Page 263 - RAQAMLI TRANSFORMATSIYA DAVRIDA PEDAGOGIK TA’LIMNI RIVOJLANTIRISH ISTIQBOLLARI

“RAQAMLI TRANSFORMATSIYA DAVRIDA

PEDAGOGIK TA’LIMNI RIVOJLANTIRISH
ISTIQBOLLARI”

PRACTICAL REASONS TO ENCOURAGE STUDENTS IN DIETITIAN
EDUCATION PROGRAMS TO USE AI TOOLS

Author: SUHHYUN KIM, PhD
1
Affiliation: Head of Department of Dietetics and Nutrition Bucheon University in Tashkent,
Uzbekistan 1
DOI: https://doi.org/10.5281/zenodo.17331803

ABSTRACT

In contemporary health sciences education, artificial intelligence (AI) tools are emerging as
valuable assistants. For students in dietetics education programs, encouraging judicious use
of AI can foster deeper learning, efficiency in tasks, and preparation for future professional
environments. This article outlines practical reasons to support AI adoption in dietetic
curricula, addresses potential risks, and proposes strategies for implementation. Three
illustrative tables present comparative features, application domains, and a recommended
integration roadmap. The article concludes that with appropriate guidance and ethical
framing, AI tools can become powerful adjuncts in dietitian training.

Keywords: Artificial Intelligence, Dietetics Education, AI Tools, Nutrition Students, AI
Adoption, Pedagogy.

INTRODUCTION
In recent years, AI tools—particularly generative large language models,
machine learning systems, and image-recognition software—have begun to reshape
many domains, including health and nutrition sciences. Within dietitian education,
these technologies offer opportunities to enhance student learning, streamline
routine tasks, and prepare learners for AI-augmented professional practice. Yet
1
integration remains limited and cautious due to concerns about accuracy, ethics, and
dependency. This article argues that encouraging dietetics students to use AI
2
tools—under structured guidance—yields multiple concrete benefits. We first review
AI in nutrition/dietetics, then present practical rationales, consider challenges, and
propose integrative strategies.
Background: AI in Nutrition and Dietetics
Overview of AI applications in nutrition
Artificial intelligence has been applied in multiple nutrition domains—dietary
assessment, food image recognition, personalized diet recommendation, predictive
modeling, and remote monitoring. For example, AI-assisted dietary assessment
3
tools (image-based or sensor-based) have achieved accuracy comparable to or
sometimes exceeding traditional self-report methods. AI systems have also been
deployed to predict dietary patterns, estimate nutrient intake, or generate meal
plans adapted to individual patient data. Within dietetics education specifically,
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some efforts are underway: for example, the ATLAS platform provides voice-to-chat 261
virtual patients for training communication skills in dietetic curricula. Also, the
1

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