In 2020, we published a 10 report series summarizing the findings of all of the research we’ve conducted to date. Nearly 100 resources were included in this review, and collectively they provide valuable insights for researchers and practitioners on many aspects of online teaching and learning, such as:
- K-12 online best practices
- Online student motivation
- K-12 blended teaching and professional development, and
- K-12 special populations
This blog series is meant to accompany these reports and further explore the practical implications of those years of research.
One of the first themes to clearly distinguish itself during the analysis of the reports published by Michigan Virtual was best practices in K-12 online learning.
Over the last several years, our research team has explored factors for online student success such as:
- Reason for enrollment and likelihood of course success
- The relationship between student pacing and course outcomes
- Student preference for an performance on auto-graded and instructor-graded assignments
- Teacher-student communication preferences, and
- The role of instructor behaviors in student satisfaction
These matters as well as resulting implications and best practices are further explored below. For more information on any of the topics below please see the full research report on K-12 online best practices.
Reason For Enrollment
Students have many different reasons for enrolling in their online course(s) and tend to register at different times during the registration period.
Regardless of the actual timing of their enrollment—so long as students are within the registration window and have enough time to complete their course—they should be allowed to enroll.
Enrollment reason, however, does seem to impact the likelihood of student success.
Students who enroll for reasons such as credit recovery or personal learning preference may need more careful monitoring as these enrollment reasons are associated with poor course outcomes.
Student Pacing
Online courses present unique challenges to students in that many are self-paced, which is to say that students are able to move through the course as they demonstrate competence without being on an assigned schedule.
Students who demonstrate consistent, on-pace progress through their course are more likely to be successful in their online courses than those who do not.
Resources such as course pacing guides can provide clear expectations for all students and provide a framework to follow for students who may struggle to successfully pace themselves.
Students with poor course pacing can fall behind and essentially “run out of time” to complete their courses.
While these students may demonstrate significant time investments near the end of the course, it is not enough to successfully catch up.
Encouraging students to follow the pacing guide and attempting to intervene early in the course may be successful strategies for these students.
Student Preference on Auto-Graded Compared to Instructor-Graded Assignments
Auto-graded assignments—assignments that are graded by the LMS rather than the instructor—allow students to practice concepts and gauge understanding in their online course.
These can be a valuable tool for both online students and teachers when used alongside teacher-graded resources.
Online students, however, tend to focus more of their effort on completing auto-graded course assignments rather than those that are teacher-graded.
This phenomenon may result from a perception that assignments that are manually teacher-graded are more complicated and involve more effort than those that can be auto-graded.
Nevertheless, because there is no subjectivity in grading for auto-graded items, students overall are awarded less points for these assignments.
Course designers and instructors should be aware of students overreliance on auto-graded assignments, and in particular, direct students who are behind in a course or struggling to focus on instructor-graded assignments as they have more impact on a student’s overall grade.
Teacher-Student Communication and Course Satisfaction
It is clear from our research, and is intuitive to those in education, that communication between students and teachers is important to most students.
Students overall preferred using the messaging tools embedded in the LMS to communicate with teachers.
Having an easily accessible, established communication forum is essential to keeping students engaged and empowered in their online course.
Students who communicated more with their teachers reported higher satisfaction in their online course.
Students also reported higher levels of satisfaction with their online courses when their teachers engaged in more pedagogical behaviors rather than managerial ones related to the course.
Key Takeaways on K-12 Online Best Practices
- Take notice of the reason a student is enrolling in an online course as they may need more careful monitoring to ensure success.
- Encourage the use of course pacing guides to assist students in maintaining a consistent pace and intervene early on if students are falling behind.
- Emphasize the importance of not over relying on auto-graded assignments as they tend to actually represent a smaller percentage of the overall points in most courses.
- Establish an easily accessible and clear communication channel back and forth between students and teachers.
MVLRI Research on K-12 Online Best Practices
Kwon, J. B. (2017c). Course engagement patterns in mathematics and non-mathematics courses. Michigan Virtual University. https://michiganvirtual.org/research/publications/course-engagement-patterns-in-mathematics-and-non-mathematics-courses/
Kwon, J. B. (2017d). Exploring patterns of time investment using time-series clustering analysis. Michigan Virtual University. https://michiganvirtual.org/research/publications/exploring-patterns-of-time-investment-in-courses-using-time-series-clustering-analysis/
Kwon, J. B. (2017e). Growth modeling with LMS data: Data preparation, plotting, and screening. Michigan Virtual University. https://michiganvirtual.org/research/publications/growth-modeling-with-lms-data-data-preparation-plotting-and-screening/
Kwon, J. B. (2018). Learning trajectories in online mathematics courses. Michigan Virtual University. https://michiganvirtual.org/research/publications/learning-trajectories-in-online-mathematics-courses/
Kwon, J. B. (2019a). Communicative interactions with teachers in K-12 online courses: From the student perspective. Michigan Virtual University. https://michiganvirtual.org/research/publications/communicative-interactions-with-teachers-in-k-12-online-courses-from-the-student-perspective/
Kwon, J. B. & DeBruler, K. (2019, September 26). Pacing Guide for Success in Online Mathematics Courses. Michigan Virtual. https://michiganvirtual.org/blog/pacing-guide-for-success-in-online-mathematics-courses/
Lin, C. H. (2019). Auto-grading versus instructor grading in online english courses. Michigan Virtual University. https://michiganvirtual.org/research/publications/auto-grading-versus-instructor-grading-in-online-english-courses/
Lin, C. H., Bae, J., & Zhang, Y. (2019). Online self-paced high-school class size and student achievement. Educational Technology Research and Development, 67, 317- 336. https://doi.org/10.1007/s11423-018-9614-x
Lin, C. H., Zheng, B. & Zhang, Y. (2016). Interactions and learning outcomes in online language courses: Online interactions and learning outcomes. British Journal of Educational Technology. 48(3). https://doi.org/10.1111/bjet.12457
Ranzolin, D. (2015, April 1). To serve and subsist: Reflections on finding the ideal registration window. Michigan Virtual. https://michiganvirtual.org/blog/to-serve-and-subsist-reflections-on-finding-the-ideal-registration-window/
Zhang, Y. & Lin, C. H. (2019). Motivational profiles and their correlates among students in virtual school foreign language courses. British Journal of Educational Technology, 51(2). https://doi.org/10.1111/bjet.12871
Zheng, B. (2018). Exploring the impact of student-, instructor-, and course-level factors on student learning in online English language and literature courses. Michigan Virtual University. https://michiganvirtual.org/research/publications/exploring-the-impact-of-student-instructor-and-course-level-factors-on-student-learning-in-online-english-language-and-literature-courses/
Research Round Up blog series
In our Research Round Up blog series, we explore the practical implications from years of digital learning research. Next month’s topic will be K-12 Special Populations and Motivation. Stay up to date on future blogs in this series by signing up for email notifications!
