139,99 €
Mehr erfahren.
- Herausgeber: John Wiley & Sons
- Kategorie: Bildung
- Sprache: Englisch
Cognitive flexibility is the cornerstone of learning and enables us to cope with a constantly changing environment. By adapting our knowledge and habits in order to respond to new situations, cognitive flexibility plays a fundamental role in learning. This book proposes a study of the fundamental notions of cognitive flexibility: its measurement and development, its links with metacognition and critical thinking and the role of context in its expression, as well as its involvement in discovering solutions, transferring knowledge and processing analogies. Convergent perspectives are also presented in order to paint a clear picture of cognitive flexibility and to discuss the issues at stake. Thanks to the combined views of specialists in cognitive and developmental psychology, Cognitive Flexibility suggests new educational possibilities based on the results of empirical work on the subject.
Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 418
Veröffentlichungsjahr: 2022
Ähnliche
Table of Contents
Cover
Title Page
Copyright
Introduction
1 Measures of Flexibility
1.1. Introduction
1.2. Why measure flexibility?
1.3. How can we measure flexibility?
1.4. Conclusion
1.5. References
2 Development of Cognitive Flexibility
2.1. Introduction
2.2. Main study paradigms and some developmental points of reference
2.3. How can we account for perseveration behaviors in the preschool years?
2.4. Beyond perseveration
2.5. Flexibility: a question of goal management
2.6. From imposed flexibility to self-regulated flexibility
2.7. Conclusion
2.8. References
3 Metacognition and Flexibility: What are the Theoretical Links and What Links have been Observed?
3.1. Introduction
3.2. Metacognition
3.3. Executive functions
3.4. The common features between metacognition and executive functions
3.5. Conclusion
3.6. References
4 Critical Thinking and Flexibility
4.1. Introduction
4.2. Characterizing critical thinking to foster its development
4.3. The critical mind, a flexible mind?
4.4. Developing critical thinking skills through multiple categorization
4.5. Conclusion
4.6. References
5 Successful Solution Discovery and Cognitive Flexibility
5.1. Introduction
5.2. Cognitive flexibility in problem solving
5.3. Flexibility, creativity and academic performance
5.4. Conclusion
5.5. References
6 Transfer of Learning and Flexibility in Childhood
6.1. Introduction
6.2. Transfer of learning: a developmental overview
6.3. Transfer and flexibility
6.4. Conclusion
6.5. References
7 Cognitive Flexibility and Analogy
7.1. Introduction
7.2. The role of prior knowledge in analogy
7.3. Cognitive flexibility as a key process in analogy-making
7.4. Conclusion
7.5. References
8 Context, Content Effects and Flexibility
8.1. Introduction
8.2. Context, concepts and flexibility
8.3. Representing situations and tasks
8.4. Semantic recoding and cognitive flexibility
8.5. Conclusion
8.6. References
List of Authors
Index
End User License Agreement
List of Illustrations
Chapter 2
Figure 2.1. The Dimensional Change Card Sorting (DCCS) task (from Zelazo et al. ...
Figure 2.2. Preschool Attentional Switching Task (PAST) proposed by Chevalier an...
Figure 2.3. Distribution of eye fixation patterns as a function of age and type ...
Chapter 4
Figure 4.1. Two representations of the two trains and bird problem
Chapter 7
Figure 7.1. Experimental stimuli
1
reproduced from Goswami and Brown (1990)
Chapter 8
Figure 8.1. Initial state (a) and final state (b) of the candle problem. For a c...
Figure 8.2. Complete (a) and truncated (b) problem space of the Tower of Hanoi p...
List of Tables
Chapter 1
Table 1.1. Examples of flexibility tasks in direct measurement
Table 1.2. Examples of indirect measures of flexibility
Guide
Cover
Table of Contents
Title Page
Copyright
Introduction
Begin Reading
List of Authors
Index
End User License Agreement
Pages
v
iii
iv
ix
x
xi
xii
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
SCIENCES
Education and Training, Field Director – Jean-Marc Labat
Cognition and Learning Processes, Subject Head – Emmanuel Sander
Cognitive Flexibility
The Cornerstone of Learning
Coordinated by
Evelyne Clément
First published 2022 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:
ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUK
www.iste.co.uk
John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USA
www.wiley.com
© ISTE Ltd 2022
The rights of Evelyne Clément to be identified as the author of this work have been asserted by her in accordance with the Copyright, Designs and Patents Act 1988.
Library of Congress Control Number: 2021946241
British Library Cataloguing-in-Publication Data
A CIP record for this book is available from the British Library
ISBN 978-1-78945-035-4
ERC code:
SH4 The Human Mind and Its Complexity
SH4_1 Cognitive basis of human development and education, developmental disorders; comparative cognition
SH4_6 Learning, memory; cognition in ageing
Introduction
Evelyne CLÉMENT
Paragraphe, CY Cergy Paris University, Gennevilliers, France
Over the past three decades, the study of the flexible nature of human cognition has been of growing interest to scientists and practitioners specializing in early childhood, neuropsychology and education. In many manifestations of human activity, an important issue is to understand the nature and development of cognitive flexibility and the processes and contexts that promote or inhibit its expression. This issue is crucial in the field of lifelong learning, and more particularly in the field of school learning.
