Online Student Readiness and Satisfaction Within Subpopulations

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1 2013 National Research Report Online Student Readiness and Satisfaction Within Subpopulations By Julie Bryant, Noel-Levitz and Dr. Mac Adkins, SmarterServices Which students are better prepared for online learning: younger or older students? How do students in different age brackets rate the strengths and challenges of online education? Do students become more or less satisfied as they complete more online courses? Noel-Levitz and SmarterServices conducted an analysis of online learners to examine these questions, as well as other issues: Older students showed higher levels of satisfaction and a greater likelihood to re-enroll in their online courses. Older students in online courses tend to score higher for personal maturity ratings; younger students score higher for ratings related to technical proficiency. Students who enrolled in four or more online courses had lower satisfaction ratings than those who enrolled in three or fewer, with students in their first online course expressing the highest levels of satisfaction. As students experience with online courses increases, the degree to which their individual attributes are a good match for distance learning also increases. Students across all age categories and experience levels rated academic quality, the value of tuition paid, and the timeliness of faculty feedback as the greatest challenges for online courses. SmarterServices

2 Introduction According to the 2012 Survey of Online Learning conducted by Babson Survey Research Group, over 6.7 million students were taking at least one online course during the fall 2011 term, an increase of 570,000 students over the previous year. Thirty-two percent of higher education students now take at least one online course. Seventy-seven percent of academic leaders rate the learning outcomes in online education as the same or superior to those in face-to-face courses. Sixty-nine percent of higher education institutions now say that online learning is a critical part of their long-term strategy. While online learning is increasing in size and importance for colleges and universities, what about its impact on students? Are they prepared for this shift and satisfied with online learning? In 2011, Noel-Levitz and SmarterMeasure conducted a study to determine whether online readiness, as measured by the SmarterMeasure Learning Readiness Indicator, was predictive of satisfaction as measured by the Noel-Levitz Priorities Survey for Online Learners (PSOL). The data were analyzed from five institutions on an individual student level for students who had completed both assessment tools. The study found that the student readiness constructs of Individual Attributes and Life Factors as measured by the SmarterMeasure Learning Readiness Indicator were statistically significant predictors of online student satisfaction as measured by the PSOL. This 2013 follow-up study focuses on subpopulations of students based on their age and previous online enrollment. Current national data sets for both the SmarterMeasure Learning Readiness Indicator and the PSOL were compared to see if subpopulations of online learners were better prepared and more satisfied with their online learning experience. The researchers also checked if these findings were similar across both instruments. The data were reviewed at the cumulative level from one academic year. Not all students completed both instruments, but the subpopulation identifiers were consistent in both data sets. The results reflect the summary satisfaction and likelihood to re-enroll for each subpopulation, as well as the priority issues for improvement, with an identification of unique issues for particular subpopulations. The results also summarize the readiness for these same populations for online programs. The instruments The Noel-Levitz Priorities Survey for Online Learners The Noel-Levitz Priorities Survey for Online Learners assesses what online learners find most important, as well as their levels of satisfaction. The PSOL includes 26 standard items rated for importance and satisfaction, plus room for up to 10 campus-defined items with similar ratings. The 26 standard items are clustered statistically and conceptually into the following five scales: Academic Services the areas that support the academic experience outside of the classroom (seven items) Enrollment Services the activities related to enrolling students in the program (four items) Institutional Perceptions how students perceive the reputation and the tuition value of the institution (two items) Instructional Services the experiences students are having in the classroom with faculty and assignments (eight items) Student Services the ways that the institution communicates and provides additional service to students (five items) 2 Noel-Levitz, LLC. and SmarterServices 2013 Report: Online Student Readiness and Satisfaction Within Subpopulations

