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Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
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Summary
Summary
Many students find it difficult to learn the kind of knowledge and thinking required by college or high school courses in mathematics, science, or other complex domains. Thus they often emerge with significant misconceptions, fragmented knowledge, and inadequate problem-solving skills. Most instructors or textbook authors approach their teaching efforts with a good knowledge of their field of expertise but little awareness of the underlying thought processes and kinds of knowledge required for learning in scientific domains. In this book, Frederick Reif presents an accessible coherent introduction to some of the cognitive issues important for thinking and learning in scientific or other complex domains (such as mathematics, science, physics, chemistry, biology, engineering, or expository writing).
Reif, whose experience teaching physics at the University of California led him to explore the relevance of cognitive science to education, examines with some care the kinds of knowledge and thought processes needed for good performance; discusses the difficulties faced by students trying to deal with unfamiliar scientific domains; describes some explicit teaching methods that can help students learn the requisite knowledge and thinking skills; and indicates how such methods can be implemented by instructors or textbook authors. Writing from a practically applied rather than predominantly theoretical perspective, Reif shows how findings from recent research in cognitive science can be applied to education. He discusses cognitive issues related to the kind of knowledge and thinking skills that are needed for science or mathematics courses in high school or colleges and that are essential prerequisites for more advanced intellectual performance. In particular, he argues that a better understanding of the underlying cognitive mechanisms should help to achieve a more scientific approach to science education.
Author Notes
Frederick Reif is Emeritus Professor of Physics and Education at Carnegie Mellon University and the University of California, Berkeley.
Reviews 1
Choice Review
This timely volume nicely blends practical and theoretical perspectives to reveal how advances in cognitive science can be applied to education. Reif (emer., physics and education, Carnegie Mellon Univ. and Univ. of California, Berkley) is specifically concerned with the challenges of learning in complex domains, such as science and mathematics. He describes learning and teaching designed to promote the acquisition of skills and knowledge for conceptual learning in these fields. Section 2 offers a readable and valuable introduction to various forms of knowledge and thinking, including the widely acclaimed notion of problem solving. Science educators will likely find section 3 of the book familiar and welcoming, as it addresses misconceptions and the fundamentally important notion of uncovering students' prior knowledge as an integral element of the learning cycle. Although the summative chapters succinctly describe unmet educational challenges, the book would have been strengthened with more examples from high school and college contexts. Those interested in the reform of science education and curriculum development in mathematics and science, including researchers and practitioners, would find this book an excellent catalyst for initiating discussions regarding how to promote high quality and effective programs. Summing Up: Recommended. Upper-division undergraduates and above. D. M. Moss University of Connecticut
Table of Contents
Preface | p. xiii |
I Basic Issues | p. 1 |
1 Performance, Learning, and Teaching | p. 3 |
1.1 Thinking about thinking | p. 3 |
1.2 Basic issues | p. 4 |
