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The coronavirus pandemic has and likely will continue to wreak havoc on higher education. In the coming months and years, experts are predicting an increase in institutions facing financial shortfalls that will require drastic action, including furloughs, layoffs, mergers, and even campus closures. These events will undoubtedly affect faculty, staff, and students in myriad ways, but it is incumbent upon the regulatory triad to protect and support students who are then left holding the proverbial bag. Even before the pandemic, over the previous five years, an average of 20 campuses have closed each month, leaving around 500,000 students (mostly working adults, low-income students, and students of color) affected, according to an analysis by the Chronicle of Higher Education. As federal and state governments, in addition to accrediting bodies prepare to serve in this consumer protection role, it will be beneficial to know how students have weathered past campus closures (e.g., Were they able to continue their education elsewhere? Did they go on to earn a credential?). The current study explores these questions and additional outcomes descriptively to gain a better understanding of what occurs to students directly affected by a campus closure.

Mason is actively engaged in changing the culture of teaching toward more active- and inquiry-based learning forms. These forms are viewed as superior mechanisms for improving student engagement, performance, and retention, especially in STEM-based classrooms (Kogan & Laursen, 2014; Freeman et al., 2014; Laursen, Hassi, Logan, & Weston, 2014; Nelson, 2010). Through Mason’s strategic plan and its building of new active learning classrooms, the opportunities to leverage this pedagogical form are ripe. Despite this commitment, teaching change is often difficult to engender in higher education organizations. Some of this difficulty lies in the challenge of changing faculty habits and norms related to their own teaching practices (Austin, 2011). However, even if individual faculty are committed to pedagogical change, that change is also highly dependent upon departmental and institutional norms and barriers, which can act to promote or constrain change (Austin, 2011; D’Avanzo, 2013; Brownell & Tanner, 2012; Henderson et al., 2012; Sunal et al., 2001; Fairweather, 2008). There are levers that go beyond the individual and their classroom to improve the likelihood of successful pedagogical change. Among these are the use of data-driven decision making and the fostering of data cultures (Bouwma-Gearheart & Hora, 2014; Hora & Bouwma-Gearhart, 2014, 2017) and the building and leveraging of collaborations across organizational units (Kezar & Lester, 2009; Klein, 2017; Leisyte & Dee, 2012) to help leverage the information, relationships, and resources needed to enact change. The purpose of this workshop is to use the context and learning from current work being done to enact pedagogical change to help attendees frame, consider, and plan for how relationships, resources, and data within and beyond their departments can be used in their own contexts to enact similar change. The presenters, members of a cross-disciplinary research team, are working alongside members of course-based communities of transformation (CCTs) in Mathematics and Physics at Mason, with CCTs in Biology and Computer Science to follow. These researchers will share empirical evidence, lessons learned, and practical implications related to their National Science Foundation funded project to create department and institution-level change that supports the adoption of active learning pedagogy at Mason. As a part of this work, CCT members have had to consider and act beyond the boundaries of their individual classrooms and departments to leverage organizational data and partnerships. This project is designed to develop a university culture that values the incorporation of active learning practices in undergraduate STEM courses and programs. Attendees will develop a better sense of how to find and use data in decision making and conversations with those within and beyond their departments, including understanding and identifying course taking and retention patterns, resource needs and opportunities, and student learning and preparedness. Attendees will identify key partnership and collaborations they can continue or begin to cultivate as they work to create change in their departments and learn how to improve cross-unit collaboration. Attendees will be given time to consider the needs, strategies, and resources necessary for change in their communities and craft plans for starting that change., Innovations in Teaching & Learning Conference Proceedings, Vol. 12 (2020): Teaching Towards the Future

