Mapping processing strategies in learning from expository text: an exploratory eye tracking study followed by a cued recall

This study starts from the observation that current empirical research on students' processing strategies in higher education has mainly focused on the use of self-report instruments to measure students' general preferences towards processing strategies. In contrast, there is a rather limited use of more direct and online observation techniques to uncover differences in processing strategies at a task specific level. We based our study on one of the most influential studies in the domain of Students' Approaches to Learning (SAL) (Marton, Dahlgren, Säljö, & Svensson, 1975). In our exploratory experiment we used eye tracking followed by a cued recall to investigate how students use processing strategies in learning from expository text. Nineteen university students participated in the experiment. Results suggested that students in the deep condition did not look longer at the essentials in the text compared with students in the surface condition, but that they processed them in a more deep way. In our sample, students in the surface condition looked longer at facts and details and also reported repeating these facts and details more often. We suggest that the combination of eye tracking followed by a cued recall is a promising tool to investigate students' processing strategies since not all differences in processing strategies are reflected in overt eye movement behaviour. The current methodology allows researchers in the domain of SAL to complement and extend the present knowledge base that has accumulated through years of research with self-report questionnaires and interviews on students' general preferences towards processing strategies

Gene expression signature predicts rate of type 1 diabetes progressionResearch in context

Summary: Background: Type 1 diabetes is a complex heterogenous autoimmune disease without therapeutic interventions available to prevent or reverse the disease. This study aimed to identify transcriptional changes associated with the disease progression in patients with recent-onset type 1 diabetes. Methods: Whole-blood samples were collected as part of the INNODIA study at baseline and 12 months after diagnosis of type 1 diabetes. We used linear mixed-effects modelling on RNA-seq data to identify genes associated with age, sex, or disease progression. Cell-type proportions were estimated from the RNA-seq data using computational deconvolution. Associations to clinical variables were estimated using Pearson's or point-biserial correlation for continuous and dichotomous variables, respectively, using only complete pairs of observations. Findings: We found that genes and pathways related to innate immunity were downregulated during the first year after diagnosis. Significant associations of the gene expression changes were found with ZnT8A autoantibody positivity. Rate of change in the expression of 16 genes between baseline and 12 months was found to predict the decline in C-peptide at 24 months. Interestingly and consistent with earlier reports, increased B cell levels and decreased neutrophil levels were associated with the rapid progression. Interpretation: There is considerable individual variation in the rate of progression from appearance of type 1 diabetes-specific autoantibodies to clinical disease. Patient stratification and prediction of disease progression can help in developing more personalised therapeutic strategies for different disease endotypes. Funding: A full list of funding bodies can be found under Acknowledgments