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Research Methods in

Education

This rewritten and updated sixth edition of the long-running bestsellerResearch Methods in Education

covers the whole range of methods currently employed by educational research at all stages. It has five main parts: the context of educational research, planning educational research, styles of educational research, strategies for data collection and researching and data analysis. The book contains references to a comprehensive dedicated web site of accompanying materials. It continues to be the standard text for students and lecturers undertaking, understanding and using educational research.

This sixth edition comprises new material including:

O complexity theory, ethics, sampling, sensitive educational research, researching powerful people, Internet-based research, interviewing and surveys

O expanded coverage of, and practical guidance in, experimental research, questionnaire design and administration

O an entirely new part, containing five new chapters covering qualitative and quantitative data analysis including content analysis, grounded theory, statistics and how to use them, effect size, and reporting data, all with practical examples

O detailed cross-referencing to a major educational resource web site designed specifically to run alongside this book.

Research Methods in Education, sixth edition, is essential reading for both the professional researcher and anyone involved in educational research.

Louis Cohenis Emeritus Professor of Education at Loughborough University, UK.

Lawrence Manionwas former Principal Lecturer in Music at Didsbury School of Education, Manchester Metropolitan University, UK.

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Research Methods in

Education

Sixth edition

Louis Cohen, Lawrence Manion

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2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN Simultaneously published in the USA and Canada by Routledge

270 Madison Avenue, New York, NY 10016

Routledge is an imprint of the Taylor & Francis Group, an informa business 2007 Louis Cohen, Lawrence Manion and Keith Morrison

All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers.

British Library Cataloguing in Publication Data

A catalogue record for this book is available from the British Library

Library of Congress Cataloging-in-Publication Data

A catalog record for this book has been requested

ISBN 10: 0–415–37410–3 (hbk) ISBN 10: 0–415–36878–2 (pbk) ISBN 10: 0–203–02905–4 (ebk) ISBN 13: 978–0–415–37410–1 (hbk) ISBN 13: 978–0–415–36878–0 (pbk) ISBN 13: 978–0–203–02905–3 (ebk)

This edition published in the Taylor & Francis e-Library, 2007.

“To purchase your own copy of this or any of Taylor & Francis or Routledge’s

collection of thousands of eBooks please go to www.eBookstore.tandf.co.uk.”

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Contents

List of boxes xiii

Acknowledgements xvii

Introduction 1

Part 1

The context of educational research

1 The nature of inquiry – Setting the field

Introduction 5

The search for truth 5

Two conceptions of social reality 7

Positivism 9

The assumptions and nature of

science 11

The tools of science 14

The scientific method 15

Criticisms of positivism and the scientific

method 17

Alternatives to positivistic social science:

naturalistic approaches 19

A question of terminology: the normative and interpretive paradigms 21 Phenomenology, ethnomethodology and

symbolic interactionism 22

Criticisms of the naturalistic and interpretive

approaches 25

Critical theory and critical educational

research 26

Criticisms of approaches from critical

theory 29

Critical theory and curriculum

research 30

A summary of the three paradigms 32 The emerging paradigm of complexity

theory 33

Feminist research 34

Research and evaluation 41

Research, politics and policy-making 46

Methods and methodology 47

Part 2

Planning educational research

2 The ethics of educational and social research

Introduction 51

Informed consent 52

Access and acceptance 55

The field of ethics 58

Sources of tension 58

Voices of experience 61

Ethical dilemmas 62

Ethics and research methods in

education 69

Ethics and evaluative research 70 Research and regulation: ethical codes and

review 71

Sponsored research 74

Responsibilities to the research

community 75

Conclusion 75

3 Planning educational research

Introduction 78

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Managing the planning of research 93

A worked example 95

Conclusion 98

4 Sampling

Introduction 100

The sample size 101

Sampling error 106

The representativeness of the sample 108 The access to the sample 109 The sampling strategy to be used 110

Probability samples 110

Non-probability samples 113

Planning a sampling strategy 117

Conclusion 117

5 Sensitive educational research

What is sensitive research? 119

Sampling and access 121

Ethical issues in sensitive research 124 Researching powerful people 127

Asking questions 130

Conclusion 131

6 Validity and reliability

Defining validity 133

Triangulation 141

Ensuring validity 144

Reliability in quantitative research 146 Reliability in qualitative research 148 Validity and reliability in interviews 150 Validity and reliability in

experiments 155

Validity and reliability in

questionnaires 157

Validity and reliability in

observations 158

Validity and reliability in tests 159 Validity and reliability in life

histories 164

Part 3

Styles of educational research

7 Naturalistic and ethnographic research

Elements of naturalistic inquiry 167 Planning naturalistic research 171

Critical ethnography 186

Some problems with ethnographic and

naturalistic approaches 188

8 Historical and documentary research

Introduction 191

Choice of subject 192

Data collection 193

Evaluation 194

Writing the research report 195 The use of quantitative methods 197

Life histories 198

Documentary research 201

9 Surveys, longitudinal, cross-sectional and trend studies

Introduction 205

Some preliminary considerations 207

Planning a survey 208

Survey sampling 211

Longitudinal, cross-sectional and trend

studies 211

Strengths and weaknesses of longitudinal, cohort and cross-sectional studies 214 Postal, interview and telephone

surveys 218

Event history analysis 224

10 Internet-based research and computer usage

Introduction 226

Internet-based surveys 226

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CONTENTS ix

Searching for research materials on the

Internet 242

Evaluating web sites 244

Computer simulations 245

Geographical Information Systems 251

11 Case studies

What is a case study? 253

Examples of kinds of case study 258 Why participant observation? 260

Recording observations 260

Planning a case study 261

Writing up a case study 262

Conclusion 263

12 Ex post factoresearch

Introduction 264

Co-relational and criterion groups

designs 265

Characteristics ofex post facto

research 266

Occasions when appropriate 268 Advantages and disadvantages of

ex post factoresearch 268

Designing anex post facto

investigation 269

Procedures inex post factoresearch 270

13 Experiments, quasi-experiments, single-case research and meta-analysis

Introduction 272

Designs in educational

experimentation 274

True experimental designs 275 A quasi-experimental design: the

non-equivalent control group design 282 Single-case research: ABAB design 284 Procedures in conducting experimental

research 285

Examples from educational research 287 Evidence-based educational research and

meta-analysis 289

14 Action research

Introduction 297

Defining action research 297 Principles and characteristics of action

research 299

Action research as critical praxis 302 Procedures for action research 304 Reflexivity in action research 310 Some practical and theoretical

matters 311

Conclusion 312

Part 4

Strategies for data collection and researching

15 Questionnaires

Introduction 317

Ethical issues 317

Approaching the planning of a

questionnaire 318

Types of questionnaire items 321 Asking sensitive questions 333 Avoiding pitfalls in question writing 334 Sequencing the questions 336 Questionnaires containing few verbal

items 337

The layout of the questionnaire 338 Covering letters or sheets and follow-up

letters 339

Piloting the questionnaire 341 Practical considerations in questionnaire

design 342

Administering questionnaires 344 Processing questionnaire data 346

16 Interviews

Introduction 349

Conceptions of the interview 349 Purposes of the interview 351

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Planning interview-based research

procedures 356

Group interviewing 373

Interviewing children 374

Focus groups 376

The non-directive interview and the

focused interview 377

Telephone interviewing 379

Ethical issues in interviewing 382

17 Accounts

Introduction 384

The ethogenic approach 384

Characteristics of accounts and

episodes 384

Procedures in eliciting, analysing and authenticating accounts: an example 385 Network analyses of qualitative data 388 What makes a good network? 388

