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In effectiveness literature, voices are rising to embrace learning contents beyond mathematics, science, and language. Meanwhile, international policy documents such as the United Nations 2019 Climate Action Summit Report point at the importance of action for sustainable development for establishing acceptable life conditions for current and future generations. Therefore, a candidate learning outcome for broadening effectiveness research’s scope is action competence in sustainable development (ACiSD), which consists of the relevant knowledge, willingness, capacity expectations, and outcome expectancy regarding actions for sustainable development. In order to initiate adding ACiSD as a learning outcome to effectiveness research, the current study contributed to establishing that formal education plays a part in changes in students’ ACiSD. Firstly, we studied how much variance in ACiSD can be attributed to what happens in classrooms. Secondly, we looked into how class groups’ and early adolescent students’ ACiSD changed after one school year. Following recommendations for rigour in effectiveness research, we performed multilevel analyses on survey data (question one: n = 1398; question two: n = 633). Our evidence showed that 11% of variance in ACiSD was attributable to what happens in classrooms with explained variance in the subconstructs ranging between 7.2 and 14.2%. Furthermore, individual students as well as class groups showed higher ACiSD scores when comparing measurements at beginning and end of one school year. We conclude that the classroom level matters to changes in ACiSD within early adolescents. Further research can now look into how and to which extent teachers’ educational approaches affect these changes.

This mixed-method quasi-experimental study examined whether metaconceptual grammar teaching impacts on (a) students’ L1 grammatical understanding, (b) their ‘blind’ use of grammatical concepts and (c) their preference of using explicit grammatical concepts over everyday concepts in explaining grammatical problems. Previous research, involving single group pre-postintervention designs, found positive effects for metaconceptual interventions on secondary school students’ grammatical reasoning ability, although a negative side effect seemed to be that some students started using grammatical concepts ‘blindly’ (i.e., in an inaccurate way). While there are thus important clues that metaconceptual grammar teaching may lead to increased grammatical understanding, there is a great need for more robust empirical research. The current study, involving 196 Dutch 14-year old pre-university students, is a methodological improvement of previous work, adopting a switching replications design. Bayesian multivariate analyses indicate medium to large effects from the metaconceptual intervention on students’ grammatical understanding. The study found a similar effect of the intervention on students’ ability to use explicit grammatical concepts over everyday concepts in tackling grammatical problems. No evidence for increased ‘blind’ concept use as a negative byproduct of the intervention was found. Additional qualitative analyses of in-intervention tasks provided further evidence for the effectiveness of metaconceptual interventions, and seemed to indicate that cases of blind concept use, rather than being a negative side effect, might actually be part of a gradual process of students’ growing understanding of grammatical (meta)concepts. We discuss these findings in relation to previous work and conclude that linguistic metaconcepts can improve L1 grammatical understanding.

Feedback acceptance and use are often seen as requirements for teacher change after a school inspection. Non-educational research, however, points to the role of feedback recipients’ willingness to use the feedback received as an intermediate phase between their acceptance and use of the feedback. It also postulates the importance of a recipient’s awareness gained from the feedback, cognitive responses and individual characteristics. However, quantitative evidence in school inspection context to support this theory has been non-existent. This study draws on quantitative data collected from 687 teachers in 80 Flemish primary schools that had recently been inspected. By means of structural equation modelling, we build a research model that focuses on the relationship between cognitive responses, teachers’ feedback acceptance, awareness gained from the inspection feedback received, and teachers’ willingness to use inspection feedback. In addition, the relationship between individual teacher characteristics and the different components in the research model were also taken into account. The analysis reveals that teachers’ willingness to use the feedback is predominantly explained by the perceived relevance of the inspection feedback. In addition, we found statistically significant relationships between teachers’ willingness to use inspection feedback and feedback acceptance, and also between teachers’ willingness to use inspection feedback and awareness gained from inspection feedback too.

BackgroundIn recent years, data derived from international large-scale assessments have significantly influenced the discourse surrounding educational equity. However, the use of such data has often neglected the full spectrum of dimensions that equity encompasses, while being limited to exploring the relationship between achievement variations and student background. This approach, however, constrains our understanding of the rich notion.MethodsThis paper aims to contribute to the advancement of current research by advocating for an alternative approach that encompasses all relevant dimensions of equity and examines their impact on both achievement and motivational outcomes. A cluster analysis manifests itself as the designated method to employ, as the concept of equity remains theoretically challenged and the detection of data patterns can serve as a strong step in its multifaceted inquiry. Moreover, this method enables us to incorporate the multidimensional concept in a country-level context.ResultsEmploying data from the Trends in International Mathematics and Science Study at grade four, this paper presents five distinct clusters of educational systems that illustrate diverse equity configurations. Notably, none of the identified clusters consistently scores high or low on all equity dimensions. This suggests that all of the clusters perform inconsistently to different degrees across the dimensions of equity. Furthermore, no single cluster emerges as superior to the others across both outcome measures.ConclusionsThese findings shed light on the intricate interplay between equity, achievement, and motivation within the examined educational systems. The unique configuration of the equity dimensions within each cluster underscores the importance of adopting a nuanced evaluation of equity, which can enhance our understanding of equity patterns.