3 In addition, the PSOL captures student perceptions on sources of information and enrollment factors, as well as three summary items: If their expectations have been met; Their overall satisfaction; and If they had it to do over again, would they re-enroll. There are also 13 standard demographic items on the survey. The PSOL provides institutions with data on the priorities of their students, as well as where the institution is performing well and where it has room for improvement. The data can inform institutional decision making for resource allocation and communication plans. The PSOL is often administered annually or every other year to track satisfaction trends and to document where improvements have been made in the student experience. Many institutions also find the data to be useful for accreditation purposes. Since it first became available in 2001, the PSOL has been administered by more than 200 institutions and completed by more than 267,000 students. Additional information about this assessment can be found at The SmarterMeasure Learning Readiness Indicator The SmarterMeasure Learning Readiness Indicator is a 124-item assessment that quantifies a learner s level of readiness for studying online. It measures variables in the following areas: Individual Attributes including motivation, procrastination, and willingness to ask for help (24 items) Learning Styles based on multiple intelligences model (35 items) Life Factors for example availability of time, support from family and employer, finances, and health (20 items) Reading Rate and Recall ability to read a passage online and then demonstrate recall of salient points in the passage (11 items) Technical Competency skills in using online instructional technology (10 items) Technical Knowledge knowledge of computing and online learning vocabulary (23 items) Typing Rate and Accuracy keyboarding skills (one item) The purpose of this tool is to inform students concerning their strengths and opportunities for improvement relative to learning in an online environment. It allows the learner to understand their traits, attributes, and skills, as well as the realities of online learning. A school can identify students who might not be a good fit for online learning, helping to inform course selection decisions and/or provide resources for remediation and support. The SmarterMeasure Learning Readiness Indicator first became available in 2002 and has been completed by over 2.3 million students at over 500 different institutions. Additional information about this assessment can be found at Noel-Levitz, LLC. 3

4 The study This study focuses on data collected from students between June 1, 2012 and May 31, The PSOL results reflect 37,901 student records at 65 different institutions. The SmarterMeasure results include 351,632 complete records from 275 institutions, with a random sample of 2 percent (N=6913) complete records selected for the comparison of means across the demographic variables, to control for the effects of a large sample. The demographic breakouts for the targeted populations were as follows: PSOL Age PSOL Previous Online Enrollment 22% 45 to 54 9% 55 and Older 11% 24 and Younger 29% 25 to 34 38% 4 or More Classes 24% No Classes 29% 35 to 44 38% 1 to 3 Classes SmarterMeasure Age 16% 35 to 44 9% 45 to 54 4% 55 and Older 30% 25 to 34 41% 24 and Younger SmarterMeasure Previous Online Enrollment 19% 4 or More Classes 28% 1 to 3 Classes 53% No Classes In general, the students who completed the SmarterMeasure Learning Readiness Indicator were younger than the students who completed the PSOL. They also were more likely to have no previous online enrollment at the time that they were completing the respective assessment instruments. This makes sense since the SmarterMeasure instrument is usually given at the beginning of a student s experience with online learning, while institutions typically administer the PSOL to currently enrolled students after they have had some experience with an online course. The following analyses isolate the data by the subpopulations to identify the satisfaction and readiness of the respective populations, as well as unique observations for the demographic groups. 4 Noel-Levitz, LLC. and SmarterServices 2013 Report: Online Student Readiness and Satisfaction Within Subpopulations

5 Traditional-age students are less satisfied with and less ready for online learning Data from both instruments indicate that younger students are less satisfied and less prepared for online learning courses. PSOL overall satisfaction and likelihood to re-enroll: age comparisons Students completing the PSOL were asked if they were satisfied with their overall experience and, if given the opportunity, would they re-enroll in the online program again. Here are the percentage of responses to those questions by age category: 73% 74% 74% 75% 76% 76% 76% Satisfaction Percentage Re-enrollment Percentage 73% 68% 66% 24 and younger 25 to to to and older Satisfaction = percentage indicating that they are satisfied or very satisfied Re-enrollment = percentage indicating that they would probably or definitely re-enroll if they had it to do over again While the majority of students 24 and younger are satisfied with their online learning experience, their scores are lower than those reflected for all age categories above age 25. This follows similar patterns observed in satisfaction data from physical campuses, where nontraditional students tend to have higher satisfaction scores. One possible explanation is if nontraditional students are not satisfied with their educational experience, they may not remain enrolled Noel-Levitz, LLC. 5

