Sharing Data with Students to Inform Decision Making

Ask eAIR invites questions from AIR members about the work of institutional research, careers in the field, and other broad topics that resonate with a large cross-section of readers. Questions may be submitted to 

This month’s question is answered by Rachel Boon, Academic Program Manager at the Iowa Board of Regents.

The ideas, opinions, and perspectives expressed are those of the author, and not necessarily AIR. Members are invited to join the discussion by commenting at the end of the article

rachelboon.jpgDear Rachel: The Statement of Aspirational Practice for Institutional Research talks about "Activating Data-Informed Student Decision Making." How can IR professionals share data with students in a way that informs their decision making?

Using data to evaluate, inform, and improve education motivates institutional researchers every day. This work takes the form of both retrospective reviews and predictive analyses that guide daily decisions and strategic directions. Technological advances allow data to be gathered on more and more of the activities in which students engage at institutions, and terabytes of data can be stored through cloud computing providers for mere pennies. Accompanying this growth are opportunities for improving student outcomes by getting useful information into the hands of the students themselves. The Statement of Aspirational Practice for Institutional Research leads with this concept and three suggestions about how to do so. It should: 1.) inform student decisions, 2. be designed with students as the target audience, 3. have student-centric timing of the information release. Before really getting into the “how” of sharing data with students, we need to have some other foundational conversations.

Steps* to guide IR professionals in sharing data with students:

  1. Determine the full range of data available.

  2. Review (or develop) institutional polices and standards for responsible use of student data.

  3. Communicate these policies and standards with students, faculty, and staff.

  4. Bring together cross-functional stakeholders, including students, to prioritize which data and analysis will most help students, and through which delivery mechanisms.

  5. Review first attempts with cross-functional stakeholders and students to ensure proper interpretation and clarity.

  6. Distribute to students.

  7. Evaluate effectiveness and adjust as necessary.

 * Each “step” is actually a series of steps

Many vendors are leap-frogging institutions and IR departments in the capacity to distribute data points directly to students. Updates to LMS platforms or analytics software often include “real-time” predictors of end-of-term grades for students using the platforms. Pushing this information out to students, whether through the vendor platform or a home-grown version is an exciting development, but the IR professional plays another critical role in these situations. Students need to be properly informed of what this information represents. Since 2014, a group of researchers and academic leaders have been meeting to discuss the importance of responsible use of student data (Stanford CAROL & Ithaka S+R), and two of the baseline principles they identified for model institutional policies are transparency to students on how they are being assessed, and shared understandings about the purposes of data collection at the institution. The ethical standards for working with, analyzing, and distributing data and knowledge gleaned from it must lead the conversation at your institution or system. Data security and individual privacy are two obvious concerns, but you should also have robust conversations about student agency, the presence of bias in predictive and analytical models, and where or how qualitative insights can add texture to information that supports student decision-making.

If strong ethical standards are in place, the IR professional should work with stakeholders to determine what student decisions the institution needs to inform through data. Do students need more information about what classes to register for each semester (perhaps to avoid “toxic” course combinations associated with high failure rates)? Are there co- or extra-curricular activities for which the institution wants to influence student participation because it is correlated to higher term-to-term retention? How many work hours are “too many”? Before rushing answers to these questions to students, share them with key administrators, faculty, and staff to determine relevant context as it affects interpretation of the results. Dissuading students from certain course combinations may result in pushing them out of sequence and delaying their graduation. Perhaps the activity correlated with higher retention is only available to students in fraternities or sororities. A key to effectively sharing data with students, as with all data and analysis that goes through the IR professional, is critically analyzing and interpreting it and then providing the recipient with the information necessary so he/she can make a decision.




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