Conference Agenda

Self-regulated learning (SRL) is widely regarded as a key competence for successful learning, and its relevance has further increased with the expansion of digital and hybrid learning formats in secondary education. SRL refers to a form of learning in which learners proactively and autonomously regulate their learning process by applying a range of cognitive, metacognitive, and volitional strategies to monitor and guide their progress (Schiefele & Pekrun, 1996).

In contemporary learning settings, students are expected to plan, monitor and adjust their learning in more autonomous ways, including the regulation of their motivation when difficulties arise (Wirth & Leutner, 2008). Despite the inclusion of motivational components in prominent SRL models, research on motivational regulation, particularly in relation to learners' selection of an appropriate motivational strategy in a given situation, remains comparatively underdeveloped (Grunschel et al., 2016; Zhang & Dong, 2022). One possible explanation for this may be the lack of adequate measurement instruments. Many established instruments in this area either record motivational orientations and beliefs or assess the general frequency with which strategies are applied (e.g. MSQL; Pintrich et al., 1991, SRQ-A; Ryan & Connell, 1989). However, these instruments do not provide insight into whether a specific strategy choice is situationally appropriate, that is to say, whether it "fits" the particular learning problem at hand.

From a pedagogical-psychological perspective, this gap points to the importance of conditional strategy knowledge. Conditional knowledge refers to knowing when and why a strategy is useful in a specific context, and it is conceptually distinct from simply knowing what a strategy is (Paris et al., 1983). This distinction is particularly relevant for understanding why students sometimes fail to translate what they have learned about effective learning into actual adaptive regulation during learning (often discussed as a knowledge–action gap; Foerst et al., 2017). While process-near approaches such as SRL microanalysis can address this issue, they are costly and difficult to scale for larger samples (Perels & Dörrenbächer, 2020).

In order to propose a suitable alternative, Perels and Dörrenbächer (2020) developed the Strategy Knowledge Test for Self-Regulated Learning (SKT-SRL), which operationalises conditional knowledge about scenario-based judgments. The theoretical basis of the test is Zimmerman's (2000) cyclical model of self-regulated learning (planning, performance, reflection). The instrument also draws on expectancy-value theory (Wigfield & Eccles, 2000) to assess motivational regulation strategies. Following the recommendations of Engelschalk et al. (2015) and Schwinger et al. (2007), motivational problems are differentiated according to whether they are primarily expectation-related (e.g. doubts about one's own competence) or value-related (e.g. low perceived relevance).

Based on this measurement tool, which was originally designed for university students, an adaptation was made for the target group of secondary school students. Therefore, the case scenarios were transferred to typical situations of self-directed learning in a school context. To make the situational reference more vivid, reduce the amount of text and increase motivation to complete the test, the scenarios were converted into a visual cartoon format. Furthermore, a parallel version of the test was developed to facilitate longitudinal assessments and mitigate potential test-retest or practice effects. This article details the adaptation process and provides an empirical evaluation of the instrument’s construct and convergent validity.

Topic and background

International large-scale assessments such as the Programme for International Student Assessment (PISA) report a sustained decline in reading and numeracy performance across many Western European countries (OECD, 2023). Educational policy responses have mainly focused on curriculum reform, instructional improvement, and teacher professional development. Although these approaches are important, meta-analytic evidence indicates that their average effects are often modest and highly dependent on contextual and learner-related factors (Hattie, 2009). Comparatively little attention has been paid to students’ own perspectives on learning, despite growing evidence that these perspectives are systematically related to learning processes and outcomes. Students’ ideas, beliefs, and mental representations about learning, referred to as learning conceptions, are associated with learning strategies, motivation, and achievement in core academic domains (Peterson et al., 2010; Robbers et al., 2015). Understanding of learning conceptions is therefore particularly relevant during educational transitions, which are a common feature across international education systems.

Conceptual and theoretical framework

Research on learning conceptions originates in phenomenographic studies that identified different ways in which learners understand learning (Säljö, 1979). Early distinctions focused on quantitative, content-related conceptions, emphasizing the acquisition and reproduction of knowledge, and qualitative, process-oriented conceptions, emphasizing understanding and meaning-making (Purdie & Hattie, 2002; Peterson et al., 2010). More recent theoretical developments have extended this framework by incorporating the social and motivational embeddedness of learning. Learning is conceptualized as a cooperative and socially situated process involving interaction and shared regulation with others (Tynjälä, 1997; Vermunt & Donche, 2017). In addition, learning conceptions include motivational aspects, such as beliefs about effort, control, obligation, personal growth, and attributions of success and failure (Pinto et al., 2018). When selecting or developing a questionnaire to measure learning conceptions, it is important to ensure that aspects of how students understand learning as identified in the literature are broadly represented, covering content-related, process-oriented, cooperative, and motivational elements, without assuming predefined dimensions or a fixed structure.

