LUCET Original Research

Longitudinal Strand

educational trajectories, mechanisms and interventions


LUCET’s first original research strand, the “longitudinal strand”, essentially revolves around the understanding and prediction of educational pathways and outcomes. Primarily drawing on the in-house longitudinal database, this first research strand encompasses original research on educational trajectories (e.g., determinants of regular vs. irregular educational careers, of grade retention and/or school dropout), educational mechanisms (e.g., interplay between academic competencies, cognition and/or motivation) as well as educational intervention studies (e.g., investigating the impact of language of instruction on STEM learning). In the long term, with the maturation of the database, a progressive shift towards a lifespan perspective is envisioned.

Selected Publications

The Effect of Morphosyntactic Training on Multilingual Fifth-Graders' Spelling in French

Visuo-spatial abilities are key for young children’s verbal number skills

How Do Different Aspects of Spatial Skills Relate to Early Arithmetic and Number Line Estimation?

Mathematical abilities in elementary school: Do they relate to number–space associations?

General and Specific Contributions of RAN to Reading and Arithmetic Fluency in First Graders: A Longitudinal Latent Variable Approach

The power of vowels: Contributions of vowel, consonant and digit RAN to clinical approaches in reading development

Teacher judgments as measures of children's cognitive ability: A multilevel analysis

How Math Anxiety relates to Number-Space Associations

Short-term and medium-term effects of grade retention in secondary school on academic achievement and psychosocial outcome variables

Die Bezugsnormorientierung von Mathematiklehrkräften am Ende der Sekundarstufe I: Konvergenz verschiedener Messverfahren und Wirkung auf motivational-affektive Aspekte des Mathematiklernens und Leistung

The Impact of Mathematical Proficiency on the Number-Space Association

The impact of inhibition capacities and age on number–space associations

Predicting first-grade mathematics achievement: the contributions of domain-general cognitive abilities, nonverbal number sense, and early number competence

Forty years on: Childhood intelligence predicts health in middle adulthood

Do teacher judgments of student intelligence predict life outcomes?

PISA proficiency scores predict educational outcomes

Childhood intelligence and adult health: The mediating roles of education and socioeconomic status

Does Childhood General Cognitive Ability at Age 12 Predict Subjective Well-Being at Age 52?

Innovation Strand

innovative constructs, measures and technology-rich instruments


LUCET’s second original research strand, the “innovation strand”, aims at continuously innovating assessment—and to some extent also learning—through the development and exploration of new constructs (e.g., introducing a human-computer interaction and user experience perspective to computer-based assessment), new measures (e.g., for non-cognitive skills) and new technology-rich instruments (e.g., tablet-computer-based battery for cognitive potential, tablet-computer-based self-assessment instrument). This second strand has a very prominent digital component and is thus intimately connected with LUCET’s in-house online assessment system OASYS. Original research projects in the innovation strand will on the one hand rely on OASYS, and on the other hand ensure a continuous and research-based development of the latter. The commercial valorisation of research derivatives from this second strand will be subject to active exploration.

Selected Publications

A Tablet-Computer-Based Tool to Facilitate Accurate Self-Assessments in Third- and Fourth-Graders

MaGrid: A Language-Neutral Early Mathematical Training and Learning Application

Domain-Specificity of Need for Cognition Among High School Students

A need for cognition scale for children and adolescents: Structural analysis and measurement invariance

Students’ Complex Problem-Solving Abilities: Their Structure and Relations to Reasoning Ability and Educational Success


Methods Strand

culture-fair measurement in multilingual learning environments


LUCET’s third original research strand, the “methods strand”, primarily tackles specific measurement challenges imposed either by the highly diverse multilingual Luxembourg context (e.g., lowering the language component in mathematics competency testing, language-free assessment of cognitive potential), or by the ambitious ÉpStan school monitoring model (e.g., methods for group-based assessments with preliterate children, Likert-type answer scales for preliterate children). In addition, the methodological research strand also approaches more general large-scale assessment issues (e.g., alternative scaling models, construction of valid short scales) and educational measurement challenges (e.g., fair feedback and value-added modelling techniques).

Selected Publications

Between‐school variation in students’ achievement, motivation, affect, and learning strategies: Results from 81 countries for planning group‐randomized trials in education

Taking Language out of the Equation: The Assessment of Basic Math Competence Without Language

How and Why Do Number-Space Associations Co-Vary in Implicit and Explicit Magnitude Processing Tasks?

Solving arithmetic problems in first and second language: Does the language context matter?

Task instructions determine the visuospatial and verbal-spatial nature of number-space associations

Inhibition of return and attentional facilitation: Numbers can be counted in, letters tell a different story

The relation between language and arithmetic in bilinguals: insights from different stages of language acquisition

"My questionnaire is too long!" The assessments of motivational-affective constructs with three-item and single-item measures

Do test takers with different language backgrounds take the same C-test? The effect of native language on the validity of C-tests

Developing number–space associations: SNARC effects using a color discrimination task in 5-year-olds


Data Mining Strand

meaningful exploitation of log-file data in technology-rich measurement


LUCET’s fourth and last original research strand, the “data mining strand”, revolves around the extraction of new and meaningful information from behavioural data gathered in the process of technology-rich measurement (e.g., indicators for test-takers’ seriousness and commitment during the assessment). In theory, the data thus collected could also be used on the fly to create responsive and interactive tailor-made assessment—and learning—situations. Out of the four original research strands, the data mining strand is the centre’s—and the entire field’s—“here be dragons” strand, meaning that it is currently the least developed, most risky, yet potentially most rewarding area of research as pioneering work is still to be conducted.

Selected Publications

Assessing Complex Problem Solving in the Classroom: Meeting Challenges and Opportunities

Learning to confront complexity: What roles can a computer-based problem-solving scenario play?

Differential relations between facets of complex problem solving and students’ immigration background

The Genetics Lab. Acceptance and psychometric characteristics of a computer-based microworld to assess Complex Problem Solving