1
Measures 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
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