DocumentCode :
2808800
Title :
An introduction to machine learning for students in secondary education
Author :
Essinger, Steven D. ; Rosen, Gail L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
fYear :
2011
fDate :
4-7 Jan. 2011
Firstpage :
243
Lastpage :
248
Abstract :
We have developed a platform for exposing high school students to machine learning techniques for signal processing problems, making use of relatively simple mathematics and engineering concepts. Along with this platform we have created two example scenarios which give motivation to the students for learning the theory underlying their solutions. The first scenario features a recycling sorting problem in which the students must setup a system so that the computer may learn the different types of objects to recycle so that it may automatically place them in the proper receptacle. The second scenario was motivated by a high school biology curriculum. The students are to develop a system that learns the different types of bacteria present in a pond sample. The system will then group the bacteria together based on similarity. One of the key strengths of this platform is that virtually any type of scenario may be built upon the concepts conveyed in this paper. This then permits student participation from a wide variety of educational motivation.
Keywords :
computer aided instruction; further education; learning (artificial intelligence); educational motivation; machine learning; recycling sorting problem; secondary education; signal processing problems; Algorithm design and analysis; Computers; Containers; Feature extraction; Measurement; Microorganisms; Recycling; Lab Modules; Machine Learning; Pattern Recognition; Secondary Education;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing Workshop and IEEE Signal Processing Education Workshop (DSP/SPE), 2011 IEEE
Conference_Location :
Sedona, AZ
Print_ISBN :
978-1-61284-226-4
Type :
conf
DOI :
10.1109/DSP-SPE.2011.5739219
Filename :
5739219
Link To Document :
بازگشت