Levy, D., 54, 101, 199, 201,
203, 245Lewandowskic, G., 48, 49Lewin, K., 249Linearity, 103Linn, M.C., 74List, 237Literature, 111, 199Little People model, 204–206Logical paradigm, 34Logo, 205Loop, 151, 236
for, 157while, 157
Ludi, S., 14Luther, W., 49Luxton, R.A., 167
MMagnusson, B., 34Maher, C.A., 14, 15Ma, J., 125Maletic, J.I., 73Malmi, L., 75Maloney, J., 49Map, 214Map coloring problem, 163Martin, F., 50, 54, 139Marx, R.W., 117Mathematics, 23, 199Mathematics education research, 65Maximum, 107, 161McCauleya, R., 48, 49McConnell, J.J., 14McCowan, D., 2, 218, 233, 239Meaningful names, 103Means-ends analysis, 65MediaComp, 141Media computation, 141Meerbaum-Salant, O., 117, 183Memory organization, 236Mental image, 109Mental process, 65Mentoring software project development,
7, 95
255Index
Mentor/Mentoring, 182in-school, 218scheduling the, 120university, 218
Merkle, L.D., 183Metaphors, 237
advantages and disadvantages of, 114flag, 103
Meta-reasoning, 148Methods, 103Methods of teaching computer science
(MTCS), 1, 3, 9, 12, 13, 83, 248course, vii, 248design of, 233
Microsoft Research, 46MicroWorlds, 140Middle school, 1Migvan, 42, 108, 212Miller, B., 49Miller, C.S., 14Mindstorms, 140Misconceptions, 50, 83Mistakes, 83Mitchener, G., 73Mittermeir, R.T., 49Model
for high school computer science education, 9, 239, 241
Little People, 204–206top-down frames, 204, 207–209
Model Curriculum for K–12 Computer, 218Modeling, 23Modularity, 42Monroy-Hernández, A., 49Moritz, S.H., 49Morphological analysis, 65Moses, L., 183Motivation, 117MTCS course, 13, 22
integrated view, 8objectives, 4organization, 197–215representation by a concept map, 108structure, 235syllabus, 3, 6, 9, 233, 234
Mulder, M.C., 22Muller, O., 73, 74Murphy, L., 48Murtagh, T., 191Music, 97, 139, 199, 211
in computer science teaching, 237Musical debugging, 139, 211Mutual recursion, 215Myller, N., 136
NNaps, T., 135, 136Narrative-algorithmic tasks, 161National Center for Computer Science
Teachers, 9, 239, 240, 242National Conference for Computer Science
Teachers, 236National Council for the Accreditation of
Teacher Education, 2National High School Computer Science
Curriculum, 240Nation-wide perspective, 245NCATE standards, 9, 233Nersessian, N.J., 125Nesting, 103Newman, I., 14, 17Newspapers, 111Nickerson, J.V., 125Nieminen, J., 191Ni, L., 49Noddings, N., 14, 15Non-programming task, 213Noonan, R., 34Novak, J.D., 107Novice
difficulties, 54knowledge, 48
Nugent, G., 49
OObject, 42Object-first approach, 236Object-oriented paradigm, 34Object-oriented programming,
49, 236, 237Object-oriented software development,
the history of, 27One-dimensional array, study unit about,
188–190Open problem, 148
PPair programming, 176Papert, S., 140Paradigms
functional, 49logical, 49object oriented, 49procedural, 49
Parameters, 42, 103Patterns, 49, 73
algorithmic, 237question, 148
Patterson, A., 49
256 Index
Paz, T., 129, 202Pea, R.D., 54Pedagogical content knowledge (PCK),
3, 51, 234Pedagogical-disciplinary
professional skills, 229Pedagogical methods, 13Pedagogical objectives, 186Pedagogical professional skills, 229Pedagogical skills, 182Pedagogical toolbox, 52Pedagogical tools, 66, 85, 95Peer assessment, 175Peer teaching, 182, 236Perkins, D.N., 50, 54, 139Personal projects, 26Petre, M., 118Petrick, E.R., 48Physics, 125Piaget, J., 15Pimentel, A.D., 136Planning
the entire curriculum, 186–187a lesson, 187–188of one topic from the curriculum, 186of a specific lesson, 186of a study unit, 187, 195–196
Pollack, S., 245Polya, G., 65Pomerantz, J., 167Portfolio, 8, 169, 170, 179, 182, 190
assessment, 180design, 181
Porvin, S.E., 73Poster, preparation, 114Practicum, 3, 9, 12, 182
bridge between theory and its application, 219
bridging the gap between the academia and the school, 222
bridging the gap between theory and practice, 219
bridging the gap between theory and reality, 221
bridging the gap between theory and the field, 221
Practicum in the high school, 218Presentation of the solution, 148Price, B., 134Prime number, 158Privacy and civil liberties, 29Problem analysis, 66, 148Problem decomposition, 66
