Le coaching individuel, source de réussite (French Edition)

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I will therefore be more interested in the form of the user pool than in its size. Second, to bring to light the conditions in which families are likely to use paid private tutoring, my unit of analysis will be not the student consumer but the household that student belongs to. Lastly, to ensure explanatory consistency and because families are most likely to turn to private tutoring for children in secondary school, I concentrate on households whose tutored child is at that stage in his or her formal schooling.

In the first section I present a working definition of private tutoring that situates it within two nesting sets: The second section describes the family environment in which paid private tutoring is used. The third identifies and focuses on each of what seem highly salient features of demand for this form of support. Comparing the two scales of analysis brings to light several relevant ways of analyzing the results, approaches which I then discuss at the end of the article.

This definition or construction of shadow education—the term is not limited by definition to paid tutoring but encompasses all practices with a perceived potential for improving scholastic performance—explains several family objectives in hiring private tutors as well as the types of tutors hired and support content sought. It may be said to be based on two broad hypotheses: The first of these, i. Second, at the international level, families are more likely to turn to shadow education when their children are having difficulty in formal schooling than to use it as part of a strategy for attaining educational excellence.

Baker and Le Tendre substantiate this interpretation with the observation that shadow education is more frequently used for students perceived to be having scholastic difficulties than for good or excellent students, contrary to what Japanese data alone indicate.

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The second general hypothesis of the above description and model is that shadow education is directly dependent on the formal educational system. According to this functionalist-type reasoning, the use of paid private tutoring, even if not necessarily part of an excellence strategy, develops in response to the academic requirements of formal schooling. Use of paid private scholastic support is sometimes thought of as an indicator in research attempting to understand and compare schooling systems Bray , If we leave aside the question of whether the hypothetical dys functioning of a given schooling system is what induces parents to turn to the private tutoring market—a question that far exceeds the scope of this article—the point becomes to understand whether, and if so to what degree, one particular type of shadow education—paid private tutoring—resembles the other types of support, which may be divided into two sets: That dimension is often cited to indicate access cost Marimuthu et al.

With all these points in mind, let me define private tutoring as extra, optional classes furnished to a user household in exchange for payment in the framework of a business relationship, by a person from outside the household to a household member enrolled in a formal schooling system and in a discipline taught in that system. While the definition just presented invites us to rank private tutoring with other types of shadow education, it also presupposes having a clear idea of which families constitute demand for private tutoring and how they come to make that choice.

For this we need to formulate two intrinsically related questions: In a lecture he delivered at the University of Tokyo Todai , Bourdieu indirectly suggested the absolute and relative weights of cultural capital in explaining why some families use juku and yobiko: This unequivocal assertion is based on the Bourdieusian hypothesis that the social reproduction strategies of families with a relatively high level of economic capital are based only partially on acquiring educational degrees, in contrast to strategies of families with a high level of cultural capital.

A second set finds active involvement of family members and activation of the cultural capital potentially present within the family to be decisive factors. Disparities here may well be considerable, and if we consider the literature it seems clear that merely indicating amount of time spent is not much help. This means we have to take into account not only parental help but the help a child may find from other sources: Household configuration provides information on the pool of people to which a child may turn. The understanding is that parents turn to private tutoring businesses to compensate for their own reduced availability.

The data used in this article allow for testing the hypothesis that household configuration is related to type s of scholastic support a household uses. But intensive parenting also encompasses a particular attitude when it comes to creating and sustaining an environment favorable to strong scholastic performance, an environment in which extracurricular activities Lareau are highly valued along with out-of-school learning materials such as summer vacation workbooks and interactive educational software Scanlon and Buckingham as well as homeschooling Aurini and Davies This reinforces the lesson we learned from examining the shadow education concept: Apprehending these two relations is a necessary step if we want to understand the scholastic and family environment features implicated in demand for private tutoring.

This construction is effective in revealing oppositions between households using different types of shadow education. Child A was defined as the child whose date of birth falls in or closest to the month of October if several children were born the same month, the child whose first name comes first alphabetically was designated child A.

This last questionnaire was filled out by a household member of at least 15 years of age randomly selected using the same criterion as for child A. More prosaically, it may point to the fact that a young respondent would not know what to answer. Given how vague this item is, households that did not answer the question were kept in the sample but are given special treatment in the analysis, as explained below.

