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In this column, describe challenges at your institution preventing meaningful data collection and strategic decision-making.

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In this column, describe challenges at your institution preventing meaningful data collection and strategic decision-making.

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Please click the + under each relevant column to add your responses

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Please click the + under each relevant column to add your responses

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In this column, describe the current role assessment plays at your institution: How does your institution communicate data to inform budget allocations? How does your institution communicate data to inform satisfaction?

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In this column, describe the current role assessment plays at your institution: How does your institution communicate data to inform budget allocations? How does your institution communicate data to inform satisfaction?

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In this column, consider the campus conversations at your institution that you can engage: What data CURRENTLY informs decision making? What data SHOULD inform decision making?

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In this column, consider the campus conversations at your institution that you can engage: What data CURRENTLY informs decision making? What data SHOULD inform decision making?

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Many faculty feel that the collection of data is the point and are not motivated to respond to the data.

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Unanswerable questions are being asked

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Describing the data in meaningful ways

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One office doesn’t talk to the other—territorialism

Competing definitions of terms

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Different data collection systems that don’t integrate well. (SIS, FinAid)

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Lack of coordination between offices/departments

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Lack of coordination between offices/departments

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Knowing what data is available and IR’s willingness to share that data.

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Getting people into the habit of looking at data before making decisions.

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Poor collaboration across units

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Centralized data collection compared to silo’d data that people may or may not know about.

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Sometimes data changes to support the presenters' decision

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Sometimes data changes to support the presenters' decision

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Knowing how to access and interpret centralized data

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Time to figure out best data. Who has what types of data?

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Decisions are being made without an understanding of what the data really means and without consulting with those that best understand the data

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Constituents don’t know how to interpret the data

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No single app/platform, nor standards for the collection of that information beyond “participation/enrollment”

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Only one IR person

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requests for compilation of data are often seen as a meaningless nuisance or (worse) a threat

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Knowing which questions to ask.

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Students and faculty aren't always seen as co-designers that deserve to have agency over whether, what, and how data should be collected. It also seems that data driven tools often accept austerity as a given, rather than a policy choice that can be challenged or changed.

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Students and faculty aren't always seen as co-designers that deserve to have agency over whether, what, and how data should be collected. It also seems that data driven tools often accept austerity as a given, rather than a policy choice that can be challenged or changed.

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Unclear what data needs to be collected and what it is that we are trying to track. There are too many people with ideas on what we should do, but nobody is willing to say this is the direction we should go

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Pushback against the idea of operationalizing strategic pillars as metrics (measurable KPIs)

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Pushback against the idea of operationalizing strategic pillars as metrics (measurable KPIs)

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Without knowing the question, what data to collect, in what form, and from where is challenging.

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Without knowing the question, what data to collect, in what form, and from where is challenging.

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Data we rely heavily on - like class sizes, faculty loads etc don't work appropriately for people teaching labs or studio classes and it may not be clear to folks using the data why this is the case

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Data we rely heavily on - like class sizes, faculty loads etc don't work appropriately for people teaching labs or studio classes and it may not be clear to folks using the data why this is the case

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Common definitions I.e. Full time/ part time ratio: what is a full time faculty member. What if he/she teaches extra courses? Adjunct for the overload courses and full time for the contracted load, or all full time?

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This is mostly done at upper administration/cabinet level (small school). I’ve only really seen it shared with faculty when we hired a consultant company.

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Learning Outcome assessment data is currently not used to tell the story of our institution. We also are not engaging in meaningful assessment of co-curricular and curricular-support.

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Pockets of data but not consistent amount/ depth across areas

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Pockets of data but not consistent amount/ depth across areas

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Clear data necessary for a proposal, but data has little influence on larger institutional priorities. Ad hoc relationships and convenient benchmarking seem to do much of the heavy lifting there

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Technology is a big issue- what do we do with the data we collect and how do we present that data? What should we use to house the data, present the data etc?

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Our office has not been part of strategic planning, though we are moving that way next fall.

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Poor data quality. Important indicators are difficult to access (e.g. number of majors). Plethora of purchased tools and reports. different tools give different answers to the same question. IR office produces misleading reports on fundamental measures ( I.e credit hours generated per department).

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We often mistakenly assume that perception is consistent with reality

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Deans are supposed to look at current numbers of majors when planning future course scheduled, but they go by last year’s data instead. Then we have low enrolled courses.

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OIR has good data but (I think) mostly works on
1) reporting out to the government, US news&world, etc.
2) helping keep track of faculty teaching loads, class sizes

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The President’s Cabinet makes most budgetary decisions with little input from the IE office or the faculty

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The President’s Cabinet makes most budgetary decisions with little input from the IE office or the faculty

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Our institutional researcher is no longer able to provide data to faculty or departments as she is too busy providing data for academic affairs, assessment, IPEDs, etc

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Our institutional researcher is no longer able to provide data to faculty or departments as she is too busy providing data for academic affairs, assessment, IPEDs, etc

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When it comes to data used for student success, it often seems to focus on nudging students to make "good" choices (the right configuration of classes, to spend more time in the library, etc.) rather than addressing institutional failures to support marginalized students, and which might require that administrators and policymakers, rather than students, become the object of the data collection and analysis. 

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When it comes to data used for student success, it often seems to focus on nudging students to make "good" choices (the right configuration of classes, to spend more time in the library, etc.) rather than addressing institutional failures to support marginalized students, and which might require that administrators and policymakers, rather than students, become the object of the data collection and analysis. 

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OIR itself emphasizes that their job is only to provide data but not to provide “the narrative”.

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Concerns about outsourcing of institutional data collection and assessment to private companies, concerns about data that can be used to curtail academic freedom of faculty and undermine student privacy and other protections.

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Concerns about outsourcing of institutional data collection and assessment to private companies, concerns about data that can be used to curtail academic freedom of faculty and undermine student privacy and other protections.

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Satisfaction survey reports come before and are at least somewhat verbally summarized at college wide functions

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Satisfaction survey reports come before and are at least somewhat verbally summarized at college wide functions

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it feels like data isn't communicated- it's more along the lines of here is the issue we are dealing with currently- what data do we have help us with this problem- it feels like data is reactive not proactive

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Current- Enrollment, retention, and graduation rates
Should include student success around stated outcomes

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The data that demonstrates money acquisition (butts in seats) is used but student learning is ignored.

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I'm concerned that some institutions are using institutional data to undermine DEI efforts and racial equity education, rather than support them.

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I'm concerned that some institutions are using institutional data to undermine DEI efforts and racial equity education, rather than support them.

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We don’t share information below the highest levels of leadership. We don’t collect good/reliable data to start with either.

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We gather data very well, and yet most curricular decisions are made by anecdotal evidence and perception

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We report various metrics (ETA assessment test scores, program assessment plan results, etc.) most faculty see this as lip service for accreditation, while a few faculty and the Dean are encouraging us to treat these data as opportunity for reflection.

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Data that shows that students are learning, they are developing critical thinking skills and that we are developing graduates that are well rounded citizens

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News and opinion articles often inform the conversation, sometimes independent of Institutional data.

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News and opinion articles often inform the conversation, sometimes independent of Institutional data.

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Instructional units, term and enrollment and majors reports all used heavily

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Should dig into retention causes and correlates 

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Should dig into retention causes and correlates 

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I’ll add - we use course grades, DFW rates. Should use student learning metrics.