Nudge Tech is prominent on the list and defined as: “a collection of technologies that work together to achieve timely, personalized interaction with students, staff and faculty, such as a just-in-time text (SMS) reminder for class. Technologies used include chatbot, texting, algorithmic analytics, machine learning and AI CI [Conversational Interfaces].”
Nudge Tech represents a remarkable fusion of advanced technologies and behavioral economics: AI and data analytics activating insights on human decision making—nudging. In Nudge: Improving Decisions about Health, Wealth, and Happiness, Thaler and Sunstein define a nudge as “any small feature of the environment that attracts people’s attention and alters their behavior but does so in a way that doesn’t compel.”
All but the most selective Higher ed institutions face numerous challenges to their continued operations from the immediate effects of COVID-19 to the long-term demographic declines in college-going populations. Nudge Tech must be a component in student engagement strategies seeking to boost enrollment and success outcomes.
“Above all, nudge tech is a concrete example of how to achieve personalization at scale, which is becoming a key competitive advantage in an increasingly global digital education ecosystem.”
Lowendahl, Jan-Martin and Morgan, Glenda. “Nudge Tech.” Top 10 Strategic Technologies Impacting Higher Education in 2020. (March 2, 2020)
Uniquely within nudge tech providers, Discourse Analytics delivers attitudinal personalization at scale. Our key insight is that humans make choices based on how they think, not their demographics. We harness artificial intelligence to deliver attitudinal personalization: nudges tailored to each person’s attitudes towards an issue.
For the second year in a row, we are honored to be referenced by Gartner in their analysis of Nudge Tech.
Gartner’s Recommendations on Using Nudge Tech in Higher Ed
Gartner provides a set of recommendations for higher ed CIO to capitalize on nudge tech, which are applicable to all institutional leaders seeking to improve enrollment management, advancement and student success. These six recommendations align with DA’s core operating principles:
- Make sure to understand nudge theory, as well as pros and cons of nudging. Look for a solid understanding of nudge theory from the vendors you invite. DA’s work is predicated on the research of leading theorists, including Amos Tversky, Daniel Kahneman and Richard Thaler.
- Ensure users’ trust by implementing transparency policies and interfaces, as well as opt-in and opt-out procedures for personal data. DA’s AI-platform only uses existing behavioral data on a university’s systems of record. Moreover, DA’s model does not use any Personally identifiable information (PII) such as name, age, gender, race for any student.
- Build a nudge tech business case by identifying narrow use cases that have clearly measurable outcomes on which to judge value. DA’s attitudinal nudging has helped colleges and universities enhance outcomes across a range of challenges—summer melt and yield management, FAFSA verification and financial aid processing, student persistence and retention, and alumni relations and advancement.
- Assess suitable data quality by identifying data sources, such as Q&A forums, SISs and LMSs that can act as the foundation for machine learning. DA ingests available student behavioral data from systems of record including the LMS, SIS, the CRM, and card swipe data from libraries and gymnasiums.
- Design for a virtuous learning cycle by capturing all interactions in a machine-readable format. DA’s AI-model uses machine learning to map new behavioral data, including responses to nudges, to the student’s individual attitudinal profiles throughout the engagement.
- Design the implementation so that statistically valid data can be collected for the “test group” as well as control group. The gold standard is to do a randomized controlled trial. DA benchmarks the results of every nudge campaign against a randomized control group from the target population.
Now more than ever, higher ed institutions must use AI to unlock the student insight buried in their systems to personalize communications. As Gartner emphasizes, “AI is a particularly good case for nudging, as it allows analyzing increasingly complex data for opportunities to impact behaviors.”
To successfully remain relevant and financially viable, institutions should deliver more student-centric personalization–motivating mindsets to attain desired outcomes. It’s time to embrace Nudge Tech.
To learn more about DA’s approach to Nudge Tech, contact: [email protected]
Download our free whitepaper, Why Attitudes Drive Decision Making: Reimagining Personalization to understand how student attitudes and “think-alike” mindsets explain student behaviors.