As evidenced by the scientific literature in this field of research, and although different understandings of flexibility have been proposed – with some defining it as a general and universal process independent of the contexts in which it is expressed, others, on the contrary, as a skill that develops at the same time as other abilities, such as conceptual and language development – a broad consensus is emerging on the flexible nature of human cognition to adapt to novelty and unexpected events. In this sense, as a cornerstone of learning, cognitive flexibility allows us to adapt to a constantly changing environment, to discover solutions in new and/or unexpected situations, to transfer knowledge learned in one context to a new context, to select the relevant stimuli in the environment to achieve a goal, to switch our attention from one stimulus to another according to the constraints of the situation, to alternate between two possible forms of processing stimuli, and to change our representation of the goal we are pursuing.
In this way, the flexible character of human cognition enables conceptual development through a creative combination of concepts as well as new learning by modifying our knowledge and habits in order to adapt to the situations in which we evolve and which we have to face. Moreover, this specificity of human cognition allows for the activation and flexible communication of representations in a wide range of activities, whether it is, for example, understanding a metaphor, being moved when reading a poem, using an object in a non-usual function, solving a problem, inferring and understanding the meaning of a new word, or adapting to a new work environment.
Cognitive flexibility plays a key role in the development of thought, reasoning and the acquisition of new knowledge, but also in the mediation of social interactions, the sharing of points of view and the elaboration of socially coordinated action plans. In short, its involvement is fundamental in accommodating the environment in which we evolve and in adapting to the predictable – or unpredictable – circumstances we encounter.
This collective work, written by French specialists in the field, presents the state of the art of current research in cognitive, educational and developmental psychology on cognitive flexibility. The book addresses current and topical questions concerning the measures of cognitive flexibility, the development of this skill in young children, its links with the development of metacognition and critical thinking, its implication in solution discovery, transfer of learning, evocation and matching between analogous situations, as well as the context and content effects that can impact our reasoning and their flexible expression in school learning situations.
Chapter 1 (Célia Maintenant and Gaëlle Bodi) reviews the different tools available to the clinician psychologist and/or researcher to evaluate this process. The authors present the so-called “direct” methods, which involve an evaluation of flexibility capacities by means of a concrete situation (a task constructed in the laboratory or a more ecological situation), and the so-called “indirect” methods, which use questionnaires and are the most commonly used in neuropsychological assessments of patients with executive dysfunction or of very young children.
Chapter 2 (Agnès Blaye) presents several developmental studies conducted with young children in which cognitive flexibility is understood as one of the manifestations of controlled and goal-directed cognitive functioning. Through various experiments focused on inflexible behaviors exhibited by very young children, this chapter empirically demonstrates that changing representations, or in other words being flexible, requires updating and then maintaining the new goals implied by the constraints of situations.
Chapter 3 (Valérie Pennequin) questions the links between executive functions and metacognition, and more specifically between cognitive flexibility and metacognition. After presenting definitions and parallel research on metacognition and executive functions, this chapter highlights the conceptual commonalities between these notions and presents empirical results on the complex links between them.
Chapter 4 (Calliste Scheibling-Sève, Elena Pasquinelli and Emmanuel Sander) deals with one of the major objectives advocated in educational policies, which is the education of critical thinking. Comparing philosophical and psychological approaches to this notion, whose definition does not have a consensus, the chapter deals with the cognitive mechanisms underlying critical thinking such as the change in point of view, metacognition or the recategorization of situations. A path for critical thinking education through the process of multiple categorization is proposed.
Chapter 5 (Evelyne Clément) deals with the crucial role of flexibility in problem solving. Focusing on the different factors involved in successful solution discovery, this chapter presents the results of empirical research conducted in education and cognitive psychology as well as recent work on the links between flexibility, creativity and academic performance. The benefit and implications of research on the development of educational programs to stimulate flexibility and creative thinking are discussed.
Chapter 6 (Jérôme Clerc and Laureen Josseron) presents a body of work on the development of transfer abilities, ranging from the transfer of perceptual properties, to the actions performed by others, via the transfer of relational properties, to the transfer of cognitive strategies. The links with cognitive flexibility, considered as the ability to apply knowledge to new situations in a flexible way, are discussed with regard to the transfer difficulties that young children may have.
Chapter 7 (Lucas Raynal) focuses on the role of cognitive flexibility in the processing of analogous situations which, although superficially different, are structurally identical. The body of research presented shows that some analogies can be perceived by relying on the way a situation is initially represented, while others require flexibility, that is, reconsidering the situation from a more abstract point of view. The study of the role of flexibility in processing analogies opens up educational avenues that are presented and discussed.
Chapter 8 (Hippolyte Gros and Katarina Gvozdic) reviews the contribution of research that studies cognitive flexibility in its interaction with the environment. In this chapter, all the works presented show how the contexts and contents of the situations on which our reasoning operates influence the expression of cognitive flexibility, which can slow down or promote the adoption of a new point of view on a concept, a situation or a problem. Reinforcing the flexibility with which individuals rely on the context to inform their reasoning is recommended.
1Measures of Flexibility
Célia MAINTENANT and Gaëlle BODI
PAVeA, University of Tours, France
1.1. Introduction
In this chapter, we will focus on the measurement of cognitive flexibility. Without aiming to be exhaustive, we will attempt to review the various tools available to psychologists and/or researchers carrying out this measurement, but we will also present the usefulness of such a measurement. This chapter will therefore be organized into two parts corresponding, respectively, to the answers to the following two questions: Why measure flexibility? And how can we measure flexibility?
1.2. Why measure flexibility?
1.2.1. Cognitive flexibility in everyday life
There are many times when we need to be flexible in our day-to-day lives, whether it is when we need to switch from one activity to another, or adapt to something new in our environment. For example, flexibility allows us to switch quickly between parenting and work obligations, or to stay focused on an important conversation while making dinner. It is also useful when we need to adapt to a new route to get to work in the event of traffic works taking place on our usual route. It also helps us adapt to the new layout of the shelves in our favorite store.