Longitudinal data is almost always burdened with missing data. However, in educational and psychological research, there is a large discrepancy between methodological suggestions and research practice. The former suggests applying sensitivity analysis in order to the robustness of the results in terms of varying assumptions regarding the mechanism generating the missing data. However, in research practice, participants with missing data are usually discarded by relying on listwise deletion. To help bridge the gap between methodological recommendations and applied research in the educational and psychological domain, this study provides a tutorial example of sensitivity analysis for latent growth analysis. The example data concern students' changes in learning strategies during higher education. One cohort of students in a Belgian university college was asked to complete the Inventory of Learning Styles-Short Version, in three measurement waves. A substantial number of students did not participate on each occasion. Change over time in student learning strategies was assessed using eight missing data techniques, which assume different mechanisms for missingness. The results indicated that, for some learning strategy subscales, growth estimates differed between the models. Guidelines in terms of reporting the results from sensitivity analysis are synthesised and applied to the results from the tutorial example.

The Revised Two-Factor Study Process Questionnaire (R-SPQ-2F) is used to examine students' study approaches in higher education. The questionnaire assumes to measure two factors: a deep and a surface study approach. Analyses into the validity and reliability of the original English R-SPQ-2F yielded positive results. In this study, we examined the degree to which these positive results can also be found for the Dutch version that we developed. By comparing our results with the results of earlier studies in different cultures, we conclude cross-cultural sensitivity is an important point to be borne in mind when using the R-SPQ-2F. Our research supports the validity and reliability of our Dutch version of the R-SPQ-2F.

Among other things, learning to write entails learning how to use complex sentences effectively in discourse. Some research has therefore focused on relating measures of syntactic complexity to text quality. Apart from the fact that the existing research on this topic appears inconclusive, most of it has been conducted in English L1 contexts. This is potentially problematic, since relevant syntactic indices may not be the same across languages. The current study is the first to explore which syntactic features predict text quality in Dutch secondary school students’ argumentative writing. In order to do so, the quality of 125 argumentative essays written by students was rated and the syntactic features of the texts were analyzed. A multilevel regression analysis was then used to investigate which features contribute to text quality. The resulting model (explaining 14.5% of the variance in text quality) shows that the relative number of finite clauses and the ratio between the number of relative clauses and the number of finite clauses positively predict text quality. Discrepancies between our findings and those of previous studies indicate that the relations between syntactic features and text quality may vary based on factors such as language and genre. Additional (cross-linguistic) research is needed to gain a more complete understanding of the relationships between syntactic constructions and text quality and the potential moderating role of language and genre.

The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles--Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain.

Research on learning strategies and learning motivation in different educational contexts has provided valuable insights, but in this field, low-educated adults remain an understudied population. This study addresses this gap by means of a person-oriented approach and seeks to investigate whether quantitatively and qualitatively different learner profiles can be distinguished among low-educated adults in second-chance education (SCE) by relating three key components of learning: learning motivation, regulation and processing strategies. Five hundred twelve adult learners of six SCE-institutions filled in a Learning and Motivation questionnaire. Latent profile analysis showed the presence of motivational profiles differing both in quantity and quality (i.e. good- versus poor-quality and high- versus low-quantity motivational profiles) and regulatory profiles being distinct in the use of regulation strategies (i.e. self-regulated versus unregulated profiles). Mainly quantitatively different processing profiles were found among low-educated adults (i.e. active, moderate, inactive processing profiles). When integrating all three components of learning, analyses identified two more optimal motivational-learning profiles, combining good-quality motivation with a moderately active use of self-regulation and processing strategies (i.e. good-quality motivation – self-regulated – active processing profile and good-quality motivation – moderate profile) and two more suboptimal profiles in which poor-quality or low-quantity motivation was combined with the inactive use of self-regulation and processing strategies (i.e. poor-quality motivation – unregulated – inactive processing profile, low-quantity motivation – unregulated – inactive processing profile). A fifth motivational-learning profile exhibited a pattern of poor-quality motivation combined with a moderately-active use of self- regulation and processing strategies.

When investigating unobservable, complex traits, data collection and aggregation processes can introduce distinctive features to the data such as boundedness, measurement error, clustering, outliers, and heteroscedasticity. Failure to collectively address these features can result in statistical challenges that prevent the investigation of hypotheses regarding these traits. This study aimed to demonstrate the efficacy of the Bayesian beta-proportion generalized linear latent and mixed model (beta-proportion GLLAMM) (Rabe-Hesketh et al., Psychometrika, 69(2), 167–90, 2004a , Journal of Econometrics , 128(2), 301–23, 2004c , 2004b ; Skrondal and Rabe-Hesketh 2004 ) in handling data features when exploring research hypotheses concerning speech intelligibility. To achieve this objective, the study reexamined data from transcriptions of spontaneous speech samples initially collected by Boonen et al. ( Journal of Child Language , 50(1), 78–103, 2023 ). The data were aggregated into entropy scores. The research compared the prediction accuracy of the beta-proportion GLLAMM with the normal linear mixed model (LMM) (Holmes et al., 2019 ) and investigated its capacity to estimate a latent intelligibility from entropy scores. The study also illustrated how hypotheses concerning the impact of speaker-related factors on intelligibility can be explored with the proposed model. The beta-proportion GLLAMM was not free of challenges; its implementation required formulating assumptions about the data-generating process and knowledge of probabilistic programming languages, both central to Bayesian methods. Nevertheless, results indicated the superiority of the model in predicting empirical phenomena over the normal LMM, and its ability to quantify a latent potential intelligibility. Additionally, the proposed model facilitated the exploration of hypotheses concerning speaker-related factors and intelligibility. Ultimately, this research has implications for researchers and data analysts interested in quantitatively measuring intricate, unobservable constructs while accurately predicting the empirical phenomena.