6 Younger students tended to be significantly less satisfied than older students, while the top two age subpopulations were more satisfied. Satisfaction with PSOL scale categories: age comparisons When examining the satisfaction breakdown by scale throughout the entire data set of 37,901 students, younger students tended to be significantly less satisfied than older students, while the top two age subpopulations were more satisfied when examining the results by scale. Those without a less or more notation showed no significant deviation in satisfaction levels. Scale 24 and younger 25 to to to and older Institutional Perceptions Less Less More More Academic Services Less Enrollment Services Instructional Services Student Service Less More More More Less More These data raise an interesting question: are online institutions serving older adults better, or do older students find the online experience a better fit for their educational needs and expectations? The data here do not point to a definitive answer, but this is an area where an institution could compare results between student populations (by age, by on-campus vs. online if at a physical institution, etc.) to understand student satisfaction more precisely. SmarterMeasure constructs: age comparisons Analysis of Variance (ANOVA) was calculated to determine if differences exist among age ranges for the SmarterMeasure Learning Readiness Indicator. Generally speaking, age did matter as significant differences existed in six of the eight constructs measured. Two differences in particular emerged: Younger students had the highest means for constructs related to technical matters. Older students had the highest means for constructs related to personal maturity. Please note that a higher mean for Reading Rate is not necessarily a good measure, as it likely indicates that the individual is not spending enough time on the reading passage. Construct 24 and younger 25 to to to and older Reading Rate Highest Typing Accuracy Highest Reading Recall Highest Typing Rate Highest Technical Knowledge Highest Technical Competency Highest Life Factors Highest Individual Attributes Highest 6 Noel-Levitz, LLC. and SmarterServices 2013 Report: Online Student Readiness and Satisfaction Within Subpopulations

7 The scale of Individual Attributes on which older students had the highest mean measures factors such as procrastination, willingness to ask for help, persistence, time management, and locus of control. Learners who are 45 or older have had the highest means for Individual Attributes for the past five years of data collection through SmarterMeasure. In this analysis, it is clear that one s individual attributes in relation to online learning do improve with age. Age range 2009 highest mean 2010 highest mean 2011 highest mean 2012 highest mean 2013 highest mean 24 and younger 25 to 34 Academic Attributes 35 to to and older Help Seeking Persistence Academic Attributes Procrastination Time Management Locus of Control Academic Attributes Procrastination Time Management Locus of Control Persistence Help Seeking Persistence Procrastination Time Management Help Seeking Persistence Academic Attributes Procrastination Time Management Locus of Control Academic Attributes Procrastination Time Management Persistence Help Seeking Locus of Control Further analysis was conducted to measure the difference in age ranges for the Individual Attributes factors. Significant differences did exist between the age categories on the factors of individual attributes. In this analysis, it is clear that one s individual attributes in relation to online learning do improve with age. Online learners 55 or older have had the highest means in persistence for the past five years. It is also worthy of notice that for the past five years, traditional-aged college students have not had the highest means in any of the factors of Individual Attributes. PSOL strengths and challenges: age comparisons With satisfaction and priorities assessment, strengths are items of high importance and high satisfaction areas where institutions are doing well in categories that are more meaningful to students. Challenges are items of high importance and low satisfaction, typically areas of high priority for improvement. The individual items on the PSOL were analyzed to identify strengths and challenges. Three items emerged as consistent challenges across all age groups: The quality of online enrollment is excellent. Tuition paid is a worthwhile investment. Faculty provide timely feedback about student progress Noel-Levitz, LLC. 7

8 Several items were viewed as strengths or challenges to only certain age groups: Item 24 and younger 25 to to to and older My program advisor is accessible by telephone and . I am aware of who to contact for questions about programs and services. Appropriate technical assistance is readily available. This institution has a good reputation. This institution responds quickly when I request information. Adequate financial aid is available. Program requirements are clear and reasonable. Strength Strength Strength Strength Strength Strength Challenge Challenge Challenge Challenge Challenge Older students placed a higher priority on technical assistance and support from the institution, but felt positive in those areas. Younger students had unmet expectations on quick responses from the institution, but at the same time, they indicated that their program advisor was easily accessible. Financial aid was a higher priority to younger students, while program requirements were consistently identified as a challenge area for all age groups of 35 and above. Students with less online enrollment are satisfied with but less ready for online learning The results were more mixed when the focus of the data was on the previous online enrollment for students. The online learners with no previous online enrollment had comparable satisfaction levels, but were less prepared for the online learning experience. 8 Noel-Levitz, LLC. and SmarterServices 2013 Report: Online Student Readiness and Satisfaction Within Subpopulations