A great deal of research has shown that cognitive flexibility is involved in a wide range of activities and is therefore essential in being able to properly adapt to our environment and enjoy a good quality of life (Cartwright et al. 2019).
From an early age, children have a form of flexibility that will then develop with advancing age, approximately until late adolescence (Fourneret and Portes 2017). From childhood, flexibility is important. It is necessary for children when they have to adapt to a change in subject matter at school, such as moving from working on a math concept to a reading activity in an adapted and controlled way. But it can also help children learn. For example, cognitive flexibility is involved in the reading fluency of 7-year-olds, and cognitive flexibility training can improve reading fluency in 8-year-olds with reading difficulties (Cartwright et al. 2019). In addition, cognitive flexibility helps children to use imagination and creativity to solve problems (Georgsdottir and Lubart 2003).
Like other executive functions, in young children, cognitive flexibility is critical for development and can predict academic success, but also later health and income (Munakata et al. 2013). It is also highly related to self-regulation and thus social adjustment (Benson and Sabbagh 2013; Rueda and Paz-Alonso 2013). Finally, various research has shown that it can be related to the development of theory of mind (Zelazo et al. 2002; Müller et al. 2005).
While cognitive flexibility plays an important role in the successful and adapted performance of many everyday activities, these activities can also play a role in the evolution of cognitive flexibility capacities. These abilities can be improved, for example, by daily or near-daily practice of video games, especially action video games. Indeed, better cognitive flexibility could be demonstrated by comparing action video game players to non-gamers (or people who play very little). This could be done by using either a purely transversal method with the direct comparison of a group of gamers to a group of non-gamers, or a semi-experimental one, creating a control condition versus an experimental condition, in which non-gamers have to play action video games for a given time with pre- and post-test flexibility measures (Colzato 2010; Karle et al. 2010; Strobach et al. 2012; Nouchi et al. 2013; Olfers and Band 2018). A recent review of the literature confirms the beneficial effects of video games on mental flexibility (Pallavicini et al. 2018).
1.2.2. Associated pathologies
Attention Deficit Hyperactivity Disorder (ADHD) is often emblematic of pathologies that may be associated with an executive deficit (Willcutt et al. 2005). Recent research has demonstrated the usefulness of cognitive tests, including attention and executive measures, such as flexibility and inhibition to predict the diagnosis of ADHD in children aged 8–15 (Perrault et al. 2019).
Cognitive flexibility difficulties have also been shown in children with pediatric bipolar disorder (Passarotti et al. 2016). Patients with bipolar disorder have a deficit in cognitive flexibility (O’Donnell et al. 2017).
People with autism spectrum disorders also have flexibility difficulties (Hughes et al. 1994; Reed 2018). Zelazo et al. (2002) showed the possibility of predicting theory of mind difficulties in individuals with autism by their performance in cognitive flexibility.
A deficit in cognitive flexibility has also been demonstrated in depression (Gabrys et al. 2018). Many neurodegenerative diseases can be affected by a cognitive flexibility deficit, with the two most iconic being Alzheimer’s disease (Swanberg et al. 2004) and Parkinson’s disease (Lange et al. 2018).
A measure of cognitive flexibility can therefore be useful in the diagnosis of certain pathologies, whether in children or adults.
1.3. How can we measure flexibility?
Can we really talk about measuring flexibility? What are we really measuring?
As with all executive functions, the measurement of pure flexibility seems unattainable. Regardless of the type of assessment chosen, there is no 100% guarantee that no other cognitive process is involved in a situation that is supposed to measure flexibility.
Therefore, we should say that a flexibility task predominantly assesses or involves flexibility to a greater extent than other executive functions, or even other cognitive processes, rather than suggesting that only flexibility is measured in this test. For example, the Trail Making Test (TMT) (Reitan and Wolfson 1993), in which we have to switch from processing a sequence of letters to processing a sequence of numbers, requires flexibility, but also inhibition, because in order to switch to the sequence of numbers, we must inhibit the sequence of letters.
1.3.1. The different types of assessment
Many criteria could be used to classify the different types of flexibility assessment. The population concerned, the more or less ecological nature of the situation used, whether it is spontaneous or reactive flexibility (Eslinger and Grattan 1993; see also Chapter 5), etc., are all criteria that could allow such a classification. In this section, we have chosen to focus on the distinction based on the type of measurement.
In the context of flexibility measurement, as in many other assessments, two main types of measurements can be used: direct measurements and indirect measurements. Measures that can be called “direct” correspond to all situations that involve an assessment of flexibility capacities through a concrete situation (a task constructed in the laboratory, in general, or a more ecological situation).
We will present the different types of direct tasks in a first part, without claiming to be exhaustive. We will see that within these tasks, different subtypes can be identified. The second type of measurement can be called “indirect”, as it is carried out by questionnaire. The questionnaire can either be filled in by the person themselves, in the case of self-assessments, or by a third party (a relative or a carer for example), in the case of hetero-assessments.
Both types of measurement have their advantages and disadvantages. Direct measurements allow an individual measurement at a given time of the individual’s flexibility; this measurement is precise and does not involve the subjectivity of any third party. Therefore, they seem more reliable and representative than indirect measurements, but they have the disadvantage of being more time consuming, and of not being able to be offered to all individuals (for example, very young children, very old people, people with certain pathologies or disabilities).
