Gert Vanthournout

Longitudinal Measurement Invariance of Likert-Type Learning Strategy Scales: Are We Using the Same Ruler at Each Wave?.

Whether or not learning strategies change during the course of higher education is an important topic in the Student Approaches to Learning field. However, there is a dearth of any empirical evaluations in the literature as to whether or not the instruments in this research domain measure equivalently over time. Therefore, this study details the procedure of longitudinal measurement invariance testing of self-report Likert-type scales, using the case of learning strategies. The sample consists of 245 University College students who filled out the Inventory of Learning Styles—Short Version three times. Using the WLSMV estimator to take into account the ordinal nature of the data, a series of models with progressively more stringent constraints were estimated using Mplus 6.1. The results indicate that longitudinal measurement invariance holds for all but two learning strategy scales. The implications for longitudinal analysis using scales with varying degrees of measurement invariance are discussed.

Modeling change in learning strategies throughout higher education: a multi-indicator latent growth perspective.

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.

To what degree does the missing-data technique influence the estimated growth in learning strategies over time? A tutorial example of sensitivity analysis for longitudinal data

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.

Verständnis der direkten und indirekten Beziehungen zwischen Teilnahmemotivation, Zielorientierung und dem Gebrauch von Selbstregulierungsstrategien während einer formellen Fortbildung

In der vorliegenden Studie werden direkte und indirekte Beziehungen zwischen der selbst- versus fremdbestimmten Motivation zur Weiterbildungsteilnahme, Zielorientierungen zu Beginn der Weiterbildung und Nutzung von Selbstregulationsstrategien wahrend der Weiterbildung untersucht. Insgesamt nahmen 717 Arbeitsnehmer an der Studie teil. Die genannten Konstrukte wurden mithilfe etablierter Skalen erfasst, die fur das Lernen im beruflichen Kontext adaptiert wurden. Die Ergebnisse zeigen einen positiven Zusammenhang zwischen selbstbestimmter Teilnahmemotivation, Lernzielorientierung und dem Einsatz von Selbstregulationsstrategien. Selbstbestimmte Teilnahmemotivation und Selbstregulationsstrategien zeigten daruber hinaus einen signifikanten uber Lernzielorientierung vermittelten indirekten Zusammenhang. Die Ergebnisse weisen zudem auf einen negativen Einfluss von Arbeitsvermeidungszielorientierung auf den Einsatz von Selbstregulationsstrategien hin. Arbeitsvermeidungszielorientierung vermittelte auch den Effekt fremdbestimmter Teilnahmemotivation bzw. Amotivation auf den Einsatz von Selbstregulationsstrategien. Insgesamt weist die Studie damit auf eine hohe Komplexitat der Zusammenhange zwischen Motivation und Lernqualitat im beruflichen Kontext hin.