Flipping the statistics classroom: How Ed.D students experience online learning
Amberly Dziesinski working with Will Doyle, Professor; Department of Leadership, Policy, and Organizations
The purpose of Decision Analysis II: Quantitative Reasoning is to provide educational leaders with the ability to use data to effectively inform decision making. This course introduces students to quantitative research methods and teaches students to use statistical software to describe, visualize, and analyze data.
Students are required to take this course during the second year of their Doctor of Education (Ed.D) program. These Ed.D students are typically mid-career K-12 and higher education leaders most interested in the practical application of what they learn. EDD students take their courses as a cohort of 25-30 students. For practitioners who are new to quantitative research methods, the most valuable aspect of this course is working through data analysis problems during class. In the classroom, they are supported by their instructor and classmates and receive immediate feedback which facilitates learning.
In its current form, the course is offered as a series of weekend sessions over the summer semester. Each class period lasts a full day and is broken up into multiple topics per day. For each topic, the instructor lectures and then students work on a problem set individually or with a group. The traditional classroom lecture model condensed into day-long classroom sessions poses a challenge to student learning, and time spent lecturing during class reduces time to practice application. To increase the opportunity for hands-on learning during class time, we redesigned the course as a flipped classroom model.
Approach: Flipped Classroom
Students will complete an online module prior to class. The module includes videos of the instructor delivering lectures and links to supplementary materials. After viewing the lectures, students will answer a question that applies the concepts to a practitioner specific example. The questions are meant as formative assessments for students to gage their understanding of the material. The module also includes a discussion board for students to annonomously submit any remaining questions to be addressed in class. Class time is devoted to student questions, discussion, and hand-on application. The instructor will be available to help as students have questions about data, coding, and analysis – challenges that could be very frustrating for students to work through on their own, outside of class in the traditional model.
In Summer 2019, we applied the flipped classroom model to the lecture on statistical inference and estimation. To understand inference, students must understand a set of interrelated concepts that build upon each other. These concepts are best learned with reinforcement over time. However, Decision Analysis is traditionally structured in a way that students are expected to learn all of these components of inference in one class period. This puts a large cognitive load on students that hiders their learning. By providing lectures online, students can view the content at their own pace and review lectures multiple time, reducing this cognitive load.
The purpose of this research is to understand how students in Decision Analysis experience this flipped classroom model. Specifically, my research question is: How do students experience engaging with an online/in-person hybrid quantitative methods course? At the end of the course, students will complete a survey assessing the extent to which students use the online tools and which components of the model were the most beneficial for their learning and engagement. Responses will be coded, noting different patterns of use and common feedback about student experiences. The results of this survey are intended to be formative to assess which components of the flipped classroom model may be scaled up from one unit to all course content in future sections of this course.