Location: JC Room E Supported by existing infrastructure and the university's strategic plan, Mason is poised to scale up its implementation of active and inquiry-based learning by engaging faculty, graduate students, and undergraduates in changing the culture of teaching. Literature shows that student engagement through active and inquiry-based learning improves student attitudes, retention, and understanding at all levels of curriculum (e.g., Fry, 2014; Freeman et al., 2014; National Research Council, 2012; and references therein) with an outsized impact on women and previously low-achieving students (Kogan & Laursen, 2014; Laursen et al., 2014). However, motivating faculty to make significant changes to their teaching practices is often challenging, and active learning methods are used only sporadically on college campuses, including Mason, despite a long history of research showing that these techniques improve student learning. The literature on change within academic departments is sparse and often touts the success of centralized units in promoting pedagogy reform (e.g., Fairweather, 2008 and references therein). At the same time, research shows that departmental norms and institutional barriers have a large impact on the way STEM faculty teach (Austin, 2011; D'Avanzo, 2013; Brownell & Tanner, 2012; Henderson et al., 2012; Sunal et al., 2001; Fairweather, 2008). Peer-to-peer learning communities have been shown to provide support for organizational learning (Kezar & Lester, 2011; Mittendorf et al., 2006), to assist in the development of new pedagogical interventions, and to shift faculty values surrounding teaching and learning (Davis & Sumara, 1997; Gallucci, 2003; Sanchez-Cardona et al., 2012; Snyder et al., 2003; Viskovic, 2006). The purpose of this panel is to showcase work being done to leverage learning communities to enact pedagogical and organizational change. The panelists, members of a cross-disciplinary team of researchers, are working alongside members of a course-based community of transformation (CCT) in Mathematics at Mason, with CCTs in Physics, Biology, and Computer Science to follow. These researchers, with members of the Math CCT, will share empirical evidence, lessons learned, and practical implications related to their National Science Foundation funded project to create department and institution-level change that supports the adoption of active learning pedagogy at Mason. As a part of this work, multi-generational teams of faculty, graduate apprentice instructors, and undergraduate learning assistants receive training on active learning techniques, learning communities, grassroots leadership, and change in higher education, as well as continued support through a network of CCTs. This project is designed to develop a university culture that values the incorporation of active learning practices in undergraduate STEM courses and programs. Attendees will leave the session with a better sense of how to employ changes in pedagogy within their own classrooms and how to facilitate change more broadly across their departments and the campus community. Specific attention will be given to effective change strategies, factors that influence change, and steps in the process of change. Attendees will also be given time to consider the needs, strategies, resources, and partnerships necessary for change in their communities., Innovations in Teaching & Learning Conference Proceedings, Vol 11 (2019): Teaching the Whole Student

Location: JC Room A Studies across the STEM disciplines have shown that student engagement and active learning improve student attitudes, retention, and understanding (e.g., Fry, 2014; Freeman et al., 2014; National Research Council, 2012; and references therein), with greater impact on women and previously low-achieving students (Kogan & Laursen, 2014; Laursen et al., 2014). A recent meta-analysis of 225 studies has shown that active learning improves student performance on examinations and concept inventories (Freeman et al., 2014). Numerous pedagogical strategies fall under the active learning umbrella, including peer instruction (Mazur, 1997), conceptual clicker questions (e.g., Miller et al., 2006), flipped classrooms, student blogs, Treisman’s emerging scholar program (Treisman, 1992), and oral reviews (Nelson, 2010). The implementation and degree of active engagement vary greatly from class to class and instructor to instructor. Nevertheless, studies have consistently shown improvements in student learning when these techniques are used (Laursen et al., 2012). Given the evidence of active learning’s efficacy for all students, and especially non-traditional populations, the need to engage in active learning at Mason is particularly relevant. Further, as a part of the university's strategic plan and its ongoing infrastructure improvements, Mason is poised to scale its implementation of active and inquiry-based learning by engaging faculty, graduate students, and undergraduates in changing the culture of teaching and learning. The purpose of this workshop is to actively engage attendees in various active learning strategies that can be employed in a variety of classroom settings to improve student learning, retention, and engagement. Based on the work of a National Science Foundation funded grant to leverage active learning pedagogy across STEM curriculum, workshop leaders will share evidence-based approaches for developing, implementing, and assessing active learning techniques. Although the expertise of the panelists lies primarily in the STEM fields, the active learning techniques shared are applicable across a variety of disciplines and can be implemented in small seminars or large lecture halls. Active learning techniques presented and discussed will range from “novice” to more advanced, and facilitators will describe how techniques can be tailored to various active learning comfort levels. As a part of the workshop, attendees will engage in student-centered learning activities, hear from leaders about their implementation of and experiences with active learning, and map out ways to integrate active learning in their own teaching practices. This this workshop provides an opportunity for participants, whether new to active learning or highly skilled in its implementation, to learn and share strategies for integrating this innovative pedagogical approach into practice., Innovations in Teaching & Learning Conference Proceedings, Vol 11 (2019): Teaching the Whole Student

Higher education institutions are facing increasing pressure to provide evidence of student learning; teaching pedagogical best practices are moving to an increasingly individualized and student-focused learning model; and innovative technologies are allowing for greater mining of student data. Within this environment, learning and advising management systems, based on educational big data, or learning analytics, are being developed to better measure, analyze, report and predict data related to student learning, retention and completion. These learning analytics-informed systems have the potential to generate new insight into courses and student learning by creating responsive feedback mechanisms that can shape data-informed decision making as it relates to teaching, learning and advising. Despite the benefits of using learning analytics-informed learning and advising management systems, there are barriers and challenges related to broad adoption and use of innovations like these systems in higher education. In the summer of 2015, we conducted an instrumental case study to learn more about the technological, institutional, and individual factors related to adoption and use of learning analytics-informed educational technology tools on campus. In this short lightning talk, we will present the findings from the study’s focus group interviews and observations. Further, we will share promising practices and practical considerations related to use of learning analytics tools to measure and predict academic performance., Innovations in Teaching & Learning Conference Proceedings, Vol 8 (2016): Cultivating Creative and Reflective Learners