Discourse analysis 389

Analysing social episodes 391 Account gathering in educational

research: an example 391

Problems in gathering and analysing

accounts 392

Strengths of the ethogenic approach 393

A note on stories 394

18 Observation

Introduction 396

Structured observation 398

Critical incidents 404

Naturalistic and participant

observation 404

Natural and artificial settings for

observation 408

Ethical considerations 408

Some cautionary comments 410

Conclusion 412

19 Tests

Introduction 414

What are we testing? 414

Parametric and non-parametric tests 414 Norm-referenced, criterion-referenced and domain-referenced tests 415 Commercially produced tests and

researcher-produced tests 416

Constructing a test 418

Devising a pretest and post-test 432 Reliability and validity of tests 432 Ethical issues in preparing for tests 432 Computerized adaptive testing 433

20 Personal constructs

Introduction 435

Characteristics of the method 435 ‘Elicited’ versus ‘provided’ constructs 436 Allotting elements to constructs 437 Laddering and pyramid constructions 439 Grid administration and analysis 439 Procedures in grid administration 439 Procedures in grid analysis 439 Strengths of repertory grid technique 442 Difficulties in the use of repertory grid

technique 442

Some examples of the use of repertory grid in educational research 443 Grid technique and audio/video lesson

recording 445

Focused grids, non-verbal grids, exchange

grids and sociogrids 446

21 Role-playing

Introduction 448

Role-playing versus deception: the

argument 450

Role-playing versus deception: the

evidence 451

Role-playing in educational settings 452 The uses of role-playing 452 Strengths and weaknesses of role-playing and other simulation exercises 455 Role-playing in an educational setting:

an example 455

Evaluating role-playing and other

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CONTENTS xi

Part 5

Data analysis

22 Approaches to qualitative data analysis

Introduction 461

Tabulating data 463

Five ways of organizing and presenting

data analysis 467

Systematic approaches to data

analysis 469

Methodological tools for analysing

qualitative data 473

23 Content analysis and grounded theory

Introduction 475

What is content analysis? 475 How does content analysis work? 476 A worked example of content

analysis 483

Computer usage in content analysis 487 Reliability in content analysis 490

Grounded theory 491

Interpretation in qualitative data

analysis: multilayered texts 495

24 Quantitative data analysis

Introduction 501

Scales of data 502

Parametric and non-parametric data 503 Descriptive and inferential statistics 503 One-tailed and two-tailed tests 504 Dependent and independent

variables 504

Reliability 506

Exploratory data analysis: frequencies, percentages and cross-tabulations 506 Statistical significance 515

Hypothesis testing 519

Effect size 520

The chi-square test 525

Degrees of freedom 527

Measuring association 528

Regression analysis 536

Measures of difference between groups

and means 542

25 Multidimensional measurement and factor analysis

Introduction 559

Elementary linkage analysis: an

example 559

Factor analysis 560

Factor analysis: an example 570 Examples of studies using

multidimensional scaling and cluster

analysis 576

Multidimensional data: some words on

notation 579

Multilevel modelling 583

Cluster analysis 584

26 Choosing a statistical test

How many samples? 586

Assumptions of tests 591

Notes 593

Bibliography 599

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Boxes

1.1 The subjective–objective

dimension 9

1.2 Alternative bases for interpreting social

reality 10

1.3 The functions of science 12

1.4 The hypothesis 15

1.5 Stages in the development of

science 16

1.6 An eight-stage model of the scientific

method 16

1.7 A classroom episode 20

1.8 Differing approaches to the study of

behaviour 33

2.1 The costs/benefits ratio 52 2.2 Guidelines for reasonably informed

consent 53

2.3 Close encounters of a researcher

kind 56

2.4 Conditions and guarantees proffered for a school-based research project 57 2.5 Negotiating access checklist 59 2.6 Absolute ethical principles in social

research 61

2.7 An extreme case of deception 67 2.8 Ethical principles for the guidance of

action researchers 70

2.9 An ethical code: an illustration 76 2.10 Ethical principles for educational

research (to be agreedbeforethe research

commences) 77

3.1 The elements of research design 79 3.2 Elements of research styles 84 3.3 A matrix for planning research 88 3.4 A planning sequence for research 94 3.5 A planning matrix for research 95 3.6 Understanding the levels of

organizational culture 96

4.1 Sample size, confidence levels and confidence intervals for random

samples 104

4.2 Distribution of sample means showing the spread of a selection of sample means around the population mean 107 5.1 Issues of sampling and access in

sensitive research 124

5.2 Ethical issues in sensitive research 127 5.3 Researching powerful people 130 5.4 Key questions in considering sensitive

educational research 132

6.1 Principal sources of bias in life history

research 164

8.1 Some historical interrelations between men, movements and institutions 192 8.2 A typology of life histories and their

modes of presentation 199

9.1 Stages in the planning of a survey 210 9.2 Types of developmental research 214 9.3 Advantages of cohort over

cross-sectional designs 217

9.4 The characteristics, strengths and weaknesses of longitudinal, cross-sectional, trend analysis, and retrospective longitudinal studies 219 10.1 Problems and solutions in

Internet-based surveys 231 10.2 Geographical Information Systems in

secondary schools 251

10.3 Location of home postcodes using Geographical Information

Systems 252

11.1 Possible advantages of case study 256 11.2 Strengths and weaknesses of case

study 256

11.3 A typology of observation studies 259 11.4 The case study and problems of

selection 261

11.5 Continua of data collection, types and analysis in case study

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13.1 Independent and dependent

variables 273

13.2 The effects of randomization 276 13.3 Interaction effects in an

experiment 281

13.4 The ABAB design 285

13.5 An ABAB design in an educational

setting 286

13.6 Class size and learning in well-controlled and poorly well-controlled

studies 296

14.1 A model of emancipatory action

research for organizational change 306 15.1 A flow chart technique for question

planning 319

15.2 A guide for questionnaire

construction 320

15.3 A 10-point marking scale in a

questionnaire 330

15.4 Potential problems in conducting

research 332

15.5 A flow chart for the planning of a

postal survey 347

16.1 Attributes of ethnographers as

interviewers 350

16.2 Summary of relative merits of

interview versus questionnaire 352 16.3 Strengths and weaknesses of different

types of interview 353

16.4 The selection of response mode 360 16.5 Guidelines for the conduct of

interviews 366

16.6 Delineating units of general

meaning 371

16.7 Units of relevant meaning 371 16.8 Clusters of relevant meaning 372 17.1 Principles in the ethogenic

approach 385

17.2 Account gathering 386

17.3 Experience sampling method 387 17.4 Concepts in children’s talk 390 17.5 ‘Ain’t nobody can talk about things

being about theirselves’ 392

17.6 Parents and teachers: divergent viewpoints on children’s

communicative competence 393 17.7 Justification of objective systematic

observation in classroom settings 394 18.1 A structured observation schedule 399 18.2 Non-participant observation:

