Niki De Bondt is a researcher and PhD student in educational sciences in the Department of Training and Education Sciences of the Faculty of Social Sciences at the University of Antwerp (Belgium). Her research focuses on such topics as Bayesian statistical modeling, the educational relevance of Dąbrowski’s Theory of Positive Disintegration, and giftedness. Master degrees she holds include a Master of Science in Economics from KU Leuven (magna cum laude) and she is a lecturer at Artesis Plantijn University College of Antwerp.
Research indicates that educational stratification may lead to a lower-track school culture of fu... more Research indicates that educational stratification may lead to a lower-track school culture of futility and a less academically-oriented culture among lower-track teachers, leading to both reduced study involvement and lower educational achievement among their students. This study investigated whether an anti-school culture in the lower tracks (in this study, in technical secondary education [TSE; N = 132] in comparison with general secondary education [GSE; N = 356]) has a solid basis that is supported by personal, ontological differences in intelligence and developmental potential (i.e., overexcitability, according to the theory of positive disintegration [TPD]). In addition, this study examined the consistency of these results with differences in mathematical and verbal achievement, the use of cognitive processing and metacognitive regulation strategies, and study motivation, as well as differences in the influence of personal competence indicators on the learning approach, all suggesting contextual, educational influences. A Bayesian analysis was applied to address the problem of a frequentist approach in complex statistical models. This study does not primarily reveal competence differences between both tracks (as indicated by no substantive differences in overexcitability and intelligence between respectively former GSE and TSE students and GSE and TSE boys), but rather substantial differences in verbal and mathematical performance, as well as regulatory/motivational problems among former TSE students, corroborating to some extent the abovementioned consequences of academic differentiation. The results are further elucidated from the perspective of self-determination theory and the TPD.
The aim of this study is to provide – first theoretically and, subsequently, through an empirical... more The aim of this study is to provide – first theoretically and, subsequently, through an empirical analysis – a rationale for including the concept of overexcitability in talent research, beyond the five-factor model personality traits. Moreover, the empirical part of this study makes use of an innovative statistical method to address the problem of a frequentist approach to statistics in complex trait models which are based on personality questionnaire data. This study offers insight into the differential significance of overexcitability in relation to the established personality traits, emphasizing Dabrowski’s dynamic approach to personality and the key contribution of overexcitability in the developmental process. Furthermore, implications for the field of giftedness are discussed.
The aim of this study is to investigate interrelationships between overexcitability and learning ... more The aim of this study is to investigate interrelationships between overexcitability and learning patterns from the perspective of personality development according to Dabrowski’s theory of positive disintegration. To this end, Bayesian structural equation modeling (BSEM) is applied which allows for the simultaneous inclusion in the measurement model of all, approximate zero cross-loadings and residual covariances based on zero-mean, small-variance priors, and represents substantive theory better. Our BSEM analysis with a sample of 516 students in higher education yields positive results regarding the validity of the model, in contrast to a frequentist approach to validation, and reveals that overexcitability – the degree and nature of which is characteristic of the potential for advanced personality development, according to Dabrowski’s theory – is substantially related to the way in which information is processed, as well as to the regulation strategies that are used for this purpose and to study motivation. Overexcitability is able to explain variations in learning patterns to varying degrees, ranging from weakly (3.3% for reproduction-directed learning for the female group) to rather strongly (46.1% for meaning-directed learning for males), with intellectual overexcitability representing the strongest indicator of deep learning. This study further argues for the relevance of including emotion dynamics – taking into account their multilevelness – in the study of the learning process.
The Overexcitability Questionnaire-Two (OEQ-II) measures the degree and nature of overexcitabilit... more The Overexcitability Questionnaire-Two (OEQ-II) measures the degree and nature of overexcitability, which assists in determining the developmental potential of an individual according to Dabrowski's Theory of Positive Disintegration. Previous validation studies using frequentist confirmatory factor analysis, which postulates exact parameter constraints, led to model rejection and a long series of model modifications. Bayesian structural equation modeling (BSEM) allows the application of zero-mean, small-variance priors for cross-loadings, residual covariances, and differences in measurement parameters across groups, better reflecting substantive theory and leading to better model fit and less overestimation of factor correlations. Our BSEM analysis with a sample of 516 students in higher education yields positive results regarding the factorial validity of the OEQ-II. Likewise, applying BSEM-based alignment with approximate measurement invariance, the absence of non-invariant factor loadings and intercepts across gender is supportive of the psychometric quality of the OEQ-II. Compared to males, females scored significantly higher on emotional and sensual overexcitability, and significantly lower on psychomotor overexcitability.
