At the end of this session, participants will know and understand how data-driven instructional outreach maximizes efficiencies for faculty and improves outcomes for students in an online world. Participants will be provided with an innovative solution that 1) targets students who are most at-risk for failing, 2) connects faculty with high impact outreach strategies, and 3) integrates documentation in a common data system. We hope to disrupt a habit of mind about student success; a conditional engagement tied to student behaviors.
As post-secondary educators, we share a common definition of what is good: students who earn a C or better to graduate with a minimum 2.0 GPA. This definition underscores a habit of mind that student engagement is synonymous with student achievement. What happens when an “A” student submits work? We provide positive reinforcement for maintaining an “A” grade. But, what happens when that same “A” student suddenly becomes a “F” student? We reach out to inquire what happened. We naturally pay attention to what reinforces or disrupts our habits of mind. Consider though…what happens when that “F” student logs in for the first time in a week? Should the “F” student’s behavior be any less disruptive to the instructor than the “A” student’s behavior? We believe it shouldn’t be as student engagement, even at the most entry level, serves as successive steps towards student achievement. We know that instructors and students adopting a growth mindset matters (Dweck, 2006). What if instructors paid as much attention to engagement as they did to achievement? Would more students reach their true potential if we break our habits of mind?
The goal of this session is to share an innovative framework for identifying and transferring behaviors that lead to student success in an online classroom environment. It is centered on the unique application of a multi-tiered systems of support (MTSS) model at the post-secondary level. The presenters will use a variety of strategies such as data chats, scenario-based role plays, and mobile technology demonstrations to engage participants in interactive and applicable ways. The session will empower participants to reflect on their own systems and how they may evolve their approaches to student success using an improvement science method (Langley, Moen, Nolan, Nolan, & Norman, 2009). The target audience for this session ranges from educational leaders, to curriculum and faculty development specialists, to online faculty who provide direct instruction to students.
Breaking habits of mind happens when leaders are faced with problems to which answers are not immediately known. When faced with our problem at Ultimate Medical Academy, we followed an improvement science approach to reflect on our current status then design a solution based on the data. Oftentimes in education, we change tools when we are confronted with issues related to student success. We throw new resources in the direction of the problem. Instead of changing the tool, we focused on understanding the problem and then refining our current tools to better capture what was happening in classroom. In taking these steps, we realized we didn’t have the correct conditions to accomplish our goals. So we revised our tool (Starfish) to set the conditions for enhanced documentation (visibility) of the relationship between instructor behaviors and student behaviors. We realized that while instructors increased their use of the tool, they needed more efficient ways of accessing student information and course progress in order to make efficient, effective instructional decisions. More documentation (data) is great, but “more” didn’t completely solve our problem. We knew based on a few key assumptions about student success that we needed a framework to help instructors strategize about how to assist struggling students based on data. This led us to our MTSS.
Our MTSS originated from studying proven educational principles while also developing an understanding of our own institutional needs. Based on our findings, we leveraged technological tools plus cross-departmental partnerships to design, execute, and evaluate the effectiveness of our data-driven solution. The model 1) targets students who are most at-risk for failing, 2) connects faculty with high impact outreach and instructional strategies, and 3) integrates documentation into a common data system. It is rooted in the assumptions that psychological engagement is essential to adult learning, students who have a history of failure (or challenges to psychological engagement) are at risk for future failure, and that targeted intervention such as early intervention and intervention matched to student need can prevent future failure. We also recognize that our instructors and students operate in an online, asynchronous environment, so, we knew we needed a solution that was easily accessible and operational to our end users. Through our story, we hope to disrupt your thinking and challenge your habits of mind about what leads to student success