a checklist of design tasks 401 18.3 Structured, unstructured, natural and

artificial settings for observation 409 19.1 A matrix of test items 419 19.2 Compiling elements of test items 420 20.1 Eliciting constructs and constructing

a repertory grid 436

20.2 Allotting elements to constructs:

three methods 438

20.3 Laddering 440

20.4 Elements 440

20.5 Difference score for constructs 441

20.6 Grid matrix 441

21.1 Dimensions of role-play methods 449 21.2 The Stanford Prison experiment 450 21.3 Critical factors in a role-play: smoking

and young people 454

21.4 Categorization of responses to four

video extracts 456

22.1 The effectiveness of English

teaching 464

22.2 The strengths and weaknesses of

English language teaching 464

22.3 Teaching methods 465

22.4 Student-related factors 466 24.1 Frequencies and percentages for a

course evaluation 507

24.2 Cross-tabulation by totals 508 24.3 Cross-tabulation by row totals 509 24.4 Rating scale of agreement and

disagreement 510

24.5 Satisfaction with a course 510 24.6 Combined categories of rating

scales 510

24.7 Representing combined categories of

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BOXES xv

24.8 How well learners are cared for,

guided and supported 511

24.9 Staff voluntarily taking on

coordination roles 511

24.10 Distribution of test scores 512 24.11 A line graph of test scores 512 24.12 Distribution around a mean with an

outlier 513

24.13 A platykurtic distribution of

scores 513

24.14 A leptokurtic distribution of

scores 514

24.15 Type I and Type II errors 520 24.16 Mean and standard deviation in an

effect size 522

24.17 The Levene test for equality of

variances 523

24.18 Mean and standard deviation in a

paired sample test 523

24.19 Difference test for a paired sample 524 24.20 Effect size in analysis of variance 524 24.21 A 2×3 contingency table for

chi-square 526

24.22 A 2×5 contingency table for

chi-square 527

24.23 Common measures of relationship 529 24.24 Percentage of public library members

by their social class origin 529 24.25 Correlation scatterplots 532 24.26 A Pearson product-moment

correlation 533

24.27 A line diagram to indicate

curvilinearity 533

24.28 Visualization of correlation of 0.65 between reading grade and arithmetic

grade 535

24.29 A scatterplot with the regression

line 537

24.30 A scatterplot with grid lines and

regression line 538

24.31 A summary of the R, R square and adjusted R square in regression

analysis 538

24.32 Significance level in regression

analysis 539

24.33 The beta coefficient in a regression

analysis 539

24.34 A summary of the R, R square and adjusted R square in multiple

regression analysis 540

24.35 Significance level in multiple

regression analysis 541

24.36 The beta coefficients in a multiple

regression analysis 541

24.37 Means and standard deviations for a

t-test 544

24.38 The Levene test for equality of

variances in a t-test 544

24.39 A t-test for leaders and teachers 545 24.40 The Levene test for equality of

variances between leaders and

teachers 545

24.41 Means and standard deviations in a

paired samples t-test 546

24.42 The paired samples t-test 547 24.43 Descriptive statistics for analysis of

variance 548

24.44 SPSS output for one-way analysis of

variance 548

24.45 The Tukey test 549

24.46 Homogeneous groupings in the Tukey

test 549

24.47 Means and standard deviations in a two-way analysis of variance 551 24.48 The Levene test of equality of

variances in a two-way analysis of

variance 551

24.49 Between-subject effects in two-way

analysis of variance 552

24.50 Graphic plots of two sets of scores on

a dependent variable 552

24.51 A cross-tabulation for a

Mann-Whitney U test 553

24.52 SPSS output on rankings for the

Mann-Whitney U test 553

24.53 The Mann-Whitney U value and

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24.54 Frequencies and percentages of

variable one in a Wilcoxon test 554 24.55 Frequencies and percentages of

variable two in a Wilcoxon test 554 24.56 Ranks and sums of ranks in a

Wilcoxon test 555

24.57 Significance level in a Wilcoxon

test 555

24.58 Cross-tabulation for the

Kruskal-Wallis test 556

24.59 Rankings for the Kruskal-Wallis

test 556

24.60 Significance levels in a Kruskal-Wallis

test 556

24.61 Frequencies for variable one in the

Friedman test 557

24.62 Frequencies for variable two in the

Friedman test 557

24.63 Frequencies for variable three in the

Friedman test 558

24.64 Rankings for the Friedman test 558 24.65 Significance level in the Friedman

test 558

25.1 Rank ordering of ten children on

seven constructs 561

25.2 Intercorrelations between seven

personal constructs 562

25.3 The structuring of relationships among the seven personal

constructs 563

25.4 Initial SPSS output for principal

components analysis 564

25.5 A scree plot 565

25.6 Three-dimensional rotation 566 25.7 The rotated components matrix in

principal components analysis 567 25.8 Factor analysis of responsibility for

stress items 571

25.9 Factor analysis of the occupational

stress items 573

25.10 Factor analysis of the occupational

satisfaction items 574

25.11 Correlations between (dependent) stress and (independent) satisfaction factors and canonical variates 575 25.12 Biographical data and stress

factors 576

25.13 Students’ perceptions of social

episodes 577

25.14 Perception of social episodes 579 25.15 Person concept coding system 580 25.16 Reliability coefficients for peer

descriptions 581

25.17 Sex, voting preference and social class: a three-way classification

table 581

25.18 Sex, voting preference and social class: a three-way notational

classification 581

25.19 Expected frequencies in sex, voting preference and social class 581 25.20 Expected frequencies assuming that

sex is independent of social class and

voting preference 582

25.21 Sex and voting preference: a two-way

classification table 583

25.22 Cluster analysis 585

26.1 Identifying statistical tests for an

experiment 587

26.2 Statistical tests to be used with different numbers of groups of

samples 587

26.3 Types of statistical tests for four scales

of data 588

26.4 Choosing statistical tests for parametric and non-parametric

data 589

26.5 Statistics available for different types

of data 590

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Acknowledgements

Our thanks are due to the following publishers and authors for permission to include materials in the text:

Allyn & Bacon/Pearson Education, for material from Best, J. W. (1970)Research in Education.

Blackwell Publishers, for material from Dyer, C. (1995) Beginning Research in Psychology; Robson, C. (1993) Real World Research; Robson, C. (2002)Real World Research(second edition).

British Psychological Society, for material from Adams-Webber, J. R. (1970) Elicited versus provided constructs in repertory grid technique: a review, British Journal of Medical Psychology, 43, 349–54. Reproduced with permission from theBritish Journal of Medical PsychologyThe British Psychological Society.