Research gap and rationale

Over the past two decades, several instruments have been developed to assess students’ learning conceptions in primary and secondary education (Klatter et al., 2001; Peterson et al., 2010). Of these instruments, only the questionnaire by Klatter et al. (2001), which is available in Dutch, is directly applicable in the Dutch context. However, both the practical and scientific utility of the questionnaire are limited by two key issues. Although reduced from 100 to 65 items, the questionnaire remains impractically long for 11- and 12-year-old students, increasing the risk of response fatigue. Methodologically, Klatter et al. (2001) divided the questionnaire into three correlated subfactors rather than conducting single factor analyses on the full item set and relied solely on the Kaiser criterion (eigenvalue > 1) to determine factors, which may have led to overfactoring (Goretzko, 2025). These choices raise concerns about the instrument’s validity. As a result, no concise and psychometrically robust Dutch instrument currently exists to assess learning conceptions in secondary education, creating a gap for both educators and researchers. Filling this gap is crucial for advancing educational practice and research.

Research objective

This study aims to psychometrically re-examinate the factorial structure of the original Learning Conceptions Questionnaire (LCQ; Klatter et al., 2001) to create a robust instrument assessing students’ learning conceptions in the first year of secondary education.

Central research question

To what extent can the original item pool of the Learning Conceptions Questionnaire be restructured into a valid, reliable, and robust multidimensional factor model for students in the first year of secondary education, and to what extent is the resulting factor structure theoretically interpretable in relation to established frameworks of learning conceptions in the educational literature?

When addressing psychological constructs and their implications for professional understanding and practice in early childhood education, educational research relies on trustworthy findings and measurement instruments originating from psychological research. In line with the conference theme Knowing and Acting, this paper conceptualises psychometric validation not as a merely technical prerequisite, but as a core epistemic condition under which educational knowledge becomes empirically visible and, consequently, actionable. Tests and questionnaires actively shape knowledge claims about children’s characteristics in educational research and professional discourse; understanding how such instruments function under specific developmental, linguistic, and contextual conditions is therefore central to the generation of robust educational knowledge.

Against this epistemological background, the study builds on the psychological conceptualisation of sensory processing sensitivity (SPS; Aron & Aron, 1997; Greven et al., 2025; Pluess, 2015), commonly discussed in the literature through the notion of highly sensitive children. SPS captures individual differences in responsiveness to physical, social and emotional stimuli and has been empirically linked to children’s socio-emotional functioning and well-being (Lionetti, 2019), central concerns in early childhood education. Research further suggests more pronounced vulnerability under adverse circumstances, alongside greater benefits in supportive environments (Li et al., 2022; Slagt et al., 2018), highlighting the importance of valid, context-sensitive measurement as a prerequisite for meaningful educational knowledge.

As systematic studies of age-appropriate measurement instruments for SPS in preschool-aged children remain rare, empirically grounded knowledge on SPS is still limited. The Highly Sensitive Child Scale – Parent Report (HSC-PR; Pluess et al., 2018), one of the core measures of SPS, was originally designed for school-aged children and requires further systematic validation for children aged 3–6 years across languages and in large-scale samples; in particular, no validation is currently available for the German-language version. Moreover, empirical work has reported item-specific difficulties (Sperati et al., 2022), which may suggest that one original item formulation did not adequately reflect age-specific developmental characteristics of early childhood.

Building on this gap, the present study aims to systematically examine the psychometric properties of the HSC-PR in preschool-aged children. The study draws on a large parent sample of children aged 3–6 years recruited through the vast majority of kindergartens in the Autonomous Province of Bozen/Bolzano (South Tyrol), a multilingual region in Northern Italy. By analysing the German and Italian language versions within a shared regional and cultural context and common institutional frameworks, the study enables a stringent test of cross-language comparability. In multilingual European education systems, comparable and transferable evidence depends on measurement equivalence rather than on translation alone (Putnick & Bornstein, 2016).

