A Methodology for Discovering how to Adaptively Personalize to Users using Experimental Comparisons

TL;DR

This paper introduces a formalism and methodology that unify experimentation and personalization, enabling adaptive technology design through randomized experiments and user data analysis.

Contribution

It presents the MOOClet Formalism, a unified framework for combining A/B testing with adaptive personalization in technology design.

Findings

Demonstrates how experimentation can inform personalization strategies.

Provides a software pattern for real-time adaptive technology.

Uses a concrete case to illustrate the methodology's effectiveness.

Abstract

We explain and provide examples of a formalism that supports the methodology of discovering how to adapt and personalize technology by combining randomized experiments with variables associated with user models. We characterize a formal relationship between the use of technology to conduct A/B experiments and use of technology for adaptive personalization. The MOOClet Formalism [11] captures the equivalence between experimentation and personalization in its conceptualization of modular components of a technology. This motivates a unified software design pattern that enables technology components that can be compared in an experiment to also be adapted based on contextual data, or personalized based on user characteristics. With the aid of a concrete use case, we illustrate the potential of the MOOClet formalism for a methodology that uses randomized experiments of alternative micro-designs to discover how to adapt technology based on user characteristics, and then dynamically implements these personalized improvements in real time.