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Showing posts with the label Learner Achievements

Student Researchers design gadget to harvest water from thin air; DepEd Sarangani supports robotics program

The technology field is rapidly evolving and experts predict that advancements in Artificial Intelligence, Machine Learning, and the Internet of Things will profoundly impact society. To keep up with these changes, the education system must adapt and stay current. In line with this, a group of senior high school students from Sarangani Division in the Philippines has taken the initiative to make a difference. The research team consisting of Jan Laurence Guieb, Jhon Wincer Elbo, Vice Navarro, and Francine Aira Sanchez, has developed a project that aims to address a critical need in remote communities - access to clean water. The team has received full support from their adviser, Shiela Butil, PhD and will participate in a training program in Manila on March 13th. They will also receive a grant of Php 50,000 worth of materials to further develop their project, with the possibility of winning a prize of Php 200,000 pesos for the best team. The Sarangani Division is committed to providing

AlSci researchers bag championship in national tilt

Another research team from Alabel National Science High School bagged yet another award, this time from the University of the Philippines-ALCHEMES Research Fair. The team composed of Ernest Gabonada, Trisha Belle Pactes, and Francine Sanchez bested 29 other schools from all over the country in the applied science category. From all the finalists, the roster was cut down to five, and then, in the championship round, the research team from AlSci went head-to-head against the team from Philippines Science High School CALABARZON Region Campus, where they emerged as the champion, and the people's choice as well. The research presented by the team is an application of machine learning, which is a subset of artificial intelligence, to the early detection of plant diseases. Entitled Project PLANTdemic - Automatic, Rapid, and Early Detection of Plant Disease Using Deep Learning, the research involves the use of a browser-based application that enables users to identify early signs of plant