Validation of the Educational and Learning Capital Questionnaire (QELC) on the Mexican population
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Psychological Test and Assessment Modeling, Volume 63, 2021 (2), 227-238 227
Validation of the Educational and
Learning Capital Questionnaire
(QELC) on the Mexican population
_____________________________________________________________
Grecia Emilia Ortiz Coronela, María de los Dolores Valadez Sierraa, María
Elena Rivera Herediab, María de Lourdes Vargas Garduñob, Óscar Ulises
Reynoso Gonzáleza, Jaime Fuentes Balderramac
a
University of Guadalajara
b
Michoacana University of San Nicolas of Hidalgo
c
University of Texas
Abstract:
The Actiotope Model of giftedness is a systemic model with a focus on actions directed to-
wards objectives of ability development. As such, the development of talents and extraordinary
achievements is considered an intelligent adaptation to environmental and personal stimuli.
The Questionnaire of Educational and Learning Capital (QELC) may allow for empirical evi-
dence of successful adaptation of an actiotope. Thus, the purpose of this study was to examine
the psychometric properties of The Questionnaire of Educational and Learning Capital in the
Mexican population. A total of 374 gifted Mexican elementary school students participated
(X̅ =11.18 age, S.D. 1.36). We calculated its internal consistency and performed confirmatory fac-
tor analysis. The results show that the original factor structure presents absolute fit, and low
levels of error. Additionally, we observed adequate values of extracted variance (0.5228 Validation of the Educational and Learning Capital Questionnaire (QELC)
Validation of the Educational and la Flor, 2016). The problems that the twen-
learning Capital Questionnaire ty-first century society needs to solve re-
(QELC) on the Mexican population garding people with high capacities and tal-
ents go beyond the intellectual coefficient
The Mexican education system is con- or cognitive capacity. A way to approach
sidered one of the largest in the world. It is how we should identify these individuals
composed of preschool, elementary school is by asking what challenges the world en-
and middle school. In its three levels, pre- counters at a given point in time. In other
school education focuses on children three words, to really understand the perfor-
to five years old, elementary education mance of people with high capacities, it is
incorporates children six to twelve years necessary to understand the resources that
old and consists of six grades, and middle can be used according to the demands pre-
school education teaches three grades to sented by their surroundings (Covarrubias,
young men and women 13 to 15 years of age. 2018; Sternberg, 2017).
Of the total student body that attends basic Ritchotte (2013) states that for decades
education levels (elementary and middle researchers have studied high capacities in
school), it is estimated that ten percent of an effort too help gifted students reach their
the students have high capacities. Despite maximum capacity and prevent potentially
the fact that attention towards these stu- devastating consequences such as school
dents has been proposed, it has not been desertion. Thus, it is important to have
carried out in all of the schools in the coun- models that explain and identify individu-
try and many students frequently go unno- als with high capacities that allows for the
ticed by the usual identification processes comprehension of their resources and fa-
(Secretary of Public Education [SEP], 2006, vors efficient attention for this population.
2017, 2019). Nowadays there is a diversity of concepts
Although there is an intervention propos- and explicative models (performance-based
al, Educational Attention for Students with models, sociocultural orientation models,
Outstanding Capacities by the Secretary of cognitive models, and capability-based
Public Education of Mexico and there is a models). Each one studies a series of spe-
clearly stated processes for identification cific characteristics, which makes identifi-
and intervention, it is important to have cation confusing and ambiguous. None of
other instruments that allow for the con- these explicative models of high capacities
sideration of the personal and social factors is able to encompass, with all of its inter-
associated with an individual. After all, it is actions, a definition, study method and an
very important that education for the stu- education proposal that corresponds to all
dents with the greatest capacities reaches of the realities of society (Ziegler, Vialle, &
the entire student body. Wimmer, 2013).
