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

Cytogenetic abnormalities and fragile-x syndrome in Autism Spectrum Disorder

BACKGROUND: Autism is a behavioral disorder with impaired social interaction, communication, and repetitive and stereotypic behaviors. About 5–10 % of individuals with autism have 'secondary' autism in which an environmental agent, chromosome abnormality, or single gene disorder can be identified. Ninety percent have idiopathic autism and a major gene has not yet been identified. We have assessed the incidence of chromosome abnormalities and Fragile X syndrome in a population of autistic patients referred to our laboratory. METHODS: Data was analyzed from 433 patients with autistic traits tested using chromosome analysis and/or fluorescence in situ hybridization (FISH) and/or molecular testing for fragile X syndrome by Southern and PCR methods. RESULTS: The median age was 4 years. Sex ratio was 4.5 males to 1 female [354:79]. A chromosome (cs) abnormality was found in 14/421 [3.33 %] cases. The aberrations were: 4/14 [28%] supernumerary markers; 4/14 [28%] deletions; 1/14 [7%] duplication; 3/14 [21%] inversions; 2/14 [14%] translocations. FISH was performed on 23 cases for reasons other than to characterize a previously identified cytogenetic abnormality. All 23 cases were negative. Fragile-X testing by Southern blots and PCR analysis found 7/316 [2.2 %] with an abnormal result. The mutations detected were: a full mutation (fM) and abnormal methylation in 3 [43 %], mosaic mutations with partial methylation of variable clinical significance in 3 [43%] and a permutation carrier [14%]. The frequency of chromosome and fragile-X abnormalities appears to be within the range in reported surveys (cs 4.8-1.7%, FRAX 2–4%). Limitations of our retrospective study include paucity of behavioral diagnostic information, and a specific clinical criterion for testing. CONCLUSIONS: Twenty-eight percent of chromosome abnormalities detected in our study were subtle; therefore a high resolution cytogenetic study with a scrutiny of 15q11.2q13, 2q37 and Xp23.3 region should be standard practice when the indication is autism. The higher incidence of mosaic fragile-X mutations with partial methylation compared to FRAXA positive population [50% vs 15–40%] suggests that faint bands and variations in the Southern band pattern may occur in autistic patients