The Ethical Use of Data in Predictive Analytics
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CANCELED
Presenter(s):
Denise Nadasen, Association of Public and Land-grant Universities (APLU)
Julie Alig, University of Massachusetts-Lowell
Prerequisites:
To participate in this workshop, an attendee will need to:
1. Know the general business processes of their institution.
2. Be familiar with how student data is collected, used, and stored on campus.
3. Have experience working with other units on campus.
4. Be a junior, mid-, or senior-level institutional research manager. This workshop is not designed for data scientists, but it may not be appropriate for newcomers.
Description:
This workshop introduces predictive analytics in higher education, ethical concerns with the use of student data, and a framework that can address these ethical issues. While institutional researchers play an important role in framing how analytics can impact student success, ethical concerns around predictive analytics is often embedded within a broader culture of the institution. Participants are given scenarios to analyze and evaluate from an ethical perspective. A cross-functional, organic approach to finding a solution is discussed. Data governance is presented as a strategy to protect students and the institution. Participants will leave with: a greater understanding of how to identify bias in data and analysis; and a collaborative governance framework that can be used to address ethical and data issues effectively.
Intended Learning Outcomes:
Participants in this workshop will:
1. Through the content presented around ethics and an examination of different case studies using examples from institutions, participants will ground their understanding of ethical principles.
2. Gain hands-on experience through project work to independently develop a governance framework that can be used on their campuses to address ethical issues effectively.
3. Leave with a greater understanding of how to identify bias in data and analysis and recognize the value of various strategies for addressing ethical issues.
CANCELED
Presenter(s):
Denise Nadasen, Association of Public and Land-grant Universities (APLU)
Julie Alig, University of Massachusetts-Lowell
Prerequisites:
To participate in this workshop, an attendee will need to:
1. Know the general business processes of their institution.
2. Be familiar with how student data is collected, used, and stored on campus.
3. Have experience working with other units on campus.
4. Be a junior, mid-, or senior-level institutional research manager. This workshop is not designed for data scientists, but it may not be appropriate for newcomers.
Description:
This workshop introduces predictive analytics in higher education, ethical concerns with the use of student data, and a framework that can address these ethical issues. While institutional researchers play an important role in framing how analytics can impact student success, ethical concerns around predictive analytics is often embedded within a broader culture of the institution. Participants are given scenarios to analyze and evaluate from an ethical perspective. A cross-functional, organic approach to finding a solution is discussed. Data governance is presented as a strategy to protect students and the institution. Participants will leave with: a greater understanding of how to identify bias in data and analysis; and a collaborative governance framework that can be used to address ethical and data issues effectively.
Intended Learning Outcomes:
Participants in this workshop will:
1. Through the content presented around ethics and an examination of different case studies using examples from institutions, participants will ground their understanding of ethical principles.
2. Gain hands-on experience through project work to independently develop a governance framework that can be used on their campuses to address ethical issues effectively.
3. Leave with a greater understanding of how to identify bias in data and analysis and recognize the value of various strategies for addressing ethical issues.