Though it is certainly useful to isolate demand for private tutoring using logistic regression in which case it is approached as the outcome of a combination of factors , doing so may also obscure the fact that this demand is part of an environment that also produces it.

This allows for extrapolating differences among support-receiving students since all households included in the analysis use at least one form of external support. Size of residence locale pop. This space is structured by two principles: Moving from left to right, that axis divides households with strong short-term and long-term ambitions for their child from those with more limited ambitions who also see no real purpose in meeting with teachers. The second principle structuring the space of education-related practices and attitudes—i. As Glasman and Collanges observed, private tutoring, like free scholastic help and despite all the differences between the two, represents an externalizing of support to the detriment of possible support from extended family and friends.

Distance between the two types of shadow education does therefore help explain variance within the sample but it is a secondary principle. Moving back and forth this way shows, among other things, that the opposition between those response categories, though secondary in the space sketched out here, proves robust when the other factors are eliminated.

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The behavior of households whose head is in a liberal profession or a teacher, manager, or head-of-business—a set unlikely to use free scholastic support while heavily consuming private tutoring—is radically opposed to the behavior of households whose head is a manual worker and who therefore belongs to a set characterized by heavy use of free scholastic support and low consumption of private tutoring. Whatever the tool see Tables 5 and 6 and Figure 2 , the two types of capital are clearly mimetic. The MCA analysis also shows the two to be intertwined. The first axis, which I have interpreted as an indicator of distance from the set of French norms around schooling as reflected by household practices and attitudes and which also distinguishes between private tutoring and free support, continuously ranks households by how much of these two types of capital they possess.

Because of its contribution in defining the first axis, private tutoring may be said to rank households by both economic and scholastic capital levels. Gaps on the first axis are wide while on the second they are minimal and even insignificant, with the exception of those between response category extremes. While distance from the set of French norms around schooling distinguishes those with more from those with less scholastic and economic capital, the choice between delegating the work of helping child A to family and friends i.

As noted above, the question of scholastic help is frequently understood in terms of household configuration factors, the main ones being single parenthood and two-worker households. But there is little resonance between this non-scientific postulate and the data used here. First, single-parent households do not on average use private tutoring any more than dual-parent households Table 7. Likewise, households where both parents work do not buy more private tutoring than households where one or no parent works Table 8.

However, these are only averages, and households in precarious economic or employment situations that feel they do not have sufficient material resources to offer their children private tutoring may indeed be more likely to be single-parent ones. At the high-income end where most private tutoring is consumed there are too few single-parent or single-income households to be able to draw any conclusion at all having two incomes—which statistically implies the presence of two parents—considerably increases the likelihood that household total income is high.

However, as we shall see, logistic regression sheds some light on the impact of single parenthood. Another observation that undermines the hypotheses put forward by private tutoring franchises is that volume of help from parents tells us little about scholastic support use rates Table 9. In fact, the distribution of this variable in the plane Figure 3 can in no way be said to indicate an increase or decrease in tutoring consumption with amount of time parent spends with child-student given how distant these semantically similar response options are, and the converse is also true.

This can perhaps be explained by how imprecise the variable is: But there is some connection between household configuration and private tutoring use. Here two salient features appear: Three competing or complementary hypotheses can be formulated to interpret these results.

The first is tutoring as default option: But this does not explain the fact that there is considerably less variation within the sample for use of free scholastic support from It is difficult to distinguish empirically between the last two hypotheses given how little data are available for example, we do not have total household spending on schooling. Also, they account for one and the same fact, which can now be tested: With other parameters controlled for, do parents of an only-child behave in a particular way? Lastly, use of private tutoring rises with size of residence locale Table 11 , in contrast to the two other types of scholastic support studied here.

But the rise is ambiguous. On the one hand, it could be an effect of supply: On the other hand, this specificity may reflect the singularity of urban populations, above all Paris, in which case it would simply reiterate the preceding point. For though MCA is a strong tool for bringing to light affinities between a considerable number of response categories, it is not as helpful when we try, as I have been gradually doing here, to apprehend one set of response categories, even when the space is explicitly constructed to emphasize one or several variables.

This first phase allows for describing the environment to which the various shadow education practices belong and within which they become differentiated from each other. In order to better understand what in this environment may be connected first and foremost to the move to use private tutoring, I now restrict the field of observation to that practice alone.

