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TRACKING THE PROCESSES OF DATA DRIVEN DECISION-MAKING IN HIGHER EDUCATION

In seeking to enhance the efficacy of pedagogical reforms at the K-12 level,
researchers and policymakers suggest that educators should utilize data-driven
decision making (DDDM) systems, instead of making curricular and programmatic
decisions based solely on anecdote or tradition. Yet the provision of data alone
is not a panacea, as data must be robust, salient to local practice, and
supported by adequate technical and administrative systems. However, little is
known about the nature of curricular decision-making processes within higher
education in general, and STEM disciplines in particular.  Further inhibiting
the use of DDDM in many organizations is the lack of high-quality data that is
useful for administrators, instructors, and designers.  Based on prior research
on postsecondary teaching we developed a new approach to studying teaching and
learning across disciplines and courses that includes insights into faculty
planning decisions, nuanced accounts of classroom teaching based on in-depth
observations, and student-based accounts of instructional quality and the
effects of classroom teaching on study habits, motivation, and learning styles.

The goals of this study are to (1) to identify whether or not formal systems
exist for curricular decision-making in STEM departments, and if so, what types
of data are used in these processes, (2) to collect data about instructor
planning, classroom teaching, and student classroom experiences, (3) to prepare
reports based on these data for departmental decision-makers to see if they
enhance local systems.  Besides providing important insights into the nature of
curriculum design in STEM departments, the study will also result in new
empirical findings about the relationships between classroom teaching and
student experiences.  In order to increase the prospects for long-term adoption
of our approach to studying teaching and learning we will also provide training
to administrators and STEM education leaders at each of our study sites in the
collection and analysis of data. 

For more information about the project that led to this work see
ccher.wceruw.org, and about the Teaching Dimensions Observation Protocol (TDOP)
instrument see tdop.wceruw.org.


NEWS

 * Paper on measuring active learning in the classroom published in Science
   Education
 * New formative feedback reports on teaching being developed and field-tested
 * New research brief on data driven decision-making published by TPDM group



TPDM Tracking the Processes of Data Driven Decision-Making in Higher Education
is housed within the Wisconsin Center for Education Research at the School of
Education, University of Wisconsin-Madison. This project is funded by the
National Science Foundation under Award #1224624. Copyright ©2012, The Board of
Regents of the University of Wisconsin System.