Number
112
Name
Implementing a Structured Safety Net Review Program to Promote Mastery Learning, Metacognition, and Continuous Quality Improvement in Pre-Clerkship Medical Education
Date & Time
Sunday, June 7, 2026, 5:30 PM - 7:00 PM
Location Name
Oglethorpe Ballroom
Speakers
Authors
Samuel Lorry, University of Cincinnati College of Medicine
Clarence Moore, Jr., University of Cincinnati College of Medicine
Heather Christensen, University of Cincinnati College of Medicine
Andrew Thompson, University of Cincinnati College of Medicine
Presentation Topic(s)
Assessment
Description
PURPOSE:
Starting medical school can elicit significant anxiety and stress, as
students adjust to the increased volume and pace of learning. To help ease
this transition and encourage reflective practice, we implemented a “safety
net program” (SNP) modeled after an approach described at Dartmouth. This
program was piloted in 2024 within our first science-based course, Scientific
Foundations of Medicine. Here, we present focus group findings and student
feedback–driven continuous quality improvement (CQI) that informed the
redesigned program fully implemented in 2025.
METHODS:
The SNP allows students scoring below a predetermined exam threshold to
recover points in real time, rather than potentially remediating the entire
course. During the pilot year, SNP sessions focused primarily on correcting
content-related errors. Using student feedback, the program was expanded in
2025 to incorporate more intentional reflective practices aimed at refining
study strategies and identifying patterns in missed questions or ineffective
learning approaches. In addition to outlining these program updates, we also
summarize 2025 results to highlight common themes among students who
participated in the SNP.
RESULTS:
2025 data demonstrated robust engagement with reflective activities, with
all participants completing both the error quantifying and goal-setting
sections. The most common error indicated by students for answering a
question incorrectly was "Did not know enough detail", which
accounted for 42.1% of all self-reported errors. Furthermore, a significant
gap in cognitive mastery was identified upon examining Bloom's-level
performance: the average upper bound percentage correct for Level 1
(Remember) was 82.7% compared to 68.2% for Level 3 (Apply) questions. This
graphical data, which revealed clear distributions of error types and
category performance, directly informed both student learning plans and
program improvement priorities.
CONCLUSIONS:
The refined SNP supports mastery learning, metacognitive skill development,
and early academic progress. The model is efficient, scalable, and adaptable
to other pre-clerkship settings.
Starting medical school can elicit significant anxiety and stress, as
students adjust to the increased volume and pace of learning. To help ease
this transition and encourage reflective practice, we implemented a “safety
net program” (SNP) modeled after an approach described at Dartmouth. This
program was piloted in 2024 within our first science-based course, Scientific
Foundations of Medicine. Here, we present focus group findings and student
feedback–driven continuous quality improvement (CQI) that informed the
redesigned program fully implemented in 2025.
METHODS:
The SNP allows students scoring below a predetermined exam threshold to
recover points in real time, rather than potentially remediating the entire
course. During the pilot year, SNP sessions focused primarily on correcting
content-related errors. Using student feedback, the program was expanded in
2025 to incorporate more intentional reflective practices aimed at refining
study strategies and identifying patterns in missed questions or ineffective
learning approaches. In addition to outlining these program updates, we also
summarize 2025 results to highlight common themes among students who
participated in the SNP.
RESULTS:
2025 data demonstrated robust engagement with reflective activities, with
all participants completing both the error quantifying and goal-setting
sections. The most common error indicated by students for answering a
question incorrectly was "Did not know enough detail", which
accounted for 42.1% of all self-reported errors. Furthermore, a significant
gap in cognitive mastery was identified upon examining Bloom's-level
performance: the average upper bound percentage correct for Level 1
(Remember) was 82.7% compared to 68.2% for Level 3 (Apply) questions. This
graphical data, which revealed clear distributions of error types and
category performance, directly informed both student learning plans and
program improvement priorities.
CONCLUSIONS:
The refined SNP supports mastery learning, metacognitive skill development,
and early academic progress. The model is efficient, scalable, and adaptable
to other pre-clerkship settings.
Presentation Tag(s)
Student Presentation