From Utopia Through Dystopia
Charting a Course for Learning Analytics in Competency-Based Medical Education
Bibliographic Data
The transition to the assessment of entrustable professional activities as part of competency-based medical education (CBME) has substantially increased the number of assessments completed on each trainee. Many CBME programs are having difficulty synthesizing the increased amount of assessment data. Learning analytics are a way of addressing this by systematically drawing inferences from large datasets to support trainee learning, faculty development, and program evaluation. Early work in this field has tended to emphasize the significant potential of analytics in medical education. However, concerns have been raised regarding data security, data ownership, validity, and other issues that could transform these dreams into nightmares. In this paper, the authors explore these contrasting perspectives by alternately describing utopian and dystopian futures for learning analytics within CBME. Seeing learning analytics as an important way to maximize the value of CBME assessment data for organizational development, they argue that their implementation should continue within the guidance of an ethical framework
Analytics · Data Analysis · Data science · Dystopia · Learning analytics · Medical education · Artificial Intelligence in Healthcare and Education · Computer Science · Innovations in Medical Education · Medicine · Psychology · Radiology practices and education · Artificial Intelligence
Deidentifying Narrative Assessments to Facilitate Data Sharing in Medical Education
Entrustable Professional Activities
Competency-based medical education
Data sharing and big data in health professions education
Defining new roles and competencies for administrative staff and faculty in the age of competency-based medical education
Implementation of competence committees during the transition to CBME in Canada
Using learning analytics in clinical competency committees
A New Initiative on Precision Medicine
Ethical and privacy principles for learning analytics
Numbers Encapsulate, Words Elaborate
Entrustable Professional Activities and Entrustment Decision Making
Building the Bridge to Quality
Using Longitudinal Milestones Data and Learning Analytics to Facilitate the Professional Development of Residents
It’s a Marathon, Not a Sprint
Harnessing the Potential Futures of CBME Here and Now
The Evolution of Assessment
Elucidating system‐level interdependence in electronic health record data
Application of continuous quality improvement to medical education
Beyond summative decision making
Becoming a deliberately developmental organization
Capturing outcomes of competency-based medical education
Ten caveats of learning analytics in health professions education
Outcomes of competency-based medical education
We Are All Social Scientists Now
Learning Analytics
| Unique citing works | 7 |
|---|---|
| Citations per year | 1,4 |
| Citation span | 2021 - 2024 (4) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 7 |