Causation in educational research:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Routledge
2009
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIV, 231 S. graph. Darst. |
| ISBN: | 9780415496483 9780415496490 |
Internformat
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| 245 | 1 | 0 | |a Causation in educational research |c Keith Morrison |
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Datensatz im Suchindex
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|---|---|
| adam_text | Titel: Causation in educational research
Autor: Morrison, Keith
Jahr: 2009
Contents
List of figures xi
List of tables xiii
Preface xv
Acknowledgements xvii
1 The world of cause and effect 1
2 Tools for understanding causation 6
A worked example: the fight in the school playground 6
Cause and effect: the problem of inclusion 7
Causes and conditions 11
Causal chains and causal lines 12
The direction of causation 17
Necessary and sufficient conditions 20
Real causes and real effects 21
Does cause always precede effect? 24
Limitations of deterministic causation 26
Taking stock 27
3 Probabilistic causation 29
A worked example: small class teaching 30
Probability, prediction and regression 34
Can one really calculate the relative strength of causes? 39
Linear and non-linear relations of cause and effect 42
Conditional probability 45
Causes, events, states, processes and effects 47
Quasi-causation 51
Calculating probabilities 55
Screening off and causal forks 5 7
The ecological fallacy 62
Recursive and non-recursive models 63
How to control for different variables 65
Example 1: Gender, earnings and educational attainment 71
Example 2: Males and females preferences for a male or
female teacher 73
Example 3: Males and females mathematics scores 75
Example 4: Juvenile smoking, exercise and heart disease 82
Example 5: Controlling with categorical bivariate data 85
Example 6: Controlling with categorical trivariate data 88
Example 7: Partial correlations using SPSS 92
Path analysis 96
Statistics and causation 99
Example 8: Qualitative research on a science innovation in schools 99
Example 9: Investigating causation in ethnographic research 103
Using tracers in qualitative research 105
Taking stock 105
4 Approaching cause and effect 108
Introduction 108
Stages in identifying causation 111
Stage 1: Establish what has to be explained 111
Stage 2: Construct a theoretical explanation of the causation 113
Stage 3: Test the causal theory 128
Stage 4: Draw conclusions 136
Taking stock 137
5 Determining the effects of causes 138
Introduction 138
Manipulating causes 138
Action research 141
Experimental methods 143
Randomized controlled trials in experimental approaches to
determine what works 150
¥urther issues in experiments 158
The timing of data collection points 167
The problem of personal perception: the base rate fallacy 170
Taking stock 172
6 Determining causes from effects 174
Introduction 174
A case study: Catherine s chemistry 174
Ex post facto experiments to determine causation 178
Example 1: Class differentials in educational attainment 182
Example 2: When causes become effects and effects become
causes: schooling for conformity 196
Taking stock 203
7 Causation: effective, inconsequential or a lost cause? 205
Summary of the argument in the book 205
Prospect and challenges 210
Notes 215
References 217
Index 229
Figures
1.1 Priority and contiguity in cause and effect 3
2.1 Temporal and non-temporal contexts of cause and effect 8
2.2 Circumstances, conditions and causation 12
2.3 A net of causation 13
2.4 A causal chain 14
2.5 Real and spurious causes 14
2.6 Causal lines producing the same effect 15
2.7 Interaction effects within causal lines 15
2.8 Directions of causation 17
3.1 A scatterplot and regression line 34
3.2 A linear relationship in a regression 43
3.3 A curvilinear relationship in a regression 43
3.4 A non-linear relationship in a regression 43
3.5 A chaotic and unpredictable relationship in a regression 44
3.6 Direct and indirect effects of a cause 46
3.7 Temporal overlap of cause and effect 48
3.8 Correlation from a prior cause 58
3.9 A conjunctive fork with two different effects 59
3.10 A conjunctive fork with a conjoint effect 59
3.11 A closed conjunctive fork 59
3.12 An interactive fork 60
3.13 Simple screening off of a cause and effect 60
3.14 Complex screening off of cause and effect 61
3.15 A common cause and screening off 61
3.16 Screening off in multiple causes 61
3.17 A recursive model of causation 63
3.18 A non-recursive model of causation 64
3.19 Reciprocal relations in a non-recursive model 64
3.20 Antecedent and intervening variables 67
3.21 Regression for two different groups 71
3.22 Construction of a causal model 85
3.23 SPSS output from partial correlation, controlling for
