Adaptive learning systems that calibrate tasks to the zone of proximal development¶

Element · All elements
Evidence · no claims cited

Description¶

The paper names adaptive learning systems as technology supporting the level dimension of personalization. It states that "Adaptive learning systems (e.g., DreamBox, i-Ready, Istation, A2I) calibrate work automatically, keeping tasks in the zone of proximal development," defined as the difference between what a learner can do without help and what he or she cannot do. Feedback from adaptive assessments helps teachers quickly pinpoint learning level and adjust units of learning.

Design Implications¶

Context¶

Requirements¶

• Access to appropriate and research-based technology; feedback loops from adaptive assessments to teacher decisions

Constraints¶

• The paper presents these systems as examples supporting differentiation, reporting no comparative effectiveness evidence in this document

Target Learners¶

• K-12 students needing individually calibrated task difficulty

Target Learning Goals¶

• Maintaining productive challenge, avoiding boredom and frustration, and pinpointing learning level

Related Elements¶

Examples¶

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Key Sources¶

• Barbara Pape and Tom Vander Ark. (2020). Policies and Practices That Meet Learners Where They Are. Digital Promise Global. https://global.digitalpromise.org