Problem solving, 48, 66, 227, 229assessment of strategies, 48–49strategies, 7, 65, 123techniques, 67
Problem understanding, 68Problem variables
choosing the, 69defining the, 69
Procedural paradigm, 34Procedures, 42, 103, 222Procedures literacy, 223Professional and
ethical responsibilities, 29Professional community, 243Professional development, 1, 2, 4, 7, 8, 11, 47,
198, 233programs, 1
Professional perception, 13, 15, 16, 18Professional skills, 16Program comprehension, 30Programming, 65
assignments, 147style, 33, 103tasks, 8, 103
Programming heuristics, teaching, 45Programming languages, 6, 33, 117, 157
learning and teaching, 49syntax, 34
Programming paradigms, 7, 21, 33, 118, 214, 236, 237
abstract-oriented examination of, 36imperative, 157learning and teaching, 49
Program visualizations, 134Project
documentation, 176, 177evaluation, 8, 169, 170, 174individual, 175non-software, 175team, 175whole-class, 26
Project-based learning (PBL), 49, 117, 124, 169
Prospective computer science teachers, 13Proteins, 25Proulx, V.K., 73Pupil
mistake, 7performance assessment, 3–4thinking processes, 8
Pupil’s answerevaluation of, 88
Pupil-teacher interaction, 85
257Index
Pure-algorithmic tasks, 161Push down automaton, 164Putnam, R.T., 217Python, 49
QQuestion
classification, 159closed, 162design, 166formulation, 163patterns, 148preparation, 165story, 161unsolvable, 163
Queue, 237Quick-sort, 189Quig, B., 49
RRagonis, N., 2, 16, 23, 34, 49, 195, 226, 227,
229, 234, 245Rajala, T., 75Rauschmayer, A., 72Readability, 104Recursion, 6, 8, 10, 42, 48, 108, 197–215, 238
animation, 215classification, 199–201double, 215in life, 213mutual, 215research on learning/teaching, 197, 198and sound, 197, 198, 211–212tail, 215
Recursive algorithm, 214Recursive patterns, 214–215Recursive phenomena, analysis of, 212–213Recursive process, 201
models of, 197, 198, 204–209Recursive structures, 211Redmond M.A., 183Reduce, 214Reduction, 65Reed, D., 69, 73Reflection, 16, 59, 76, 175, 195–196,
236, 237Reflective activity, 77Reflective diary, 182Reflective discourse, 200Reflective essay, 142Reflective practitioners, 16
perspective, 248Reflective process, 175, 217
Reflective skills, 180Reflective thinking, 4, 229Regular language, 164Reid, J.M., 167Representative inputs and outputs,
representative, 68Research, 123
in computer science education, 7, 9, 47–60, 170, 233, 234, 239, 240, 243–245, 248
on learning/teaching recursion, 197, 209–210
root cause analysis, 65in science education, 236
Researcher’s point of view, 52Resnick, M., 49Resources for computer science education
research, 48, 52Reward allocation, 176Reynolds, R.G., 73Rich tasks, 95, 237Risks and liabilities of computer-based
systems, 29Robins, A., 48, 69Rodger, S.H., 49Roschelle, J., 15, 50Rößing, G., 135Rössling, G.J., 135Rountree, J., 69Rountree, N., 69
SSahraoui, H., 48Sajaniemi, J., 70Salakoski, T., 75Samal, A., 49Samurçay, R., 48, 54Sánchez, J., 49Sanders, I., 204, 210Sarvela, J.N., 72Schoenfeld, A.H., 65Scholtz, T., 204, 210Schön, D.A., 16, 76, 222School culture, 220Science, technology, and society (STS), 29Scientific curricula, 13Scientific experimentation, 124Scratch, 49, 140Self confidence, 117Sethi, R., 34Shaffer, C.A., 135Shepherd, H.G., 117Shepherd, M., 34
258 Index
Shulman, L.S., 3, 51, 60, 84, 209, 233, 234, 248
Shulman’s model of teachers’ knowledge, 9, 233, 234
SIGCSE, 52Silberman, M., 14Simula, 27Skills, pedagogical, 2, 4Small, I., 134Smalltalk, 49Smith, J.P., III, 15, 50Social and Professional Issues, 29Social aspects, 237Social context of computing, 29Soft ideas, 21, 22, 38, 110, 237
introduction to, 41in the MTCS course, 39
Software engineering code of ethics and professional practice, 30
Software project, 174developed by individuals, 175developed by teams, 175management, 30
Software project development, 236, 237mentoring, 7, 117
Software requirements, 30Software visualization and animation, 139Soh, L., 49Soloway, E., 54, 69, 117, 139, 210Solution
construction, 69design, 69examination, 70presentation, 148
