MIT
MIT Faculty Newsletter  
Vol. XXXI No. 1
September / October 2018
contents
Education for Credit/Education for Progress
MIT's Relationship to China
How Not to Teach Ethics
On Critical Thinking and Nerd Epistemology
A Collaboration in Learning
MIT Open Access Task Force Shares
White Paper on OA Landscape
The Transition to Retirement
Climate and Accountability
Stephen Hawking:
The Eminent Physicist vs. The Media Myth
Introducing the MIT
Academic Climate Survey
Study Abroad IAP Opportunities
Continue to Grow
Nominate a Colleague as a MacVicar Fellow
Request for Proposals
for Innovative Curricular Projects
from the 2018 MIT Survey of New Students
Printable Version

Introducing the MIT Academic Climate Survey

Lydia Snover, Jonathan Schwarz

Illustration: Jose-Luis Olivares

This fall, the Institutional Research (IR) group in the Provost’s Office will invite all faculty, staff, and students in academic departments and research units to participate in the MIT Academic Climate Survey. Although similar to the Faculty and Staff Quality of Life Survey administered in 2016 and the Student Quality of Life Survey administered in 2017, this survey is much shorter and more focused on the climate in academic departments and research units.

We appreciate that surveys can be an intrusion into the lives of respondents. In Institutional Research, we vigilantly seek to minimize the length and number of surveys that are administered at MIT for two reasons.

First, every response to every question on an IR survey is voluntary – respondents generously fill out our surveys to inform administrative policies and practices, and we want to be respectful of their time and effort. Second, we seek to minimize survey fatigue – there is a limit to how much you can survey a population; passing that threshold threatens the integrity and limits the utility of the data.

So why are we doing this?

By focusing on a limited number of metrics for the entire population in the same time frame and in shorter intervals, we will be providing department, laboratory, and center leadership with more useful and timely data. With a biennial rather than a quadrennial administration, it will be easier to measure changes that might result from initiatives taken by the local administration. Like most survey data, there will be a number of uses for data we collect in this survey. We will post overall results on the IR website. These data will also undergird the ongoing Department Support Program, a part of the MindHandHeart initiative, and provide important data for department and lab administrators.

Short and to the Point

We have designed this survey to be short, and focused with the goal of increasing response rates. About half of the survey may look familiar, because we have selected questions from previous surveys that have provided campus and department leaders with the most useful information. Higher response rates provide leadership with more reliable data.

Reporting and Confidentiality

It is essential that we receive candid and honest feedback through our surveys, especially for a topic as important as department climate. In order to improve the earnestness of responses, we want to be transparent about data security and confidentiality procedures so that respondents can have confidence that their responses are safe. We consider responses in climate surveys to be “highly sensitive” in nature and restrict access to these data to a small core of experienced Institutional Research analysts.

We take meticulous care to guard against inadvertent disclosure of individual responses. We only report quantitative survey data in aggregate form and do not report any survey responses for a sample of fewer than five respondents.

If there are fewer than five responses for any subgroup, we will follow one of two paths: pooling or redaction. Where possible, we will combine (pool) your data with data from colleagues in a similar area until we reach at least five. While five is our minimum, in practice, we often avoid reporting data for any category for which there are fewer than 10 or 15 respondents.

If we are unable to pool data in a logical way to obtain a large enough sample size, we will redact results for that group. In this case, one’s responses will be part of the aggregate data for a division, School, or the Institute, but will not be included at any level where there are fewer than five total responses.

Open responses play an increasingly important role in the data IR analyzes. The more nuanced information from these comments is incredibly valuable and we want to honor the effort that survey-takers invest in writing thoughtful answers to questions. At the same time, text boxes pose a particular challenge in reporting because they are subject to intentional or accidental disclosure of identifying information by the survey respondent. In most cases, we will analyze these qualitative data and provide summary findings. As is standard practice in qualitative research, occasionally we may use excerpts from open response items as illustrative examples. In doing so, we take precautions to guard against disclosing any identifying information.

We are also concerned about inadvertent disclosure of identifying characteristics. For instance, a colleague may have a distinctive writing style or favored turns of phrase that could make their open response identifiable. To minimize the likelihood of inadvertent disclosure, we will analyze and present open response data with an eye to protecting respondents as much as possible.

Thank you in advance for engaging with the Academic Climate Survey. Your feedback on areas such as workplace values, work-life balance, stressors, and what you like about your job will provide useful insight into what is going well at MIT and illuminate ways to improve the academic and research experiences of faculty, staff, and students. Your participation is highly valued and greatly appreciated. If you have any questions about the Academic Climate Survey or data protection in Institutional Research, please do not hesitate to contact us.

Back to top
Send your comments
   
MIT