Presentations: Session II

Higher education institutions throughout the nation employ various continuous improvement processes to operationalize change at all organization levels. Through our ongoing work with three public, urban research universities that serve a high population of low-income, minoritized, and non-traditional students, we have documented how the COVID-19 pandemic caused their continuous improvement models to shift. Given there is no formula for successful change leadership, especially in the context of a pandemic, institutional leaders leaned heavily on a "Prepare, Reflect, Prioritize, Act, Monitor" framework. Although these institutions' quick responses to finding solutions to the barriers created by COVID-19 were not intentionally designed, the driving force behind institutional change was their capacity to swiftly and efficiently pivot to address and support their campus and community needs.

The institutions' ability to use current efforts to address prompt needs spanned from leveraging data to developing a network of leaders across the campus; ultimately, their ecosystem allowed for an agile shift to provide immediate support. Some examples include: 1) democratizing data for faculty, staff, and external use which allows institutions to hold themselves accountable by constantly evaluating and adjusting support structures; 2) implementing a campus-wide student success campaign and receiving widespread participation from faculty and staff of all levels. By unifying all leaders across campus behind one central theme, this institution has demonstrated transformation by affirming their commitment to student success as central to their overall mission. These changes, among many others, exemplify the ways change leaders prepare, reflect, prioritize, act, and monitor when evaluating how to best navigate the many uncertainties of the past year.

This session will explore the various ways our campus partners have demonstrated a recommitment to student success through change leadership. Through mid- and executive-level leadership, these institutions have implemented initiatives to improve the student experience and shift their institutional cultures through an equity lens.  

 To assess whether any change initiative has succeeded, it is important to be able to measure the resulting change. Our project draws on data from an established professional development initiative that has offered workshops for mathematics instructors to learn to use inquiry-based learning (IBL). In this talk, we will use observational data from a subset of workshop participants to show how differences in observation and analysis methods affect our ability to detect whether their instructional practices changed after attending a workshop.

We collected video observations from 15 participants teaching a course prior to the workshop and the same course the year after the workshop. We coded the videos using two observation protocols, our own Toolkit for Assessing Mathematics Instruction-Observation Protocol (TAMI-OP) (Hayward et al., 2017) and the Reformed Teaching Observation Protocol (RTOP) (Sawada et al., 2002), a protocol used in numerous other studies of instructional change. We place each into Hora and Ferrare's (2012) framework of observation protocols and show how their differing designs (segmented/descriptive vs. holistic/evaluative) provide different measurement sensitivities.

Two methods of analysis and visualization of the segmented, descriptive TAMI-OP data provide different levels of detail from the same dataset. We use cumulative proportions of various activities to measure change via central tendency. We also use a "heatmap" approach to help visualize patterns in how class classroom activities vary from day to day across a whole course. Paired side-by-side comparisons of these two analyses allow us to detect changes in the sequencing of instruction that may be significant even if the overall proportions of instructional methods do not change. We will also share matched results from RTOP scores. We will engage the audience in a broader discussion about what change, if any, we can detect with different measurement and analysis methods.

Presenters will map the systems change processes necessary to realize the benefits of creating new physical innovation spaces--agnostic/neutral spaces, made accessible to all, and inclusive of instruction about the process of innovation, along with some combination of interdisciplinary, project based, and/or experiential learning. Below the surface of visible innovation space artifacts are department and college norms for teaching and pedagogy, which are often bounded by both campus and departmental policies for teaching, which have roots in disciplines across time. Unpacking these systems is important because new ventures fail when actors fail to respond to both the depth and inertia of history upon which a new innovation space (IS) likely sits.

Presenters will detail resources, inputs, values, rewards, along with power and influence. Further, presenters will demonstrate how locating a new IS in a network. Networks can help strengthen the position of an IS through momentum from creating peer-to-peer partnerships, strengthening research processes and outcomes, and providing direct support to faculty (i.e., external funding; publishing opportunities). These opportunities are closely linked to external stakeholders like governments, communities, and industry, creating unique access for institutional impact, expert/faculty collaboration, and student career outcomes.

The examples of innovation ecosystems presented here can be informative to other change makers attempting to establish space for or, importantly, the practice of transformative undergraduate education.