1.3 Importance of these issues | p. 5 |
1.4 Structure of the book | p. 8 |
2 Intellectual Performance | p. 11 |
2.1 Description of performance | p. 11 |
2.2 Performance in complex domains | p. 13 |
2.3 Characteristics of good performance | p. 15 |
2.4 Analysis of performance | p. 18 |
2.5 Analysis of good performance | p. 21 |
2.6 Comparisons and overview | p. 23 |
2.7 Summary | p. 26 |
II Good Performance | p. 27 |
II-A Usability | p. 29 |
3 Important Kinds of Knowledge | p. 31 |
3.1 Declarative and procedural knowledge | p. 32 |
3.2 Comparative advantages and disadvantages | p. 33 |
3.3 Uses of declarative and procedural knowledge | p. 34 |
3.4 Condition-dependent knowledge | p. 37 |
3.5 Educational implications | p. 38 |
3.6 Summary | p. 41 |
4 Specifying and Interpreting Concepts | p. 43 |
4.1 Knowledge and concepts | p. 44 |
4.2 Types of concepts | p. 47 |
4.3 Kinds of concept specifications | p. 51 |
4.4 Scientific importance of concept specifications | p. 54 |
4.5 Educational implications | p. 57 |
4.6 Summary | p. 59 |
5 Interpreting Scientific Concepts | p. 61 |
5.1 Students' interpretation of the concept acceleration | p. 62 |
5.2 Motion and the concept of acceleration | p. 66 |
5.3 Specification of acceleration | p. 69 |
5.4 Causes of interpretation deficiencies | p. 71 |
5.5 Requirements for usable concept knowledge | p. 77 |
5.6 Educational implications | p. 80 |
5.7 Summary | p. 83 |
6 Managing Memory | p. 85 |
6.1 Properties of human memory | p. 86 |
6.2 Basic memory processes | p. 88 |
6.3 Practical memory management | p. 94 |
6.4 Educational implications | p. 98 |
6.5 Summary | p. 100 |
II-B Effectiveness | p. 101 |
7 Methods and Inferences | p. 103 |
7.1 Methods and procedures | p. 104 |
7.2 Specification of procedures | p. 106 |
7.3 Making inferences | p. 109 |
7.4 Educational implications | p. 113 |
7.5 Summary | p. 116 |
8 Describing Knowledge | p. 119 |
8.1 Descriptions and their referents | p. 120 |
8.2 Alternative descriptions | p. 122 |
8.3 Characteristics of different descriptions | p. 126 |
8.4 Complementary use of different descriptions | p. 129 |
8.5 Educational implications | p. 132 |
8.6 Summary | p. 136 |
9 Organizing Knowledge | p. 137 |
9.1 Importance of knowledge organization | p. 138 |
9.2 Some forms of knowledge organization | p. 139 |
9.3 Dealing with large amounts of knowledge | p. 142 |
9.4 Knowledge elaboration | p. 143 |
9.5 Hierarchical knowledge organization | p. 145 |
9.6 Examples of hierarchical knowledge organizations | p. 149 |
9.7 Educational implications | p. 155 |
9.8 Summary | p. 161 |
II-C Flexibility | p. 163 |
10 Making Decisions | p. 165 |
10.1 Importance of decision making | p. 166 |
10.2 Kinds of decisions | p. 168 |
10.3 Making complex decisions | p. 170 |
10.4 More refined option assessments | p. 173 |
10.5 Limitations of analytic decisions | p. 177 |
10.6 Practical decision making | p. 180 |
10.7 Decisions in scientific domains | p. 183 |
10.8 Educational implications | p. 185 |
10.9 Summary | p. 187 |
11 Introduction to Problem Solving | p. 189 |
11.1 Problem Characteristics | p. 190 |
11.2 Challenges of improving problem solving | p. 196 |
11.3 Educational implications | p. 199 |
11.4 Summary | p. 200 |
12 Systematic Problem Solving | p. 201 |
12.1 A useful problem-solving strategy | p. 201 |
12.2 Describing a problem | p. 204 |
12.3 Analyzing a problem | p. 207 |
12.4 Constructing a solution | p. 210 |
12.5 Examples of solution constructions | p. 214 |
12.6 Assessing a solution | p. 221 |
12.7 Exploiting a solution | p. 223 |
12.8 Educational implications | p. 224 |
12.9 Summary | p. 227 |
13 Dealing with Complex Problems | p. 229 |
13.1 Managing complexity by task decomposition | p. 229 |
13.2 Planning | p. 231 |
13.3 Supportive knowledge | p. 235 |
13.4 Helpful form of solution | p. 237 |
13.5 Quantitative and qualitative problems | p. 238 |
13.6 Writing as problem solving | p. 243 |
