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The Influence of the Gap Between Parental and Their Children’s Expectations on Children’s Academic Attainment

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Abstract

Parents and their children’s expectations on educational achievement have been highlighted in the literature as proper proxy indicators for students’ forthcoming performance. In this research we intend to measure the effect of these indicators accounting for the existence of endogeneity—due to their reciprocal relationship—and also their correlation with unobservable variables conditioning students’ achievement. The aim is to determine the extent to which the potential positive correlation between expectations and children’s educational performance could help to overcome the limiting effect of low socio-economic characteristics of the household on the latter and, consequently, the well-being of children in the medium and long run. Our results show a positive influence of the agreement of parental and children’s expectations on students’ achievement and on the likelihood of children’s enrollment in a particular academic track. In addition, parental expectations have been found to be dependent on family socio-economic background, what supports the persistence of strong barriers to socioeconomic mobility of children. We suggest policy interventions as, e.g., fostering the participation of both parents and children on university and professional orientation in early stages of secondary education, so they could have complete and symmetric information to set their expectations on a realistic basis.

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Notes

  1. We have not included repeaters in our analysis due to the specific characteristics that these students present—like a high likelihood of grade retention and dropping out, as highlighted by many authors, e.g., Carabaña (2013), and thus their lower achievement (Cordero et al. 2013)—what could potentially bias the results of our research. In addition, to the extent that repeater students were also born in 1994 and 1998—respectively, they will be attending at least one course under that of non-repeater students, so repeaters’ achievement in reading and mathematics would not be comparable to that of non-repeaters.

  2. These categories are: fail −2.5–, pass −5–, good −6–, very good −7.5– and excellent −9–.

  3. For the estimations reported in Table 4, the use of students’ scores in reading/mathematics, the variable for the high school track chosen by the students in the course 2010/11 and the variable that indicates coincidences/discordances between students’ and parental expectations contribute to slightly reduce the subsample.

  4. Both parental and students’ expectations are coded according to the translation of the ISCED level of studies that students or parents expect—for students’ highest level of education—to the correspondent number of years of education: not finishing secondary studies (6 years), secondary studies (10 years), middle-level vocational training or high school (12 years), high-level vocational training (14 years) and university studies (16 years).

  5. We have considered that parental expectations are higher or lower than students’ when they show a difference of 1 year or more.

  6. We have considered the categories of repeating, high school track of science and technology, and high school track of social and human sciences. The categories of high school track of arts and vocational cycles have not been used due to their low number of observations.

  7. The income grouping, as stated in the ESOC10-SEN, is a standard commonly employed by the Office for National Statistics and corresponds—approximately—to the quartiles of the income distribution in Spain.

  8. The estimations for parental and students’ expectations presented in Table 2 were replicated by removing the level of studies of fathers or mothers—alternatively. In both cases, the coefficient of semi-private schools for parental expectations turned positive and significant, while its effect on students’ expectations was negative and significant—as in Table 2. These tables are available upon request to the authors.

  9. Relative risk ratios are calculated by the exponentiation of the values of the coefficients in Table 4 (columns 3 and 4).

  10. BOE 10th December 2013, Organic Law 8/2013.

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Acknowledgments

This work was partly supported by the Andalusian Regional Ministry of Innovation, Science and Employment [PAI group SEJ-532 and Excellence Project SEJ-2727]; the Research Plan of the University of Malaga (Capacity Building Programme I+D+i of Universities 2014–2015); the Ministry of Economy and Competitiveness of Spain [Research Project ECO2014-56397-P] and the scholarship FPU2014 04518 of the Spanish Ministry of Education.

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Correspondence to Oscar David Marcenaro-Gutierrez.

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Table 5 Bivariate analysis

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Marcenaro-Gutierrez, O.D., Lopez-Agudo, L.A. The Influence of the Gap Between Parental and Their Children’s Expectations on Children’s Academic Attainment. Child Ind Res 10, 57–80 (2017). https://doi.org/10.1007/s12187-015-9361-z

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