Student Engagement and Programs

CAIDS Data Peer Mentors act as teaching assistants, guiding fellow students who take data courses at CAIDS by exploring and troubleshooting data questions and problems during support sessions. Peer mentors help shape positive and supportive learning communities around data.

Program Objectives

1. Foster a positive learning environment for students at all data literacy levels by actively building learning communities around care, mutual support, and curiosity.
2. Make data education accessible to all undergraduate students through assessment feedback and curriculum support sessions (office hours, group sessions, tutoring).
3. Uses equitable data strategies while collecting and analyzing student data such as grades, attendance, and surveys.  
4. Support in the development of new course materials around data literacy topics.

Types of Projects:

Students will discover data skills relating to Data Literacy, Data Analysis, Data Visualization, and Generative AI by: 

• Providing weekly support sessions on data and data technologies through office hours, one-on-one tutorials, and group learning,
• Collecting and analyzing student data such as troubleshooting questions, attendance and surveys,
• Supporting instruction by grading assignments and providing constructive feedback, managing course content in LMS, researching topics for new course material, leading lab sessions, and proctoring exams, as requested,
• Planning socials such as screenings about data topics,
• Meeting with students individually and those working in groups,
• Sharing information and opportunities about CAIDS and other data events with students,  
• Meeting monthly with other peer mentors to discuss teaching strategy and to write a joint poster on data literacy and teaching for the CAIDS Data Zine and Poster Session. 

Our Data Ambassador Council (DAC), a diverse cohort of undergraduate and graduate students, is a focal point of student input and engagement at CAIDS.  As advocates for data equity, DAC members communicate CAIDS initiatives to the student body at Tulane and act as a student-led focus group that explores data initiatives and solves problems to ensure that CAIDS data programming supports the needs of Tulane students.

Program Objectives:

1. Collects information and provides feedback on the data needs (curriculum, programming, workshops, etc.) of undergraduate and graduate students at Tulane University.
2. Works collaboratively as a focus group to brainstorm and solve problems around data programming.
3. Produces projects and products to openly share information across campus about CAIDS student programming and curriculum.

Project Types:

Students will discover data skills relating to Data Collection (Surveys), Focus Groups, Data Visualization, Graphic Design, Science Communication, and UX/UI by:

• Designing campaigns around swag, posters, and social media using graphic design.
• Developing and administering surveys and polls on campus about data initiatives,
• Sharing information with Tulane students through event planning, tabling, and presentations,
• Showcasing advocacy work with a poster at the CAIDS Data Zine and Poster Session.

Undergraduate and graduate interns collaborate on the Data Developer Internship scrum team, gaining data skills and product development experience. They actively contribute to data research projects led by Tulane faculty, staff, and community partners. In partnership with Newcomb Institute, students practice data equity methods.

Program Objectives:

1. Solves multi-disciplinary research questions using data research methods supported by equity frameworks. (e.g., queer, feminist, social justice pedagogies and epistemologies).
2. Works collaboratively as a team on a range of data research projects of Tulane faculty and community partners while building a portfolio of data and essential skills.
3. Continually focus and reflect on building projects and relationships around data equity frameworks such as partnership and reciprocity, collaboration, leveraging resources, and agentic co-education.

Project Types:

Students will discover data skills relating to Data Collection and Management, Metadata, Data Analysis, Data Visualization, Programming, Project Management, Data Communication

• Developing Apps, Digital Archives, Visualizations, GIS Maps, Databases, and other data scholarship projects.
• Working with spreadsheets to include data entry, data collection, data cleaning, and data analysis, and data visualization. 
• Creating websites, social campaigns, and academic posters related to data projects. 

Previous Lab projects from Newcomb Institute and CAIDS can be viewed via our student-produced Data and Technology Zines.