In contrast, indirect measurements are quicker and less costly to implement. They make it possible to obtain a representation of the various people close to the individual (family, caregivers, teachers, etc.) – or of the individual themselves – of their flexibility. However, they necessarily involve their subjectivity and may therefore be biased and less representative of reality.
1.3.1.1. Direct evaluations
1.3.1.1.1. Historical and classical tasks
One of the best known measurements of flexibility, or at least the most widely used and cited in this field, is the Wisconsin Card Sorting Test (WCST; Grant and Berg (1948)). This task consists of sorting cards, in which no explicit instructions are given and the sorting rule must be inferred on the basis of feedback (correct sorting or not). Once the rule is found, a rule change is performed and the task involves discovering the new sorting rule. The sorting rules are based on perceptual criteria of the elements present on the cards such as color, shape or number. As Miyake (2000) pointed out, the WCST seems to be much more than a test of cognitive flexibility and, according to him, corresponds to a test of high-level executive function, certainly involving cognitive flexibility, but not only this. This task has been considered by different researchers as an inhibition task, a problem-solving task, a categorization task, or other.
Based on the same principle of switching from one process to another on a series of items, several tasks have been proposed that attempt to target an assessment of cognitive flexibility more directly. One of these, often considered a WCST for children, was originally proposed as a flexibility task for preschoolers: the Dimensional Change Card Sort (DCCS) by Frye et al. (1995) – for a recent meta-analysis on this task, see Doebel and Zelazo (2015). In this test, the child must sort two types of test cards (red boats and blue rabbits), matching them to two target cards (a blue boat and a red rabbit). The test consists of two blocks. In the first block, the child must sort the test cards along one dimension (color or shape) and in the second block, the child must sort the same test cards along the other dimension. The instruction is repeated at each trial and the change of dimension is explicitly announced.
We can also mention the Brixton Spatial Anticipation Test, by Burgess and Shallice (1996), which is a test quite similar to the WCST. This test consists of a prediction of displacement according to a rule to be discovered. The rule changes during the test and thus requires the discovery of the new rule. This version is often considered less time consuming than the WCST and more accessible to patients. This test has been adapted for preschoolers by Lehto and Uusitalo (2006) (Brixton Preschool). The child has to predict the spatial location of a character that changes at each trial according to a rule to be discovered on the basis of feedback. In this version, a change of rule also occurs during the test.
The common feature of the above tests is that they require flexible switching from one rule to another on a set of items. Other tasks, on the other hand, require a change in stimulus processing, not between several blocks of items, but from one item to another. One example is the “plus minus” task (Jersild 1927), which compares the performance obtained when performing simple operations (addition or subtraction) without the need to switch to those obtained when performing a series of operations involving a systematic switch between these two simple operations.
This procedure can be seen as the basis of the task switching paradigm, which is used in a great deal of research on processing flexibility in adults (Mayr 2001; Monsell 2003; Schuch and Koch 2003; Mayr and Bell 2006).
Other tasks built on this task switching format can be cited as classic cognitive flexibility tasks and are still widely used, such as the number-letter task (Rogers and Monsell 1995). In this task, pairs of numbers and letters (e.g. 4F) are presented either at the top or bottom of a screen. Depending on the location of the number-letter pair on the screen (top or bottom), a question has to be answered about the number (even or odd?), or about the letter (consonant or vowel?).
The local-global task (Miyake et al. 2000) presents a geometric figure (often referred to as a “Navon figure”; Navon (1977)), in which the shape of a global figure (e.g. a triangle) is composed of other figures, local figures this time, which are much smaller (e.g. squares). A cue (e.g. the color of the figure) tells participants whether to give the number of lines used to compose the figure (e.g. 1 for a circle, 2 for an X, 3 for a triangle, or 4 for a square) for either the global figure or the local figure.
Like the two tasks just presented, some tasks are qualified as cueing, as a cue (usually visual or auditory) signals to the participant what processing they should perform on the stimuli presented to them. For example, in the Color Shape Task (Miyake and Friedman 2012), a cue is given to the participant (C or S) to indicate whether they will have to judge the color (C for color, red or green) or the shape (S for shape, circle or triangle) of the stimulus that will appear. The switching cost is calculated by comparing the reaction times between repeated items (when the processing of the presented item is the same as for the previous item, color then color, for example) and switching items (when the processing of the presented item is different from the previous item, color then shape, for example).
In the TMT (Reitan and Wolfson 1993), the participant must switch from processing a sequence of letters in alphabetical order (A, B, C, etc.) to processing a sequence of numbers in ascending order (1, 2, 3, etc.), alternating between the two processes from one item to the next. Several numbers and letters are placed on a sheet of paper and the participant has to connect the elements with a pencil, going from the first letter (A), to the first number (1), to the second letter (B), and so on (A, 1, B, 2, C, 3, etc.).
A simplified version of this test exists to make it accessible to preschoolers, the TMT for preschoolers (Espy and Cwik 2004). In this test, a sheet of paper shows dogs and bones of different sizes. The child is asked to stamp dogs in order of size (smallest to largest), while stamping the bones corresponding to the size of the dog as they go. The child must stamp the smallest dog, then the smallest bone, then the second dog, the second bone, etc. However, this version for children does not seem quite satisfactory, at least if it is to be used in conjunction with the adult version, because it does not allow for the same type of change to be assessed. The adult version requires switching from one task to another (connecting numbers and connecting letters), whereas the child version only proposes switching between two identical tasks: connecting according to size, certainly by alternating dog and bone, but the task remains identical.
