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By Sarah Bechard, Michael Ferlisi, and Sydni Williams, III Form
Project Based Learning in The Global Seminar: The Zamibia Presentation
Editor’s Note: All III Formers took part in The Global Seminar’s project to create a proposal to improve the state of the fictitious country Zamibia. The students collaborated in groups as United Nations Development Programme Sustainable Development Teams. The two artifacts below include the slide presentation that the students delivered to their classmates, teachers, and visitors as well as the video of the presentation.
By Lukas Hanenberger, Syndey Howard, Cait Lochhead, Lucy Martinson, Hans Wu, Ryan Yang, and Justin Zhang, VI Form
Herbst Musikvideo Projekt: 99 Luftballons
CLICK IMAGE FOR GERMAN IV’s CLASS VIDEO or CLICK HERE:
Read below for assignment parameters in Mr. Daniel Mertsch’s class (auf Deutsch): (more…)
By Truman Chamberlin, V Form
Bikes, Water, and Soul 2018
As we transition into the cold and gloomy winters of New England, we cannot help but think about the warmth of summer. Naturally, for teenagers, the hallmark of summer is summer vacation. When I go through the “God-I-wish-it-were-summer” time, my mind immediately wanders back to the 750-mile bike trip I went on in July. Eleven riders ranging from ages fourteen to seventeen, three adult leaders, and two support van drivers all took a step away from their mundane lives and embarked on a week-long journey through North Carolina. This unforgettable trip was a transcendent experience in my life.
By Jenny Shan, VI Form
Casual Bike Rental Volume Prediction via Artificial Neural Network
Aim: This study aimed to build a predictive model for casual bike rental volume using artificial neural network and compare its performance with traditional regression method, linear regression.
Method: The data set under study is related to 2-year usage log of a bike sharing system namely Capital Bike Sharing (CBS) at Washington, D.C., USA. There were some external sources that corresponding historical environmental values such as weather conditions, weekday and holidays are extractable. All the records were randomly assigned into 2 groups: training sample (50%) and testing sample (50%). Two models were built using training sample: artificial neural network and linear regression. For artificial neural network, the input layer has 11 inputs, the two hidden layers have 3 and 2 neurons and the output layer has a single output. Mean squared errors (MSE) were calculated and compared between both models. A cross-validation was conducted using a loop for the neural network and the cv.glm() function in the boot package for the linear model. A package called “neuralnet” in R was used to conduct neural network analysis.
By Julian Yang, V Form
What My Brain Learned via the Dissection of Another
Before walking into class on Monday, I was filled with curiosity and excitement. It has been six years since I saw an actual brain, and I was barely engaged at that time – although there was a parent who worked with brains and explained the information to us, no actual dissection was involved. The closest I got was holding the brain in my hand
My anticipation began to build during the “instructing” phase. Two feelings stirred inside me: one, I would be able to see everything that I learned in the past two weeks, and two, I was going to feel like a surgeon while using the scalpel. I made sure, however, to be careful: the way it sliced during Ms. Lohwater’s demonstration was enough to curb my excitement. (more…)