Students that are identified as possessing In the last decade different research-
high capacities have academic, social and ers such as Renzulli, Gagné, Tannenbaum,
emotional experiences that are related to Mönks and Gardner have contributed to the
their individual resources and their envi- understanding of gifted individuals through
ronment. This generates great challenges in the expansion of both the individual and so-
different dimensions (García-Barrera & de cial fields of action. This is the case of theValidation of the Educational and Learning Capital Questionnaire (QELC) 229 actiotope model of giftedness, which aids in capital, and the term endogenous resources the identification of the resources that are with learning capital. partially found in the student (endogenous To offer empirical evidence for the model, resources) and outside of the student (exog- we administered a low-cost instrument that enous resources). This is a systemic model, measures two general factors: Education- which means that all of its elements inter- al Capital and Learning. Each factor con- act (Ziegler & Stoeger, 2017). Actions are tains five subscales (i.e. educational capital: directed towards the development of abili- economic, cultural, social, infrastructure ties. As such the development of talent and and didactic; learning capital: organic, ac- extraordinary achievements is considered tional, telic, episodic and attentional). This an intelligent adaptation to environmen- instrument is called The Questionnaire of tal stimuli (Vladut, Vialle, & Ziegler, 2015; Educational and Learning Capital (QELC) Ziegler et al., 2013). developed by Vladut, Liu, Leana-Taşcilar, The actiotope model of giftedness focus- Vialle, and Ziegler, (2013) and adapted by es on the actions of an individual and its Leana-Taşcılar (2016) for teachers. First evolution. The development of excellence studies demonstrated satisfactory psycho- is understood as a dynamic system adapta- metric qualities across different cultures, tion that intensifies in complexity through demonstrating content and construct va- the interactions with the objective struc- lidity (Vladut et al., 2013; Leana-Taşcılar, ture of a dominion. Thus, with increasing 2016). excellence, the individual will also achieve Furthermore, Vladut, et al. (2015) adapt- greater changes in the objective structure ed the QELC for elementary and middle of self-dominion. The model takes into ac- school students. The results show that the count the co-adaptation and co-evolution reliability of the ten QELC subscales had a of the components of the Actiotope such satisfactory range. However, reliability was as the range of actions and determinants, low for the subscale that measures actional goals, subjective space of action and envi- learning capital (α = 0.62) and telic learn- ronment and the interpretation of these ing capital (α = 0.68). The CFA model fits to components within a network. These are the data when the five forms of educational gifts and talents that are traditionally un- capacity are influenced by a latent variable derstood as attributes of an individual and the remaining five forms of learning (Ziegler, 2005). capacity are influenced by a second latent Ziegler and colleagues (Ziegler & Baker, variable. 2013; Ziegler, Chandler, Vialle, & Stoeger, In Israel, Paz-Baruch (2015) evaluated 2017; Ziegler, Debatin, & Stoeger, 2019) the validity of the QELC with a sample of suggest that the regulation of endogenous 187 elementary school students from Isra- resources is subjected exclusively to the el to examine if the educational and learn- subsystem of the “person”. However, even ing capital of the students was related to though exogenous resources may be used by intelligence and academic achievement. the person, its supply generally depends on The study found correlations between in- other systems (i.e. school, teachers, piers, frastructure, didactic, organic, actional, educational system). They associate exoge- episodic and attentional capacity. No cor- nous resources with the term educational relation was found between general intelli-
230 Validation of the Educational and Learning Capital Questionnaire (QELC)
gence and other QELC subscales. The inter- Instrument
nal consistency results and bifactorial CFA
model confirmed the validity and reliability The Questionnaire of Educational and
of learning and educational capital using Learning Capital (QELC) (Vladut et al.,
the Hebrew version of the QELC. 2013) is a 50 item-long self-report (e.g. I
Based on the validity and confidence know from experience how to learn better),
results obtained by the above-mentioned which is answered with a 6-point Likert-
studies, this research has the objective of type scale, ranging from 1 = “Strongly dis-
understanding the psychometric properties agree” to 6 = “Strongly agree”. The 50 items
of The Questionnaire of Educational and are grouped into 10 subscales divided into
Learning Capacities to validate its use on two factors: Educational (Economic [1, 11,
the Mexican population. 21, 31, 41], Cultural [2, 12, 22, 32, 42], So-
cial [3, 13, 23, 33, 43], Infrastructure [4, 14,
24, 34, 44], and Didactic [5, 15, 25, 35, 45])
Method and Learning (Organic [6, 16, 26, 36, 46],
Actional [7, 17, 27, 37, 47], Telic [8, 18, 28,
Participants 38, 48], Episodic [9, 19, 29, 39, 49] and At-
tentional [10, 20, 30, 40, 50]). The QELC has
A convenience sampling was chosen, due demonstrated construct validity as well as
to the availability for the application of the acceptable internal consistencies (α = .57
instrument, this ex post facto study recruit-Validation of the Educational and Learning Capital Questionnaire (QELC) 231
Analysis Information Criterion) as comparative cri-
teria, where smaller values indicate better
To identify whether the QELC is a valid in- fit (see table 2) (Browner & Crudeck, 1993;
strument for Mexican samples, a Confirma- Byrne, 2001; Littlewood & Bernal, 2011;
tory Factor Analysis (CFA) was carried out. Moral, 2006). Additionally, the Average Vari-
To adapt the QELC from German to Span- ance Extracted (AVE) and the Composite
ish, we used the guidelines proposed by Reliability Index (CRI) were calculated. Val-
Beaton et al., (2000) for the translation and ues of AVE > 0.5 indicate an adequate per-
semantic equivalence of the items. The adap- centage of explained variance and, values of
tation is composed by four phases: translation CRI > 0.7 are sufficient (Hair et al., & Black,
to Spanish, correspondence analysis, cultural 1999). Preliminary analyses were carried
adaptation and empirical adaptation. out in SPSS V.25 and the CFA was performed
Prior to the CFA, frequency distributions in AMOS V.24.
of the items and subscales were reviewed
to assess their normality. Similarly, internal
consistency analyses were carried out us- RESULTS
ing the subscales reported by the authors.
