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Implementation Guidelines for Students

As generative AI becomes more integrated into academic and clinical training, students in Communication Sciences and Disorders (CSD) programs must develop responsible and ethical practices for using these tools. This section provides guidance on ethical considerations, proper disclosure, critical evaluation of AI-generated content, and strategies for effective AI use in coursework.

 

Ethical Frameworks for AI Use in Coursework

Generative AI can be a powerful tool for learning, but its use must align with academic integrity, clinical accuracy, and professional ethics. Below are key principles students should follow when incorporating AI into their work:

✔ Transparency – Always acknowledge when AI tools have been used in assignments, research, or clinical materials.
✔ Accuracy & Verification – AI-generated content should be carefully reviewed for errors, particularly in clinical and academic contexts.
✔ Confidentiality & Privacy – Never input real patient or client data into AI systems, as this may violate HIPAA and ethical guidelines.
✔ Critical Engagement – AI should be used as a learning aid, not a replacement for critical thinking and personal effort.
✔ Equity & Bias Awareness – AI systems can reflect biases in their training data. Always evaluate outputs for fairness and accuracy, especially in culturally and linguistically diverse contexts.

Following these ethical guidelines ensures that AI enhances learning without compromising professional and academic standards.

 

Guidelines for Disclosing AI Assistance

Many academic institutions now require students to explicitly state when and how AI tools have been used. Below are suggested ways to properly disclose AI assistance:

✔ In Written Assignments

  • Example Disclosure: “AI tools such as ChatGPT were used to generate an initial outline for this paper. The final content was revised and expanded based on personal research and analysis.”

✔ In Research Papers & Presentations

  • Example Citation (APA 7th Edition):

    • OpenAI. (2023). ChatGPT (March 14 version) [Large language model]. https://openai.com
    • “This literature review was partially assisted by ChatGPT, which provided initial summaries of sources. The final analysis was independently conducted.”

✔ In Clinical or Case-Based Work

  • Example Statement: “AI-generated templates were used as a starting point for this SOAP note. All clinical interpretations and recommendations were made independently.”

Being transparent about AI use demonstrates academic honesty and professionalism, ensuring that AI supports learning rather than replacing independent work.

 

Critical Evaluation of AI-Generated Content

AI-generated responses can sometimes be incorrect, outdated, or biased. To ensure reliability, students should critically evaluate AI outputs using the following strategies:

✔ Fact-Checking

  • Cross-check AI-generated information with peer-reviewed journals, textbooks, and official guidelines (e.g., ASHA, CAPCSD).
  • Avoid relying on AI for clinical diagnoses or treatment recommendations—always verify with evidence-based sources.

✔ Assessing Bias & Fairness

  • AI systems may lack diverse perspectives—check if responses accurately reflect culturally responsive practices in CSD.
  • If an AI-generated case study lacks linguistic or cultural considerations, refine the prompt or manually adjust the content.

✔ Evaluating Clinical Accuracy

  • AI-generated clinical content should be reviewed for alignment with current best practices in speech-language pathology and audiology.
  • When using AI for practice materials, ensure that terminology and assessment methods adhere to professional standards.

✔ Improving AI Outputs Through Refinement

  • Instead of accepting an initial AI response at face value, ask follow-up questions, request explanations, and refine prompts to improve accuracy and relevance.

By critically engaging with AI outputs, students develop stronger analytical skills and ensure their work maintains high academic and professional standards.

 

Skills for Effective Prompting and Refining AI Outputs

To maximize the benefits of AI in coursework, students should learn how to write precise and structured prompts that generate useful responses.

✔ Effective Prompting Techniques

  • Be Specific – Instead of “Explain phonological disorders,” try “Summarize the key characteristics of phonological disorders in children, including examples and treatment approaches.”
  • Request Multiple Perspectives – “Explain the impact of AI in clinical documentation from both an SLP and an ethics perspective.”
  • Ask for Step-by-Step Explanations – “Provide a step-by-step guide for conducting an oral mechanism exam.”
  • Customize for Different Learning Styles – “Generate a summary of fluency disorders in bullet points and a short narrative explanation.”

✔ Refining AI Outputs

  • If an AI-generated response is too general, add context (e.g., “Provide an advanced-level explanation suitable for graduate students in CSD.”).
  • If the content is inaccurate or outdated, ask AI to cite sources (though verification with trusted materials is still required).
  • If AI lacks cultural responsiveness, refine the prompt: “Explain aphasia therapy strategies with examples relevant to bilingual patients.”

Practicing effective prompting and refinement skills ensures that AI is used as a constructive educational tool rather than an unreliable shortcut.

 

Final Thoughts

By following ethical guidelines, disclosing AI assistance, critically evaluating content, and refining AI-generated outputs, students can responsibly incorporate AI into their learning while upholding academic integrity and clinical accuracy. Developing these skills will prepare students for future professional environments where AI may play an increasing role in speech-language pathology and audiology.

Updated November 2025

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