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AP HigherEdge Solutions:

Data Science & Analytics

Improving student outcomes through data analysis

Our Process

Our Data Science and Analytics team supports all AP services with evidence-based insights that drive strategies and tactics related to student experience, performance and efficiency. The use of behavioral data enables us to better understand the student experience and share these actionable insights with our partners.

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Using evidence-based insights, our team shares opportunities that enhance the university and student experience.

These insights have led to:

Improvements in admission
processing time

Enrollment growth

Higher student persistence rates

Resource management efficiencies

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Our Team

Our Data Science and Analytics team applies its cross-disciplinary experience and uses multiple techniques to conduct analyses—all for the purpose of improving university partner and student experiences. We share these findings to be insightful and actionable and to help our partners deliver optimal online student experiences.

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Technology

The AP Data Science and Analytics team uses a variety of tools, including state-of-the-art predictive analytics software to derive insights from data and model it in a way that delivers actionable and prescriptive solutions for our partner universities.


Tools for Gaining Understanding

The AP team uses a variety of tools and techniques to:

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Mine and analyze structured and unstructured data

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Create data visualizations

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Import and export from other data-collection channels

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Create predictive models to forecast future probabilities

In addition to using software to derive information from aggregated data, the team engages with partner universities to provide qualitative feedback and insights to meet our shared enrollment, retention and student satisfaction goals.

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Successes

Our analytical discovery is tailored to each university partner and seeks to discover patterns that subsequently inform relevant solutions to identified challenges. Below is an example of generalized findings from the Data Science and Analytics team:


Analyzing Retention Patterns and Step-Out Reduction

Our team recently assessed step-out trends across partners and programs in order to understand the impact of an online student onboarding program. For five out of the six programs studied, the onboarding program appeared to have had a positive effect in reducing program step-outs.

Exhibit:

Chart - Step-Outs as Percentage of On-Boarded and Non-Onboarded Students [close-]