Song debugging, 237Sorting, 42Sort-merge algorithm, 156Sort method of an array, 157Sort, selection sort, 189Spandel, V., 183Special Interest Group on Computer Science
Education, 52Spohrer, J.C., 54, 210Spohrer, J.G., 139Squeak, 140Stack, 237Starlogo, 140Stein, D., 227Steinová, M., 49Stephenson, C., 2, 218, 233, 239Stepwise refinement, 42, 73Stolin, Y., 33, 49Story questions, 161The Structure of Scientific Revolution, 33
Students’cognitive abilities, 7difficulties, 7misconceptions, 7
Summative assessment, 175Sussman, G., 23Sussman, J., 23Sutinen, E., 136System-level computer architecture, 136System state, 42
TTaghavi, T., 136Tail-recursion, 215Task
narrative-algorithmic, 161non-programming, 213pure-algorithmic, 161
The task stage, 84Teacher
evaluation, 175license, 241–242as a researcher, 55–56role in computer lab, 126
Teacher experienceimpact stage, 84self stage, 84task stage, 84variables, 84written exam, 88
Teacher Knowledge Base Model, 3Teacher preparation, vii
pre-service, 2programs, 9, 239, 240, 242, 244
Teachers’ awareness of learning processes, 51
Teachingconceptual, 226the first lesson about one-dimensional
array, 190–193license, 239, 240materials, 5process, 179strategies, 234technical, 224
Teaching approach, lab-first, 8Teaching methods, vii, 3, 5, 7, 10, 11, 16, 49,
220, 234, 237, 251active-learning based, 7, 95in computer science education, 10
Teaching planning, 8, 44, 185–196, 236comprehensive, 195–196top-down approach for, 185yearly, 187
259Index
Team project, 175Teamwork, 30, 176Technical teaching, 224Teitel, L., 230Test-driven-development, 176Testing, 47Tests, 7, 8, 17, 47, 169, 170, 186
analysis, 172construction, 8, 171, 197, 237design, 166evaluation, 8, 32failure, 77on recursion, 213solving, 172
Theory, 23Thinking practices, 117Thomas, J.W., 117Thomas, S.R., 73Thompson, E., 167Thompson, M., 136Tiling problem, 163Time allocation, 194Time line, 187Time planning, 187TOCE, 52, 135Toleman, M., 48Tomayko, J., 30, 31Tools, pedagogical, 4, 7Top-down frames model, 204, 207–209Top-down methodology, 72Towards 2020 Science, 25Tracing, 42Transportation, 111Trees, 42, 197
binary, 237Trial-and-error, 65Trigger, 16, 18Tucker, A., 2, 22, 34, 218, 233, 239Turing Award, 28Turing Machine, 27, 28Turing machine, 164, 238Turing test, 28Turkle, S., 34Turner, A.J., 22Tutoring, 217, 226
framework, 9problem-solving process, 227session feedback worksheet, 228
Tutoring coordinator, 227Tutoring model, implementation, 227Types of questions, 8, 133, 147, 149, 169, 170,
215, 236, 237, 251analysis of code execution, 151combining several, 158
completion a given solution, 153development a solution that uses a given
module, 150development of a solution, 150efficiency estimation, 155examination of the correctness of a given
solution, 152finding the purpose of a given
solution, 152instruction manipulations, 154programming style questions, 156question design, 156tracing a given solution, 151transformation of a solution, 157
Types of tasks, 135
UUnicode, 161United States, 2University level, 1University mentor, 218Unsolvable questions, 163Uronen, P.A., 49Urquiza-Fuentes, J., 134Using History To Teach Computer Science
and Related Disciplines, 27
VVan Roy, P., 34, 49Variables, 10, 38, 42, 48, 84, 114, 237
roles of, 70Variety of question types,
advantages of using, 147Vasconcelos, J., 67Velázquez-Iturbide, J.A., 134Ventura, P., 191Verno, A., 2, 218, 233, 239Vickers, P., 211Vilner, T., 49, 244Visualization, 8, 17, 123, 201,
211, 237and animation, 138tools, 123
Voyles, M.M., 49
WWaks, S., 117Wallingford, E., 73Wang, L., 167Ware, F.N., 218, 230Watson, R., 48Watt, D.A., 34Web applications, 143Wenger, E., 227
260 Index
Whalley, J., 167While loop, 157Whittington, K.J., 14Wilkins, D.E., 183Williams, L., 115Wilson, S.M., 217Wing, J., 22Winstead, J., 49Wirth, N., 72Wolz, U., 126Working in groups, 116Wright, M., 198, 201Written exam, 88
Wu, C., 204, 210Wu, J., 167
YYang, A., 167Yehezkel, C., 136Yehudai, A., 240Young, P.R., 22
ZZeldes, A., 245Zimmerman, B.A., 34Zur, E., 49, 245