Social identity is an important social determinant of student outcomes such as mental health and well-being. Currently, no validated social identity measures exist for adolescents in secondary school settings. A new ‘Adolescent Social Identity’ measure was developed by adapting two social identity dimensions from a validated reputation enhancement scale. The Social Identity Measure comprises two scales of 10 items each to measure how adolescents think their peers view them (e.g., reputational status) in terms of their conforming and nonconforming behaviour (Self-perception of Public Self) and how adolescents would ideally like to be viewed (Ideal Public Self) by peers. Exploratory and confirmatory factor analyses were conducted along with assessments of reliability, validity, and measurement invariance. Conforming and Nonconforming subscales for both scales were shown to be reliable, valid, and invariant across age and gender groupings. There were significant but small differences in the latent means for gender.

This research article focuses on the design and validation of a questionnaire to analyse future teachers' perceptions of professional skills through the use of Augmented Reality (AR) in higher education, specifically for students in the field of Educational Sciences. The sample consisted of 575 students of Early Childhood Education, Primary Education and Pedagogy during the academic year (2021/2022). The focus of this study is to authenticate a questionnaire that measures the influence of Augmented Reality (AR) on aspects such as situated learning, motivation, and the necessary instructional preparations for the successful integration of AR within classroom educational encounters. The questionnaire is an online Likert-type scale developed based on three dimensions: situated learning, motivation and training. The data were analysed using the Statistical Package for the Social Sciences (SPSS) version 25 and JASP 0.17.1. The questionnaire met the standards recommended for validation. However, improvements to the instrument are suggested. In conclusion, validation of instruments is necessary to gain a rigorous understanding of the impact of new learning environments.

This study explores the relationship between language competence and intercultural communicative competence (ICC) among English as a Foreign Language (EFL) learners through a mixed-methods approach. A sample of 196 Chinese EFL learners was divided into three proficiency groups (low, intermediate, and high), with data collected through Likert-scale questionnaires and semi-structured interviews involving 16 participants. Quantitative analysis revealed that higher language proficiency is linked to improved overall ICC scores and its specific dimensions. The Kruskal-Wallis H test confirmed significant differences in overall ICC, attitude, and skill across proficiency levels, with attitude showing the strongest effect. Spearman's correlation analysis demonstrated small but significant positive correlations between English proficiency and overall ICC, attitude, and skill. Qualitative findings further enriched the quantitative results, emphasizing the foundational and catalytic role of language competence in enhancing ICC and its dimensions. However, participants acknowledged that language competence alone is insufficient for fully successful intercultural interactions. This study expands Byram’s model by offering detailed insights into the intricate relationship between language competence and various ICC dimensions. The study recommends that to fully cultivate ICC, it is essential to integrate the development of language competence into instructional practices.

Self-report surveys are extensively utilized in educational research to understand students’ perceptions and experiences. However, younger children, particularly those in elementary school, may exhibit a tendency to provide socially desirable responses, potentially compromising the data quality. This study examined the prevalence and impact of socially desirable responses in self-report surveys administered to elementary school students. A total of 1,024 students from grades 4 and 5 in five elementary schools participated in the study. Socially desirable responses were measured using detection items embedded within questionnaires. The findings indicate that (a) more than 20% of elementary school students demonstrated socially desirable responses; (b) female students and those with higher academic achievement were more likely to provide socially desirable responses; (c) socially desirable responses skewed the sample distribution by inflating mean scores and reducing standard deviations; and (d) while internal correlations within scales remained relatively stable, external validity, as reflected in correlations between self-reports and academic performance metrics, was significantly affected after adjusting for socially desirable responses. These results underscore the importance of addressing socially desirable responses when interpreting self-report data from young students. The study concludes with practical recommendations for improving the validity of self-report surveys in educational research.

Educational researchers, as well as researchers in other disciplines, often work with ordinal data, such as Likert item responses and test item scores. Critical questions arise when researchers attempt to implement statistical models to analyse ordinal data, given that many statistical techniques assume the data analysed to be continuous. Could ordinal data be treated as continuous data, that is, assuming the ordinal data to be continuous and then applying statistical techniques as if analysing continuous data? Why and why not? Focusing on structural equation models (SEMs), particularly confirmatory factor analysis (CFA), this article discusses an ongoing debate on the treatment of ordinal data and reports a short review on the practices of conducting and reporting SEMs, in the context of mathematics education research. The author reviewed 70 publications in mathematics education research that reported a study involving SEMs to analyse ordinal data, but less than half discussed how data were treated or guided readers through the analysis; it is therefore harder to repeat such an analysis and evaluate the results. This article invites methodological discussions on SEMs with ordinal variables in the practices of educational research. Subsequently, a standard for reporting SEMs with ordinal data is proposed, followed by an example. This standard contributes to educational research by enabling researchers (self and others) to evaluate SEMs reported. The example demonstrates, using real-life research data, how two different approaches for analysing ordinal data (as continuous or as a product of discretisation from some continuous distributions) can lead to results that disagree.