1. The Effect of Student Readiness on Student Success in Online Courses Leah A. Geiger Daphne Morris Susan L. Subocz

2. Research generously funded by Quality Matters

3. Hypothesis 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 factors.

4. individual attributes (such as motivation) life factors (such as time available) comprehension general knowledge reading rate and recall typing speed and accuracy

5. Goal The goal of the study was to determine which of these hypothesized factors correlated most closely to student success.

6. Controls 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 economic classes. 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 earned. The study was considered quantitative as the findings were analyzed through Chi Square tests examining for statistical significance.

8. Statistical Measures Scores from the Smarter Measure Indicator ranges : 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.

10. Findings Life factors, individual attributes, reading comprehension, and general knowledge were not found statistically significant at the 95% confidence level. By contrast, at the 95% confidence level, typing speed and accuracy along with reading rate and recall were found statistically significant.

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 and recall. 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: -located online -available to all students -incorporated into developmental classes as well as credit-bearing ones

14. Questions 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 Measure. It imparts motivation and relevance for an institution to increase its number of QM certifications.