Data Dashboards for Faculty Collaboration, Professional Learning, and Student Success

Data Dashboards for Faculty Collaboration, Professional Learning, and Student Success

Data dashboards, faculty, decision-making, equity gaps, completion
  • Diversity
  • Program Review
  • Quality Assurance
  • Collaboration
  • Data Warehouse
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Pierce College (WA)
https://www.pierce.ctc.edu/
  • Institutions
  • Systems
  • State Agencies
  • Institutions
  • Systems
  • State Agencies

PURPOSE

Faculty and administrators have a long list of data needs. When we presented data in the past, we often did so only at an institutional level. This resulted in a general sense of belief, but with a simultaneous belief of either "that's not happening in my classes," or "I don't see myself/my classes in these data". So, how then do we expect faculty to help increase student success at the course level without giving them the opportunity to dig deep into their own course and departmental data?

  • Develop accessible, interpretable, (near) real-time data dashboards that can be easily accessed and used by faculty, staff, and administrators.

  • Develop dashboards that provide details down to the section level and that provide the ability to disaggregate data by student demographics in order to reveal equity gaps.

  • Provide robust training to support faculty, staff, and administrators in understanding and using department, course, and section-level data in order to create a culture of discovery rather than one of fear.

  • Provide support to engage discourse around data analysis and innovative and active steps for responding to identified gaps.

  • Grow our institutional research capacity by training large numbers of faculty, staff, and administrators to seek and find data, transitioning the IR department from "data waitstaff" to "data stewards" that aid us in doing deeper analysis rather than simply responding to data requests.

DESCRIPTION

We are all likely familiar with the concepts of data, data analysis, and, to some degree, dashboards. What is unique about this innovation is the intersection of the tool, the depth, the training, and the culture.

The tool we are using is Tableau, which we have access to through a state-wide license. It creates both accessible/understandable visualizations of data, as well as statistical details for those who wish to dig deeper. The depth is that we have *released the data to everyone* who is trained such that faculty can see both their own data and the data of their colleagues. This provides context for understanding student experiences across courses, rather than simply within one's own. The training is designed to provide the technical, ethical, and emotional support and guidance needed in order to understand how the tool works, how to use it effectively and in ways that support and grow, and how to prepare oneself both for what they will see in their own data and how to discuss that in a broader context with faculty peers.

The tools was introduced in what we framed as a "non-punitive" environment. That is, the data and discovery that occurs were to be used to identify gaps, prompt conversations between faculty about student success, and to help identify professional learning opportunities that may be undertaken individually or by teams.

We introduced the the tool (and broad access to the data) first to a small group of faculty who asked to see "all the data." They, in turn, became "evangelists" of the data access and soon other faculty were asking for similar access. Having already built a culture of evidence wherein data is used to provide understanding and drive decision-making, we were well staged to elevate that to a culture of discovery wherein individuals were inspired to explore, identify areas of focus, and engage themselves and their colleagues to find approaches to learning that advance student success. This was initially introduced and used in institutes that focused on faculty learning/doing research and eventually expanded to be a part of the discipline and program review process.

The tool is widely accessible. It is web-based and also app-enabled. Thus, we often find that it is open in department meetings and being used to frame departmental conversations about outcomes, how those are measured, etc.

The tool is easy to use. The data dashboards use simple menus to identify the data one wants to look at, to set up comparisons, and to facilitate disaggregation of the data in multiple ways.

The tool can be fairly quickly launched. Tableau programmer is generally able to put together a dashboard in a matter of hours, rather than days or weeks. This is a testament both to her technical wizardry, but also to the design of the software that facilitates quick design and launch of new dashboards.

The tool is customizable. Users can identify favorite dashboards, views, and characteristics of the dashboards so that they are not "recreating," or hunting for the information they need.

The tool prompts discourse! The tool can be designed to restrict data to certain populations, but through the training and cultural development around the positive and transparency aspects of data, the tool has become a mechanism for collaboration and innovation.

The tool allows for the opportunity to build on itself. As an example, in response to a concern that differences may be due to inattention to rigor, we were able to build a "subsequent course completion" dashboard that was able to demonstrate how students performed in the next course (or all courses!), which aids in demonstrating mastery (or not) of outcomes.

  • Training (full-time faculty, adjunct faculty, staff, administration)

  • Tool Usage

  • Professional learning and development identified as a result of data discoveries using dashboards.

  • Curriculum alteration (e.g. Changing outcomes, norming, etc.) as a result of collaborative discourse prompted by the dashboards.

  • Longitudinal tracking of equity gaps at multiple levels. (Indeed, the tool itself is a means of assessing effectiveness).

The dashboards have been a game changer at Pierce College. Decisions are made based on evidence, whereas in the past they might have been made based on anecdotal information. We no longer wait so long for answers to our data-related questions a we have access, training, and support for finding and analyzing those data. Very importantly, our IR staff has been relieved of their duties as data “wait staff” and can engage in more meaningful and in-depth institutional research.

Most important, we are seeing real changes in student outcomes. With norming work completed or underway in nearly every academic department and with intentional and focused attention on equity gaps, we are realizing improved student retention, course completion, and degree
completion…and equity gaps are closing! Ultimately, faculty now know how students are doing in their classes and those of their peers and that, we are finding, is the most important precondition for improvement.

The tool has changed the conversation. By removing a sense of isolation that has existed for the faculty role for much of its history, colleagues can now see where differences exist and then discuss how appropriate those differences are. What follows are rich conversations about outcomes, student learning, pedagogy, norming, and a reaffirmation of both the value of having actionable data and the intentionality for student success that is the natural response.

RESOURCES AND LESSONS LEARNED

Tableau Software
Data/Tableau specialist
Capacity to undertake training and shifts in culture, particularly for faculty (see above).

  • Software license: Unsure on cost as we are part of a statewide contract.

  • Local cost for 0.5-1.0 FTE to build and support Tableau as a data delivery tool.

  • Faculty want these data. Both their own and those of their colleagues/departments.

  • Starting from a "volunteer" usage rather than a "mandated" usage was effective in getting us to a place where one is now seen as disconnected if they are not using the tool.

  • Some faculty/departments may need guidance beyond the foundational training. Thus, identifying a data coach may be beneficial to helping some departments launch the conversation and understand/analyze their data.

  • You will see things that make you uncomfortable, but those are precisely the things that lead to professional learning, improved teaching & learning, and the advancement of student success.

FOR MORE INFORMATION

https://www.nisod.org/password/abstracts/XXXVIII_22.html

Carly Haddon
Data Solutions Developer/Analyst
Pierce College
9401 Farwest Drive
Lakewood, Washington 98498
Phone: 253-912-3754

chaddon@pierce.ctc.edu

Matthew Campbell
Vice President, Learning & Student Success
Pierce College Puyallup
1601 39th Avenue SE
Puyallup, Washington 98374-2222
Phone: 253-840-8419

Mcampbell@pierce.ctc.edu