Savanna Hoffman
Data is an invaluable resource for universities to improve the student and faculty experience. Universities collect student data through various methods, including admissions processes, online forms, surveys, and digital footprints. This data helps universities make informed decisions about recruitment, admissions, and financial aid, as well as identify areas for improvement and make proactive choices. Additionally, data analysis provides insights into student learning journeys, allowing universities to support students' academic progress and completion. The effective use of student data also enables universities to measure the impact of financial donations and allocate resources efficiently. While data collection offers significant benefits, it raises concerns about student privacy, ethical practices, and responsible data usage.
| Characteristics | Values |
|---|---|
| Student data privacy | Strict federal privacy laws protect the private information of students. |
| Student data privacy in practice | Schools may unwittingly help data brokers by distributing third-party surveys to students. |
| Student data sources | Potential sources of data include public records, retailers, or information students provide online. |
| Student data use | Data is used to inform recruitment campaigns, admissions decisions, and financial aid offers. |
| Student data and technology | Learning management systems, online forums, AI-based tutors, and conference platforms all leave digital traces of instructional effectiveness, learning, and user preferences. |
| Student data analytics | Predictive analytics are used by instructors, advisors, and students to improve performance and flag issues. |
| Student data and privacy policies | Most students are unaware of how much data their institutions have about them, but they are also not overly concerned. |
| Student data transparency | Students seem to trust educational institutions more than tech companies when it comes to handling private information. |
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What You'll Learn
Student data privacy
Federal privacy laws, such as the Family Educational Rights and Privacy Act (FERPA) in the US, protect the private information of students. FERPA gives parents and students assurance that the data used to create school records is reliable, relevant, and fair. It also grants parents and adult students the right to inspect, correct, and request amendments to education records. However, FERPA only applies to a small subset of records, and its interpretation can vary. For example, many universities interpret FERPA as forbidding them from sharing information about the outcomes of disciplinary cases, even in serious crimes.
Universities must navigate a complex landscape of ethical and responsible data usage while also complying with regulatory requirements. They need to understand student perceptions of privacy and create a culture that values data protection. This includes addressing concerns about how data is handled and ensuring transparency in data practices.
Additionally, universities should be aware of potential data brokers who may be acquiring student data from various sources, including public records, retailers, or online activity. While schools and universities are not found to be directly providing data to these brokers, they may inadvertently contribute by distributing third-party surveys.
To ensure student data privacy, universities should implement measures such as data encryption, secure data storage, and clear data-sharing protocols. They should also provide students with clear and transparent privacy policies and obtain consent for data usage. By prioritizing student data privacy, universities can build trust and ensure the ethical handling of sensitive information.
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Data-driven recruitment
Universities have access to a wide range of student data, from their digital learning activities to their personal information. With the steeply diminished costs of computation, universities can now use student data in innovative ways to improve student outcomes, build basic science, and sell products.
- Monitoring application sources: By tracking the sources of applications (job boards, ads, agencies, social media, etc.), universities can identify which channels bring in the most qualified candidates and allocate their budget accordingly.
- Reducing bad hires: Data on previously successful candidates can be used to establish criteria and improve the quality of future hires. This can help universities avoid costly mistakes and improve their short and long-term performance.
- Improving timing: Data-driven prospecting provides better decision-making frameworks and forecasted workloads, allowing universities to better manage the timing of the hiring process.
- Predicting student success: Early-alert systems can aggregate and analyze data from multiple sources to identify student behavior associated with lower academic success rates. This information can be used to intervene and improve student outcomes.
- Addressing retention issues: By analyzing historical data, universities can identify areas where students consistently struggle and develop supplemental instruction programs to improve retention and completion rates.
Overall, data-driven recruitment enables universities to make more informed decisions, eliminate guesswork and biases, and ultimately select the best candidates for their programs.
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Student data analytics
Universities collect student data from various sources, including learning management systems, online forums, AI-based tutors, and conference platforms. These digital services leave traces of instructional effectiveness, learning patterns, and user preferences. For example, universities can track how prospective students navigate their websites, analysing the digital breadcrumbs to understand the college search process. This data helps admissions teams make calculated decisions about their outreach strategies and personalise their content and communication.
Another example of student data analytics is the use of early-alert systems that aggregate data from multiple sources, such as gradebooks and student information systems, to identify students who may be at risk of lower academic success. Advisor-facing systems, such as Arizona State University's eAdvisor, integrate data about student activity, registration, and background characteristics to notify advisors and encourage timely interventions.