Campbell, D. T. and Stanley, J. C. Experimental and Quasi-Experimental Designs for Research. Copyright  1963 by Houghton Mifflin Company.

Continuum Books, for material from Walford, G. (2001) Doing Qualitative Educational Research, pp. 30, 31, 36, 137.

Deakin University Press, Deakin, Australia, for words from Kemmis, S. and McTaggart, R. (1981)

The Action Research Planner, and Kemmis, S. and McTaggart, R. (1992)The Action Research Planner(third edition) 8 and 21–8.

Elsevier, for material reprinted from International Journal of Educational Research, vol. 18(3), Edwards, D. Concepts, memory and the or-ganisation of pedagogic discourse, pp. 205–25, copyright1993, with permission from Else-vier;Social Method and Social Life, M. Brenner (ed.), article by J. Brown and J. Sime: A methodology for accounts, p. 163, copyright 1981, with permission from Elsevier. Hughes, J. (1976), for material from Sociological

Analysis: Methods of Discovery, Nelson Thornes, p. 34.

Lawrence Erlbaum Associates, for material from Murphy, J., John, M. and Brown, H. (eds) (1984) Dialogues and Debates in Social Psychology. London: Lawrence Erlbaum Associates.

McAleese, R. and Hamilton, D. (eds) (1978)

Understanding Classroom Life. Slough: National Foundation for Educational Research.

Multilingual Matters Ltd, Clevedon, for figures from Parsons, E., Chalkley, B. and Jones, A. (1996) The role of Geographic Information Systems in the study of parental choice and secondary school catchments, Evaluation and Research in Education, 10(1), 23–34; for words from Stronach, I. and Morris, B (1994) Polemical notes on educational evaluation in an age of ‘policy hysteria’, Evaluation and Research in Education, 8(1), 5–19.

Patton, M. Q. (1980)Qualitative Evaluation Meth-ods, p. 206, copyrightSage Publications Inc., reprinted by permission of Sage Publications Inc.

Pearson Education Ltd, for material from Harris, N., Pearce, P. and Johnstone, S. (1992)The Legal Context of Teaching.

Penguin Group UK, for material from Armis-tead, N. (1974)Reconstructing Social Psychology.

Prentice-Hall, for material from Garfinkel, H. (1974) Studies in Ethnomethodology; Smith, R. W. (1978)Strategies in Social Research.

Princeton University Press, for material from Kierkegaard, S. (1974) Concluding Unscientific Postscript.

Reips, U.-D. (2002a) Internet-based psychological experimenting: five dos and don’ts. Social Sci-ence Computer Review, 20(3), 241–9; (2002b) Standards for Internet-based experimenting.

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Springer, for Hycner, R. H. (1985) Some guidelines for the phenomenological analysis of interview data, Human Studies, 8, 279–303, with kind permission of Springer Science and Business Media.

Stanford University Press, for material from Sears, R., Maccoby, E. and Levin, H. (1976)

Patterns of Child Rearing (originally published 1957).

Taylor & Francis, for Brenner, M. and Marsh, P. (eds) (1978) The Social Contexts of Method; Burgess, R. (ed.) (1993) Educational Research for Policy and Practice, pp. 119 and 135; Burgess, R. (ed.) (1985) Issues in Educational Research, pp. 116–28 and 244–7; Burgess, R. (ed.) (1989)The Ethics of Educational Research, p. 194; Cuff, E. G. and Payne, G. (1979)

Perspectives in Sociology, p. 4; Hammersley, M. and Atkinson, P. (1983)Ethnography: Principles and Practice, pp. 18, 19, 76; Hitchcock, G. and Hughes, D. (1995) Research and the Teacher (second edition), pp. 20–2, 41; Kincheloe, J. (2003) Teachers as Researchers: Qualitative Inquiry as a Path to Empowerment

(second edition), pp. 138–9; McCormick, J.

and Solman, R. (1992) Teachers’ attributions of responsibility for occupational stress and satisfaction: an organisational perspective,

Educational Studies, 18(92), 201–22; McNiff, J. (2002) Action Research: Principles and Practice

(second edition), pp. 85–91; Medawar, P. (1972)The Hope of Progress; Oldroyd, G. (1986)

The Arch of Knowledge: An Introductory Study of the History of the Philosophy and Methodology of Science; Plummer, K. (1983)Documents of Life: An Introduction to the Problems and Literature of a Humanistic Method; Rex, J. (1974)Approaches to Sociology; Simons, H. and Usher, R. (2000)

Situated Ethics in Educational Research, pp. 1–2; Walford, G. (1994) Researching the Powerful in Education; Zuber-Skerritt, O. (1996) New Directions in Action Research, p. 99; Winter, R. (1982) Dilemma analysis: a contribution to methodology for action research, Cambridge Journal of Education, 12(3), 161–74.

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Introduction

It is seven years since the fifth edition ofResearch Methods in Education was published and we are indebted to Routledge for the opportunity to produce a sixth edition. The book continues to be received very favourably worldwide and is the standard text for many courses in research methods.

The sixth edition contains much new material, including a completely new part on data analysis. This means that the book now covers all stages of educational research, from planning and design, through data collection to data analysis and reporting. While retaining the best features of the former edition, the reshaping, updating and new additions undertaken for this new volume now mean that the book covers a greater spread of issues than the previous editions. In particular, the following new material has been included: Part One:

O feminist theory

O complexity theory and educational research. Part Two:

O ethical codes and responsibilities to sponsors and the research community

O informed consent and deception

O sampling, confidence levels and confidence intervals, together with the calculation of sample sizes

O an entirely new chapter on planning and conducting sensitive educational research, including researching powerful people. Part Three:

O further coverage of documentary research O postal, interview and telephone surveys O an entirely new chapter on Internet-based

research and computer usage, covering Internet surveys, experiments, interviews, questionnaire design, evaluation of web sites, searching

for materials, computer simulations and Geographical Information Systems

O very considerably expanded coverage of ex-perimental research, reflecting the resurgence of interest in this method in evidence-based education.

Part Four:

O more detailed coverage of questionnaire design and administration, with practical guidance on these matters

O interviewing children and telephone inter-viewing.

Part Five:

O an entirely new part, containing five new chapters, covering qualitative and quantitative data analysis

O how to conduct a content analysis O grounded theory and ‘how to do it’ O how to present and report qualitative data O computer usage in qualitative data analysis O an introduction to statistics and statistical

concepts

O hypotheses and how to test them O variables and how to handle them

O effect size and how to calculate and interpret it O practical ‘hands on’ advice for novice researchers, on which statistics to choose and how to use them, from the simplest statistics to high-level factor analysis and multiple regression, and from descriptive to inferential statistics

O advice on how to select appropriate statistics, with charts and diagrams to ease selection O how to avoid selecting incorrect statistics, and

what are the assumptions underlying the main kinds of statistics

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Package for the Social Sciences (SPSS) is the most widely used statistical package in the social sciences).

Additionally there are copious web site references in nearly every chapter, most of which provide free online materials. A signal feature of this edition is the inclusion of several worked examples, particularly in the chapters on data analysis in the new Part Five.

