CURE Examples
Nature of Research
CURE Duration
DisciplineResults 1 - 6 of 6 matches
Using R to Build Powerful Predictive Models for Kaggle Competitions
Earvin Balderama, California State University-Fresno
Core Competencies: Using mathematics and computational thinking, Analyzing and interpreting data, Developing and using models
Nature of Research: Informatics/Computational Research, Applied Research
State: California
Target Audience: Non-major, Major, Upper Division
CURE Duration: A full term
Brain Mapping of Psychiatric Disorders
Chris Miller, California State University-Fresno
This course will introduce students to the neuroscience of psychiatric disorders by guiding them through the process of conducting a meta-analysis of fMRI studies of a particular psychiatric disorder of their choice.
Core Competencies: Analyzing and interpreting data, Asking questions (for science) and defining problems (for engineering), Using mathematics and computational thinking
Nature of Research: Informatics/Computational Research
State: California
Target Audience: Major
CURE Duration: A full term, Multiple terms
Effect of Short Blood Sample on Patient Results Validity
Anna Marti-Subirana, Phoenix College
This CURE addresses how body fluid short sampling affects result interpretation and diagnostics. Short sampling can lead to false result interpretation and misdiagnosis. No data are available on the impact of short sampling and clinical diagnostics.
Core Competencies: Analyzing and interpreting data, Planning and carrying out investigations, Using mathematics and computational thinking, Asking questions (for science) and defining problems (for engineering)
Nature of Research: Applied Research
State: Arizona
Target Audience: Major
CURE Duration: A full term
Emerging Contaminants in Arizona
Frank Marfai, Phoenix College
Core Competencies: Constructing explanations (for science) and designing solutions (for engineering), Asking questions (for science) and defining problems (for engineering), Analyzing and interpreting data, Using mathematics and computational thinking, Developing and using models
Nature of Research: Basic Research, Applied Research
State: Arizona
Target Audience: Introductory, Upper Division, Non-major, Major
CURE Duration: Multiple terms, A full term
Beyond the acronym: Employing data science to improve engagement in STEM
Pamela Reynolds, University of California-Davis
Forbes magazine ranked UC Davis as the "best value college for women in STEM." Let's investigate why, together! In this hands-on Course-based Undergraduate Research Experience (CURE), you will leverage computational tools and methodologies to explore, analyze and design solutions to maximize discoverability and engagement with STEM offerings right here at UC Davis. Community-based tools like the UC Davis STEM portal help students and members of the broader community discover and connect with opportunities in science, technology, engineering and math. How do we define STEM, and how do people interface with the diversity of offerings at our university? Through this seminar you will learn about web scraping, text mining, natural language processing, and user interface design as you work on projects to optimize search functionality and increase content management automation for the Portal, which serves as a single point of entry for catalogued information related to STEM initiatives, clubs, programs and events on campus. This research will be used to improve the discoverability and accessibility of our university's resources, and identify new opportunities for multidisciplinary research and engagement with STEM. The data we collect and workflows designed in this class will contribute to research in the digital humanities and philosophy of science regarding the shape of the discourse surrounding STEM in academia. It will also have a direct application in helping our students and broader community discover new resources and opportunities. Students will be required to work both individually and collaboratively in groups, and to share their learning with each other. This class is open to first-year freshman and transfer students from all majors. You do not need to be a computer scientist to be successful in this course, but you should be comfortable using a computer and have prior exposure to programming (R, Python, etc.). Your instructor team is looking forward to supporting your learning and engagement with research in this class!
Core Competencies: Analyzing and interpreting data, Using mathematics and computational thinking, Planning and carrying out investigations, Asking questions (for science) and defining problems (for engineering)
Nature of Research: Applied Research, Informatics/Computational Research
State: California
Target Audience: Introductory, Major, Non-major
CURE Duration: A full term
Introduction to Statistical Methods "for the CURE"
Meredith Anderson, Adams State University; Ashley Meek, Adams State University
Students will take data collected from other CURE classes and perform a variety of statistical analyses. They will learn how to prepare data sets for analysis and about experimental design. Students will see how technology facilitates the calculation of summary statistics and the visualization of data.
Core Competencies: Analyzing and interpreting data, Using mathematics and computational thinking