Faculty TIDES Grants

The Connolly Alexander Institute for Data Science (CAIDS), in partnership with NTC College Programs's First-Year Experience, is offering grants to support faculty in the development of data-centered First Year Seminars, known as TIDES (Tulane Interdisciplinary Experiential Seminar). These grants aim to encourage faculty to develop new data-focused TIDES courses or add more data-centered course content to their existing TIDES offerings. 

 

Applications are now open for Fall 2026 & Spring 2027! 

Submission Deadline: The deadline for grants in preparation for TIDES courses offered in Fall 2026 and Spring 2027 is January 30, 2026 at 11:59 pm. 

Link to Application: Applications are open beginning October 15, 2025. Click here to apply. 

Grant Contact: If you have questions about the application and/or funding criteria, please contact Lisa Dilks, Professor of Practice & Associate Director for Curriculum and Assessment at CAIDS (ldilks@tulane.edu).

 

Funding Criteria, Amounts, and Eligibility

 

Funding Criteria:

In an era driven by the exponential growth of and reliance on data, possessing the skills to effectively navigate and comprehend information is vital. Furthermore, developing a solid foundation in data literacy is an essential competency for everyone. Data literacy entails not only the ability to analyze numerical data and visualizations but also the capacity to critically evaluate, interpret, and communicate data insights from a variety of data types and sources. The field of data uses broad and interdisciplinary approaches and can encompass all areas of specialization. This is not limited to only a quantitative- or numerical-based data literacy, but encompasses all forms and functions of data work related to qualitative, textual, spatial, image, and audio data, along with skills in data communication, presentation, storytelling, analysis, and ethics, as well as the use and understanding of AI.

At CAIDS, we are dedicated to creating, fostering, and supporting a comprehensive and inclusive culture of data literacy, including those data literacy elements related to artificial intelligence (AI). One of our programmatic initiatives is increasing the prevalence of data literacy across the Tulane and NTC curricula. Data-centered curricula provides students with an overview of what data is, how it is used correctly and incorrectly, how it is collected, managed and analyzed, and how it can be used as a basis for critical thinking and decision-making. The inclusion of data-centered learning in TIDES courses can help students understand how data shapes their environment and how data literacy is a crucial component of all fields of study.

To this end, there are a myriad of ways faculty can create data-centered TIDES courses or add data-focused content to existing courses. Topics that would constitute course content relevant to "data" may include, but are not limited to, the following student learning outcomes: 

  • DATA EVALUATION: Students accurately interpret, explain, and apply the results produced by data analyses and methods of data visualization, recognizing any limitations from data sources, analytical, and/or visualization techniques.
  • DATA COLLECTION: Students access and/or collect data and learn about issues related to data privacy and security as well as the quality, trustworthiness, and limitations of different data sources.
  • DATA ANALYSIS: Students identify and perform appropriate descriptive and/or inferential data analyses on various data sources (e.g., quantitative, text, spatial) and explain/interpret the analytical results and limitations of those methods.
  • DATA COMMUNICATION: Students clearly, effectively, and honestly communicate insights from data work in oral, written, and visual forms to professional and lay audiences.
  • DATA ETHICS: Students identify, explain, and evaluate issues of data ethics, privacy, and governance in various aspects of data-related work (e.g., collection, analysis, communication) and discuss solutions for creating socially responsible and beneficial data practices.
  • DATA & TECHNOLOGY: Students competently use appropriate data tools and software to perform data-related tasks or complete data work.
  • AI LITERACY: Students learn to engage, create, and/or design AI, while critically evaluating its benefits, risks, and ethical/social implications.  

 

Funding Amounts:

Grant support is offered via a tiered system wherein awards increase with the amount of new course content that is data-focused:

  • $1000 for the creation of a new TIDES course or significant revision to an existing TIDES course that focuses primarily on data. In these courses, data-focused topics and coursework constitute at least 50% of the course content.
  • $500 for the creation of a new TIDES course or revision to an existing TIDES course that focuses partly on data. In these courses, data-focused topics and coursework constitute at least 20-49% of the course content.
  • $100 to $500 for the creation or addition of course modules centered on data. These modules may be included in either new or existing TIDES courses, with the maximum award amount available for larger modules (20% of course content) and the minimum award amount available for smaller modules (at least one hour or one class period of instruction).

 

Eligibility Criteria:

TIDES Faculty Grants are open to:

  • Any instructor(s) scheduled to teach a TIDES course(s) in Fall 2026 or Spring 2027. Receiving the grant funding is contingent on new TIDES course proposals being approved by the NTC Curriculum Committee and new or existing TIDES courses being placed on the Fall 2026 and/or Spring 2027 TIDES course schedule.
  • These grants are meant to support course development so instructors will apply in advance of course approval and class scheduling. Final award notices will be made once a course is confirmed on the TIDES course schedule.
  • Instructors who are co-teaching TIDES courses are eligible to apply. Grant support will be split between instructors unless otherwise indicated in their application. 

 

Required Application Documents:

Applicants are required to submit the following documents: 

  • A copy of their TIDES course syllabus.
  • Short statement (500 words) on how the course content or module(s) fits the funding criteria (outlined above).
  • Documentation explaining/outlining the proposed data-centered content to be created for the course.

 

Requirements of Grant Recipients:

Grant recipients agree to the following requirements: 

  • Allow CAIDS to feature their grant-related work on our website and/or social media.
  • Recipients will consider, if requested, presenting their grant-related work at a CAIDS event (e.g., workshop, seminar, Love Data Week, Lunch and Learn Series, etc.).
  • Listing CAIDS as a sponsor of the resulting work at public lectures and in publications (i.e., “This project/publication/poster was supported by Tulane University’s Connolly Alexander Institute for Data Science. Its contents are solely the responsibilities of the author(s) and do not necessarily represent official views of Tulane University or the grant funder.").