To accompany this volume, a companion web site provides a comprehensive range of materials to cover all aspects of research (including a full course on research methods on PowerPoint slides), exercises and examples, explanatory material and further notes, SPSS data files and SPSS

manual for novice researchers, QSR data files and manual for qualitative data treatment, together with further statistics and statistical tables. (Qualitative Solutions and Research (QSR) is a company which had produced software such as N-Vivo for qualitative data analysis.) These are indicated in the book. A wealth of supporting materials is available on the web site.

We have refined the referencing, relocating several backup references to the Notes, thereby indicating in the main text the most prominent sources and key issues.

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Part One

The context of educational

research

This part locates the research enterprise in several contexts. It commences with positivist and scientific contexts of research and then proceeds to show the strengths and weaknesses of such traditions for educational research. As an alternative paradigm, the cluster of approaches that can loosely be termed interpretive, naturalistic, phenomenological, interactionist and ethnographic are brought together and their strengths and weaknesses for educational research are examined. The rise of critical theory as a paradigm in which educational research is conducted has been spectacular and its implications for the research undertaking are addressed in several ways here, resonating with curriculum research and feminist research (this too has been expanded and updated). Indeed

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1

The nature of inquiry – Setting the field

Introduction

This chapter explores the context of educational research. It sets out several foundations on which different kinds of empirical research are constructed:

O scientific and positivistic methodologies O naturalistic and interpretive methodologies O methodologies from critical theory

O feminist educational research.

Our analysis takes an important notion from Hitchcock and Hughes (1995: 21) who sug-gest that ontological assumptions give rise to epistemological assumptions; these, in turn, give rise to methodological considerations; and these, in turn, give rise to issues of instrumentation and data collection. This view moves us beyond regard-ing research methods as simply a technical exercise and as concerned with understanding the world; this is informed by how we view our world(s), what we take understanding to be, and what we see as the purposes of understanding. The chapter also acknowledges that educational research, politics and decision-making are inextricably intertwined, and it draws attention to the politics of educa-tional research and the implications that this has for undertaking research (e.g. the move towards applied and evaluative research and away from ‘pure’ research). Finally, we add a note about methodology.

The search for truth

People have long been concerned to come to grips with their environment and to understand the nature of the phenomena it presents to their senses. The means by which they set

out to achieve these ends may be classified into three broad categories: experience, reasoning

and research(Mouly 1978). Far from being independent and mutually exclusive, however, these categories must be seen as complementary and overlapping, features most readily in evidence where solutions to complex modern problems are sought.

In our endeavours to come to terms with the problems of day-to-day living, we are heavily dependent upon experience and authority. It must be remembered that as tools for uncovering ultimate truth they have decided limitations. The limitations of personal experience in the form of

common-sense knowing, for instance, can quickly be exposed when compared with features of the scientific approach to problem-solving. Consider, for example, the striking differences in the way in which theories are used. Laypeople base them on haphazard events and use them in a loose and uncritical manner. When they are required to test them, they do so in a selective fashion, often choosing only that evidence that is consistent with their hunches and ignoring that which is counter to them. Scientists, by contrast, construct their theories carefully and systematically. Whatever hypotheses they formulate have to be tested empirically so that their explanations have a firm basis in fact. And there is the concept ofcontrol

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attitude to the relationships among phenomena. Laypeople’s concerns with such relationships are loose, unsystematic and uncontrolled. The chance occurrence of two events in close proximity is sufficient reason to predicate a causal link between them. Scientists, however, display a much more serious professional concern with relationships and only as a result of rigorous experimentation will they postulate a relationship between two phenomena.

People attempt to comprehend the world around them by using three types of reasoning:

deductive reasoning, inductive reasoning and the

combined inductive-deductive approach. Deductive reasoning is based on the syllogism which was Aristotle’s great contribution to formal logic. In its simplest form the syllogism consists of a major premise based on an a priori or self-evident proposition, a minor premise providing a particular instance, and a conclusion. Thus:

All planets orbit the sun. The earth is a planet.

Therefore the earth orbits the sun.

The assumption underlying the syllogism is that through a sequence of formal steps of logic, from the general to the particular, a valid conclusion can be deduced from a valid premise. Its chief limitation is that it can handle only certain kinds of statement. The syllogism formed the basis of systematic reasoning from the time of its inception until the Renaissance. Thereafter its effectiveness was diminished because it was no longer related to observation and experience and became merely a mental exercise. One of the consequences of this was that empirical evidence as the basis of proof was superseded by authority and the more authorities one could quote, the stronger one’s position became. Naturally, with such abuse of its principal tool, science became sterile.

The history of reasoning was to undergo a dramatic change in the 1600s when Francis Bacon began to lay increasing stress on the observational basis of science. Being critical of the model of deductive reasoning on the grounds that its major premises were often preconceived notions which

inevitably bias the conclusions, he proposed in its place the method of inductive reasoning by means of which the study of a number of individual cases would lead to an hypothesis and eventually to a generalization. Mouly (1978) explains it by suggesting that Bacon’s basic premise was that, with sufficient data, even if one does not have a preconceived idea of their significance or meaning, nevertheless important relationships and laws would be discovered by the alert observer. Bacon’s major contribution to science was thus that he was able to rescue it from the death-grip of the deductive method whose abuse had brought scientific progress to a standstill. He thus directed the attention of scientists to nature for solutions to people’s problems, demanding empirical evidence for verification. Logic and authority in themselves were no longer regarded as conclusive means of proof and instead became sources of hypotheses about the world and its phenomena.

Bacon’s inductive method was eventually followed by the inductive-deductive approach which combines Aristotelian deduction with Baconian induction. Here the researcher is involved in a back-and-forth process of induction (from observation to hypothesis) and deduction (from hypothesis to implications) (Mouly 1978). Hypotheses are tested rigorously and, if necessary, revised.

Although both deduction and induction have their weaknesses, their contributions to the development of science are enormous and fall into three categories:

O the suggestion of hypotheses

O the logical development of these hypotheses O the clarification and interpretation of scientific

findings and their synthesis into a conceptual framework.

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TWO CONCEPTIONS OF SOCIAL REALITY 7

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1

particular which distinguish it from the first means of problem-solving identified earlier, namely, experience. First, whereas experience deals with events occurring in a haphazard manner, research is systematic and controlled, basing its operations on the inductive-deductive model outlined above. Second, research is empirical. The scientist turns to experience for validation. As Kerlinger (1970) puts it, subjective, personal belief has to have a reality check against objective, empirical facts and tests. And third, research is self-correcting. Not only does the scientific method have built-in mechanisms to protect scientists from error as far as is humanly possible, but also their procedures and results are open to public scrutiny by fellow professionals. Incorrect results in time will be found and either revised or discarded (Mouly 1978). Research is a combination of both experience and reasoning and must be regarded as the most successful approach to the discovery of truth, particularly as far as the natural sciences are concerned (Borg 1963).1

Educational research has absorbed several com-peting views of the social sciences – the es-tablished, traditional view and an interpretive view, and several others that we explore in this chapter – critical theory, feminist theory and com-plexity theory. The established, traditional view holds that the social sciences are essentially the same as the natural sciences and are therefore concerned with discovering natural and universal laws regulating and determining individual and social behaviour; the interpretive view, however, while sharing the rigour of the natural sciences and the same concern of traditional social science to describe and explain human behaviour, em-phasizes how people differ from inanimate natural phenomena and, indeed, from each other. These contending views – and also their corresponding reflections in educational research – stem in the first instance from different conceptions of social reality and of individual and social behaviour. It will help our understanding of the issues to be developed subsequently if we examine these in a little more detail (see http://www.routledge.com/ textbooks/9780415368780 – Chapter 1, file 1.1. ppt).

