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Access and Student Success in Large Online Programs Matt Leavy – President, eCollege.

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Presentation on theme: "Access and Student Success in Large Online Programs Matt Leavy – President, eCollege."— Presentation transcript:

1 Access and Student Success in Large Online Programs Matt Leavy – President, eCollege

2 Copyright© 2008 Representative clients Higher Education K-12

3 Copyright© 2008 Evolution of Online Program Focus Basic Functionality Turn-key solution Service & Reliability Authoring & Content Management Data Analytics Outcomes Management Interoperability eCollege Enrollments Pedagogy, Teaching Resources, Learning Styles

4 Copyright© 2008 The Promise of Online Education Today 1.Access for new populations of learners 2.Improved learning & Improved Completion 3.Evidence of learning = accountability movement

5 Access

6 Copyright© 2008 Source: The Condition of Education, 2002, NCES, DOE Access for Non-Traditional Learners Percent of Undergrad Students with Non-Traditional Characteristics

7 Copyright© 2008 Market Drivers – Online Growth Bulk of Projected Student Growth Are Ages 22 - 34 NCES, Projections of Education Statistics to 2015, 9/14/2006

8 Copyright© 2008 Access for Under-Prepared Learners In the United States: – Only 70% of students graduate from high school on time – 34% graduate ready for college – 33% of those who make it to college must take remedial courses Alliance for Excellent Education

9 Success

10 Copyright© 2008 Meet Claudia Taking classes in the Fall Didnt have a great high school experience Has a full-time job Older than she looks

11 Copyright© 2008 Meet Claudia Unsure of how online works Motivated to try Has Questions…

12 Copyright© 2008 How Long will I Need to Spend? * Based on Census Enrollment Avg. = 11.67 Avg. = 83.55% BIO COM ECO EDU ENG FIN GEO HIS MGT MKT MTH PHL ZOO Goal = 90%

13 Copyright© 2008 How will I be successful? We focus on three levers through which we can help institutions improve student success in an online environment: 1. Online learning applications that assess student progress and personalize remediation through graded homework exercises. 2. Analysis of activity data, help desk interactions and instructor indications to identify students who display characteristics of struggling. 3. Continuous improvement to online pedagogy in the course design, construction and facilitation.

14 Copyright© 2008 Claudia never was very good at math… She doesnt learn very well from a textbook – Actually, she never opened the textbooks How will she learn online?

15 Copyright© 2008

16 Lots of other students like Claudia use MyMathLab Success rate – University of Alabama, Tuscaloosa Success rate – Onondaga CC, New York Success rate – Youngstown State University, Ohio Success rate – DeVry / Miramar Campus

17 Copyright© 2008 Claudia has a bad day… Her computer breaks Her apartment has termites She has to find a new place to live asap! Notify Administrators Email sent to instructor Auto-generated email sent to Claudia

18 Copyright© 2008 2006 Fall Week 1 Activity – Completed vs. Dropped Student Completed Avg. = 3.1 Dropped Avg. = 1.3 Avg. Student Activity/Section by Department (hrs) Completed Student at Add/DropDropped Student at Add/Drop

19 Copyright© 2008 Claudia is back in business! Back in the course, she becomes engaged in learning She develops a sense of community with her instructor and colleagues She connects with interactive content

20 Copyright© 2008 Interactive Content

21 Copyright© 2008 Case Studies & Simulations

22 Copyright© 2008 Claudia has some trouble in the class Claudia gets frustrated Claudia goes to her instructors office hours The instructor notes in the system that she is having trouble…

23 Copyright© 2008 Not understanding course material Stopped participating Not completing assignments Low exam and/or quiz scores Low grade Other ICCOC Identification Criteria After Term Start

24 Copyright© 2008 Iowa Community College Online Consortium

25 Copyright© 2008 Claudia Completes Her Course

26 Program Improvement

27 Copyright© 2008 Claudias Program There are many reasons that schools want to know how they are doing and how they are improving over time. – Educational mission – Accreditation – Legislative lobby Challenges around externally imposed standards. – Skepticism around our ability to assess learning, particularly in critical thinking disciplines Collegiate Learning Assessment, community assessment? Emphasis around flexible tools for internally developed standards in post-secondary. – Outcomes managers – Portfolios – Program analytics

28 Copyright© 2008 Learning Outcome Manager Learning Outcome Manager Course Content Grades Course Content Grades Institution Outcomes & Rubrics Institution Outcomes & Rubrics A Comprehensive Toolset that Provides an Evidence-based Approach to Measuring Student Achievement of Outcomes Presentation Assessment Accreditation Quality Tagging Repository

29 Copyright© 2008 University Mission Program Goals & OutcomesSpecialization Goals & Outcomes Course Outcomes / Objectives Are Aligned With … Criteria Rubrics Leads To… Score / Benchmark / Adjust Instruction Leads To… Learning Outcomes Manager

30 Copyright© 2008 ePortfolio: Students

31 Copyright© 2008 2006 Completion Rates vs. Enrollments - Department Avg. Section Completion Rate = 77% Department Term Start Enrollments Business I IIIII IV Median Dept Enrollments = 767 Department Completion Rates – Term Start to Term End Other Psychology English Sociology Health Sciences Mathematics Science Computer Science History Biology Humanities Economics Speech Art Criminal Justice Accounting Social Science Philosophy Literature Music

32 Copyright© 2008 Conclusion The extension of access offered by online programs brings into the educational system learners with previously unmet needs. – Convenience – Personalized support The current frontier in large online programs is in the capture and use of data on teaching and learning activity and outcomes. Data is being employed to improve student success through personalized learning and program improvement. Online pedagogy innovation is validated by data.

33 FIN

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