Introduction
Learning by actively engaging is key to developing this app to allow new volunteers to learn about Parkinson’s patient (Pp) interaction in a safe environment. This involves conversations and textual depiction of possible responses from Pp. It provides feedback and rubric scoring to assist users in better understanding their involvement and how to improve their interaction with Pp in the future. There are multiple roles that a user can adopt: Volunteer, Professional Caregiver, Doctor and Nurse. Various scenarios can be written to train the Large Language Model (LLM) to accentuate familiarity with these scenarios and minimise, if not prevent, hallucinations.
Experiential Learning (Learning Pedagogy)
Experiential learning (EL) is the pedagogical approach underlying it. It is a process through which individuals acquire knowledge, skills, and values by direct experience. It emphasises active involvement in a task, reflection on that experience, and application of the insights gained.
Based on David Kolb’s Experiential Learning Theory (ELT), the process typically follows a four-stage cycle:
- Concrete Experience – the learner actively experiences an activity (e.g., a lab experiment, field trip, role-play).
- Reflective Observation – the learner reflects on the experience and notes what was observed or felt.
- Abstract Conceptualisation – the learner draws conclusions and learns from the experience, forming theories or generalisations.
- Active Experimentation – the learner applies what was learned to new situations, testing the theories or concepts.
Key Characteristics
• Learner-centred: Places the learner at the heart of the process.
• Contextualised: Often involves real-world or simulated environments.
• Reflective: Emphasises learning from doing and reflecting on it.
• Iterative: Learning is a cycle that builds on past experiences.
Examples of Experiential Learning include Internships or apprenticeships, simulations and role-playing (e.g., Tabletop Exercises), service learning or volunteering, problem-based or project-based learning, and lab experiments and field work.
Case Study Example: Training Nursing Students with a Text-Based Virtual Parkinson’s Patient
Context:
A nursing school uses a text-based simulation platform where students interact with a virtual Parkinson’s Disease (PD) patient named Mr. Tan. The platform is designed to mimic real patient conversations, and it employs conversational AI to simulate Mr. Tan’s speech delays, tremors, medication timing, and emotional states.
Application of Kolb’s Experiential Learning Cycle
Stage Description Example in Simulation
- Concrete Experience Students roleplay as nurses conversing with Mr. Tan, asking questions about his symptoms and care. A student types, “Good morning, Mr. Tan. How are you feeling today?” and gets a slow, shaky reply: “Tired… missed… meds.”
- Reflective Observation After the session, students reflect on their experience. The student notes that Mr. Tan seemed anxious and had difficulty expressing himself.
- Abstract Conceptualisation Students link the experience to medical knowledge and patient care theories. They identify signs of medication non-compliance and relate it to PD symptom worsening.
- Active Experimentation Students revise their approach for future interactions or simulations. Next time, the student checks medication adherence early and uses simpler phrasing.
Learning Outcomes
• Recognise PD symptoms from text cues (e.g. tremors, bradykinesia, sleep issues)
• Practice therapeutic communication
• Adapt communication strategies for neurodegenerative conditions
• Reflect on patient-centred care in chronic disease management
The above flow chart shows the steps through Kolb’s framework’s four main phases.
It is paramount that the application hinges on a sound and proven pedagogy/andragogy that provides structure to the learning.
Experiencing Concrete Experience [1] through a conversation with the Virtual PD patient brings knowledge and lesson reinforcement through reflecting on the experience [2]. The user then attempts to derive his/her strategies to see if they work in this safe environment [3]. Finally, they can equate the experience by formulating their theories and concepts [4].
The Application
The Application uses the trained LLM from OpenAI 4o.
You can visit the link to the Beta Version: https://bit.ly/Edtrix-PSS or scan the following QR code:
Feedback to trainees
What you did nicely:
• Your warm introduction and offer to engage created a trusting atmosphere.
• You allowed Mr. Lim to share his thoughts and feelings without rushing him.
• You maintained a friendly, respectful tone throughout.
Suggestions to improve:
• Consider asking more about Mr. Lim’s experience with Parkinson’s (e.g., challenges or what helps him cope).
• You might also offer light encouragement like, “That must be hard, but it’s amazing you’re still staying positive,” to boost morale.
Well done, Sally. You created a safe, supportive space, just what a person with Parkinson’s needs.
How can PSS use the Virtual PD Application?
• Cost saving to have a textual AI-powered simulator, as compared to a metaverse-like 3D environment.
• Newbies has a chance to practice how to converse with PD patients.
• It might also be a tool to engage caregivers (related persons to the PD patient) in interacting with their PD patient loved ones.
• Able to take on various roles, change the context using written cases in MSWord (no programming is needed)
• Scoring and feedback to encourage trainees on their performance, areas that were done well, and areas of improvement.
Conclusion
This is the first version of a simulated virtual PD patient. We can change the roles, use different cases, different patient age groups, gender and other foreseeable factors to provide a comprehensive experiential learning application that will enhance volunteer training, professional caregiver interaction, and doctor and nurse engagement with PD patients.
Here is the sample system for trial:
This does not replace the real-life interaction between a trainee and an actual PD patient. Still, it provides a safe and engaging environment for learners to understand better a PD patient’s behaviour, language style, and engagement opportunities. This might also provide a buffer so that a new learner will not be surprised or overwhelmed by the actions of a PD patient.
Using Kolb’s framework, we can provide virtual training to people in contact with PD patients.
Mak Wai Keong
• Ed.D, MSc (Mgmt of Technology) and BSc (Chemistry & Math)
• CEO, Edtrix Solutions
• AI Agent developer
• Trainer in AI, Generative AI, eLearning Development Tools, and Educational Technology with Tertiary Infotech and Adept Academy
• Online Resume
• Member of Smart Cities Network – member of the Parkinson’s Society Singapore Work Group
• Former Academic Board member (Ngee Ann Academy)