13.7 Applying the problem-solving strategy to writing | p. 244 |
13.8 Educational implications | p. 249 |
13.9 Summary | p. 252 |
II-D Efficiency | p. 255 |
14 Efficiency and Compiled Knowledge | p. 257 |
14.1 Importance of efficiency | p. 258 |
14.2 Compiling knowledge | p. 260 |
14.3 Routine performance | p. 261 |
14.4 Automatic performance | p. 263 |
14.5 Benefits and dangers of efficient performance | p. 266 |
14.6 Educational implications | p. 267 |
14.7 Summary | p. 269 |
II-E Reliability | p. 271 |
15 Quality Assurance | p. 273 |
15.1 Ensuring good quality | p. 274 |
15.2 Preventing defects | p. 276 |
15.3 Assessing performance | p. 278 |
15.4 Improving performance | p. 280 |
15.5 Metacognition | p. 281 |
15.6 Educational implications | p. 282 |
15.7 Summary | p. 284 |
15.8 Good performance and the instructional challenge | p. 285 |
III Prior Knowledge | p. 287 |
16 Unfamiliar Knowledge Domains | p. 289 |
16.1 Prior knowledge and new learning | p. 290 |
16.2 Everyday and scientific domains | p. 293 |
16.3 Contrasting scientific and everyday cognitions | p. 297 |
16.4 Scientists' and students' conceptions of science | p. 302 |
16.5 Educational implications | p. 306 |
16.6 Summary | p. 308 |
17 Naive Scientific Knowledge | p. 311 |
17.1 Characteristics of naive scientific knowledge | p. 312 |
17.2 Students' prior knowledge about science | p. 314 |
17.3 Naive conceptions about motion | p. 316 |
17.4 Naive notions about the causes of motion | p. 319 |
17.5 Force as a cause of motion | p. 322 |
17.6 Educational implications | p. 327 |
17.7 Summary | p. 332 |
IV Learning and Teaching | p. 333 |
18 Developing Instruction | p. 335 |
18.1 Instructional development as a problem-solving task | p. 335 |
18.2 Stages of instructional development | p. 337 |
18.3 Overview of instructional development | p. 339 |
18.4 Summary | p. 342 |
19 Designing the Learning Process: Goals | p. 343 |
19.1 Describing the learning problem | p. 343 |
19.2 Analyzing the learning problem | p. 347 |
19.3 Comparative analysis | p. 354 |
19.4 Summary | p. 355 |
20 Designing the Learning Process: Means | p. 357 |
20.1 Decomposing and sequencing the learning process | p. 357 |
20.2 Encoding new knowledge | p. 360 |
20.3 Managing cognitive load | p. 361 |
20.4 Exploiting useful organization | p. 365 |
20.5 Ensuring the utility of acquired knowledge | p. 372 |
20.6 Ensuring the reliability of acquired knowledge | p. 373 |
20.7 Assessing a learning design | p. 374 |
20.8 Achieving genuinely good performance | p. 375 |
20.9 Summary | p. 375 |
21 Producing Instruction to Foster Learning | p. 377 |
21.1 Describing the instructional problem | p. 377 |
21.2 Analyzing instructional needs | p. 380 |
21.3 Helpful instructional interactions | p. 381 |
21.4 Managing instruction | p. 384 |
21.5 Learning by teaching | p. 388 |
21.6 Assessing instruction | p. 394 |
21.7 Summary | p. 399 |
V Implementing Practical Instruction | p. 401 |
22 Traditional Instructional Methods | p. 403 |
22.1 The instructional delivery problem | p. 403 |
22.2 Lectures | p. 406 |
22.3 Textbooks | p. 408 |
22.4 Homework assignments | p. 409 |
22.5 Small instructional groups | p. 411 |
22.6 Assessment of instructional delivery | p. 412 |
22.7 Summary | p. 415 |
23 Innovative Instructional Methods | p. 417 |
23.1 Modified lecture forms | p. 417 |
23.2 Cooperative learning | p. 420 |
23.3 Packaged instruction | p. 423 |
23.4 Technology-supported instruction | p. 428 |
23.5 Potential benefits of educational technology | p. 432 |
23.6 Summary | p. 437 |
24 Some Educational Challenges | p. 439 |
24.1 Providing more individual learning assistance | p. 439 |
24.2 Teaching general thinking and learning skills | p. 440 |
24.3 More scientific approaches to education | p. 443 |
24.4 More significant educational role of universities | p. 445 |
24.5 Summary | p. 448 |
References | p. 451 |
Index | p. 465 |