9 PSOL overall satisfaction and likelihood to re-enroll: previous online enrollment Students who completed the PSOL were also asked to report how many online courses they took. The chart on the next page shows the numbers who said they were satisfied with their online experience and if they would re-enroll again. 76% Satisfaction Percentage Re-enrollment Percentage 74% 74% 74% 73% 72% No previous online enrollment 1 to 3 previous online classes 4 to 6 previous online classes Satisfaction = percentage indicating that they are satisfied or very satisfied Re-enrollment = percentage indicating that they would probably or definitely re-enroll if they had it to do over again These data suggest that students with various prior experiences with online learning have similar overall satisfaction levels with their experience. When the data was explored further, categories where some of these students were significantly more or less satisfied were discovered. Satisfaction with PSOL scale categories: previous online enrollment When compared with the entire data of 37,901 students for , students showed significantly lower levels of satisfaction as they enrolled in more online courses. Scale No previous online enrollment 1 to 3 previous online classes 4 to 6 previous online classes Institutional Perceptions More Academic Services More Less Enrollment Services More Instructional Services More Less Student Services More Less These data follow patterns observed in traditional, on-ground data sets where first-year students tend to have higher satisfaction scores than upper-class students, who have had more experiences to base their responses on (and more opportunity for negative experiences). Like their counterparts in physical classrooms, online students may also feel more comfortable with expressing negative opinions as they have more longevity in the online learning environment Noel-Levitz, LLC. 9

10 Learners who had taken five or more prior online courses had several areas with higher means. SmarterMeasure constructs: previous online enrollment Analysis of Variance (ANOVA) was calculated to determine the impact that a person taking prior online courses had on their readiness. The results demonstrated that experience matters with online learning. In each of the eight constructs measured, as persons took more online courses, they had higher means in all categories, meaning their overall readiness for online learning improved. The differences in the means were statistically significant in six of the seven scales. The greatest difference in means from students with no prior online course experience and those who had taken five or more courses continued to be in the area of technical knowledge, for the fifth consecutive year. This indicates that with experience, students can learn to use the technology required for online courses. The percentage of students taking SmarterMeasure who have never taken an online course is decreasing (2009=65%, 2010=60%, 2011=55%, 2012=54%, and 2013=54%). This is an indicator that distance learning is becoming a more common educational delivery system. Learners who had taken five or more prior online courses had statistically significant higher means for the constructs of Individual Attributes, Typing Rate, Technical Knowledge, Technical Competency, and Life Factors. Those who had taken four or more courses had the highest mean for Reading Recall. The only area that was not significantly different was Typing Accuracy. Number of prior online courses Construct Individual Attributes Lowest Highest Reading Recall Lowest Highest Typing Accuracy Lowest Highest Typing Rate Lowest Highest Technical Knowledge Lowest Highest Technical Competency Lowest Highest Life Factors Lowest Highest Further analysis was conducted to measure the difference in Individual Attributes across online learning experience. Significant differences did exist depending on the number of prior online courses taken in four of the six categories of Individual Attributes. In each case, the highest mean existed for students who had taken five or more online courses. This indicates that as students experience with online courses increases, the degree to which their individual attributes are a good match for distance learning also increases. Number of prior online courses Construct Academic Attributes Lowest Highest Help Seeking Lowest Highest Procrastination Lowest Highest Time Management Lowest Highest 10 Noel-Levitz, LLC. and SmarterServices 2013 Report: Online Student Readiness and Satisfaction Within Subpopulations

11 PSOL strengths and challenges: previous online enrollment As shared in the age analysis, the individual items on the PSOL were analyzed to identify strengths (items of high importance and high satisfaction) and challenges (items of high importance and low satisfaction). The same three items identified as challenges across all age levels were also identified across the previous online enrollment categories: The quality of online enrollment is excellent. Tuition paid is a worthwhile investment. Faculty provide timely feedback about student progress. There were also several items that were viewed as strengths or challenges to only certain previous online enrollment categories: Item No previous online enrollment 1 to 3 previous online classes 4 to 6 previous online classes My program advisor is accessible by telephone and . I am aware of who to contact for questions about programs and services. Appropriate technical assistance is readily available. Adequate financial aid is available. Program requirements are clear and reasonable. Strength Strength Strength Challenge Challenge Students with no previous online enrollment gave positive scores to knowing who to contact with questions and on the technical support they were receiving, while they identified issues with financial aid availability and program requirements. Students enrolled in four to six previous courses had one unique strength regarding program advisors, while students enrolled in one to three previous courses had no unique strengths or challenges. These students appear to be more ambivalent about their online learning experience, neither more or less satisfied than students with more or less experience. Conclusion These observations provide a snapshot of the experiences students had with online learning during the academic year. These data highlight the value of looking within the larger data sets to identify unique perceptions for demographic subpopulations, allowing institutions to target initiatives to particular students appropriately. It is clear that younger students have lower levels of readiness and satisfaction, and those who have had no prior online learning experience are not as prepared. While they may be relatively satisfied, that could be a reflection of optimism brought on by inexperience. These data suggest that students who are younger and have had no experience with online learning should be targeted for appropriate action to better prepare them for the online learning environment. These students should receive focused communication messages to address satisfaction issues and to establish appropriate expectations. Older, more experienced students may also benefit from these efforts, but if budgets and resources are limited, then colleges and universities will want to be sure to target their efforts to the younger, less experienced student populations Noel-Levitz, LLC. 11

