The purpose of this project is to assess how well today’s youth is able to learn new skills<br/>in the realm of engineering through online video-conferencing resources. Each semester of this<br/>last year, a class of students in both 3rd and 6th grade learned about computer-aided design (CAD)<br/>and 3D printing through their laptops at school. This was done by conducting online lessons of<br/>TinkerCAD via Zoom and Google Meet. TinkerCAD is a simple website that incorporates easy-to-learn skills and gives students an introduction to some of the basic operations that are used in<br/>everyday CAD endeavors. In each lesson, the students would learn new skills by creating<br/>increasingly difficult objects that would test both their ability to learn new skills and their overall<br/>enjoyment with the subject matter. The findings of this project reflect that students are able to<br/>quickly learn and retain new information relating to CAD. The group of 6th graders was able to<br/>learn much faster, which was expected, but the class of 3rd graders still maintained the<br/>knowledge gained from previous lessons and were able to construct increasingly complicated<br/>objects without much struggle. Overall, the students in both classes enjoyed the lessons and did<br/>not find them too difficult, despite the online environment that we were required to use. Some<br/>students found the material more interesting than others, but in general, the students found it<br/>enjoyable to learn about a new skill that has significant real-world applications
In this study, I sought to determine which NFL Combine metrics are predictive of future NFL success among the quarterback, running back, and wide receiver positions, with the hope of providing meaningful information that can be utilized by NFL executives when making decisions about draft selections. I gathered samples spanning across the years 2010-2015 of all three of the aforementioned position groups. Among these samples, I used certain criteria which split them up within their position groups. The two groups of players were identified as: those who had successful careers and those who had unsuccessful careers. Given this information, I performed t-tests and ANOVA between successful and unsuccessful groups with the goal of identifying which combine metrics are predictive of future NFL success, and which are not. For quarterbacks, the 40-yard dash, broad jump, three-cone, and 10-yard shuttle all appear to be predictive of success. Notably, quarterback height does not appear to be predictive, despite the popular belief that a quarterback should be tall if they are to succeed. For running backs, player weight, 40-yard dash, and three-cone all appear to be predictive of success, with the broad jump and 10-yard shuttle seemingly predicting success as well, albeit to a lesser degree of strength. For wide receivers, all metrics do not appear to be predictive of success, with the exception of the 40-yard dash, which only appears to be slightly predictive. While there are likely many other factors that contribute to a player’s success than tests administered at the NFL combine, NFL general managers can look to these results when making draft selections.