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Making data science tools count toward tenure πŸ‘©β€πŸ«πŸ‘¨β€πŸ«

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data-science-tenure

In the 1990s, Ernest Boyer of the Carnegie Foundation for the Advancement of Teaching articulated the value of different types of interdisciplinary scholarship in his highly cited Scholarship Reconsidered: Priorities for the Professoriate (latest, expanded edition: Boyer et al. 2016). This report, very familiar to university administrators such as deans, provosts, and presidents, but often less well known by junior faculty, highlights the value of multiple types of faculty contributions within academia, specifically noting four types of scholarship. The first, scholarship of discovery, mirrors the standard disciplinary model of original research advancing knowledge within a field, often evidenced by peer reviewed publications in established disciplinary journals and success in obtaining competitive research funding. A second type, scholarship of integration, recognizes innovative synthesis of information across traditional disciplines, across subdivisions within a discipline, or across time. Such scholarship creates new knowledge through novel links between specific concepts, tools, and studies from disparate fields of inquiry. Boyer's third type, scholarship of application (sometimes called scholarship of engagement), goes beyond simply applying existing tools (as would a technician) to value the deep collaborative contributions in creating advances in interdisciplinary studies, particularly within a team science framework. The fourth type, scholarship of teaching and learning, values the systematic study of pedagogical methods for the transfer and creation of new knowledge between faculty members, colleagues, and the next generation of scholars.

These four categories provide rich support for many current efforts within the field of Data Science and its link to academic departments of Statistics and Biostatistics and topics for the continuing critical conversations between the chair, the candidate, and senior faculty. The four types of scholarship also provide a context for collecting, presenting, and reviewing scholarly contributions of junior faculty. The concept of the scholarship of integration is immediately extensible to Data Science, particularly with respect to linking heterogeneous data components and developing new analytic tools, hence enabling new lines of inquiry. Documentation of such contributions within a promotion dossier is somewhat non-traditional and may include citable data within repositories and software packages/toolboxes in addition to peer-reviewed publications and funded grants. The scholarship of application is evidenced by interdisciplinary publishing, the creation of data repositories and complex data sets, and clear contributions unique to the candidate within an interdisciplinary team. Data Science research contributions often are linked deeply to the intersection of Boyer's scholarships of integration and application, and it will be advantageous to highlight the impact of these contributions within this context.

The rapid development of training programs, concentrations, and degree programs within the area of Data Science offers multiple opportunities for the scholarship of teaching and learning. Success in this area extends well beyond simply teaching new courses and advising students, it involves research and discovery on the modes and methods of instruction and learning, an area of clear interest in the statistical education research community, but only just developing in the broader area of Data Science (National Academies 2014).

Boyer's categories provide a valuable framework for organizing and presenting a candidate's scholarly contributions for review. The candidate can organize materials under Boyer's categories in the CV, and mention them in their Personal Statement. A department chair can frame contributions in light of discovery, integration, application, and teaching to external reviewers and when presenting a candidate's promotion for consideration by senior faculty and promotion committees. Senior faculty can use Boyer's categories as a lens through which to view accomplishments and assess impact of a candidate's scholarly work.

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