Research indicates that educational stratification may lead to a lower-track school culture of fu... more Research indicates that educational stratification may lead to a lower-track school culture of futility and a less academically-oriented culture among lower-track teachers, leading to both reduced study involvement and lower educational achievement among their students. This study investigated whether an anti-school culture in the lower tracks (in this study, in technical secondary education [TSE; N = 132] in comparison with general secondary education [GSE; N = 356]) has a solid basis that is supported by personal, ontological differences in intelligence and developmental potential (i.e., overexcitability, according to the theory of positive disintegration [TPD]). In addition, this study examined the consistency of these results with differences in mathematical and verbal achievement, the use of cognitive processing and metacognitive regulation strategies, and study motivation, as well as differences in the influence of personal competence indicators on the learning approach, all suggesting contextual, educational influences. A Bayesian analysis was applied to address the problem of a frequentist approach in complex statistical models. This study does not primarily reveal competence differences between both tracks (as indicated by no substantive differences in overexcitability and intelligence between respectively former GSE and TSE students and GSE and TSE boys), but rather substantial differences in verbal and mathematical performance, as well as regulatory/motivational problems among former TSE students, corroborating to some extent the abovementioned consequences of academic differentiation. The results are further elucidated from the perspective of self-determination theory and the TPD.
The aim of this study is to provide – first theoretically and, subsequently, through an empirical... more The aim of this study is to provide – first theoretically and, subsequently, through an empirical analysis – a rationale for including the concept of overexcitability in talent research, beyond the five-factor model personality traits. Moreover, the empirical part of this study makes use of an innovative statistical method to address the problem of a frequentist approach to statistics in complex trait models which are based on personality questionnaire data. This study offers insight into the differential significance of overexcitability in relation to the established personality traits, emphasizing Dabrowski’s dynamic approach to personality and the key contribution of overexcitability in the developmental process. Furthermore, implications for the field of giftedness are discussed.
The aim of this study is to investigate interrelationships between overexcitability and learning ... more The aim of this study is to investigate interrelationships between overexcitability and learning patterns from the perspective of personality development according to Dabrowski’s theory of positive disintegration. To this end, Bayesian structural equation modeling (BSEM) is applied which allows for the simultaneous inclusion in the measurement model of all, approximate zero cross-loadings and residual covariances based on zero-mean, small-variance priors, and represents substantive theory better. Our BSEM analysis with a sample of 516 students in higher education yields positive results regarding the validity of the model, in contrast to a frequentist approach to validation, and reveals that overexcitability – the degree and nature of which is characteristic of the potential for advanced personality development, according to Dabrowski’s theory – is substantially related to the way in which information is processed, as well as to the regulation strategies that are used for this purpose and to study motivation. Overexcitability is able to explain variations in learning patterns to varying degrees, ranging from weakly (3.3% for reproduction-directed learning for the female group) to rather strongly (46.1% for meaning-directed learning for males), with intellectual overexcitability representing the strongest indicator of deep learning. This study further argues for the relevance of including emotion dynamics – taking into account their multilevelness – in the study of the learning process.
The Overexcitability Questionnaire-Two (OEQ-II) measures the degree and nature of overexcitabilit... more The Overexcitability Questionnaire-Two (OEQ-II) measures the degree and nature of overexcitability, which assists in determining the developmental potential of an individual according to Dabrowski's Theory of Positive Disintegration. Previous validation studies using frequentist confirmatory factor analysis, which postulates exact parameter constraints, led to model rejection and a long series of model modifications. Bayesian structural equation modeling (BSEM) allows the application of zero-mean, small-variance priors for cross-loadings, residual covariances, and differences in measurement parameters across groups, better reflecting substantive theory and leading to better model fit and less overestimation of factor correlations. Our BSEM analysis with a sample of 516 students in higher education yields positive results regarding the factorial validity of the OEQ-II. Likewise, applying BSEM-based alignment with approximate measurement invariance, the absence of non-invariant factor loadings and intercepts across gender is supportive of the psychometric quality of the OEQ-II. Compared to males, females scored significantly higher on emotional and sensual overexcitability, and significantly lower on psychomotor overexcitability.
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Papers by Niki De Bondt