Another adult version with a version for children exists: the Color Trail Test (CTT) (D’Elia et al. 1996) and the Children’s Color Trail Test (CCTT) (Williams et al. 1995), this time being more similar to the adult version. In both cases, the test consists of alternating between two series of numbers, one in pink circles, the other in yellow circles. These versions are simpler than the original version, proposing to alternate between two identical tasks (connecting the sequence of numbers, although alternating according to the color of the items). However, they are still useful in some cases and have the advantage of proposing two equivalent versions, allowing for a comparison of the results of children and adults.
1.3.1.1.2. Executive function assessment batteries
Direct assessments are often less used by practitioners than by researchers, due to the greater material and temporal cost than for indirect assessments. However, there are several batteries of executive function assessments that include measures that can be likened to measures of cognitive flexibility, which have the advantage of providing useful calibrations for practitioners.
The Test of Everyday Attention for Children (TEA-Ch) (Manly et al. 2001), which assesses the attentional abilities of children aged 6 to 12 years, includes the Creature Counting subtest, which can be used to assess cognitive flexibility. In this test, the task is to switch from counting up to the creature to counting down based on explicit visual cues (arrows indicating the counting direction). If the arrow points up, count upwards, but if the arrow points down, count backwards. This test involves flexibly switching from one process to another several times during the test.
Another battery that includes possible flexibility assessments is the developmental neuropsychological assessment, second edition (NEPSY II) (Korkman et al. 2012), intended for children aged 5 to 16 years and 11 months. This battery includes the drawing fluency subtest (also usable for children aged 5 to 16 years and 11 months), in which the child is asked to connect dots in different ways by drawing lines in a limited time. Flexibility is assessed here by the child’s ability to produce different “drawings” for each item and to produce as many as possible within the time limit. As the name implies, this task is also often not considered a flexibility task, but a fluency task.
A second subtest of the NEPSY II could be related to a measure of flexibility: it is the categorization subtest that can be used for children aged 7 to 16 years and 11 months. In this subtest, the child must produce categories to sort cards showing pictures that can be grouped in different ways. For example, the cards show animals of different sizes (large versus small), on different colored backgrounds (blue versus yellow), etc. The child is given an initial categorization by the adult and is then asked to produce others. This subtest can be used to assess cognitive flexibility, as it involves producing several different sorting actions for the same material.
We can also mention a verbal fluency test that can be used to measure flexibility (spontaneous flexibility in particular): the switching part of the verbal fluency test of the Delis-Kaplan Executive Function System (D-KEFS) (Delis et al. 2001). This battery can assess the executive functions of participants aged 8 to 89. One of the subtests can also be used as a measure of flexibility: the switching part of verbal fluency. After the fluency part, where the person has to give as many words as possible on the basis of a semantic or phonological primer, the person is asked to alternate the propositions between two different semantic categories.
These four subtests could therefore all be considered as assessing, or at least partly involving, cognitive flexibility, but none of the four are explicitly described as such, and to our knowledge, there is no cognitive or executive test battery that includes an assessment of cognitive flexibility named as such.
1.3.1.1.3. More playful tasks
Whether in practice or in research, we may wish to use more playful situations to assess flexibility, depending on the age or specificity of the participants. The following two situations, for example, can be used for this purpose.
The innovation paradigm consists of asking the child to draw an object that does not exist (Karmiloff-Smith 1990). The child must first draw objects that really exist (house, man, animal) and then draw these same objects, but also those that do not exist in our world (Picard and Vinter 2005). Young children (4 to 6 years) make intracategorical changes, that is, they only change the size or shape of the object itself, without introducing intercategorical changes. These changes appear later (8 to 10 years) and correspond to the introduction of an element of one category (the wings of a bird for example) on a drawing of another category (a house).
Another fun way to assess flexibility in young children, for example, is to use a drawing of a character starting with the foot (Baldy 2010) to assess the possibility of switching to another procedure in a flexible way. This involves slowing down the routine of drawing a man, which usually always starts with the head, by requiring the child to start the drawing with one of the man’s feet.
Table 1.1 summarizes the examples of direct measurement flexibility tests presented in this chapter. The target population (children or adults) is specified, as well as the ages, if necessary, and the presence of a norm is indicated in brackets when available. The last column shows the type of measurement proposed: first, if it is a question of reactive flexibility, that is, in response to an instruction or cue, or a change in the characteristics of the stimuli, or spontaneous flexibility, the situation proposed induces a certain amount of flexibility, but the changes are initiated by the individual themselves. Then, it details if the change is requested at each trial (item by item) or by series of items (by block), or if the procedure corresponds to task switching.
