Page 143 - JRCERT Update Articles
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JRCERT Update
A Picture Is Worth a Thousand Words:
Visualization in Data Analysis
Tricia Leggett, DHEd, R.T.(R)(QM)
ssessment is not merely collecting and report- Box
ing data, but also analyzing the results to rep- JRCERT Standard 5: Assessment 1
resent the current state of student learning
Aand program effectiveness. Educators can The program develops and implements a system of planning
and evaluation of student learning and program effectiveness
communicate data in many ways; a narrative often is outcomes in support of its mission.
appropriate for qualitative data, whereas quantitative Objective 5.4: Analyzes and shares student learning outcome
data often are shown in a table, chart, or graph. No mat- data and program effectiveness data to foster continuous
ter how data are communicated, it is crucial that the program improvement.
information accurately reflects the level of student
learning or the effectiveness of a program. Joint Review
Committee on Education in Radiologic Technology This article demonstrates methods of data visualiza-
(JRCERT) standards require programs to analyze and tion as well as explains its importance in identifying
communicate results as identified in Objective 5.4 program strengths and weaknesses. Please note that
(see Box). Sharing information with communities of all the data in the examples, with the exception of
interest whose members come from diverse professional the American Registry of Radiologic Technologists
backgrounds requires educators to present data in (ARRT) radiography examination content sections,
numerous ways that “tell the story.” Data visualization were created by the author to demonstrate visualization
can help educators understand data and identify pro- techniques.
gram successes as well as areas for improvement.
Educators often collect program data, but might Sources of Data
be unsure how to use the information to evaluate the Educators collect data from multiple sources: inter-
effectiveness of a program or communicate the impor- nal direct data (eg, evaluations by program faculty),
tance of the information to others. Data visualization external direct data (eg, evaluations by clinical staff),
techniques simplify complex data and present it in a and indirect data (eg, graduate and employer surveys).
comprehensible, insightful, and actionable way that sup- Direct data is described as measurement of student
ports the assessment process. Further, data visualization learning that determine whether the content has been
and analysis do not necessarily require a statistician and masterered, whereas indirect data is generally a reflec-
much can be completed with easily accessible software tion of a student's learning. Organizing data in charts,
2
programs. graphs, or tables is the next step after data collection.
RADIOLOGIC TECHNOLOGY, September/October 2017, Volume 89, Number 1 79
Reprinted with permission from the American Society of Radiologic Technologists for educational purposes. ©2019. All rights reserved.