Increase Revenue with Modern Continuing Education Software
How using modern eCommerce principles drives revenue in Continuing Education
This article was originally published on March 22, 2017
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Areas such as online education, credit for prior learning, and student retention are just as critical now as they were when these stories were written.
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Observers and leaders across the higher education space have been saying for years that the status quo no longer works when it comes to institutional management and student success. While budgetary issues and shifting expectations have driven this conversation, the growth of the online learning environment really hammers this home. An entirely different approach to education than traditional, face-to-face offerings, online learning demands unique approaches to management, support and success. Underpinning these efforts are data analytics, which can be leveraged by institutional leaders to identify trends, design policy and intervene as necessary. However, higher education institutions are not the average business, and the use of that data must be carefully considered. In this interview, Phil DiSalvio examines these critical issues around leveraging data to support students in the online environment.
Phil DiSalvio (PD): We know that online learners face different retention challenges. There’s no single dominant reason explaining why students drop out of an online learning course. In fact, the research shows that there are a number of reasons why students drop out. Nonetheless, with the ever-increasing demand for online learning and institutions becoming more dependent on online revenues, we must identify and act upon strategic initiatives that increase retention among the online student population. Additionally, boosting online retention rates is fundamental in an accrediting environment that is increasingly demanding outcomes and results. Because the experience for the online learner is different than for the traditional on-ground student, there are different challenges in retaining the online student. For example, where classroom learning tends to be more instructor-led, online learning is student-focused and participative and the professor is a facilitator in online learning. Because of its asynchronous nature, it requires considerably more self-direction and time management, students must gauge the amount of time to complete assignments and set their personal schedules accordingly. Most of the communication is written, therefore solid writing skills are important for success. As a result, students attending online classes might be surprised to find that the convenience of flexible hours are outweighed by the inconveniences of a high demand on lifestyle, the technical issues and the concern for the attitude and aptitude.
PD: Social interaction is certainly a factor in persistence, but I have seen cases where in some online courses the students forge a much more intimate learning community because of the ongoing, sometimes daily, contact between their fellow students and professor. If a course is designed in a way that encourages social interaction, and there is a high level of faculty presence, the issue of isolation and distance can be mitigated. Although distance may separate people geographically, it does not mean that technology can’t, in fact, bring them closer together and improve the learning experience. We’re still in the early stages of understanding online learning and the implications that this mode of delivery has on learning, retention and student success. More research has to be done. Again though, I can’t stress strongly enough that online learning is different and retention strategies have to conform to the needs of the student in that mode of delivery.
PD: There is no doubt that there are issues unique to the online learning environment. Online learning requires considerably more self-direction and time management from students than traditional offerings. Added to that is the fact that online students must be willing to take the initiative to reach out to their professor or advisor if they are having difficulties. Moreover, the processes that support effective online learning must include students practicing digital responsibility in interacting with others, digital literacy, organization of online content, and synthesizing large quantities of information. Students must also acclimate themselves to a new networking and social interaction environment. One of the great benefits of online learning I often hear is that you can learn at any time or any place. I think that’s a myth—anytime or anyplace really means being self-disciplined and being self-directed within the framework and requirements of the course. Therefore, students must be willing to change their way of learning. The cliché of the sage on the stage is gone. In an online learning setting students are more responsible for their learning and consequently must be prepared for that responsibility. As faculty and academic administrators, I believe we are obliged to create tools that can measure our digital students who are at risk, their academic progress and their level of success. Some call this a digital responsibility that must be incorporated into our commitment to academic excellence.
PD: It’s very interesting that there really isn’t an extensive amount of research on retention for online students. In fact, if you take a close look at any number of published college or university retention rates, you’ll find very few institutions that bifurcate their retention rate into online students and on-ground students. An assumption one might make is that because many of the variables retention researchers attribute to traditional face-to-face students aren’t present in the online environment, or manifest in different ways. Most models of retention were really never meant to generalize beyond the traditional on-ground student.
Bean and Metzner’s (1985) research on non-traditional student attrition—one of the first forays into non-traditional student attrition—showed that environmental factors have a greater impact on departure decisions of adult students than academic variables. That seems significant to me because when we talk about environmental factors, we can just as well be talking about cyberspace. Environment is not necessarily defined as the campus site, the residence hall, and ongoing campus life activities. The nature of the delivery system is as important or more important when we refer to environmental issues.
PD: There are number of ways to approach retention strategies, and collecting mountains of data may be last on the list for many institutions. But data can help us understand how well students are adjusting to the online learning environment. That requires the creation of a cyber institutional environment where students are prepared for the online learning environment before they log on. The data compiled can be used by advisors, faculty and anyone who deals with online students. At the outset of each course, faculty and advisors might have at their disposal data on how much time students are spending online to identify areas where they might be struggling, patterns of student engagement, signs of students not engaging, daily tracking of student performance, and identification of at-risk students, including patterns that might explain why students drop out. Faculty and advisor interventions might have comparative data for students who are performing excellently and develop strategies for each student to address their issues.
PD: There are a number of ethical and moral implications for higher education institutions as they digitally compile and track online student performance. As we move into the age of learning analytics for use in retention, institutions require guiding principles for ethical use of Big Data. First, it must be through a moral lens. Second, as much as anything else, data analytics must be aligned with the core organizational principles of the institution. Third, the institution must recognize the responsibility of all of its stakeholders—including its students—to extract meaning from that data while also understanding that certain data may not necessarily hold true for all students. Fourth, there must be a recognition that students aren’t totally defined by data or our interpretation of data. There may be reasons beyond the visible data why students are failing or why students are doing as well as they are. And fifth, there is the issue of complete transparency. Students must be part of this process and must know what data that is being collected and how that data leads to their learning and success in their course of study.
PD: I know in many higher education institutions, extensive resources are being expended for data protection and privacy. Hackers see higher education as a prime target for private information. While we can design and invest millions of dollars in data privacy and firewalls, human error is inevitable and higher education must continue to make it one of their primary concerns, developing concrete guides on how to deal with these questions.
How using modern eCommerce principles drives revenue in Continuing Education
Author Perspective: Administrator