I began focusing on challenges in higher education, developing and delivering the teacher training for new PhD student teaching assistants (TAs) for the School of Social Sciences, in 1993. Training and mentoring new TAs 1993-1996 added an unexpected dimension of authentic application to my PhD studies in Cognitive Science. Five years consulting as a biostatistician raised my awareness of the sometimes-apparently-unbridgeable gap between clinical researchers and both measurement and statistical considerations in their research. Arriving at Georgetown in 2002, these gaps became more apparent as I served as the sole consulting biostatistician for the medical research across departments.
I have been studying, consulting in/on, and supporting higher, graduate, and post-graduate/professional education with Mastery Rubrics (MRs) since 2005. In this work, I have been able to bring my background in cognitive sciences together with my experience training new faculty, teaching undergraduates and graduate students, and especially the particular challenges of teaching the “singleton” course- one out-of-discipline course that is required by a degree program, like “introductory statistics” or “research ethics” for students of neither statistics nor ethics. I have been an active proponent of disciplinary (and science generally) stewardship since 2005, and of ethical practice of statistics and data science since 2009; irrespective of your degree discipline, ethical practice of statistics and data science, statistical literacy, and general research ethics are essential features of the stewardship of your discipline. Since 2005 I have sought ways to help instructors promote stewardly science, leveraging cognitive science to help minimize the perceived (and actual) barriers in higher education to teaching disciplinary content together with stewardship and ethical research and statistical/data science practice. A recent (2021) example discusses the importance of stewardship for ethical mathematical practice.
The MR construct was created when I was faced with the task of designing a new research training curriculum that many different instructors would be teaching in (as part of a grant 2004-2009). As the Curriculum Director, I wanted to make sure that no matter who taught any given class, every completer of the curriculum would leave with the same level of the same knowledge, skills, and abilities. A learner should be able to see where they are in the curriculum, and be empowered to ask for additional instruction, feedback, or opportunities to practice or demonstrate achievement of the target level of the target knowledge, skills, and abilities. Additionally, learners should also see where they could progress beyond the end of the curriculum. Most, if not all, higher education institutions assume all of these characteristics exist in their curricula; the innovation of the MR construct is to ensure that they do.
My areas of interest (rather outside my day job) include higher education curriculum development and evaluation; statistical methodology and statistical literacy for effective stewardship of the discipline in PhD students/holders; effective instruction and mentoring in research- and data work-specific ethics. On sabbatical in 2019, I wrote three books on these topics; two – supporting ethical statistics and data science- are in press and one -about the MR construct -is nearly there. In mid 2021 I started pulling together materials intended to support any interested visitor in utilizing these books and ideas; this website was created to help direct interested parties to potentially useful materials. Speaking of “useful materials”, I have created a page for books I use/reuse frequently – I plan to annotate this list in the future, but the list reflects a variety of important starting points for different research and work I do.