12 Appendix PSOL demographic variables of note Characteristic Percentage Gender Female 69% Male 31% Ethnicity/Race Caucasian/White 60% African American 22% Hispanic 6% Other ethnicity 7% Prefer not to respond 5% Enrollment Status Primarily online 94% Primarily on-campus 6% Class Load Full-time 60% Part-time 40% Class Level First year 22% Second year 17% Third year 16% Fourth year 12% Graduate student 29% Other class level 4% SmarterMeasure demographic variables of note Characteristic Percentage Gender Female 69% Male 31% Ethnicity/Race Caucasian/White 54% Students of color 46% 12 Noel-Levitz, LLC. and SmarterServices 2013 Report: Online Student Readiness and Satisfaction Within Subpopulations

13 Participating Institutions: PSOL The following list includes the 65 schools with students represented in the PSOL analysis. AIU-Online, IL Allen Community, KS Argosy University Online, PA Art Institute Online, PA Ashford University, IA Bemidji State University, MN Bon Secours Memorial of Nursing, VA Brookhaven (DCCCD), TX Bryant & Stratton, NY California State University-San Bernardino, CA Capella University, MN Carlow University, PA Central Lakes, MN Central Washington University, WA Champlain, VT Colorado State University-Global Campus, CO Columbia, MO Corban University, OR Crown, MN CUNY School of Professional Studies, NY Cuyahoga Community, OH Dakota State University, SD Education Futures Group, LLC, TX Everglades University, FL Fort Hays State University, KS Friends University, KS Georgia Military, GA Georgia Northwestern Technical, GA Great Falls Montana State University, MT Gwinnett Technical, GA Hope International University, CA Isothermal Community, NC Jones International University, Kettering, OH Lincoln of New England, CT Linfield, OR Mercy, NY Mesa Community, AZ Moberly Area Community, MO Nebraska Methodist, NE Northcentral University, AZ Northwood University, MI Patrick Henry, VA Post University, CT Rio Salado, AZ San Juan, NM Savannah of Art and Design, GA South University Online, PA Southwestern Assemblies of God University, TX Spring Arbor University, MI St. John Fisher, NY State Fair Community, MO Strayer University, DC Sullivan University, KY Texas Woman s University, TX Trident University International, CA University of Illinois at Springfield, IL University of Maryland University, MD University of San Francisco, CA University of the Rockies, CO University of Wisconsin-Stout, WI University of Wisconsin-Superior, WI Virginia -Birmingham, VA Virginia Commonwealth University, VA Walden University, GA Participating Institutions: SmarterMeasure The following list reflects the 275 schools with students represented in the SmarterMeasure analysis. Adams State Air University Alamo-Northwest Vista Alamo-San Antonio Alamo-St. Philip s Algonquin Altamaha Technical Alvin Community Amarillo Angelina Anne Arundel Community Anoka-Ramsey Community Argosy University Arkansas State University Art Institute Online Ashford University Athens State University Atlanta Technical Augusta Technical Austin Community District Bainbridge Beckfield Bellevue University Blackhawk Technical Blinn Bob Jones University Brazosport Briarcliffe Brookdale Community Teaching and Learning Brookhaven Buena Vista University California Baptist University California State University, Fullerton Cape Cod Community Capella University Carl Sandburg Cedar Valley Center for Adult Learning in Louisiana (CALL) Center For Advanced Legal Studies Central Georgia Technical Central New Mexico Community Century Community and Technical Cerro Coso Community Chaminade University of Honolulu Chattahoochee Technical Chesapeake Chicago State University Chippewa Valley Technical Cincinnati State Technical and Community Cisco Clarendon Clark Clark State Community Coahoma Community Cochise County Community District of DuPage of Southern Maryland of the Mainland Sector Committee for Adult Upgrading Collin County Community Collins Colorado State University-Global Campus Columbus State Community Columbus State University Columbus Technical Creighton School of Pharmacy and Health Cuyahoga Community Dallas Christian Dallas s Online Darton Davenport University Del Mar Delta East Mississippi Community Eastfield ECPI University Edison State Edison State - Cornerstone El Centro El Paso Community Empire State Florida State at Jacksonville- Open Campus Fortis Online Front Range Community Gateway Community Harford Community Hill Hillsborough Community Hinds Community Holmes Community Horry-Georgetown Technical 2013 Noel-Levitz, LLC. 13