Two conceptions of social reality

The views of social science that we have just identified represent strikingly different ways of looking at social reality and are constructed on correspondingly different ways of interpreting it. We can perhaps most profitably approach these conceptions of the social world by examining the explicit and implicit assumptions underpinning them. Our analysis is based on the work of Burrell and Morgan (1979), who identified four sets of such assumptions.

First, there are assumptions of an ontological kind – assumptions which concern the very nature or essence of the social phenomena being investigated. Thus, the authors ask, is social reality external to individuals – imposing itself on their consciousness from without – or is it the product of individual consciousness? Is reality of an objective nature, or the result of individual cognition? Is it a given ‘out there’ in the world, or is it created by one’s own mind? These questions spring directly from what philosophy terms the nominalist–realist debate. The former view holds that objects of thought are merely words and that there is no independently accessible thing constituting the meaning of a word. The realist position, however, contends that objects have an independent existence and are not dependent for it on the knower.

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The third set of assumptions concern human nature and, in particular, the relationship between human beings and their environment. Since the human being is both its subject and object of study, the consequences for social science of assumptions of this kind are indeed far-reaching. Two images of human beings emerge from such assumptions – the one portrays them as responding mechanically and deterministically to their environment, i.e. as products of the environment, controlled like puppets; the other, as initiators of their own actions with free will and creativity, producing their own environments. The difference is between

determinism and voluntarism respectively (Burrell and Morgan 1979).

It would follow from what we have said so far that the three sets of assumptions identified above have direct implications for the methodological concerns of researchers, since the contrasting ontologies, epistemologies and models of human beings will in turn demand different research methods. Investigators adopting an objectivist (or positivist) approach to the social world and who treat it like the world of natural phenomena as being hard, real and external to the individual will choose from a range of traditional options – surveys, experiments, and the like. Others favouring the more subjectivist (or anti-positivist) approach and who view the social world as being of a much softer, personal and humanly created kind will select from a comparable range of recent and emerging techniques – accounts, participant observation and personal constructs, for example.

Where one subscribes to the view that treats the social world like the natural world – as if it were a hard, external and objective reality – then scientific investigation will be directed at analysing the relationships and regularities between selected factors in that world. It will be predominantly quantitative and will be concerned with identifying and defining elements and discovering ways in which their relationships can be expressed. Hence, they argue, methodological issues, of fundamental importance, are thus the concepts themselves, their measurement and the identification of

underlying themes in a search for universal laws that explain and govern that which is being observed (Burrell and Morgan 1979). An approach characterized by procedures and methods designed to discover general laws may be referred to as

nomothetic.

However, if one favours the alternative view of social reality which stresses the importance of the subjective experience of individuals in the creation of the social world, then the search for understanding focuses upon different issues and approaches them in different ways. The principal concern is with an understanding of the way in which the individual creates, modifies and interprets the world in which he or she finds himself or herself. The approach now takes on a qualitative as well as quantitative aspect. As Burrell and Morgan (1979) and Kirk and Miller (1986: 14) observe, emphasis here is placed on explanation and understanding of the unique and the particular individual case rather than the general and the universal; the interest is in a subjective, relativistic social world rather than an absolutist, external reality. In its emphasis on the particular and individual this approach to understanding individual behaviour may be termedidiographic.

In this review of Burrell and Morgan’s analysis of the ontological, epistemological, human and methodological assumptions underlying two ways of conceiving social reality, we have laid the foundations for a more extended study of the two contrasting perspectives evident in the practices of researchers investigating human behaviour and, by adoption, educational problems. Box 1.1 summarizes these assumptions along a subjective–objective dimension. It identifies the four sets of assumptions by using terms we have adopted in the text and by which they are known in the literature of social philosophy.

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POSITIVISM 9

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Box 1.1

The subjective–objective dimension

Nominalism

Anti-positivism

Voluntarism

Idiographic

Realism

Positivism

Determinism

Nomothetic ontology

epistemology

human nature

methodology The subjectivist

approach to social science

The objectivist approach to social science A scheme for analysing assumptions about the nature of social science

Source: Burrell and Morgan 1979

all are influenced by the viewpoint held. Some idea of the considerable practical implications of the contrasting views can be gained by examining Box 1.2 which compares them with respect to a number of critical issues within a broadly societal and organizational framework. Implications of the two perspectives for research into classrooms and schools will unfold in the course of the text.

Because of its significance for the epistemologi-cal basis of social science and its consequences for educational research, we devote much discussion in this chapter to the positivist and anti-positivist debate.

Positivism

Although positivism has been a recurrent theme in the history of western thought from the Ancient Greeks to the present day, it is historically associated with the nineteenth-century French philosopher, Auguste Comte, who was the first thinker to use the word for a philosophical position (Beck 1979). His positivism turns to observation and reason as means of understanding behaviour; explanation proceeds by way of scientific description. In

his study of the history of the philosophy and methodology of science, Oldroyd (1986) says:

It was Comte who consciously ‘invented’ the new science of society and gave it the name to which we are accustomed. . .. For social phenomena were to be viewed in the light of physiological (or biological) laws and theories and investigated empirically, just like physical phenomena.

(Oldroyd 1986)

Comte’s position was to lead to a general doctrine of positivism which held that all genuine knowledge is based on sense experience and can be advanced only by means of observation and experiment. Following in the empiricist tradition, it limited inquiry and belief to what can be firmly established and in thus abandoning metaphysical and speculative attempts to gain knowledge by reason alone, the movement developed what has been described as a ‘tough-minded orientation to facts and natural phenomena’ (Beck 1979).

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Box 1.2

Alternative bases for interpreting social reality

Conceptions of social reality

Dimensions of comparison Objectivist Subjectivist

Philosophical basis Realism: the world exists and is knowable as it really is. Organizations are real entities with a life of their own.

Idealism: the world exists but different people construe it in very different ways. Organizations are invented social reality.

The role of social science Discovering the universal laws of society and human conduct within it.

Discovering how different people interpret the world in which they live.

Basic units of social reality The collectivity: society or organizations. Individuals acting singly or together.

Methods of understanding Identifying conditions or relationships which permit the collectivity to exist. Conceiving what these conditions and relationships are.

Interpretation of the subjective meanings which individuals place upon their action. Discovering the subjective rules for such action.

Theory A rational edifice built by scientists to explain human behaviour.

Sets of meanings which people use to make sense of their world and behaviour within it.