Complementary to analyzing the factorial Analysis of normality and internal
solution of Vladut et al., (2013), we present consistency
the analysis when constraining to a single
factor instead of two, as well as using the 10 Although only seven items presented
subscales as first-order factors and the Ed- non-significant Shapiro-Wilk values, none
ucational and Learning scales as second-or- of the items or subscales presented asym-
der factors. metry or kurtosis values greater than the
Given the absence of negative multivari- cut-off points (|2| and |6| respectively),
ate kurtosis and approximate multivariate which suggests approximately normal dis-
normality, the CFA were carried out using tributions. With the exception of “Econom-
the default Maximum Likelihood estima- ic”, the subscales showed moderate to high
tor and fit was assessed using the following internal consistencies (α=0.79 < 0.86) and
indices: For absolute fit we used the χ² sta- the consistencies of the factors were excel-
tistic, where a non-significant discrepancy lent: Educational (α = 0.94) and Learning (α
value is expected; for close fit we used CFI, = 0.96). Item 31 (i.e. “I think my education is
TLI and GFI, where values above 0.9 indi- very expensive”) had a low total correlation
cate good fit and values above 0.95 indicate with the rest of the items in the “Economic”
excellent fit (Abad et al., 2011; Hair et al., subscale (r = 0.21), which threatened inter-
1999). To evaluate acceptable error values, nal consistency. By eliminating this item,
we used the SRMR and the RMSEA; SRMR the internal consistency reached accept-
values < 0.10 are considered acceptable, able levels (α = 0.59 to α = 0.64). Subsequent
whereas for RMSEA values232 Validation of the Educational and Learning Capital Questionnaire (QELC)
Confirmatory Factor Analysis The original model by Vladut et al., (2013)
demonstrates close fit as well as moderate
The CFA was carried out using the factorial levels of error (see Table 2: Model 1). Mod-
solution reported by Vladut et al., (2013), ification indices do not suggest cross-load-
where five subscales correspond to each ings, all factorial loadings are significant,
of the two factors (Educational and Learn- latent variables present significant varianc-
ing). We complementarily ran an analysis es and the variances explained for the sub-
constraining all subscales to one factor, and scales are high (R² = 0.41 < 0.89) (see figure
another model with second order factors 1). Given the high correlation between both
where each subscale is estimated as first or- factors, another analysis was run linking
der latent factors. the 10 subscales to a single factor but the
chi-squared fit index demonstrated a sig-
Figure 1. Questionnaire of Educational and Learning Capital (QELC) (Vladut et al., 2013). Model 4:
Original factorial solution with two Modification Indices.
Source: Original work based on AMOS outputValidation of the Educational and Learning Capital Questionnaire (QELC) 233 nificantly worse fit when compared to the variate normality posed by the Maximum first model Δχ (1) = 31.62 p 3.84 in both cases), increased equate values of variance extracted (0.5 close fit and decreased residual errors
234 Validation of the Educational and Learning Capital Questionnaire (QELC) Table 3 Fit indices for first-order factors Factor χ² gl p CFI TLI GFI SRMR RMSEA AVE CRI Educational Capital Economic 2.01 2 .365 1.00 1.00 .99 .01 .004 [.000- .103] .37 .67 Cultural 5.30 3 .151 .99 .98 .99 .01 .045 [.000- .107] .51 .77 Social 6.45 3 .091 .99 .98 .99 .01 .056 [.000- .115] .65 .84 Infraestructure 5.46 5 .362 .99 .99 .99 .01 .016 [.000- .075] .68 .85 Didactic 1.56 5 .906 1.00 1.00 .99 .00 .000 [.000- .029] .68 .85 Learning Capital Organic 5.50 5 .357 .99 .99 .99 .01 .000 [.000- .029] .67 .85 Actional 1.72 3 .632 1.00 1.00 .99 .00 .000 [.000- .070] .62 .83 Telic 5.36 3 .147 .99 .98 .99 .01 .046 [.000- .108] .61 .82 Episodic 2.85 4 .582 1.00 1.00 .99 .01 .000 [.000- .067] .68 .85 Atttentional 4.40 3 .221 .99 .99 .99 .01 .000 [.000- .029] .56 .80 Note: AVE=Average Variance 0.65 < 0.97 vs. r = 0.55
Validation of the Educational and Learning Capital Questionnaire (QELC) 235 still insufficient. Efforts are isolated, and on this model, Vladut et al. (2013) devel- previously generated resources and experi- oped a questionnaire that is a quantitative ences are underutilized (Valadez, 2019). In economic measurement instrument that Mexico the identification and evaluation of allows for large-scale surveys on students. these students is frequently expensive due The resulting instrument, the QELC, in- to parents, professors and specialists imple- cludes only 50 items grouped into 10 sub- menting different resources. Identification scales ( five for educational capital and five is through exploratory activities by teachers for learning capital), and was designed as and through products of the children’s ap- transculturally