14 Participating Institutions: SmarterMeasure continued Houston Community System Howard Howard Community Hudson County Community Indian River State International Academy of Design and Technology: Chicago Detroit Las Vegas Nashville Orlando Sacramento San Antonio Seattle Tampa International Distance Ed Certification Center Itawamba Community Ivy Tech Community J. Sargeant Reynolds Community Jefferson Jones County Junior Kennesaw State University Kilgore Kodiak Lanier Technical Laredo Community Le Cordon Bleu of Culinary Arts Scottsdale Lee Lehigh Carbon Community Lone Star System Lorain County Community Lubbock Christian University Madison Manchester Community Maryville University MassBay Community McLennan Community Mesa Community Metropolitan Community - Kansas City Miami Dade Michigan Virtual University Mid Michigan Community Mid-Plains Community Middle Georgia Technical Middlesex Community Midland Midlands Technical Minneapolis Community and Technical Mississippi Gulf Coast Community Mississippi State University Missouri Montcalm Community Moultrie Technical Mount Washington Mountain View National Park Community National University Navarro Nebraska Methodist New River Community and Technical Norfolk State University North Central Michigan North Central Texas North Lake North Park University Northeast Mississippi Community Northeast Texas Community Northern Essex Community Northern Virginia Community Northern Wyoming Community District Northwest Mississippi Community Oconee Fall Line Technical Ogeechee Technical Ohio University Okefenokee Technical Olympic Ottawa University Owens Community Pacific of Oriental Medicine Panola Rochester Institute of Technology Ross San Diego Christian San Jacinto Sanford Brown -Atlanta Sanford Brown -Dearborn Sanford Brown -Fenton Sanford Brown - Grand Rapids Sanford Brown -Houston Sanford Brown -Phoenix Sanford Brown -Skokie Sanford Brown Institute-Dallas Sanford Brown Institute- Ft. Lauderdale Sanford Brown Institute-Jacksonville Sanford Brown Institute-Milwaukee Sanford Brown Institute-Northloop Sanford Brown Institute-Pittsburgh Sanford Brown Institute-Tampa Sanford Brown Institute-Wilkens Township Savannah Technical Scottsdale Community SFMC of Nursing South Arkansas Community South Central South Florida State South Georgia Technical South Plains South Texas Southeast Arkansas Southeastern Technical Southern Crescent Technical Southern Nazarene University Southern University at New Orleans Southside Virginia Community Southwest Georgia Technical Southwest Mississippi Community Southwestern Southwestern Community Spartan of Aeronautics and Technology Spokane Community St. Charles Community St. Louis Community State of Florida, Manatee- Sarasota Stephen F. Austin State University Tallahassee Community Tarrant County Temple Texarkana Texas A&M-Commerce Texas A&M University-Central Texas Texas Woman s University The Community of Baltimore County The University of AL, of Continuing Studies Three Rivers Community Tri-County Technical Trinity Valley Community Truckee Meadows Community Tyler Junior University of Cincinnati-Clermont University of Colorado-Colorado Springs University of Nebraska at Kearney ecampus University of North Carolina at Pembroke University of Northern Colorado University of Southern Indiana University of Texas of the Permian Basin University of Washington University of Wisconsin-Extension University System of Georgia Board of Regents Valdosta State University Vatterott Educational Centers, Inc. Victory University Virginia Volunteer State Community Washtenaw Community Wayland Baptist University Weatherford West Georgia Technical Western Texas Western Wyoming Community Wharton County Junior Whatcom Community Wilmington University Wiregrass Georgia Technical Wisconsin Indianhead Technical Wytheville Community 14 Noel-Levitz, LLC. and SmarterServices 2013 Report: Online Student Readiness and Satisfaction Within Subpopulations

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