Additionally, universities can use student data to improve retention and completion rates. Georgia State University, for instance, analysed historical data to identify courses with low student performance and implemented a supplemental instruction program, resulting in a significant increase in their graduation rate.
While student data analytics offers valuable insights, it also raises concerns about student privacy. Most students are unaware of the extent of data collected by their institutions, and many are not concerned about it. However, some worry that data-mining invades privacy, especially when it comes to tracking prospective students' website usage. Universities like the University of Michigan have addressed these concerns by appointing chief information security officers to ensure data privacy and ethical handling of student information.
In conclusion, student data analytics is a powerful tool for universities to enhance the student experience and make data-driven decisions. However, it is crucial to balance the benefits with the need to protect student privacy and ensure transparent data practices.
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Student data sources
Universities and colleges are increasingly relying on student data to inform their decision-making. This includes admissions and recruitment, with sophisticated algorithms now being used to inform recruitment campaigns and admissions decisions.
Student data is sourced from a variety of places, including:
- Digital footprints: Universities can track prospective students' digital footprints to make calculated decisions about their admissions outreach. This includes tracking how they use university websites and resources, such as through unique email links sent to prospective students.
- Third-party surveys: Schools may distribute third-party surveys to students, which can be a source of sensitive information such as race, religion, disabilities, sexual orientation, and immigration status.
- Public records: Publicly available records can be a source of student data.
- Retailers: Retailers may also provide a source of student data.
- Online activity: Students' online activity, such as their use of learning management systems and discussion forums, can be a source of data for universities.
- Student-provided information: Data can also come from information students provide to universities, such as through applications or enrolment forms. However, non-responses and incorrect information from students are becoming an issue.
- Student background characteristics: Information about students' backgrounds, such as family income, can be used in admissions and recruitment decisions.
- Academic performance: Data on students' academic performance, such as grades and course completion, can be used to inform decisions about student support and intervention.
- Student behaviour: Universities can collect data on student behaviour, such as attendance and participation, which can be used to identify students who may be at risk of lower academic success.
Privacy Concerns
While student data can be used to improve student outcomes, there are also privacy concerns. Many students are unaware of how much data their institutions have about them, and there are worries that data is being sold or shared without students' knowledge or consent. Strict federal privacy laws protect student information, but these only apply to schools, and there are data brokers that freely sell student data. Universities and colleges are therefore facing increasing pressure to ensure student data privacy and transparency in their data practices.
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Student data and privacy policies
Universities and colleges are increasingly relying on digital services to provide instruction, facilitate discussions, and simulate face-to-face interactions. All of these services leave digital traces of instructional effectiveness, learning, and user preferences, which are collectively known as student data. Student data can be used to improve student outcomes, build basic science, and sell products.
Student data is protected by strict federal privacy laws such as FERPA (Family Educational Rights and Privacy Act) and PPRA (Protection of Pupil Rights Amendment). FERPA, for example, allows educational institutions to share student information with contractors, volunteers, or other individuals providing services to the institution. In some cases, written agreements must be developed to protect student data, and the requirements vary depending on the specific context.
Despite these protections, student data can still be bought and sold by private data brokers. A study from Fordham University identified 14 companies that market student data to commercial interests. The sources of this data are unclear but could include public records, retailers, or information students provide online. Schools may inadvertently contribute to this issue by distributing third-party surveys to students. While this does not violate privacy laws as long as parental permission is obtained, it can provide an entry point for data brokers.
To address these concerns, schools should create comprehensive internal data policies that outline how employees can use student data. This includes establishing norms of confidentiality, obtaining informed consent, and ensuring secure storage of student data. Additionally, schools should provide training on data privacy legal requirements and establish a Data Breach Response Policy to handle potential breaches.
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Frequently asked questions
Universities collect student data through various means, including learning management systems, online forums, AI-based tutors, and conference platforms. Additionally, universities may acquire student data through third-party surveys, digital footprints, and tracking software on university websites.
Universities collect a wide range of student data, including but not limited to: course engagement behaviour data, financial information, academic performance, background characteristics, and health information.
Universities use student data for various purposes, including admissions and enrollment management, recruitment campaigns, financial aid decisions, and improving student outcomes. Universities also use predictive analytics to inform instructors, advisors, and students about potential issues and provide suggestions for improvement.
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