Table 1.1.Examples of flexibility tasks in direct measurement
Authors
Population
Type of measurement
Trail Making Test
Reitan and Wolfson (1993)
Adults
Reactive Item by item
Trail Making Test for preschoolers
Espy and Cwik (2004)
Preschoolers
Reactive Item by item
Color Trail Test
D’Elia et al. (1996)
Adults
Reactive Item by item
Children’s Color Trail Test
Williams et al. (1995)
Children aged 8 to 16 years old
Reactive Item by item
Plus minus
Jersild (1927)
Adults
Reactive Task switching
Wisconsin Card Sorting Test
Grant and Berg (1948)
Adults
Reactive Per block
Brixton Spatial Anticipation Test
Burgess and Shallice (1996)
Adults
Reactive Per block
Brixton Preschool
Lehto and Uusitalo (2006)
Preschoolers
Reactive Per block
Dimensional Change Card Sort
Doebel and Zelazo (2015)
Preschoolers
Reactive Per block
Local Global Task
Miyake et al. (2000)
Adults
Reactive Task switching
Number-letter task
Rogers and Monsell (1995)
Adults
Reactive Task switching
The color-shape task
Miyake and Friedman (2012)
Adults
Reactive Task switching
Verbal fluency
Delis et al. (2001)
8–89 years old (norm)
Spontaneous
The Creature Counting
Manly et al. (2001)
Children aged 6 to 12 years old (norm)
Reactive Per block
Fluidity of drawings
Korkman et al. (2012)
Children aged 5 to 16 years and 11 months (norm)
Spontaneous
Categorization
Korkman et al. (2012)
Children aged 7 to 16 years and 11 months (norm)
Spontaneous
Innovation paradigm
Karmiloff-Smith (1990)
Children
Spontaneous
Drawing of a man starting with the foot
Baldy (2010)
Children
Spontaneous
1.3.1.2. Indirect assessments
Several questionnaires allow for the indirect assessment of cognitive flexibility. One of the first to be proposed was the Cognitive Flexibility Scale (Martin and Ruben 1995). This scale consists of 12 items, to which the participant responds using a five-point Likert scale. Example of an item: “I am willing to work on problems that require a creative solution”.
The next three correspond to three versions of the Behavioral Assessment of Executive Functions Inventory, depending on the population. These three scales were constructed on an ecological basis and propose to evaluate the consequences of executive deficits in daily life, by adapting the situations to the three age groups targeted (preschoolers, children/adolescents, adults).
The BRIEF-A (Behavioral Assessment of Executive Function Inventory; Roth et al. (2005)), adult version, can be used to assess all executive functions, including flexibility. This questionnaire can be used in self or hetero-assessment.
It is composed of 75 questions grouped into nine scales: inhibition, flexibility, emotional control, self-control, initiation, working memory, planning/organization, task control and material organization. This tool was designed from an ecological perspective and allows the identification of executive deficits in adults (aged 18–93 years old) through their consequences in daily life.
Two other versions have been proposed, one for children and another for adolescents: the BRIEF (Behavioral Assessment of Executive Functions Inventory), child and adolescent version calibrated from 5 to 18 years of age (Gioia et al. 2000); the other for preschoolers: the BRIEF-P (Gioia et al. 2003). These two versions are proposed in hetero-assessment.
The BRIEF consists of 86 questions that can be grouped into eight scales: inhibition, flexibility, emotional control, initiation, material organization, working memory, planning/organization and control.
For each of the first two versions (BRIEF and BRIEF-A), two indices – a behavioral regulation index (BRI) and a metacognition index (MCI) – can be calculated, as well as a global executive composite score (ECS).
The BRIEF-P assesses behaviors in the school and/or family context of young preschoolers (aged 2–5 years and 11 months). It is composed of 63 questions (grouped into five scales: inhibition, flexibility, emotional control, working memory, planning/organization). In particular, three indices can be calculated:
1) the inhibitory control index (ICI), which combines inhibition and emotional control;
2) the flexibility index (FI), which combines flexibility and emotional control;
3) the emerging metacognition index (EMI), which combines working memory and planning/organization.
The Cognitive Flexibility Inventory (CFI) (Dennis and Vander Wal 2010) provides a quick measure of cognitive flexibility. It is composed of 20 items in all. It is offered in a self-report format. Three aspects of cognitive flexibility can be measured through the following three subscales:
1) the tendency to perceive difficult situations as controllable;
2) the ability to perceive multiple alternative explanations for life events and human behavior;
3) the ability to generate multiple alternative solutions to difficult situations.
On the basis of observation that cognitive flexibility may be particularly involved in emotion regulation, as a deficit in cognitive flexibility may be observed in mood and anxiety disorders; Gabrys et al. (2018) proposed the Cognitive Control and Flexibility Questionnaire (CCFQ).
This questionnaire was constructed to assess cognitive flexibility in the specific context of stressful situations. The CCFQ is a quick, self-report measure of cognitive flexibility with 18 items, all of which focus on stress management.
Table 1.2 summarizes the examples of indirect measures of flexibility presented in this chapter.
Table 1.2.Examples of indirect measures of flexibility
Authors
Population
Number of items
Cognitive Flexibility Scale
Martin and Rubin (1995)
Adults
12
BRIEF-A: Behavioral Assessment of Executive Function Inventory
Roth et al. (2005)
Adults
75
BRIEF
Gioia et al. (2000)
Children and teenagers (aged 5 to 18 years old)
86
BRIEF-P
Gioia et al. (2003)
Preschoolers (aged 2–5 years old)
63
Cognitive Flexibility Inventory
Dennis and Vander Wal (2010)
Adults
20
Cognitive Control and Flexibility Questionnaire (CCFQ)
Gabrys et al. (2018)
Adults
18
1.3.2. Which measure for which flexibility?
Beyond the fact that no measure can be considered to uniquely and purely assess cognitive flexibility, each chosen measure influences the type of flexibility that is assessed. Researchers and practitioners wishing to use a measure of flexibility should therefore first establish precisely what flexibility they wish to measure, in order to choose their tool accordingly.
In the field of categorization development, for example, as Blaye and Bonthoux (2001) proposed, we consider that two levels of flexibility must be distinguished.
The first, long considered as evidence of flexibility in the use of several categorization modes, rather corresponds to the possibility of multiple pairings for the same object. In a situation of choice of association with a target image (e.g. a dog), children aged 2–3 are able to choose, in turn, a thematic associate (a doghouse) and a taxonomic associate (a frog).
