Page 267 - RAQAMLI TRANSFORMATSIYA DAVRIDA PEDAGOGIK TA’LIMNI RIVOJLANTIRISH ISTIQBOLLARI

• Periodically evaluate outcomes: compare performance, satisfaction, and
critical thinking metrics before/after AI integration.

• Encourage student-led innovation: allow students to propose AI-based mini-
projects or tools as part of capstone work.
By following a phased, reflective, and policy-supported approach, dietetics
programs can harness AI benefits while maintaining educational integrity. In table 3,
we suggest proposed roadmap for integrative AI use for Dietetics Program.

Table 3. Proposed roadmap for integrating AI into dietetic curriculum

Phase Activities Support needed Evaluation metric

Awareness & Workshops on AI literacy, Faculty training, platform Student surveys of
training tool demos licenses understanding
Guided Scaffolded assignments with Sample prompts, guardrails Quality of student AI-
assignments AI prompts augmented work

Independent Students choose AI tools for Support sessions, oversight Impact on project
use projects quality/time

Reflection & Students critique AI outputs Reflection prompts, peer Depth of critique in essays
critique discussion
Continuous Adjust tools & policies Institutional support Longitudinal outcomes
improvement (grades, satisfaction)

CONCLUSION
In the dynamic landscape of nutrition and health sciences, AI tools are
increasingly becoming part of professional practice. For dietitian education
programs, encouraging students to adopt and critically engage with AI tools yields
multiple practical benefits: personalized learning, time savings, enhanced analytical
capacity, and readiness for AI-augmented professional environments. Although
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challenges exist—accuracy, overreliance, bias, faculty readiness—they can be
mitigated via pedagogical design, reflective scaffolding, and institutional support.
Ultimately, integrating AI into dietetics education can help cultivate a generation of
dietitians who are not only nutrition experts but also discerning users (and perhaps
creators) of AI tools.

REFERENCES

1. Generative Artificial Intelligence as a Tool for Teaching Communication in
Nutrition and Dietetics Education—A Novel Education Innovation, Lisa A
Barker, Joel D Moore, and Helmy A Cook, Nutrients 2024 Mar 22;16(7):914.
2. The Role of Artificial Intelligence in Nutrition Research: A Scoping Review,
Andrea Sosa-Holwerda, Oak-Hee Park, Kembra Albracht-Schulte, Surya
Niraula, Leslie Thompson, and Wilna Oldewage-Theron, Nutrients 2024
Jun 28;16(13):2066.
3. Applications of Artificial Intelligence, Machine Learning, and Deep
Learning in Nutrition: A Systematic Review, Tagne Poupi Theodore 265

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