News
Project on Educational Interventions - April 2020
RAPID: Educational Interventions for Undergraduate Students and Informal Learners for Robust Learning of COVID-19 Knowledge
Principal Investigators: Raphael Isokpehi, Sarah Krejci, Matilda Johnson and Baraka Mapp
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2029363
An educational intervention is defined as a systematic application of a program, product, practice, or policy with the intent of affecting an outcome. The COVID-19 pandemic in 2020 has accelerated digital transformation of educational interventions including the innovative use of advances in AI technology.
Societal Need: Learning experiences that prepare undergraduate students to thrive in a global data economy necessitated by COVID-19.
Project Goal:
Contribute transdisciplinary solutions to the current COVID-19 and future disease outbreaks.
Project Objectives:
1. Produce designers of effective, efficient, and engaging distance learning.
2. Equip undergraduate students and informal learners with relevant skills and competencies.
Project Outcomes:
1. Data Economy Education Programs
2. Educational Interventions Study Teams
Annotation Jamboree for Classifying Images of Biofilm Processes Summer 2019
Benefits:
Enriched their decision making expertise
Gained knowledge of microbiology
Worked with data analytics software
Enhanced their resume for internships and scholarships
Built research collaboration skills
Facilitated by: Baraka Mapp, Shrima Ramroop Butts, Raphael Isokpehi, Kaylynn Wilson and Antoinette Destefano.
Student Participants: Research Experiences for Undergraduates (REU) Students, Arianna Sanders, Ridge Wells, Robert Mckinzie and Kehinde Ezekiel
Data Challenges Training Summer 2019
Facilitated by: Antoinette Destefano, Raphael Isokpehi, Arianna Sanders and Kehinde Ezekiel
Student Participants: Research Experiences for Undergraduates (REU) Students
The goal of this Data Challenges Training were for participants to understand how to work effectively with data.
The training looked at: the background on data, how to create a data set in Excel, Notepad ++, Cognitive activities and action patterns, 5 content types, Data challenges, three V’s of data, interpreting visuals, concept maps, word clouds, difference between table, matrix and list, visual analytic software including Tableau, Tableau Prep and the design and implementation of a visual representation of the constructed data set.
Career Day Visit Fall 2019
Facilitated by: Antoinette Destefano, Raphael Isokpehi and Arianna Sanders
Student Participants: Inspirations Learning Center Daytona Beach, FL Ages from 2-5
The goal of this Career Day Visit was to show the students at the learning center what Microbiologists do. We showed them various bacterial slides of both gram-negative and gram-positive bacteria on the electron microscope and compound microscope. We also created bacteria replicas in petri dishes made from jello, mike and ikes, gummy worms, sprinkles and food coloring. We showed the children the different shapes and colors that microbes can form. Lastly, we showed the children the kinds of safety apparel Microbiologists have to wear on a daily basis in the lab.
B-CU student participants: Taylor Brooks, Aakriti Gautam, Jamous Jakeiss, Remi Jones, Laquera Motley, Meshia McCoy, Tangela Tinsley, and Kaylynn Wilson.
Extreme Science and Engineering Discovery Environment (XSEDE) presented its 5th annual conference in Miami Florida, from July 17-21, 2016. The conference showcased discoveries, innovations, challenges and achievements of those who use and support XSEDE resources and services, as well as other digital resources and services throughout the world. This year's themes of XSEDE 16 were diversity, big data, & science at scale. Scientists and engineers around the world use these resources and service supercomputers, collections of data, and new tools, to improve our lives to be healthier and safer.
Bethune-Cookman University was represented at the XSEDE conference by eight students who were accompanied by two faculty members Dr. Raphael Isokpehi and Dr. Aneesah Baker. The students represent a vast diversity of majors and educational backgrounds. The students are cohorts of the Transdisciplinary Data Scholars Development Program, funded by the National Science Foundation. The students and faculty participated in training workshops in informatics, data science, visualization, supercomputing, and python training. The main goal of the Transdisciplinary Data Scholars Development Program is to provide learning experiences that develop participants into professionals who are capable of working effectively with data.