Abstract
Academic integration turns out to be an important predictor of first-year students' study success in higher education. This concept refers to the extent to which students can adjust themselves to fit into the new academic environment. Academic integration can be investigated by looking at different student characteristics. Although academic integration is viewed as an 'evolving' concept, it is mainly investigated from a static viewpoint. Integration of transition theories into longitudinal process models can help resolve this issue.
The aim of this research project is to examine changes in first-year students' academic integration by integrating Nicholson's transition model with a longitudinal process model. Nicholson's transition model (1990) generally describes transition as a four-phase process: preparation, encounter, adjustment and stabilization. This implies an expanded conceptual framework including variables related to students' preparation in secondary education (prior achievement, study choice processes) and a refinement of the academic transition into an encounter and an adjustment phase.
This conceptual framework will be tested using a longitudinal dataset already collected within another study project on students' transition from secondary to higher education or the labour market (N=3700 students). To examine the relations between study success, changes in academic integration and the preparation in secondary education, this research project will be set up in four research stages: a descriptive, an explorative, a testing and a theoretical stage. The first three stage will each aim at a higher level of analysis and gradually investigate the conceptual model underpinning this project. The last stage will be aimed at theory building by integration of the results of this project with the relevant knowledge bases.
This project is innovative in multiple ways. As far as we know, it is the first research project to fully integrate a longitudinal process model with a transition model. Second, the five-wave longitudinal data set allows for in depth examination of causality. Third, the data set contains students from both professional and academic bachelor programs. This will enhance the generalizability of the results of this research project. Finally, this research project will contribute to theory building which is highly needed within this research domain.
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