In the Developmental Intelligence Laboratory, we are interested in understanding fundamental cognitive mechanisms of human intelligence, human learning, and human interaction and communication in everyday activities. To do so, we collect and analyze micro-level multimodal behavioral data using state-of-the-art sensing and computational techniques. One of our primary research aims is to understand human learning and early development. How do young children acquire fundamental knowledge of the world? How do they select and process the information around them and learn from scratch? How do they learn to move their bodies and to communicate and interact with others? Learning this kind of knowledge and skills is the core of human intelligence. To understand how human learners achieve the learning goal, the primary approach in our research is to attach GoPro-like cameras on the head of young children to record egocentric video from their point of view. Using this innovative approach, we've been collecting video data of children’s everyday activities, such as playing with their parents and their peers, reading books with parents and caregivers, and playing outside. We've been using state-of-the-art machine learning and data mining approaches to analyze high-density behavioral data. This research line will ultimately solve the mystery on why human children are such efficient learners. Moreover, the findings from our research will be used to help improve learning of children with developmental deficits. A complimentary research line is to explore how human learning can teach us about how machines can learn. Can we model and simulate how a human child learns and develops? To this end, our research aims at bridging and connecting developmental science in psychology and machine learning and computer vision in computer science.
Zoom interview with Stella Lee by Guy W. Wallace, recorded on July 12, 2022, regarding Stella's background, education, career history, and how she came to an HPT - Human Performance Technology/ Evidence-Based Practices approach in her L&D work.
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The accumulation of solid waste and consumption of fossil fuels are two phenomenons which already have a major destructive effect on the environment. The lack of alternative solid waste management procedures and shortage of the development of renewable energy resources should be addressed in order to sustain environmental quality. Sawdust is a major waste product along the Lagos lagoon with cellulose one of the predominant structural components of sawdust. The bio-conversion of waste cellulose, a glucose biopolymer into glucose a fermentable sugar has been performed with cellulase from Aspergillus Niger. Delignified and non-delignified sawdust from five different trees along the Lagos Lagoon have been saccharified with A. niger cellulase. The saccharification of these sawdust materials have been performed at different incubation temperatures of 30°C, 40°C, 50°C and 60°C. Optimum saccharification of non-delignified and delignified cellulose from the various trees along the Lagos Lagoon were optimum saccharified at different temperatures resulting in different sugar concentrations produced. A temperature of 40°C was optimum for maximum degradation of non-delignified cellulose from al
L'International Journal of Educational Research Open a publié une étude bibliométrique sur le Learning Analytics (LA), ou Analyse de l’apprentissage. L'étude, qui s'étend de 2010 à 2020, permet d'établir le développement croissant de cette discipline. Elle croise les méthodes quantitatives traditionnelles dans l'éducation avec l'utilisation de mégadonnées, comme dans les domaines de l'Intelligence artificielle.