The Place of Gender Stereotypes in the Network of Cognitive Abilities, Self-Perceived Ability and Intrinsic Value of School in School Children Depending on Sex and Preferences in STEM

Ismatullina, Victoria; Adamovich, Timofey; Zakharov, Ilya; Vasin, Georgy; Voronin, Iván

doi:10.3390/bs12030075

Cited by 4 publications

(2 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Perceived Difficulty of Math (subscale of a questionnaire used in "Gender stereotypes and incremental beliefs about STEM") (Ismatullina et al, 2022). This subscale is used to identify difficulties associated with the study of mathematics reported by adolescents.…”

Section: Instrumentsmentioning

confidence: 99%

The Russian version of the Abbreviated Math Anxiety Scale: psychometric properties in adolescents aged 13–16 years

Marakshina,

Pavlova,

Ismatullina

et al. 2023

Front. Psychol.

Self Cite

View full text Add to dashboard Cite

This study is the first to assess the internal consistency and factor validity of the Abbreviated Math Anxiety Scale (AMAS) in a sample of Russian adolescents as well as gender differences and gender invariance. The study included 4,218 adolescents in grades 7–9 (M = 14.23, SD = 0.92). Internal consistency, measured with Cronbach’s alpha, was high. Analysis of the factor structure revealed the best correspondence of the second-order factor model, which included two scales (learning math anxiety and math evaluation anxiety) and the general scale of math anxiety. There were greater gender differences in the all three scales. Analysis of gender invariance demonstrated that the mathematics anxiety construct was uniform in boys and girls. These findings confirm the reliable psychometric properties and validity of the AMAS, enabling its use in adolescents.

show abstract

Section: Instrumentsmentioning

confidence: 99%

The Russian version of the Abbreviated Math Anxiety Scale: psychometric properties in adolescents aged 13–16 years

Marakshina,

Pavlova,

Ismatullina

et al. 2023

Front. Psychol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In recent years, due to the CP algorithm being able to detect overlapping symptoms that belong to multiple communities, the CP algorithm has been used to investigate psychological networks of depression and anxiety (Blanken et al, 2018;Kaiser, Herzog, Voderholzer, & Brakemeier, 2021), semantic memory (Cosgrove, Kenett, Beaty, & Diaz, 2021), emotions (Lange & Zickfeld, 2021), cognitive ability (Ismatullina, Adamovich, Zakharov, Vasin, & Voronin, 2022), aphasia (Ashaie & Castro, 2021), among others (Martarelli, Bertrams, & Wolff, 2021). However, the performance of the CP algorithm to identify nodes belonging to multiple communities in psychological data has not been evaluated by simulation studies.…”

Section: Performance Of the Cp Algorithm In Psychological Networkmentioning

confidence: 99%

Comparing the Clique Percolation with other overlapping community detection algorithms in psychological networks: A Monte Carlo simulation study

Santiago¹,

Soares²,

Quintero³

et al. 2022

Preprint

View full text Add to dashboard Cite

In psychological networks, a crucial feature is the identification of network communities through community detection algorithms. One limitation of the most frequently used community detection algorithms (e.g. Walktrap algorithm) in psychological networks is that they can only assign one node per community, without being able to identify overlapping symptoms. The clique percolation (CP) is a promising algorithm to identify overlapping symptoms in psychological networks. However, there have been no studies that evaluate the performance of the CP algorithm in psychological networks. The current paper aims to assess the performance of the CP algorithm to: (1) identify the correct number of latent factors (i.e. correct number of communities); and (2) identify the observed variables with substantive cross-loadings (i.e. overlapping symptoms). For this, we carried out simulations under 108 conditions (2x2x3x3x3): (1) number of factors (2 and 4); (2) number of observed variables per factor (4 and 8); (3) factor correlations (0.0, 0.5, and 0.7); (4) proportion of observed variables with cross loadings (0.0%, 12.5% and 25.0%); and (5) sample size (300, 500 and 1000). Performance was evaluated through the Omega index, Mean Bias Error (MBE), Mean Absolute Error (MAE), Sensitivity, Specificity and mean number of isolated nodes. The simulations indicated that the CP algorithm with fuzzy modularity for signed weighted networks (CPMod) had the best performance across almost all conditions. Based on our findings, the CPMod is the recommended option to identify communities with overlapping symptoms in psychological networks.

show abstract

Psychometric properties of abbreviated math anxiety scale in Russian high schoolers

Marakshina,

Pavlova,

Ismatullina

et al. 2024

Acta biomedica scientifica

Self Cite

View full text Add to dashboard Cite

Background. Math anxiety is a state of fear and anxiety that an individual experiences when interacting with mathematical problems. Currently, there is a lack of questionnaires to measure mathematical anxiety for Russian-speaking schoolchildren.The aim. The study analyzed the factor structure and psychometric properties of the Abbreviated Math Anxiety Scale (AMAS).Materials and methods. The study involved 1,198 schoolchildren in grades 10–11. The psychometric properties of the AMAS were analyzed.Results. AMAS demonstrated bifactor structure: subscales of Learning Math Anxiety (LMA) and Math Evaluation Anxiety (MEA) and general scale of Math Anxiety. The bifactor model demonstrated the best fit indices. Analysis confirmed reliable internal consistency (Cronbach’s alphas for LMA = 0.82, MEA = 0.75, total AMAS = 0.95). External validity of AMAS has been confirmed. LMA showed lower scores than MEA. The distribution of scores on the general AMAS scale was shifted to low values. Girls showed higher scores on all scales of the questionnaire. The analysis also confirmed measurement invariance for both boys and girls.Conclusion. Based on the analysis, we can conclude that the AMAS is a valid tool for assessing mathematical anxiety in high school students.

show abstract

The Place of Gender Stereotypes in the Network of Cognitive Abilities, Self-Perceived Ability and Intrinsic Value of School in School Children Depending on Sex and Preferences in STEM

Cited by 4 publications

References 84 publications

The Russian version of the Abbreviated Math Anxiety Scale: psychometric properties in adolescents aged 13–16 years

The Russian version of the Abbreviated Math Anxiety Scale: psychometric properties in adolescents aged 13–16 years

Comparing the Clique Percolation with other overlapping community detection algorithms in psychological networks: A Monte Carlo simulation study

Psychometric properties of abbreviated math anxiety scale in Russian high schoolers

Contact Info

Product

Resources

About