Comparison of learning between Digital gallery and Hands-on Laboratory

This thesis has been done in ROM (Royal Ontario Museum) located in Toronto Canada. It focuses on learning in two parts of the museum. It tries to find out how much each part is effective in terms of learning. Studies have been done in the Digital gallery, which has been equipped with digital video projector and workstation that allows visitors to interact with the collections in 2 or 3 dimensional spaces while they are watching the presenting film. The rest of the study was in Hands-on laboratory, which allows students to examine artifacts and discuss their findings .The method was used in this research is Concept mapping .In Digital gallery, 24 schools surveys in the form of pre-post- test by help of the concept mapping method has been done. In Hands-on laboratory, 12 schools have been studied by using the combination of interviewing and written pre post-test of concept mapping.

Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).