The project seeks to provide a program evaluation of the Girls E-Mentorship Innovation (GEM) youth mentoring program. GEMs program is a socially innovative approach linking high school aged girls with successful professional leaders in the employment sector, to support the development of positive attitudes and future career attainment. Using mixed methods, this project develops key outcome measures assessing the effectiveness of the GEM program, along with providing a general assessment of the overall economic and social impact the organization has in its local area.
A joint research agreement was adopted between Concordia University and Zoo de Granby in the spring 2014. The firm BBA joined this partnership in November 2014. The aim of the initiative is to foster the training of highly qualified personnel in conservation and welfare of captive wildlife, by allowing Concordia students to get hands-on experience at the zoo.
Classroom response tools such as the ‘clicker’ are devices that students use in class to answer multiple-choice questions. Many studies have shown that clickers can lead to increased learning when properly used. Learning Catalytics is a new web-based tool marketed by Pearson that is meant to replace clickers. While Learning Catalytics offers more features than clickers there are also concerns which must be addressed: 1) Does the use of a web-based tool lead to more distraction in class (texting, facebook)? 2) Is Learning Catalytics as efficient as clickers in supporting students’ learning?
Mild traumatic brain injury (mTBI) is one of the least understood neurological injuries. Increasing evidence shows that the effects of mTBI are not transient and may be associated with significant long-term consequences on brain function and may lead to long-term changes in the functioning of the brain with impacts on many areas related to information processing. Over a lifetime, repeated brain trauma is a significant risk factor for developing neurodegenerative disorders including Alzheimer’s disease (AD) and Parkinson’s disease (PD).
This research project aims to provide a robust account of school performance across Canada by collecting and measuring data on six critical indicators. These indicators are academic achievement, physical and mental health, social-emotional development, creativity and innovation, citizenship and democracy, and school climate. To address this inquiry, survey data will be collected and integrated with existing government data sources to aptly measure the six indicators.
I will be involved in two different projects with Pearson Education, 1) evaluate Knewton’s adaptive learningtechnology, and 2) assess the efficacy and improve the quality of the existing assessment tools and items. My proposalwill focus on the first project.The goal of the project is to evaluate the effectiveness and pedagogical values of Knewton’s adaptive learningtechnology, a technology meant to differentially help students depending on their needs.
This cross-sectoral research project will track the process of supporting four nascent community-based enterprises (CBEs) in indigenous communities in the Bolivian highlands, examining the complex interaction of factors that contribute to successful CBEs.
The accurate localization of facial keypoints in static images, and their tracking in video has many potential applications. In this project we will address the problem of fine-grained facial keypoint tracking using multiple images and cameras, possibly including depth cameras. We have identified three potential partners, each of whom focus on applications that require the accurate localization and/or tracking of facial keypoints. In one potential application we are interested in detecting certain congenital syndromes using detailed facial analysis.
This project is aimed to develop novel catalytic system and process for production of valuable chemicals such as 1,3-propanediol and acrylic acid from glycerol. Glycerol is a byproduct of biodiesel production (10 kg of biodiesel yields 1 kg of glycerol). The production of biodiesel is expected to grow almost 7-fold from 3.8 MMTPA in 2005 to about 25 MMTPA in 2015. This increase in demand for biodiesel in the world market has increased the quantity of glycerol generated.
Poor data quality is a barrier to effective, high-quality decision-making based on data. Declarative data cleaning has emerged as an effective tool for both assessing and improving the quality of data. In this work, we will address some important challenges in applying declarative data cleaning to big data, challenges that arise due to the scale, complexity, and massive heterogeneity of such data. First, we will investigate the use of domain ontologies to enhance declarative data cleaning. Second, given the dynamic nature of big data, we will develop new continuous data cleaning methods.