Profiling the Success of Online Students Through Their Chosen Learning Environments

Concurrent Session 1

Brief Abstract

Using Astin's IEO model as a lens to better understand online students' experiences with their educational environments in an effort to improve academic achievement.

Presenters

Lead Presenter: Maeghen L MacDonald, Pennsylvania State University

Maeghen is currently a doctoral student at Penn State University in pursuit of her PhD in Higher Education with a minor in Adult Education. During her doctoral studies she will be focusing on student success and online education. Maeghen is also pursuing graduate certificates in the fields of Institutional Research and Distance Education during her time at PSU. Outside of her studies, Maeghen is the graduate assistant for the Center of Online Innovations in Learning at PSU as well as Co-Chairing the archiving and narrating the history of Penn State's World Campus with Executive Director Emeritus Gary Miller and Vice President for Outreach/Vice Provost for Online Education Craig Weidemann. Maeghen has previously served as Assistant Dean for the College of Professional Studies at Alfred University and worked in Corporate Development at Tutor.com. Maeghen holds a Master of Business Administration in Executive Management from St. John's University, and a dual Bachelor of Arts in Communications and Political Science with minors in Criminal Justice, Marketing, and Public Law from Alfred University.

Extended Abstract

Topic
Using Astin's I-E-O model as a lens through which to better understand online students' experiences with their educational environments in an effort to improve their academic achievement.

Proposed Study Framework
Alexander Astin's I-E-O Assessment Model
The I-E-O model was developed by Alexander Astin to serve as a conceptual guide for studying college student development. The foundation of the model is based in the elements of inputs (I), environment (E), and outcomes (O) and the interaction between the three. Inputs are defined as characteristics of the student at the time of initial entry; environment is defined as the various programs, policies, faculty, peers, and educational experiences to which the student is exposed; and outcomes refer to the student's characteristics after exposure to the environment (Astin, 1993). Astin (1993) states the "purpose of the model is to assess the impact of various environmental experiences by determining whether students grow or change differently under varying environmental conditions." Astin and Antonio (2012) believe that the environmental information is the most critical in the model as the environment includes those things that the educator and institution directly control to develop the student's outcomes.
The variables can be used in different ways but Astin and Antonio (2012) refer to the outcomes as dependent variables, environmental and inputs as independent variables and also inputs as control variables. The arrows in the above Figure of the model represent the relationships of the variables with relationship B (environment and outcomes) as the most important for assessment and evaluation of education (Astin & Antonio, 2012). However, the relationship between environments and outcomes cannot be explained without consideration of the student inputs that can be related to both outcomes (relationship C) and environments (relationship A). Since inputs can be related to both outcomes and environments, inputs can then affect the observed relationship between environments and outcomes. This design allows for educators to measure input characteristics of each student and then correct/adjust these input differences to get a less biased estimate of the comparative effects of different environments on outcomes (Astin & Antonio, 2012). The combination of the three types of variables is necessary due to the concept of if you have input and outcome data of students is of lesser or limited value if you don't know what was occurring during the students learning over the same period of time. The choice of environmental factors to consider in the model are those that you may change or control because if that is possible then you can improve these factors to influence more desirable outcomes for inputs as a whole or in groups.

The Study
This study will be unique in that Astin's I-E-O model has not been fully applied to understanding and profiling online students. V.A. Thurmond (2001, 2002, 2003) completed three studies using Astin's I-E-O model for studies in student satisfaction of web-based courses in the early 21st century. These studies were focused on the topic of student satisfaction and used the measurement in association with the I-E-O model to predict re-enrollment, controlling environmental variables, and the combination of I-E-O with Middle Range Theory.
The proposed study will provide a profile of students categorized by inputs aligned with their learning environments that result in success. Correlations of environmental factors and inputs that lead to a "non-success" will also be highlighted. "Non-success" is defined as a grade lower than a C in a course, or an overall grade point average of below 2.0. An example of a student profile is as follows: a female, 25-35 years old, 30 credits completed, part-time learner with federal loans who is most successful exclusively online in the community college environment versus a state four-year college or state research university. This study will provide a more detailed view of the profile of current online students and how particular environments may contribute to students' academic success. The study will use correlation and regression analyses to develop profiles of students.

Research Questions
1. What input characteristics are highly correlated with online students' educational environments for a desired outcome of 3.0 GPA or higher?
2. What input characteristics are highly correlated with online students' educational environments for a negative outcome of a 2.0 GPA or lower?
3. How much does the environment account for success of the student and their inputs?
4. How similar or different are online students based on institutional type regarding their input profile and levels of success?

This presentation is sought to be explored with feedback from practitioners in online education. This study seeks to find commonalities of students achieving success in vary institutions of varying levels (community college to large research universities). The results of this study could lead to the ability to target certain students based on their inputs and the environment they are in for student support, recruitment, course placement, and learning style to achieve a higher level of student success.