1. AFACCT ’14 Conference, Prince George’s
Session 1.1. January 9, 2014
The Effect of Student
Readiness on Student
Success in Online Courses
Leah A. Geiger
Susan L. Subocz
2. Research generously funded by
The team hypothesized that student success in
well-designed courses (those that meet the QM
standards) and that are taught by engaged
faculty are most influenced by student readiness
individual attributes (such as motivation)
life factors (such as time available)
reading rate and recall
typing speed and accuracy
The goal of the study was to determine which of
these hypothesized factors correlated most
closely to student success.
• The course design was considered high quality, as only
courses which meet QM standards were utilized.
• The learning management system being employed was
industry-standard and well-proven (Blackboard).
• The faculty participating in the study have a proven track
record of student engagement, were highly trained in the
LMS, QM process (Master Reviewer level) and
instructional design, and agreed to abide by certain
"engagement standards" throughout the study.
7. Research Specifics
• CSM is a regionally accredited community college located in
the mid-Atlantic, serving three counties of mixed social and
• Data collected in this study occurred in 11 classes with 200
students over the period of two semesters.
• Smarter Measure test data was aggregated with measures of
academic success as indicated by final course grades
• The study was considered quantitative as the findings were
analyzed through Chi Square tests examining for statistical
8. Statistical Measures
Scores from the Smarter Measure Indicator
• blue (85-100% success)
• green (70%- 84% success)
• red (0%-69% success).
9. Statistical Measures
• Red and green scores were aggregated to
ensure observed values greater than .05 to
ensure statistical significance was measured.
• Final grades for the class were measured as
“successful” at the rate of 70% (C) or higher
(B or A). Institutional policy supports this
valuation as 70% is the cut-off score for credit
being earned for the course as well as its
ability to be transferred to another school.
• Life factors, individual attributes, reading
comprehension, and general knowledge were
not found statistically significant at the 95%
• By contrast, at the 95% confidence level,
typing speed and accuracy along with reading
rate and recall were found statistically
11. Reading Rate Data
12. Typing Speed Data
13. Bringing Meaning to the Findings
• A pro-active online program would pre-test students in
measures of typing speed and accuracy as well as reading rate
• Students found to be deficient in these areas (possibly using
the 70% benchmark or higher) could be placed in remedial
tutorials to increase such skills. These tutorials should be:
-available to all students
-incorporated into developmental classes as well as
What implications could come from these findings?
• It provides a good direction for remediation.
• It demonstrates strength of QM-influence on student
success when quality measures are controlled.
• It encourages colleges to measure students’ readiness
for online learning through analytics like Smarter
• It imparts motivation and relevance for an institution to
increase its number of QM certifications.
Leah A. Geiger:
Susan L. Subocz: