TCU Digital Culture & Data Analytics Program

Thinking about an internship for Fall 2026?

DCDA 40273: DCDA Internship gives students a way to connect digital culture, data analytics, writing, communication, design, research, and technology skills to real workplace experience.

The course counts for three hours of academic elective credit toward the DCDA major or minor. Interns complete digitally intensive work such as research, data analytics, audio or video production, web authoring, social media, or related project work for 8-20 hours per week, totaling 120-160 hours during the semester.

The timing is good. NACE reports that employers expect to hire 3.9% more interns in 2025-26 than they did in 2024-25, and internships can be an important path toward full-time opportunities.

Internships are especially valuable because they help students build evidence of what they can do:

applying classroom skills to real projects

working with teams, clients, users, or community partners

translating technical work for nontechnical audiences

reflecting on how digital tools and data shape decisions

building examples for resumes, portfolios, interviews, and graduate applications

Students interested in DCDA 40273 for Fall 2026 should start planning now. Internship placements, approvals, and registration steps can take time.

Interested? Review the DCDA Internship page, then contact Dr. Curt Rode at [email protected] to discuss enrollment.

Learn more:
https://cdex.tcu.edu/dcda-internship/



https://naceweb.org/job-market/trends-and-predictions/employers-expect-to-hire-nearly-four-percent-more-interns-this-year

AI ethics is not just an abstract debate. It is a practical design question.

MIT News recently highlighted a research framework for testing whether AI decision-support systems align with human-defined ethical criteria. The example is useful for students: an AI system might optimize for measurable goals like cost or reliability, while still creating unfair outcomes for different communities.

That is exactly why DCDA matters.

Students working with data and technology need more than technical fluency. They also need the habits of the humanities and social sciences: asking who is affected, which values are engaged, what trade-offs are hidden, and how evidence should be communicated before systems are deployed.

Questions worth asking:

Who benefits from this automated decision?

Who becomes more vulnerable?

Which values are measurable, and which are harder to quantify?

How should technical systems be tested against human consequences?

Read the MIT News article:
https://news.mit.edu/2026/evaluating-autonomous-systems-ethics-0402

Evaluating the ethics of autonomous systems SEED-SET is a new evaluation framework that can test whether recommendations of autonomous systems are well-aligned with human-defined ethical criteria. It can also pinpoint unexpected scenarios that violate ethical preferences.