Implications for the Future of Online Learning

Overview Implications for the Future of Online Learning

Implications for the Future of Online Learning, In many ways, the California Community College System’s experience provides an excellent look into the future of online learning. The remarkable expansion of online learning in our state’s community colleges offers valuable lessons as this technology takes a more prominent place in U.S. ISTOCK Online learning must be recognized as an important tool for increasing access to higher education. 18 successful online courses in California community colleges higher education. One in four U.S. community college students attends a California college, and 55 percent of California community college students are ethnic or racial minorities. Furthermore, the number of California community college students taking an online course has more than doubled in the past decade. Demand for online learning is growing rapidly. Yet, even as online courses grow in popularity, students are less likely to complete them successfully, and ethnic and racial achievement gaps are wider than in traditional courses. The piecemeal, idiosyncratic online education system that has evolved over time at California community colleges has not narrowed those gaps.

Our research suggests that a more data-driven, integrated, and systematic approach is needed to make students more successful in online learning. It is critical to moving away from the individual, faculty-driven model of online course design and delivery toward a more systematic approach. Under such a model, faculty members collaborate with administrators, media developers, and information technology experts to maximize the online medium’s potential. A systematic approach better ensures excellence by creating teams with a range of abilities that a single instructor is unlikely to have. Greater integration and planning at the system level could also create a more consistent course-approval process. Such an approach would make it easier to add online courses in response to student demand, helping student’s complete degrees on time.

Development of new online learning technologies provides data collection opportunities that benefit students at all educational levels, whether they take courses online, face-to-face, or both. Improved data systems and advances in data visualization will allow faculty, administrators, and researchers to better track student engagement with course material and provide opportunities for instructors to customize teaching to each student’s learning style. Predictive analytics and real-time data dashboards will allow faculty to assess student progress more accurately and help identify at-risk students before they become frustrated and withdrawn.

New online education technologies are shifting the debate from a zero-sum comparison of the merits of online versus face-to-face instruction to something more valuable: a discussion on how best to integrate new teaching methods into the educational process. The California Community College System’s Online Education Initiative is a vital start. If it is successful, it will be a model that other states can follow to build their higher-education online education programs.

Implications for the Future of Online Learning

Personalized Learning and Instantaneous Feedback

Any course, whether taught face-to-face or online, includes individual students with individual learning styles, experiences, and abilities. In the face-to-face environment, the instructor must adjust a course’s pace and adapt content to accommodate multiple learning styles. The typical community college student body is diverse in ability and experience and includes many nontraditional students. Developing courses that meet the needs of students with dissimilar academic backgrounds, learning styles, and capabilities can be challenging. Some students may lose interest and become frustrated because a course is moving too slowly. Other students may get discouraged because they feel the course is progressing too rapidly.

The asynchronous, individualized nature of online education allows differentiation of course content. Scholars can control a course’s pace to fit their learning styles and capability. This individualization is achieved using adaptive instructional software, which personalizes lessons and customizes instruction in response to real-time feedback and assessment. Enterprises such as Khan Academy have championed this technology in the K–12 setting.

Ours explore found that interactive course software that gives instantaneous feedback could be particularly effective in improving scholar performance in online courses. Four of the top 10 performing online courses in our study were beginning microeconomics and macroeconomics classes taught by two professors at separate colleges. The common link between these courses and professors was the use of the same interactive course content software, initially developed by a Stanford economist. The software is a course content and management system providing problem sets, links to relevant news sources, multimedia, assessment, and grading. Chapter assignments and problem sets are automatically graded, providing students immediate explanations for every question. The software lets instructors monitor student progress in real time. It also allows instructors to follow each student topic by topic, achieving high levels of course personalization.

In the four microeconomics and macroeconomics courses using this software, the online success rate was 79.2 percent. By comparison, our predicted average success rate for these courses, taking into account the demographic makeup of enrolled students, was 68 percent, which is 11 percentage points lower. To put this in perspective, the typical online course pass rate in the community college system is 60 percent. It should be noted that these beginning economics courses require students to master difficult quantitative concepts. The courses qualify for transfer credit to both the University of California and California State University systems. Our analysis suggests that employing software that provides instantaneous feedback improves student results. One distance education coordinator noted that such software allows students to remediate continually. If a student reaches an impasse in the content and the system cannot find a solution, the instructor is alerted. The instructor can step in, providing a story or example that helps the student understand the concept and move forward. In this way, technology improves student performance and makes instructors more efficient.

Demand for online education is growing. This makes it essential to shift the online learning paradigm from replicating face-to-face pedagogy to practicing teaching methods that take full advantage of rapidly advancing technology. As bandwidth increases and software improves, online instructors are able to expand their repertoire and explore new teaching methods. Instructors become more capable of personalizing lessons to cater to student strengths and grow more efficient in delivering high-quality online education. These new technologies will be essential if we are to narrow the significant online-learning achievement gap. These tools can help ensure that online education in the community college system carries out the mission of access laid out in the Master Plan for Higher Education. What then are community colleges and higher education policymakers doing to meet these challenges?.

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