LUCET Original Research

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.

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.

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).

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.