What is the term for a systematic approach to predicting learner outcomes?

The term that accurately describes a systematic approach to predicting learner outcomes is predictive learning analytics. This type of analytics focuses on using historical data and statistical algorithms to forecast future performance and learner engagement. By analyzing patterns within the data, educators and instructional designers can identify potential learner success factors or challenges, enabling them to proactively adjust strategies to enhance learning outcomes.

Predictive learning analytics plays a vital role in creating targeted interventions and tailored learning experiences based on the predictions made about learner needs. This aligns closely with the goals of talent development professionals, who seek to optimize educational paths and improve individual and organizational performance.

In contrast, adaptive learning analytics refers to the customization of learning experiences in real-time based on learner data, while descriptive learning analytics focuses on interpreting past learner performance to understand patterns and trends. Prescriptive learning analytics goes a step further by recommending actions based on data analysis but does not primarily aim at predicting future outcomes.