| CTRI Number |
CTRI/2024/12/078507 [Registered on: 24/12/2024] Trial Registered Prospectively |
| Last Modified On: |
23/12/2024 |
| Post Graduate Thesis |
No |
| Type of Trial |
Interventional |
|
Type of Study
|
Other (Specify) [Educational research as a part of NMC Advance Course in Medical Education] |
| Study Design |
Other |
|
Public Title of Study
|
Artificial Intelligence (AI) as a tool for self-directed learning by MBBS students |
|
Scientific Title of Study
|
Generative Artificial Intelligence (AI) as a tool for heutagogical learning in comparison to web crawler search engines and standard textbooks |
| Trial Acronym |
NIL |
|
Secondary IDs if Any
|
| Secondary ID |
Identifier |
| NIL |
NIL |
|
|
Details of Principal Investigator or overall Trial Coordinator (multi-center study)
|
| Name |
Dr Aneesh K V |
| Designation |
Assisstant Professor |
| Affiliation |
Govt Medical College, Manjeri |
| Address |
Dept of Physiology,
1st floor,
Academic block-1,
Govt Medical College, Manjeri
Malappuram
KERALA
676121
India |
| Phone |
09895686247 |
| Fax |
|
| Email |
drkvaneesh@gmail.com |
|
Details of Contact Person
Scientific Query
|
| Name |
Dr Aneesh K V |
| Designation |
Assisstant Professor |
| Affiliation |
Govt Medical College, Manjeri |
| Address |
Dept of Physiology,
1st floor,
Academic block-1,
Govt Medical College, Manjeri
Malappuram
KERALA
676121
India |
| Phone |
09895686247 |
| Fax |
|
| Email |
drkvaneesh@gmail.com |
|
Details of Contact Person
Public Query
|
| Name |
Dr Aneesh K V |
| Designation |
Assisstant Professor |
| Affiliation |
Govt Medical College, Manjeri |
| Address |
Dept of Physiology
1st floor,
Academic block-1,
Govt Medical College, Manjeri
Malappuram
KERALA
676121
India |
| Phone |
09895686247 |
| Fax |
|
| Email |
drkvaneesh@gmail.com |
|
|
Source of Monetary or Material Support
|
| Govt Medical College, Manjeri, Malappuram district, Kerala.India. Pin code:676121 |
|
|
Primary Sponsor
|
| Name |
Dr Aneesh K V |
| Address |
Assistant Professor,
Dept of Physiology,
Govt Medical College, Manjeri. Kerala. 676121 |
| Type of Sponsor |
Other [Self] |
|
|
Details of Secondary Sponsor
|
|
|
Countries of Recruitment
|
India |
|
Sites of Study
|
| No of Sites = 1 |
| Name of Principal
Investigator |
Name of Site |
Site Address |
Phone/Fax/Email |
| Dr Aneesh K V |
Government Medical College, Manjeri |
Dept. of Physiology,
1st floor, Academic block-1,
Pin 676121
Malappuram
KERALA |
09895686247
drkvaneesh@gmail.com |
|
|
Details of Ethics Committee
|
| No of Ethics Committees= 1 |
| Name of Committee |
Approval Status |
| Institutional Ethics Committee, Govt Medical College, Manjeri |
Approved |
|
|
Regulatory Clearance Status from DCGI
|
|
|
Health Condition / Problems Studied
|
| Health Type |
Condition |
| Healthy Human Volunteers |
To compare the effectiveness of using standard textbooks, Google search engine and Perplexity
AI as tools for self-directed learning of Physiology topics by Phase I MBBS students |
|
|
Intervention / Comparator Agent
|
| Type |
Name |
Details |
| Intervention |
Comparison of tools for self-directed learning |
To compare the effectiveness of using standard textbooks, Google search engine and Perplexity AI as tools for self-directed learning (SDL) of Physiology topics by Phase I MBBS students. Total 3 sessions of SDL with 3 different topics will be conducted. Students will be divided into 3 groups. In one session a group will be using only one tool for learning. The tool used will be shuffled for further sessions, so that all the students will be exposed to all 3 tools for SDL. |
| Comparator Agent |
NIL |
NIL |
|
|
Inclusion Criteria
|
| Age From |
18.00 Year(s) |
| Age To |
25.00 Year(s) |
| Gender |
Both |
| Details |
1. Phase I MBBS students
2. Students admitted in the year 2024 |
|
| ExclusionCriteria |
| Details |
1. Students who are not willing to give consent
2. Students who are absent in any of the sessions will be excluded |
|
|
Method of Generating Random Sequence
|
Computer generated randomization |
|
Method of Concealment
|
Centralized |
|
Blinding/Masking
|
Outcome Assessor Blinded |
|
Primary Outcome
|
| Outcome |
TimePoints |
| Knowledge acquisition assessed by post test scores |
baseline
1 week
|
|
|
Secondary Outcome
|
| Outcome |
TimePoints |
| Student perception collected with questionnaire & long-term retention of knowledge |
4 week |
|
|
Target Sample Size
|
Total Sample Size="110"
Sample Size from India="110"
Final Enrollment numbers achieved (Total)= "Applicable only for Completed/Terminated trials"
Final Enrollment numbers achieved (India)="Applicable only for Completed/Terminated trials" |
|
Phase of Trial
|
N/A |
|
Date of First Enrollment (India)
|
03/01/2025 |
| Date of Study Completion (India) |
Applicable only for Completed/Terminated trials |
| Date of First Enrollment (Global) |
Date Missing |
| Date of Study Completion (Global) |
Applicable only for Completed/Terminated trials |
|
Estimated Duration of Trial
|
Years="0"
Months="1"
Days="0" |
|
Recruitment Status of Trial (Global)
|
Not Yet Recruiting |
| Recruitment Status of Trial (India) |
Not Yet Recruiting |
|
Publication Details
|
N/A |
|
Individual Participant Data (IPD) Sharing Statement
|
Will individual participant data (IPD) be shared publicly (including data dictionaries)?
Response - NO
|
|
Brief Summary
|
Generative Artificial Intelligence (AI) as a tool for heutagogical learning in comparison to web crawler search engines and standard textbooks Research question:
Is Perplexity AI a better tool for heutagogical learning of Physiology topics by phase I MBBS students in comparison to Google search engine and standard textbooks?
Hypothesis:
Null hypothesis: Perplexity AI is not a better tool for heutagogical learning of Physiology topics by Phase I MBBS students compared to the Google search engine and standard textbooks.
Alternate hypothesis: Perplexity AI is a better tool for heutagogical learning of Physiology topics by Phase I MBBS students compared to the Google search engine and standard textbooks.
Lifelong learning is one of the roles defined for an Indian medical graduate under CBME. The medical students can be prepared for this role during their course through heutagogical or self-directed learning sessions. Despite the potential of Generative AI tools like Perplexity AI to enhance self-directed learning in medical education, there is little research comparing its effectiveness to conventional resources like textbooks and web search tools. This educational project will help to shed light on the usefulness of Generative AI in medical education especially in the implementation of self-directed learning sessions.
|