But this first level does not imply a real controlled switch between two modes of categorization, used in a conscious and controlled way by the child. It implies, certainly, a possibility of pluri-representations for the same object, but a weak representation of the categorical relations in play.
In this case, choices could be guided on a case-by-case basis by the stimuli. A more controlled flexible use of categorical relations would correspond to what we call categorical flexibility and could be assessed by a task, as we have proposed (Maintenant and Blaye 2008; Maintenant et al. 2011), involving maintaining the use of one categorization mode over several trials, concerning several different targets, and then switching to the use of another categorization mode over several trials again.
This second level of flexibility would require top-down control and thus more precise representations of categorical relations. This second level would be accessible later. We have been able to show that, when it comes to switching in a controlled way from one mode of categorization to another, it is necessary to wait until 8–9 years of age (Maintenant and Blaye 2008). Moreover, this categorical flexibility would imply sufficient conceptualization of the categorical relations to be used (Maintenant and Pennequin 2016).
Indeed, whether in children or adults, whether the switch is requested on instruction (deductive categorial flexibility) or induced by feedback (inductive categorial flexibility), we have been able to demonstrate that this categorial flexibility requires a sufficient level of representation of the categorization modes and a better conceptualization than during multi-pairing (Maintenant et al. 2013; Maintenant and Pennequin 2016).
Moreover, with Blaye et al. (2007), Maintenant and Blaye (2008), Maintenant et al. (2011), we consider that categorial flexibility has two components: certainly the switching component, allowing us to be flexible in a controlled way according to the demands of the situation, but also the maintenance component, allowing us to not change our functioning or way of thinking in a controlled way, if this proves to be appropriate to the situation.
We can thus ask ourselves what it means to be flexible, to change, in a controlled way, representation, ways of thinking and strategy according to the requirements of the situation. If we subscribe to such a definition, some of the tasks mentioned above might not fall into the category of cognitive flexibility tasks as such.
All of these tasks, of the reaction time type, which only involve switching from one mode of response to another in a few fractions of a second, certainly make it possible to assess a switching cost. But they do not really allow us to assess cognitive flexibility in the sense of our ability to switch, in a controlled way, from one task to another according to the requirements of the situation, and not according to a possible learning of a correspondence between a cue and a task to be performed.
This assessment would require, on the one hand, proposing more elaborate tasks and, on the other hand, making sure that there has been a conceptualization and a maintenance of the use of the first task. Indeed, in order to consider that a person switches in a flexible, controlled way between two tasks, it is necessary to be sure that the first task has been implemented as such by the person. To take an example: if I sleep during the mathematics lesson, it will probably be easier for me to switch to the French lesson than for another student who has fully invested themselves in learning during the mathematics lesson and in doing the exercises.
As we have been able to demonstrate (Maintenant et al. 2013; Maintenant and Pennequin 2016), in the field of categorial flexibility, switching in a controlled manner from one mode of categorization to another involves not only the executive aspects inherent to this activity (flexibility, inhibition), but also the conceptualization of the modes of categorization to be used. The quality of the representation and the level of mastery of the activities, which we must switch between during a flexibility task, are therefore crucial and must be taken into account during an assessment.
As already proposed by Karmiloff-Smith (1992, 1994), cognitive flexibility implies a possibility of representational redescription. Whether it is in the context of an assessment by a task switching situation or in the context of an assessment by categorial flexibility or problem-solving tasks (Clément 2006; Clément and Gavornikova-Baligand 2010), it seems to emerge from these measures of cognitive flexibility that it is necessary to represent the same object or the same situation in different ways. Cognitive flexibility thus seems to imply “re” representing a stimulus, with different levels of possible conceptual representations, from the lowest level, such as learned associations between cues and specific responses (task switching) to higher levels, such as problem-solving situations involving a modification of the conceptualization of a situation.
1.4. Conclusion
Cognitive flexibility is very present in our daily lives, throughout our lives and is lacking in many pathologies, so its measurement appears to be necessary and informative for psychologists and psychological researchers.
The set of measures presented here clearly shows the great diversity that exists concerning these tools for measuring cognitive flexibility. In addition to the reminder of the type of flexibility measured, which may depend largely on the type of tool chosen, we encourage practitioners and researchers to cross-reference information sources and to make this great diversity a strength, allowing for a better approach to the real competence of the person being assessed.
1.5. References
Baldy, R. (2010). Dessine-moi un bonhomme. Dessins d’enfants et développement cognitif. Éditions In Press, Paris.
Benson, J. and Sabbagh, M.A. (2013). Le lien entre les fonctions exécutives et la cognition sociale. In Encyclopédie sur le développement des jeunes enfants [Online]. Available at: http://www.enfant-encyclopedie.com/fonctions-executives/selon-experts/le-lien-entre-les-fonctions-executives-et-la-cognition-sociale.
Blaye, A. and Bonthoux, F. (2001). Thematic and taxonomic relations in preschoolers: The development of flexibility in categorization choices. British Journal of Developmental Psychology, 19, 395–412.
Blaye, A., Bernard-Peyron, V., Paour, J.L., Bonthoux, F. (2006). Categorical flexibility in children: Distinguishing response flexibility from conceptual flexibility; the protracted development of taxonomic representations. European Journal of Developmental Psychology, 3(2), 163–188.
Blaye, A., Chevalier, N., Paour, J.L. (2007). A dog as an animal or a dog as a rescuer; the development of categorical flexibility. Cognition, Brain, and Behavior, 11(4), 791–808.
