Building a Learning Architecture : e-Learning and e-Services

With the rapid advancement of the webtechnology, more and more educationalresources, including software applications forteaching/learning methods, are available acrossthe web, which enables learners to access thelearning materials and use various ways oflearning at any time and any place. Moreover,various web-based teaching/learning approacheshave been developed during the last decade toenhance the capability of both educators andlearners. Particularly, researchers from bothcomputer science and education are workingtogether, collaboratively focusing ondevelopment of pedagogically enablingtechnologies which are believed to improve theinfrastructure of education systems andprocesses, including curriculum developmentmodels, teaching/learning methods, managementof educational resources, systematic organizationof communication and dissemination ofknowledge and skills required by and adapted tousers. Despite of its fast development, however,there are still great gaps between learningintentions, organization of supporting resources,management of educational structures,knowledge points to be learned and interknowledgepoint relationships such as prerequisites,assessment of learning outcomes, andtechnical and pedagogic approaches. Moreconcretely, the issues have been widelyaddressed in literature include a) availability andusefulness of resources, b) smooth integration ofvarious resources and their presentation, c)learners’ requirements and supposed learningoutcomes, d) automation of learning process interms of its schedule and interaction, and e)customization of the resources and agilemanagement of the learning services for deliveryas well as necessary human interferences.Considering these problems and bearing in mindthe advanced web technology of which weshould make full use, in this report we willaddress the following two aspects of systematicarchitecture of learning/teaching systems: 1)learning objects – a semantic description andorganization of learning resources using the webservice models and methods, and 2) learningservices discovery and learning goals match foreducational coordination and learning serviceplanning.

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).

Likelihood prediction for generalized linear mixed models under covariate uncertainty

This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.

Methods and background characteristics of the TOHNN study : a population-based study of oral health conditions in northern Norway

OBJECTIVES: The aim of the Tromstannen - Oral Health in Northern Norway (TOHNN) study was to investigate oral health and dental-related diseases in an adult population. This article provides an overview of the background of the study and a description of the sample characteristics and methods employed in data collection. STUDY DESIGN: Cross-sectional population-based study including a questionnaire and clinical dental examination. METHODS: A randomly selected sample of 2,909 individuals (20-79 years old) drawn from the population register was invited to participate in the study. The data were collected between October 2013 and November 2014 in Troms County in northern Norway. The questionnaire focused on oral health-related behaviours and attitudes, oral health-related quality of life, sense of coherence, dental anxiety and symptoms from the temporomandibular joint. The dental examinations, including radiographs, were conducted by 11 dental teams in 5 dental offices. The examination comprised of registration of dental caries, full mouth periodontal status, temporomandibular disorders, mucosal lesions and height and weight. The participants were grouped by age (20-34, 35-49, 50-64 and 65-79) and ethnicity (Norwegian, Sámi, other European and other world). RESULTS: From the original sample of 2,909 individuals, 1,986 (68.3%) people participated, of whom 1,019 (51.3%) were women. The highest attendance rate was among women 20-34 years old (80.3%) and the lowest in the oldest age group of women (55.4%). There was no difference in response rate between rural and urban areas. There was a positive correlation between population size and household gross income (p < 0.001) and education level (p < 0.001). The majority of Sámi resided in smaller municipalities. In larger cities, most participants used private dental health care services, whereas, in rural areas, most participants used the public dental health care service. CONCLUSION: The TOHNN study has the potential to generate new knowledge on a wide range of oral health conditions beneficial to the population in Troms County. Due to the high participation rate, generalization both nationally and to the circumpolar area ought to be possible.