socio-economic status 94
— -o—. --
3.24 SPSS output for partial correlations, controlling for part-time work 95
3.25 Path analysis modelling with AMOS (AMOS output) 97
3.26 Path analysis with calculations added (AMOS output) 98
3.27 Cross-site analysis of qualitative data 101
3.28 Factors facilitating and impeding change in qualitative data 102
analysis
4.1 Different causal motives behind the same response 117
4.2 Same effect, many causes 117
4.3 Cause and effect of young people s low attainment 121
4.4 Modelling causes and effects of low attainment in young people 124
5.1 Mathematics scores by age and sex 140
5.2 The true experiment 144
5.3 A causal chain of many links 165
5.4 Initial causes and later effects 167
6.1 Two causes and two effects 181
6.2 Rival theories to explain a phenomenon 189
6.3 A model of determining causes from effects 195
6.4 The circular nature of causality 202
Tables
2.1 Attendance and non-attendance at lessons 10
3-1 Scores on a mathematics test for control and experimental groups 30
3.2 The strength of causal factors 33
3.3 The Adjusted R square (SPSS output) 35
3.4 Analysis of variance in a regression table (SPSS output) 35
3.5 The beta coefficient (SPSS output) 36
3.6 Adjusted R square for more than one predictor variable
(SPSS output) 36
3.7 Analysis of variance for more than one predictor variable
(SPSS output) 37
3-8 Beta coefficients with two variable predictors (SPSS output) 37
3-9 Beta coefficients of multiple variables (SPSS output) 40
3.10 Altered weightings in beta coefficients (SPSS output) 40
3.11 Further altered weightings in beta coefficients (SPSS output) 41
3.12 Class size, students scores and interactive teaching 55
3.13 Years of teaching and acceptance of dictatorial leadership 68
3.14 Controlling for a third variable 69
3.15 The effects of a distorter variable 70
3.16 Controlling for the effects of a distorter variable 70
317 Differences in earnings at age 25 72
3.18 Qualifications of males and females 72
3-19 Earnings and levels of qualification 72
3.20 Earnings and qualifications by males and females 73
3.21 Differences in earnings by males and females, by
different qualifications 73
3.22 Teacher preferences of primary school boys and girls 73
3-23 Teacher preferences of younger and older primary school
boys and girls 74
3.24 Different teacher preferences of younger and older primary
school children 74
3.25 Do males score higher or lower marks in maths than females? 75
3.26 Multiple regression for mathematics scores 75
3.27 Crosstabulation of sex, mathematics and IQ (SPSS output) 77
3.28 Do males score higher or lower marks in maths than females, and
why? 78
3.29 Comparative results of factors influencing mathematics scores 80
3.30 Smoking, heart disease and exercise 83
3.31 Socio-economic status, part-time work and class of degree 86
3.32 Probability of gaining a certain class of degree 86
3.33 Socio-economic status and class of degree 87
3.34 Part-time work and class of degree 87
3.35 A trivariate crosstabulation 88
3.36 Likelihood of obtaining a high-class degree 89
3.37 Likelihood of obtaining a low-class degree 89
3.38 Grouping data on socio-economic status, part-time work and
level of degree 92
3.39 Part-time work and class of degree, controlled for socio-economic
status (SPSS output) 93
5.1 Resources, student motivation and examination results 139
5.2 Two experimental and two control groups 145
5.3 Experimental results for control and experimental groups 145
6.1 An ex post facto experiment 180
|
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| spelling | Morrison, Keith 1948- Verfasser (DE-588)135687896 aut Causation in educational research Keith Morrison 1. publ. New York [u.a.] Routledge 2009 XIV, 231 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Erziehung Education Research Causation Pädagogik (DE-588)4044302-4 gnd rswk-swf Forschung (DE-588)4017894-8 gnd rswk-swf Pädagogik (DE-588)4044302-4 s Forschung (DE-588)4017894-8 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017644084&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Causation in educational research |
| title_auth | Causation in educational research |
| title_exact_search | Causation in educational research |
| title_full | Causation in educational research Keith Morrison |
| title_fullStr | Causation in educational research Keith Morrison |
| title_full_unstemmed | Causation in educational research Keith Morrison |
| title_short | Causation in educational research |
| title_sort | causation in educational research |
| topic | Erziehung Education Research Causation Pädagogik (DE-588)4044302-4 gnd Forschung (DE-588)4017894-8 gnd |
| topic_facet | Erziehung Education Research Causation Pädagogik Forschung |
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