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Introduction: This study presents our online-teaching material within the k-MED project (Knowledge in Medical Education) at the university of Marburg. It is currently organized in five e-learning modules: cytogenetics, chromosomal aberrations, formal genetics, fundamentals of molecular diagnostics, and congenital abnormalities and syndromes. These are basic courses intended to do the educational groundwork, which will enable academic teachers to concentrate on more sophisticated topics during their lectures. Methods: The e-learning modules have been offered to a large group of about 3300 students during four years at the Faculty of Medicine in Marburg. The group consists of science students (human biology) and medical students in the preclinical or the clinical period, respectively. Participants were surveyed on acceptance by evaluating user-tracking data and questionnaires. Results and Conclusion: Analysis of the evaluation data proofs the broad acceptance of the e-learning modules during eight semesters. The courses are in stable or even increasing use from winter term 2005/06 until spring term 2009. Conclusion: Our e-learning-model is broadly accepted among students with different levels of knowledge at the Faculty of Medicine in Marburg. If the e-learning courses are maintained thoroughly, minor adaptations can increase acceptance and usage even furthermore. Their use should be extended to the medical education of technical assistances and nurses, who work in the field of human genetics. Keywords: Human genetics, e-Learning, evaluation, multimedia
Einleitung: Die vorliegende Studie beschreibt unser Online-Lehrmaterial Humangenetik im Zusammenhang mit dem k-MED-Projekt (Knowledge in Medical Education) an der Philipps-Universität Marburg. Es besteht aus fünf E-Learning-Modulen: Zytogenetik, Chromosomenstörungen, Formalgenetik, Grundlagen der molekularen Diagnostik sowie Kongenitale Abnormitäten und Fehlbildungssyndrome. Diese E-Module sollen ein einheitliches Wissensniveau der Studierenden gewährleisten und die Dozenten in der Präsenzlehre entlasten. Methoden: Die fünf E-Learning-Module Humangenetik wurden auf freiwilliger Basis einer großen Personengruppe von ca. 3300 Studierenden am Fachbereich Humanmedizin der Universität Marburg über eine Dauer von vier Jahren angeboten. Die Teilnehmer bestanden aus Naturwissenschaftlern (Humanbiologie) im 5. Fachsemester und Studierenden der Humanmedizin, die sich entweder in der Vorklinik (1. Semester) oder im klinischen Studienabschnitt (7./8. Semester) befanden. Von diesen wurden Daten zur Akzeptanz in Form von Usertrackingdaten und klausur-begleitenden Fragebögen erhoben. Ergebnisse und Schlussfolgerung: Die Evaluation zeigte eine breite Akzeptanz unserer Lehrmodule über einen Zeitraum von acht Semestern. Obwohl das Angebot freiwillig ist, werden die Online-Kurse Humangenetik konstant oder sogar in zunehmendem Maße zwischen Wintersemester 2005/06 und Sommersemester 2009 genutzt. Fazit: Unser E-Learning-Modell Humangenetik wird von Studierenden aus unterschiedlichen Semestern und Studiengängen am Fachbereich Humanmedizin gut angenommen und genutzt. Bei sorgfältiger Pflege der Online-Kurse steigern moderate Anpassungen sowohl Akzeptanz als auch Benutzungshäufigkeit in signifikanter Weise. Die Anwendung der E-Learning Module erscheint uns auch in der Ausbildung von MTAs oder Pflegekräften sinnvoll, um ein ausreichendes Grundwissen in Humangenetik zu gewährleisten. Schlüsselwörter: Humangenetik, Evaluation, Multimedia, E-Learning
Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.