14 research outputs found
Academic and social integration and study progress in problem based learning
The present study explores the effects of problem-based learning (PBL) on social and academic integration and study progress. Three hundred and five first-year students from three different psychology curricula completed a questionnaire on social and academic integration. Effects of a full-fledged PBL environment were compared to (1) effects of a conventional lecture-based learning environment, and (2) effects of a learning environment that combined lectures and other methods aimed at activating students. Lisrel analyses show direct positive effects of the learning environment on study progress: students in PBL obtained more credits compared to students in more conventional curricula. Moreover, the levels of social and academic integration were also higher among students in the PBL curriculum. The links between integration and study progress were less straightforward. Formal social integration positively affected study progress, but informal academic integration was negatively related to study progress
Learning Environment, Interaction, Sense of Belonging and Study Success in Ethnically Diverse Student Groups
Visualising the invisible: a network approach to reveal the informal social side of student learning
World-wide, universities in health sciences have transformed their curriculum to include collaborative learning and facilitate the students’ learning process. Interaction has been acknowledged to be the synergistic element in this learning context. However, students spend the majority of their time outside their classroom and interaction does not stop outside the classroom. Therefore we studied how informal social interaction influences student learning. Moreover, to explore what really matters in the students learning process, a model was tested how the generally known important constructs—prior performance, motivation and social integration—relate to informal social interaction and student learning. 301 undergraduate medical students participated in this cross-sectional quantitative study. Informal social interaction was assessed using self-reported surveys following the network approach. Students’ individual motivation, social integration and prior performance were assessed by the Academic Motivation Scale, the College Adaption Questionnaire and students’ GPA respectively. A factual knowledge test represented student’ learning. All social networks were positively associated with student learning significantly: friendships (β = 0.11), providing information to other students (β = 0.16), receiving information from other students (β = 0.25). Structural equation modelling revealed a model in which social networks increased student learning (r = 0.43), followed by prior performance (r = 0.31). In contrast to prior literature, students’ academic motivation and social integration were not associated with students’ learning. Students’ informal social interaction is strongly associated with students’ learning. These findings underline the need to change our focus from the formal context (classroom) to the informal context to optimize student learning and deliver modern medics
Academic Fatalism: Applying Durkheim’s Fatalistic Suicide Typology to Student Drop-Out and the Climate of Higher Education
The work–study interface: similarities and differences between ethnic minority and ethnic majority students
Student perceptions of the fairness of grading procedures: a multilevel investigation of the role of the academic environment
Problem-based learning and the relevance of teaching and learning European Studies in times of crises
Understanding diversity: a Dutch case study on teachers’ attitudes towards their diverse student population
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