The study is guided by three interconnected research questions: (1) To what extent does the HSC-PR demonstrate satisfactory psychometric functioning in preschool-aged children in the German and Italian language versions, with regard to item behaviour, reliability, and factorial structure, and which latent representation of SPS is most appropriate in early childhood? (2) To what extent is the measurement of SPS comparable across the two language versions and key demographic groups (gender and age), as examined through multi-group confirmatory factor analysis and measurement invariance testing within a shared regional and institutional context? (3) To what extent do development-informed item revisions improve the measurement of SPS and its underlying dimensions in preschool-aged children, and what does this imply for epistemic robustness in educational research?

By approaching psychometric validation as an empirical examination of the conditions under which knowledge about children’s sensitivity becomes epistemically accessible and transferable, the paper contributes to international debates on situated educational knowledge, cross-language comparability, and the epistemic responsibilities associated with the use of standardised measurement instruments in early childhood research.

Students’ learning-related agency is receiving increasing attention in scientific literature and in policy debates (see, for example, The OECD Learning Compass 2030, OECD, 2019). In a broader sense, learning-related agency refers to learners’ decision-making in learning situations, including planning, implementing, and evaluating learning (Lipponen & Kumpulainen, 2011; Priestley et al., 2015). In the present study, we draw on the ecological model of agency (Leijen et al., 2024; Priestley et al., 2015), which helps to understand three main dimensions that influence learners’ decision-making related to learning. First, the iterational dimension indicates that decision-making is based on prior experiences. Over time, learners develop learning-related knowledge, attitudes, and skills that begin to influence their subsequent learning-related decisions (see, for example, Lange, 2010; Lauermann et al., 2017). Second, agency is oriented toward the future. The projective dimension reflects students’ short-term and long-term purposes, which guide decision-making toward their future plans. For example, when students have a clear purpose related to learning a particular subject, they are more likely to decide to engage actively in learning that content. By contrast, when students do not understand the relevance of learning certain content or skills, it becomes more difficult for them to engage in learning (see Eccles & Wigfield, 2020). Third, the practical-evaluative dimension indicates students’ capacity to make decisions in specific situations. This decision-making process is guided, on the one hand, by the iterational and projective dimensions and, on the other hand, by the cultural, structural, and material conditions of a particular learning situation. These various learning-related environmental conditions may be perceived as affordances, constraints, or resources, and may therefore either hinder or support learners’ agency. Learning environments that are responsive to students’ perspectives, offer alternatives, and support horizontal relationships and collaboration among students are considered supportive of learners’ agency, whereas rigid rules, hierarchical relationships, and an orientation toward competition are regarded as constraining agency (Nieminen et al., 2022; Priestley et al., 2015).

In previous studies, learners’ agency in mathematics learning was operationalised using a three-dimensional questionnaire reflecting the dimensions described above (Leijen et al., 2024; Pedaste et al., 2023). Building on these studies, the present study aims to examine the psychometric properties of a revised agency questionnaire that conceptualises learners’ agency in learning-related decision-making situations beyond a specific school subject and includes additional items developed based on interviews with students from Grades 6 to 12. Using Confirmatory factor analysis (CFA), we examined whether the hypothesised three-factor measurement model of learners’ agency provides an adequate fit to the data when agency is operationalised in relation to students’ general learning experiences. Furthermore, using multi-group CFA, we investigated the extent to which the revised instrument demonstrates measurement invariance across students in Grades 6, 9, and 12. Accordingly, the study addressed the following research questions: (1) To what extent does a three-factor confirmatory factor model of learners’ agency fit the data when agency is operationalised in relation to general learning experiences?, and (2) To what extent does the revised learners’ agency questionnaire exhibit scalar measurement invariance across students in Grades 6, 9, and 12?

Data was collected from 549 students (166 – 6th Grade, 133 – 9th Grade, 250 – 12th Grade) in Estonia. CFA showed that the initially developed questionnaire had a near-acceptable fit. Based on the empirical and theoretical considerations, we decided to remove some items; the final version of the questionnaire included 24 items. This version of the questionnaire had good model fit. A comparison of configural and scalar models suggested scalar invariance across grade levels. Therefore, the new questionnaire appears suitable and sensitive for monitoring and comparing student learning-related agency among 6^th- to 12^th-grade students.