Follow-Up Evaluation: Machine Learning and Artificial Intelligence Applications in Translational Science Un-Meeting

Purpose

To elicit participant follow up feedback on the 2019 Machine Learning and Artificial Intelligence Applications in Translational Science Un-Meeting.

Executive Summary

On Monday, June 1st, 2019 an Un-Meeting addressing the topics of Machine Learning and Artificial Intelligence Applications in Translational Science was held at the University of Rochester Medical Center. An evaluation survey was sent to all meeting participants following the Un-Meeting. CLIC conducted post-event evaluations of attendees to examine how well the meeting goals were achieved: one at the conclusion of the Un-Meeting (previously reported), and one at six-months post-Un-Meeting.
This report details the evaluation survey disseminated in December 4th, 2019, six months after the Un-Meeting. Six-month evaluation questions addressed Un-Meeting Collaborations, Value and Overall Experience.

An email and four reminders were sent to attendees at the six-month anniversary of the meeting with a link to the follow-up evaluation survey. At the conclusion of the online survey process, a total of 22 responses were received from the original 94 attendees, for a 6-month response rate of 23.4%. The majority of the respondents (n=15, 68.2%) “Agreed” or “Strongly Agreed” that the Un-Meeting continues to impact their work.

A total of 14 respondents answered a question about actions they had pursued or started to pursue as a result of attending the Un-Meeting. The top three responses were implementing a new research idea (n=8, 57.1%), developing a new pilot project/program (n=4, 28.6%), and collaborating on a grant proposal (n=3, 21.4%).

The survey included open-ended questions, in which attendees were asked to describe any benefits or valuable outcomes of attending the Un-Meeting. The text responses were iteratively coded between three and five times, via an open read through and then they were categorized into core themes. Text responses were independently coded by a minimum of two coders and reviewed iteratively until agreement was reached on the theme or themes present in the response. The most frequently reported themes were “Networking” and “Understanding, learning new ideas” (n=7 and 8, respectively).

Distributed Date
Files

Please log in to access this content

Instrument Fields
Order Instrument Field
1

Please provide your Email Address.
(Only de-identified data will be used for analysis and reporting).

2

From which setting are you?

3

Please specify "other" institutional setting.

4

Please select the name of your Institution.

5

Please specify what "other" institution you are affiliated with.

6

Please select your role (Select the role most applicable to your attendance at the Un-Meeting).

7

Please specify "other" role.

8

Which of these actions have you pursued or started to pursue as a result of the Un-Meeting?

9

Please specify any "other" actions you have pursued/started to pursue as a result of the Un-Meeting.

10

Please briefly describe actions you have pursued/started to pursue as a result of the Un-Meeting, including any new collaborators you have engaged.

11

Please describe any other benefits and/or valuable outcomes of attending the Un-Meeting.

12

Please rate your level of agreement with the following statement: "Attending the Un-Meeting continues to impact my work."

13

Please explain your rating for "Attending the Un-Meeting continues to impact my work."

14

Please provide any additional comments or feedback here:


Submitted by Jacqueline Attia on Fri, 06/19/2020 - 12:50