Page 266 - RAQAMLI TRANSFORMATSIYA DAVRIDA PEDAGOGIK TA’LIMNI RIVOJLANTIRISH ISTIQBOLLARI

Data analytics Nutrient database mining Students perform automated clustering

Simulated
counseling Virtual patient via chatbot Students practice interviewing responses

Challenges and Mitigation Strategies
While the advantages are compelling, adopting AI in educational settings
entails risks. Below is a discussion of key challenges and suggested mitigations.
Accuracy, hallucination, and misinformation
AI systems may generate inaccurate or fabricated content (“hallucinations”).
Students must be taught to fact-check, cross-validate, and not accept AI outputs
uncritically. We suggest mitigation as follows; require students to append references,
compare AI suggestions with primary literature, and annotate where they modified
AI content.
Overreliance and erosion of analytical skills
Excessive dependence on AI could hamper development of students’ own
problem-solving or reasoning skills. Mitigation can be design assignments that
require students to reflect on AI’s limitations, or partially disable AI (e.g. “no-AI”
components).
Ethical considerations, bias, and equity
AI models may encode biases (e.g. socio-cultural, food-culture biases), and
access to AI tools may favor better-resourced students. Mitigation: include modules
on algorithmic bias, ensure equitable access to tools, anonymize or randomize
assignments to reduce advantage bias.
Privacy and data security
Some AI tools use servers, logs, or cloud storage, raising concerns about student
data privacy. Mitigation measures include using tools that respect privacy, requiring
anonymization, and emphasizing institutional policies. Privacy protections should be
a policy or system development priority.
Faculty readiness and institutional support
Many instructors lack familiarity with AI tools, or resist change. Institutional
policies may restrict AI use. Mitigation: invest in faculty professional development,
pilot projects, and clear institutional policies promoting guided AI use. It is important
to provide guidelines for AI education policy, either nationally or through the Ministry
of Education.
Implementation Recommendations
Here are actionable recommendations for dietetics programs seeking to
encourage AI use among students: Fist, develop an AI literacy module early in the
curriculum (covering tool types, biases, best practices). Secondly, use scaffolded
assignments where early tasks guide prompt formulation and critique. In third,
model AI use in class (instructors show how they use AI tools and critique outputs).
9
A few more extra activity suggestions are as follows; 10, 11, 12
• Require “human in the loop” review: students must validate and annotate AI
outputs.
• Promote reflective practice: students write short reflections on AI tool
strengths and failures.
• Ensure equity of access: provide institutional subscriptions or free tools to all 264
students.

I SHO‘BA:

Sifatli ta’lim – barqaror taraqqiyot kafolati: xorijiy tajriba va mahalliy amaliyot

https://www.asr-conference.com/