Likert-type rating scales are still the most widely used method when measuring psychoeducational constructs. The present study investigates a long-standing issue of identifying the optimal number of response categories. A special emphasis is given to categorical data, which were generated by the Item Response Theory (IRT) Graded-Response Modeling (GRM). Along with number of categories (from 2 to 6), two scale characteristics of scale length (n = 5, 10, and 20 items) and item discrimination (high/medium/low) were examined. Results of this study show that there was virtually no difference in psychometric properties of the scales using 4, 5, or 6 categories. Most deteriorating change was observed when the number of response categories reduced from 3 to 2 points in all six psychometric measures. Small moderating effects by scale length and item discrimination seem to be present, that is, a slightly larger impact on the psychometric properties by changing the number of response categories in a shorter and/or highly discriminating scale. This study concludes with the suggestion that a caution should be made if a scale has only 2 response categories but that limitation may be overcome by manipulating other scale features, namely, scale length or item discrimination.

The current study presents a systematic review of teachers’ data literacy, arising from a synthesis of 83 empirical studies published between 1990 to 2021. Our review identified 95 distinct indicators across five dimensions: (a) knowledge about data, (b) skills in using data, (c) dispositions towards data use, (d) data application for various purposes, and (e) data-related behaviors. Our findings indicate that teachers' data literacy goes beyond addressing the needs of supporting student learning and includes elements such as teacher reflection, collaboration, communication, and participation in professional development. Considering these findings, future policies should acknowledge the significance of teacher dispositions and behaviors in relation to data, recognizing that they are as important as knowledge and skills acquisition. Additionally, prioritizing the provision of system-level support to foster teacher collaboration within in-school professional development programs may prove useful in enhancing teachers’ data literacy.

The present study examined the globally relevant predictors of adolescents’ subjective well-being (SWB) using data from the Programme for International Student Assessment (PISA) 2015 Student Questionnaire. Guided by the social-cognitive-behavior model (Suldo et al., 2008) and self-determination theory (Ryan & Deci, 2000), nine variables were selected and subjected to a statistical procedure of decision tree modeling (DTM). Our results showed that parent and peer support were the most salient predictors of adolescents’ SWB across all eight world regions under investigation, followed by anxiety and gender. However, we also noted some variations in the relative importance of parent and peer support and multiple pathways that lead to SWB. The study concludes with practical implications.

This study aims to identify which socio-economic status (SES) variables have the best predictive validity for academic achievement, based on the international data sets of the Programme for International Student Assessment (PISA) in 2012, 2009, 2006, and 2003. From among 10 SES measures, two composite variables - Index of economic, social and cultural status (ESCS) and Home possessions (HOMEPOS) - showed superior predictive power for student achievement. Their pan-cultural correlations with the PISA 2012 mathematics achievement were r = .40 and r = .36, respectively. Parental occupation status (r = .33) outperformed all other single measures of SES, including parental education (r = .29). Only two SES variables (i.e., family wealth and home possessions) showed non-linear relationships with academic achievement. We conclude with practical implications and recommendations for using SES measures as predictors of student achievement in educational research and point to the importance of a theoretical alignment between SES measures and particular issues to be addressed.

We investigated psychological dimensions of academic interest among undergraduate students (N = 325) using a global academic interest scale. The scale was administered together with measures of academic performance, educational aspiration, career planning, goal setting, life satisfaction, attitudes towards leisure, personality and value. Exploratory factor analyses revealed four dimensions of academic interest: passion for learning, confidence in the future, career aspiration and self-expression. All four dimensions were significantly related to career planning, goal setting and life satisfaction. On the other hand, specific pairings of significant relationships were found between different dimensions of academic interest and personality and value, suggesting that students with different personalities and different sets of values are likely to appreciate and respond to different aspects of academic interest. We conclude with implications for research on academic interest development across a more diverse range of age groups.