This is not without its dangers, the main one being that it will conceal the skein of practices that tutoring is part of. But it will give us a more detailed picture of that feature and help bring to light features of family economy that may induce demand for private tutoring.

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To shed new light on the questions raised in the introduction, we can now turn to a binomial logistic regression in which the dependent variable is private tutoring use, taking into account all middle school and high school students in the sample, i. Two points should be made about how regression is used here. Second, the point is to bring to light partial correlations.

Raccourcis

This means not making any assumptions at this point on the meaning of the relations examined. However, my interpretations of model results will lead to a discussion of possible causal relations. Next come four household variables that seem highly dependent on private tutoring use given the cross-tabulations presented in the preceding section: The last two variables—help from other family or friends, free scholastic support—introduced together and with other maintained variables controlled for, inform us on the relation between them and private tutoring use.

This test leads to keeping only variables whose contribution is significant at the 0. The thirteen consecutive models thus generated are presented in Appendix B, showing the partial correlation between private tutoring and each variable at the time it was introduced and in the following stages for all maintained variables, thereby presenting the entire procedure, which is just as important to my analysis as the final model, if not more so.

Table 12 presents the final model, i. The conclusions thus reached point up the salient features of the population that uses private tutoring in France.

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But this hypothesis on the primacy of scholastic concerns is only partially confirmed: The scholastic goals variables seem fairly irrelevant in explaining private tutoring use. The impact of long-term scholastic ambitions is partly social in that ambitions increase with volume of economic and scholastic capital and partly scholastic the further along the student is in the schooling process, the more his parents expect of him , and this seems a key to correctly understanding private tutoring use: Likewise, an explanation in terms of short-term competitiveness is relevant only compared to other types of support as may be seen in the interpretation of Axis 1 of the MCA , not in absolute terms.

Moreover, its effect is ambiguous. While it does allow for concluding that the scholastic capital differential is not what induces private tutoring use and that consequently private tutoring use is not part of a transmission process reserved for households with little economic capital, it does not allow for concluding that private tutoring is a strategy reserved for households with relatively high economic capital.

Instead, the regression shows that economic capital is a stronger discriminating principle than scholastic capital, regardless of whether households possess the latter or not. As observed elsewhere for France Olier and Flipo , high income is the first explanatory factor for use of personal and home services because such services remain costly despite the various French tax deduction arrangements Devetter, Jany-Catrice and Ribault At the level of the sample and with other parameters controlled for i.

Another point brought to light by the regression is already suggested by simple rate comparison Table 4: This was already noted in connection with the ellipses Appendix 1, Figure A2: Lastly, a main feature of demand for private tutoring is that material resource availability complements perception of a need and makes it possible to meet it. When we look at households possessing the most of this type of capital we discover what appears a quantitative leap.

There are two points here: And while the available information does not allow us to choose between the hypothesis that amount of available resources is higher in only-child households than in households with more than one child and the hypothesis that only-child families have their own educational style, of which private tutoring use is a manifestation, the considerable impact of income seems to argue in favor of the first hypothesis. If the latter augurs the development of a self-service economy where households turn to the market to procure the goods needed to get services performed within the home, then private tutoring seems, on the contrary, an indication of an economy in which services are outsourced outside the home.

The absence of any apparent relation between private tutoring use and parental assistance, together with the non-substitution of private tutoring for other types of support, all converge toward this conclusion. Performance 4,31a 4,34a 4,51b 9. Implication affective 4,97a 5,51b 6,00c ? Parce que ce que je fais dans ce travail a beaucoup de sens pour moi. Parce que, autrement, je me sentirais coupable.

Journal of Educational Psychology, , , Mediating and moderating roles of motivation, The International Journal of Human Resource Management , a, 17 , Journal of Research in Personality , , 42 , Journal of Sports Science , , 21 , Academic Press, , p. English Motivational profiles and work adjustment: A cluster analysis showed three motivational profiles which were linked in different ways to the organizational variables studied.

The most self-determined motivational profile was characterized by high levels of autonomous motivation, moderate levels of controlled motivation and low-levels of amotivation. This profile was generally associated with more positive consequences than the other two profiles. Overall, these findings are in accordance with the tenets of self-determination theory Deci and Ryan, Keywords motivation work cluster analysis self-determination theory. Profils motivationnels et ajustement au travail:

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