Burgess, P.W. and Shallice, T. (1996). Response suppression, initiation and strategy use following frontal lobe lesions. Neuropsychologia, 34(4), 263–273.
Cartwright, K.B., Marshall, T.R., Huemer, C.M., Payne, J.B. (2019). Executive function in the classroom: Cognitive flexibility supports reading fluency for typical readers and teacher-identified low-achieving readers. Research in Developmental Disabilities, 88, 42–52.
Clément, E. (2006). Approche de la flexibilité cognitive dans la problématique de la résolution de problème. L’Année psychologique, 106(03), 415.
Clément, E. and Gavornikova-Baligand, Z. (2010). Étude des stratégies d’adultes présentant un retard mental dans la résolution de la Twenty Questions Task. Psychologie Française, 55(1), 25–39.
Colzato, L.S. (2010). DOOM’d to switch: Superior cognitive flexibility in players of first person shooter games. Frontiers in Psychology, 1, 8.
D’Elia, L.F., Satz, P., Uchiyama, C.L., White, T. (1996). Color trails test. Professional manual. Psychological Assessment Resources, Odessa, FL.
Delis, D.C., Kaplan, E., Kramer, J. (2001). Delis Kaplan Executive Function System. The Psychological Corporation, San Antonio, TX.
Dennis, J.P. and Vander Wal, J.S. (2010). The cognitive flexibility inventory: Instrument development and estimates of reliability and validity. Cognitive Therapy and Research, 34(3), 241–253.
Doebel, S. and Zelazo, P.D. (2015). A meta-analysis of the dimensional change card sort: Implications for developmental theories and the measurement of executive function in children. Developmental Review, 38, 241–268.
Eslinger, P.J. and Grattan, L.M. (1993). Frontal lobe and frontal-striatal substrates for different forms of human cognitive flexibility. Neuropsychologia, 31, 17–28.
Espy, K.A. and Cwik, M.F. (2004). The development of a trial making test in young children: The TRAILS-P. Clinical Neuropsychologist, 18(3), 411–422.
Fourneret, P. and Portes, V. (2017). Approche développementale des fonctions exécutives : du bébé à l’adolescence [Online]. Available at: https://www.emconsulte.com/en/article/1099322.
Frye, D., Zelazo, P.D., Palfai, T. (1995). Theory of mind and rule-based reasoning. Cognitive Development, 10(4), 483–527.
Gabrys, R.L., Tabri, N., Anisman, H., Matheson, K. (2018). Cognitive control and flexibility in the context of stress and depressive symptoms: The cognitive control and flexibility questionnaire. Frontiers in Psychology, 9, 2219.
Georgsdottir, A. and Lubart, T. (2003). La flexibilité cognitive et la créativité : une approche développementale, différentielle et expérimentale. Psychologie française, 48(3), 29–40.
Gioia, G.A., Isquith, P.K., Guy, S.C., Kenworthy, L. (2000). BRIEF: Behavior Rating Inventory of Executive Function. Psychological Assessment Resources, PAR-USA, Lutz, FL.
Gioia, G.A., Espy, K.A., Isquith, P.K. (2003). BRIEF-P: Behavior Rating Inventory of Executive Function – Preschool Version. Psychological Assessment Resources, PAR-USA, Lutz, FL.
Grant, D.A. and Berg, E.A. (1948). A behavioral analysis of degree of reinforcement and ease of shifting to new responses in a Weigl-type card-sorting problem. Journal of Experimental Psychology, 38, 404–411.
Hughes, C., Russell, J., Robbins, T.W. (1994). Evidence for executive dysfunction in autism. Neuropsychologia, 32(4), 477–492.
Isquith, P.K., Gioia, G.A., Espy, K.A. (2004). Executive function in preschool children: Examination through everyday behavior. Developmental Neuropsychology, 26, 403–422.
Jersild, A.T. (1927). Mental set and shift. Archives of Psychology, 89.
Karle, J.W., Watter, S., Shedden, J.M. (2010). Task switching in video game players: Benefits of selective attention but not resistance to proactive interference. Acta Psychologica, 134(1), 70–78.
Karmiloff-Smith, A. (1990). Constraints on representational change: Evidence from children’s drawing. Cognition, 34, 57–83.
Karmiloff-Smith, A. (1992). Beyond Modularity: A Developmental Perspective on Cognitive Science. MIT Press, Cambridge.
Karmiloff-Smith, A. (1994). Precis of beyond modularity: A developmental perspective on cognitive science. Behavioral and Brain Sciences, 17, 693–745.
Korkman, M., Kirk, U., Kemp, S. (2012). Bilan neuropsychologique de l’enfant, 2nd edition. Éditions du Centre de Psychologie Appliquée, Paris.
Lange, F., Brückner, C., Knebel, A., Seer, C., Kopp, B. (2018). Executive dysfunction in Parkinson’s disease: A meta-analysis on the Wisconsin Card Sorting Test literature. Neuroscience & Biobehavioral Reviews, 93, 38–56.
Lehto, J.E. and Uusitalo, A.-K. (2006). Rule detection in preschool-aged children. European Journal of Developmental Psychology, 3, 209–221.
Maintenant, C. and Blaye, A. (2008). Développement de la flexibilité catégorielle de 3 à 8 ans : rôle des aspects conceptuels. L’Année psychologique, 108(04), 659.
Maintenant, C. and Pennequin, V. (2016). Développement de la flexibilité catégorielle : rôles respectifs de la conceptualisation de relations et des forces d’association. L’Année psychologique, 116(01), 21–44.