applicable product (Lea- titudes. Meanwhile evaluation is a series of na-Taşcılar, 2016). standardized psycho-pedagogical tests that The objective of this study was to under- include the application of intelligence tests, stand the psychometric properties of the creativity and socialization. QELC instrument to validate the theoretical As was mentioned earlier, there are var- assumptions of the Actiotope Model of Gift- ious models of explanation and giftedness edness in the Mexican population. However, and talent. However, none of them are ca- this study was not without limitations. The pable of encompassing, with all of its inter- sample was collected from seven schools actions, a definition, a study method and an in Guadalajara through non-probabilistic educational proposal, that matches all of methods meaning our results should be the realities of society (Ziegler et al., 2013). interpreted in light of these conditions and However, the Actiotope Model of Gifted- its generalizations should be done with cau- ness is a systemic model with a focus on di- tion. rected actions towards objectives concern- Once the items were adapted from the ing the development of abilities. As such, original scale through the direct translation the development of talents and extraordi- method, we modified the items in the eco- nary achievements is considered an intel- nomic subscale from the education capital ligent adaptation to environmental stimuli with the help of the authors of the question- (Vladut et al., 2015). naire. The changes were requested because Instead of identifying individuals through the perception of insecurity in Mexico re- classic cognitive methods (tests of intelli- garding violence is a public problem that gence coefficients), it analyzes the route of makes the people’s quality of life more vul- entry that learning and excellence will have nerable. In Mexico, more than half (66.1 %) (Leana-Taşcılar, 2016). These resources are of the populations feels insecure in the state partially found in the student (endogenous in where they live. This has stopped people resources) and partly found outside of the from doing everyday activities, which has student (exogenous resources). repercussions on social recreation and re- Ziegler et al. (2017) suggest that the reg- laxation, and inhibits social cohesion, even ulation of endogenous resources is subject generating fear when providing information exclusively to the “person” and that the per- on personal economy ( Jasso, 2013). son can use exogenous resources. Their pro- Afterwards we revised the psychomet- vision generally depends on other systems. ric properties of the instrument through Thus, they associated the term of learning confirmatory factor analysis. We found ev- capital with endogenous resources. Based idence for satisfactory psychometric prop-
236 Validation of the Educational and Learning Capital Questionnaire (QELC)
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238 Validation of the Educational and Learning Capital Questionnaire (QELC) Ziegler, A., Chandler, K., Vialle, W., & Corresponding author: Stoeger, H. (2017). Exogenous and endog- María de los Dolores Valadez Sierra, PhD enous learning resources in the Actiotope University of Guadalajara Model of Giftedness and its significance Sierra Mojada 950 for gifted education. Journal for the Edu- Guadalajara, México cation of the Gifted, 40, 310-333. https:// E-mail: dolores.valadez@academicos.udg.mx doi.org/10.1177/0162353217734376 Ziegler, A., Debatin, T. & Stoeger, H. (2019). Learning resources and talent develop- ment from a systemic point of view. An- nals of the New York Academy of Sciences, 1-13, https://doi.org/10.1111/nyas.14018 Ziegler, A. & Stoeger, H. (2017). Systemic gift- ed education. A theoretical introduction. Gifted Child Quarterly, 61, 183–193. https:// doi.org/10.1177%2F0016986217705713 Ziegler, A., Vialle, W. & Wimmer, B. (2013). The actiotope model of giftedness: A short introduction to some central theo- retical assumptions. In S. N. Phillipson, H. Stoeger & A. Ziegler (Eds.), Exceptionality in East Asia (pp. 1-17). Routledge. Author Note Grecia Emilia Ortiz Coronel, Interinstitution- al PhD in Psychology, University of Guadala- jara; María de los Dolores Valadez Sierra, Applied Psychology Department, University of Guadalajara; María Elena Rivera Here- dia & María de Lourdes Vargas Garduño, Researcher-Professor at Michoacana Univer- sity of San Nicolas of Hidalgo; Óscar Ulises Reynoso González, Research professor at the University of Guadalajara; Jaime Fuentes Balderrama, Research Associate Steve Hicks School of Social Work University of Texas at Austin. The results of this research are part of the doc- toral thesis of Grecia Emilia Ortiz Coronel, carried out with the support of the Mexican National Council of Science and Technology (CONACyT).We have no conflicts of interest to disclose.
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