Research Experimental or quasi-experimental validation of theory.

The search for meaningful relationships and the discovery of their consequences for action.

Methodology Abstraction of reality, especially through mathematical models and quantitative analysis.

The representation of reality for purposes of comparison. Analysis of language and meaning.

Society Ordered. Governed by a uniform set of values and made possible only by those values.

Conflicted. Governed by the values of people with access to power.

Organizations Goal oriented. Independent of people. Instruments of order in society serving both society and the individual.

Dependent upon people and their goals. Instruments of power which some people control and can use to attain ends which seem good to them.

Organizational pathologies Organizations get out of kilter with social values and individual needs.

Given diverse human ends, there is always conflict among people acting to pursue them.

Prescription for change Change the structure of the organization to meet social values and individual needs.

Find out what values are embodied in organizational action and whose they are. Change the people or change their values if you can.

Source: adapted from Barr Greenfield 1975

the following connected suppositions, identified by Giddens (1975). First, the methodological procedures of natural science may be directly applied to the social sciences. Positivism here implies a particular stance concerning the social scientist as an observer of social reality. Second, the end-product of investigations by social

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THE ASSUMPTIONS AND NATURE OF SCIENCE 11

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matter. Positivism claims that science provides us with the clearest possible ideal of knowledge.

Where positivism is less successful, however, is in its application to the study of human behaviour where the immense complexity of human nature and the elusive and intangible quality of social phenomena contrast strikingly with the order and regularity of the natural world. This point is nowhere more apparent than in the contexts of classroom and school where the problems of teaching, learning and human interaction present the positivistic researcher with a mammoth challenge (see http://www.routledge.com/textbooks/

9780415368780 – Chapter 1, file 1.2. ppt). For further information on positivism within the history of the philosophy and methodology of science, see Oldroyd (1986). We now look more closely at some of its features.

The assumptions and nature of science

We begin with an examination of the tenets of scientific faith: the kinds of assumptions held by scientists, often implicitly, as they go about their daily work. First, there is the assumption of determinism. This means simply that events have causes, that events are determined by other circumstances; and science proceeds on the belief that these causal links can eventually be uncovered and understood, that the events are explicable in terms of their antecedents. Moreover, not only are events in the natural world determined by other circumstances, but also there is regularity about the way they are determined: the universe does not behave capriciously. It is the ultimate aim of scientists to formulate laws to account for the happenings in the world, thus giving them a firm basis for prediction and control.

The second assumption is that ofempiricism. We have already touched upon this viewpoint, which holds that certain kinds of reliable knowledge can only derive from experience. In practice, this means scientifically that the tenability of a theory or hypothesis depends on the nature of the empirical evidence for its support. Empirical here means that which is verifiable by observation and

direct experience (Barratt 1971); and evidence, data yielding proof or strong confirmation, in probability terms, of a theory or hypothesis in a research setting.

Mouly (1978) identifies five steps in the process of empirical science:

1 experience: the starting point of scientific endeavour at the most elementary level 2 classification: the formal systematization of

otherwise incomprehensible masses of data 3 quantification: a more sophisticated stage

where precision of measurement allows more adequate analysis of phenomena by mathematical means

4 discovery of relationships: the identification and classification of functional relationships among phenomena

5 approximation to the truth: science proceeds by gradual approximation to the truth.

The third assumption underlying the work of the scientist is the principle of parsimony. The basic idea is that phenomena should be explained in the most economical way possible, as Einstein was known to remark – one should make matters as simple as possible, but no simpler! The first historical statement of the principle was by William of Occam when he said that explanatory principles (entities) should not be needlessly multiplied. It may, of course, be interpreted in various ways: that it is preferable to account for a phenomenon by two concepts rather than three; that a simple theory is to be preferred to a complex one.

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chiefly with inanimate matter than to human scientists who, of necessity having to deal with samples of larger human populations, have to exercise great caution when generalizing their findings to the particular parent populations.

We come now to the core question: What is science? Kerlinger (1970) points out that in the scientific world itself two broad views of science may be found: thestaticand thedynamic. Thestatic

view, which has particular appeal for laypeople, is that science is an activity that contributes systematized information to the world. The work of the scientist is to uncover new facts and add them to the existing corpus of knowledge. Science is thus seen as an accumulated body of findings, the emphasis being chiefly on the present state of knowledge and adding to it.2 The dynamicview,

by contrast, conceives science more as an activity, as something that scientistsdo. According to this conception it is important to have an accumulated body of knowledge of course, but what really matter most are the discoveries that scientists make. The emphasis here, then, is more on the heuristic nature of science.

Contrasting views exist on the functions of science. We give a composite summary of these in Box 1.3. For the professional scientists, however, science is seen as a way of comprehending the world; as a means of explanation and understanding, of prediction and control. For them the ultimate aim of science is theory.

Theoryhas been defined by Kerlinger as ‘a set of interrelated constructs [concepts], definitions, and propositions that presents a systematic view of phenomena by specifying relations among variables, with the purpose of explaining and predicting the phenomena’ (Kerlinger 1970). In a sense, theory gathers together all the isolated bits of empirical data into a coherent conceptual framework of wider applicability. More than this, however, theory is itself a potential source of further information and discoveries. It is in this way a source of new hypotheses and hitherto unasked questions; it identifies critical areas for further investigation; it discloses gaps in our knowledge; and enables a researcher to postulate the existence of previously unknown phenomena.

Box 1.3

The functions of science

1 Its problem-seeking, question-asking,

hunch-encouraging, hypotheses-producing function. 2 Its testing, checking, certifying function; its trying out

and testing of hypotheses; its repetition and checking of experiments; its piling up of facts. 3 Its organizing, theorizing, structuring function; its

search for larger and larger generalizations. 4 Its history-collecting, scholarly function. 5 Its technological side; instruments,

methods, techniques.

6 Its administrative, executive and organizational side. 7 Its publicizing and educational functions.

8 Its applications to human use.

9 Its appreciation, enjoyment, celebration and glorification.

Source: Maslow 1954

Clearly there are several different types of the-ory, and each type of theory defines its own kinds of ‘proof’. For example, Morrison (1995a) identi-fies empirical theories, ‘grandtheories and ‘critical

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THE ASSUMPTIONS AND NATURE OF SCIENCE 13

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heterogeneity and fragmentation. This book does not endeavour to refer to this type of theory.

The status of theory varies quite considerably according to the discipline or area of knowledge in question. Some theories, as in the natural sciences, are characterized by a high degree of elegance and sophistication; others, perhaps like educational theory, are only at the early stages of formulation and are thus characterized by great un-evenness. Popper (1968), Lakatos (1970),3Mouly (1978), Laudan (1990) and Rasmussen (1990) identify the following characteristics of an effec-tive empirical theory:

O A theoretical system must permit deductions and generate laws that can be tested empirically; that is, it must provide the means for its confirmation or rejection. One can test the validity of a theory only through the validity of the propositions (hypotheses) that can be derived from it. If repeated attempts to disconfirm its various hypotheses fail, then greater confidence can be placed in its validity. This can go on indefinitely, until possibly some hypothesis proves untenable. This would constitute indirect evidence of the inadequacy of the theory and could lead to its rejection (or more commonly to its replacement by a more adequate theory that can incorporate the exception).

