To help stakeholders meet the educational challenges they face and better support online learners, the search is on for a new full-time quantitative researcher for MVLRI. The person in this position will build the Institute team’s capacity to use and analyze the wealth of available data and meet our mission to serve the education community by contributing to high quality, applicable research on K-12 online and blended learning.The primary responsibilities of the new researcher are to plan, develop and conduct educational research projects with an emphasis on quantitative methodologies. We’re looking for an individual who has employed techniques in data collection and data analysis used in educational and psychological research, has experience with SQL databases and Report Services, and has conducted advanced statistical analyses including, for example, multiple regression, time-series analysis, survival analysis, hierarchical linear modeling (HLM) and structural equation modeling (SEM). Involvement with data visualization is a valued asset for the person in this position as well.This individual will design and implement a wide variety of education research activities – planning data collection, developing both quantitative and qualitative data instruments, and conducting analyses of both quantitative and qualitative data – with the goal of developing recommendations for strengthening online teaching and learning.The quantitative researcher will work closely with other MVLRI team members and often with other Michigan Virtual staff and MVLRI Fellows to author reports, literature reviews, research articles and policy papers that contribute significantly to the field of K-12 online and blended learning. Because Michigan Virtual has relationships with educational and research organizations and stakeholders at the local, state and national levels, the researcher will contribute to the ongoing growth and development of those relationships. Though we would prefer the person to be on-site, we may consider remote working under certain circumstances. (Position filled.)
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Cuccolo & Green’s (2025) report highlighted the relationship between students’ assignment submission patterns and final course scores. Given that pacing has important implications for student performance, knowing what assignment submission patterns look like across schools with varying demographics could help prompt early identification and intervention. As such, this blog explores students’ assignment submission patterns based on school-level demographic information.
Explore how immersive VR simulations helped students step into real-world roles: from EMTs to chefs, all without leaving the classroom.
In this blog, MVLRI researchers synthesize the key findings from two research studies about student assignment submission patterns in Michigan Virtual online courses.
In this interview, MVLRI researchers discuss key findings from a report highlighting how personalized, consistent, and timely communication in online courses can help students feel more connected to their online teachers and may also impact their success in the course. This blog also explores practical strategies for communicating effectively and building relationships with online students.
This blog digs into the key findings from two MVLRI research studies exploring educator engagement with professional learning (PL), their beliefs about implementing what they’ve learned, and insights into continuing to tailor PL to meet educators’ needs.