As the development and adoption of AI technologies accelerates, teachers are faced with the challenge of embracing the change - without compromising academic standards, or undermining fundamental principles of learning. This is a rapidly changing arena, and the resources below are chosen from a range of institutions and organisations to help educators understand the range of technologies that are becoming available - and how they might be used to impact positively the delivery of oral health education.

ADEE would encourage educators to complete the free Futurelearn online course, 'Generative AI in Higher Education'

Summary of AI Types:

• Iterative Learning / Reinforcement Learning: Involves continual adaptation based on data, learning, and feedback (e.g., ITS, Adaptive Learning Platforms).
• Generative AI: Focuses on creating new content or solutions based on patterns and data (e.g., AI in content creation, educational games).
• Rule-Based AI: Uses predefined rules and structures to process and respond to input (e.g., automated grading, NLP for grammar checks).
• Predictive AI: Uses data and algorithms to predict future outcomes (e.g., Learning Analytics).
• Conversational AI: Focused on human-computer interaction through natural language (e.g., chatbots, virtual assistants).
• Assistive/Reactive AI: Responds to real-time environmental input to aid users, particularly in special education (e.g., robotics, assistive tech).

Generative and Conversational AI

Increasingly AI is being used to assist students with searching the literature. It is important to note that generic and openly accessible Conversational AI tools cannot access databases or other restricted parts of the internet - and so the advice they give, and the results they formulate should be checked carefully. See this post on Insta to demonstrate the pitfalls of asking a Conversational AI tool about published literature

Cardiff University have published a Xerte tutorial on using Generative AI to support literature searching - click here to access this resource

They also provide information to students about the advantages and disadvantages of GenAI and how to acknowledge its use when carrying out in course assessments, or submitting work

Conversational AI is an area which is extremely interesting for clinical educators, as it provides the opportunity for students to interact with AI chat bots who are pre-programmed with a range of attributes, conditions, behaviours and traits - which allow students to interact either freely, or in a more programmed way. These models can allow students to practice taking patient histories, practice conversational skills, or be assessed in their ability to obtain accurate information. Often system will allow educators to provide pre-and post-discussion information and ask students questions before and after the activity. Try this example that was set up by Cardiff University Dental School with Nitin, who is a 7-year-old boy presenting for a check-up. The model contains issues around safeguarding and Nitin also presents with mild autistic tendencies. 

We have two main platforms offering this service at the time of writing, namely SimFlowAI, and SomaLabAI

Assistive AI

To combat the problem outlined above, we are seeing the emergence of paid/subscription services to technologies that utilise AI. The AI assists the user in what would ordinarily be a fairly extensive process - combining the benefits of AI capability, with the limits of robust and credible sources. A good example of this is Elicit, which automated research tasks like summarising papers from databases, extracting data and synthesizing findings. You can access details about it here.