O Theory must be compatible with both observation and previously validated theories. It must be grounded in empirical data that have been verified and must rest on sound postulates and hypotheses. The better the theory, the more adequately it can explain the phenomena under consideration, and the more facts it can incorporate into a meaningful structure of ever-greater generalizability. There should be internal consistency between these facts. It should clarify the precise terms in which it seeks to explain, predict and generalize about empirical phenomena.

O Theories must be stated in simple terms; that theory is best that explains the most in the simplest way. This is the law of parsimony. A theory must explain the data adequately

and yet must not be so comprehensive as to be unwieldy. On the other hand, it must not overlook variables simply because they are difficult to explain.

O A theory should have considerable explanatory and predictive potential.

O A theory should be able to respond to observed anomalies.

O A theory should spawn a research enterprise (echoing Siegel’s (1987) comment that one of the characteristics of an effective theory is its fertility).

O A theory should demonstrate precision and universality, and set the grounds for its own falsification and verification, identifying the nature and operation of a ‘severe test’ (Popper 1968). An effective empirical theory is tested in contexts which are different from those that gave rise to the theory, i.e. they should move beyond simply corroboration and induction and towards ‘testing’ (Laudan 1990). It should identify the type of evidence which is required to confirm or refute the theory.

O A theory must be operationalizable precisely. O A test of the theory must be replicable. Sometimes the wordmodel is used instead of, or interchangeably with,theory. Both may be seen as explanatory devices or schemes having a broadly conceptual framework, though models are often characterized by the use of analogies to give a more graphic or visual representation of a particular phenomenon. Providing they are accurate and do not misrepresent the facts, models can be of great help in achieving clarity and focusing on key issues in the nature of phenomena.

Hitchcock and Hughes (1995) draw together the strands of the discussion so far when they describe a theory thus:

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events in ways which are consistent with a particular philosophical rationale or, for example, a particular sociological or psychological perspective. Theories therefore aim to both propose and analyze sets of relations existing between a number of variables when certain regularities and continuities can be demonstrated via empirical enquiry.

(Hitchcock and Hughes 1995: 20–1)

Scientific theories must, by their very nature, be provisional. A theory can never be complete in the sense that it encompasses all that can be known or understood about the given phenomenon. As Mouly (1978) argues, one scientific theory is replaced by a superior, more sophisticated theory, as new knowledge is acquired.

In referring to theory and models, we have begun to touch upon the tools used by scientists in their work. We look now in more detail at two such tools which play a crucial role in science – the concept and the hypothesis.

The tools of science

Concepts express generalizations from particu-lars – anger, achievement, alienation, velocity, in-telligence, democracy. Examining these examples more closely, we see that each is a word repre-senting an idea: more accurately, a concept is the relationship between the word (or symbol) and an idea or conception. Whoever we are and whatever we do, we all make use of concepts. Naturally, some are shared and used by all groups of people within the same culture – child, love, justice, for example; others, however, have a restricted currency and are used only by certain groups, specialists, or members of professions – idioglossia, retroactive inhibition, anticipatory socialization.

Concepts enable us to impose some sort of meaning on the world; through them reality is given sense, order and coherence. They are the means by which we are able to come to terms with our experience. How we perceive the world, then, is highly dependent on the repertoire of concepts we can command. The more we have, the more sense data we can pick up and the surer will be our perceptual (and cognitive) grasp of

whatever is ‘out there’. If our perceptions of the world are determined by the concepts available to us, it follows that people with differing sets of concepts will tend to view the ‘same’ objective reality differently – a doctor diagnosing an illness will draw upon a vastly different range of concepts from, say, the restricted and simplistic notions of the layperson in that context.

So, you may ask, where is all this leading? Simply to this: that social scientists have likewise developed, or appropriated by giving precise meaning to, a set of concepts which enable them to shape their perceptions of the world in a particular way, to represent that slice of reality which is their special study. And collectively, these concepts form part of their wider meaning system which permits them to give accounts of that reality, accounts which are rooted and validated in the direct experience of everyday life. These points may be exemplified by the concept of social class. Hughes (1976) says that it offers

a rule, a grid, even though vague at times, to use in talking about certain sorts of experience that have to do with economic position, life-style, life-chances, and so on. It serves to identify aspects of experience, and by relating the concept to other concepts we are able to construct theories about experience in a particular order or sphere.

(Hughes 1976: 34)

There are two important points to stress when considering scientific concepts. The first is that they do not exist independently of us: they are indeed our inventions enabling us to acquire some understanding at least of the apparent chaos of nature. The second is that they are limited in number and in this way contrast with the infinite number of phenomena they are required to explain.

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THE SCIENTIFIC METHOD 15

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an educated guess in that it is often the result of considerable study, reflective thinking and observation. Medawar (1972) writes of the hypothesis and its function thus:

All advances of scientific understanding, at every level, begin with a speculative adventure, an imaginative preconceptionof what might be true– a preconception which always, and necessarily, goes a little way (sometimes a long way) beyond anything which we have logical or factual authority to believe in. It is the invention of a possible world, or of a tiny fraction of that world. The conjecture is then exposed to criticism to find out whether or not that imagined world is anything like the real one. Scientific reasoning is therefore at all levels an interaction between two episodes of thought – a dialogue between two voices, the one imaginative and the other critical; a dialogue, if you like, between the possible and the actual, between proposal and disposal, conjecture and criticism, between what might be true and what is in fact the case.

(Medawar 1972)

Kerlinger (1970) has identified two criteria for ‘good’ hypotheses. The first is that hypotheses are statements about the relations between variables; and second, that hypotheses carry clear implications for testing the stated relations. To these he adds two ancillary criteria: that hypotheses disclose compatibility with current knowledge; and that they are expressed as economically as possible. Thus if we conjecture that social class background determines academic achievement, we have a relationship between one variable, social class, and another, academic achievement. And since both can be measured, the primary criteria specified by Kerlinger can be met. Neither do they violate the ancillary criteria proposed by Kerlinger (see also Box 1.4).

He further identifies four reasons for the importance of hypotheses as tools of research. First, they organize the efforts of researchers. The relationship expressed in the hypothesis indicates what they should do. They enable them to understand the problem with greater clarity and provide them with a framework for collecting, analysing and interpreting their data.

Box 1.4

The hypothesis

Once one has a hypothesis to work on, the scientist can move forward; the hypothesis will guide the researcher on the selection of some observations rather than others and will suggest experiments. Scientists soon learn by experience the characteristics of a good hypothesis. A hypothesis that is so loose as to accommodateanyphenomenon tells us precisely nothing; the more phenomena it prohibits, the more informative it is.

A good hypothesis must also havelogical immediacy, i.e. it must provide an explanation of whatever it is that needs to be explained and not an explanation of other pheno

Gambar

Table 1 of the Appendices of Statistical Tables. For
table of significance reproduced above shows, the
table is shown here.

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