Learning OutcomesFor MATH 3220 – Data Mining FoundationsRationale:There are four specific learning issues that this course will directly address. These issues are: (1) students have little exposure to how mathematicaltechniques are applied to actual problems in research and industry, (2) students have a limited experience with the data extraction, cleansing, and manipulation processes necessary for successful mathematical analysis, (3) students have a narrow understanding of the computational issues associated with the applicationof various mathematical techniques to these problems in research and industry, and (4) students have little experience presenting their research findings to an audience in writing or in an oral presentation.Learning Outcomes:The following learning outcomes will allow the assessment of these project courses to address the learning issues identified above:1.Students will demonstrate the ability to solve problems related to the course content and assignments. (Issues # 1, 2 and 3)2.Students will be able to analyze, design and implement a research solution using techniques and models from the course content. (Issues # 1, 2 and 3)3.Students will be able to document their research work and conclusions including both an executive summary and technical documentation. (Issue# 4)4.Students will be able to make a formal presentation of their research work and conclusions. (Issue # 4)Assessment Plan:The following assessment rubrics will be used to assess the learning outcomes for this course.
NOTACCEPTABLEBELOWEXPECTATIONSMEETSEXPECTATIONSEXCEEDSEXPECTATIONS1. Students will demonstrate the ability to solve problems related to the course content and assignments.1-A) Identify, understand and summarize the problem and constraints.Is unable to identify, understand and summarize the problemand constraints.Attempts but provides incomplete or inconsistent description of problem. Often overlooks a constraint or concept or include unnecessary constraints.