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Adaptivity & Expert Learners

Sketches of a student using the Clusive in two different contexts

The adaptive features in Clusive will provide recommendations for supports and content that individualize learning with the ultimate goal of creating expert learners.

Adaptive learning environments customize content and supports in response to individual learner needs and preferences. The CISL project leverages adaptivity in service of the ultimate goal of Universal Design for Learning: to build expert learners.  It does this by making clear, data-driven recommendations transparent for learners, putting ultimate control in the hands of learners themselves, in order to promote student learning, motivation, and self-agency.

How does CISL use adaptive learning solutions to help build expert learners? CISL tools:

Try out the adaptive features in Clusive

What does adaptivity mean to you?

The creators of Clusive share their thoughts on what adaptivity means from their perspective in the design and implementation process.

User Experience / Design: Kim Ducharme

Photo of Kim Ducharme

“In my mind, the best kind of adaptivity means the system knows me seemingly better than I do, at least at first. It notes my patterns and preferences, delivers me a just-right experience both seamlessly and with my full knowledge of what’s going on behind the curtain and why, at least when and where I want it. The best kind of adaptive system scaffolds my learning experience and, together with me, releases the training wheels as I learn where to reach for what I need — as I gain a better command of what works best for me.”

Kim Ducharme, CAST Director of Educational User Experience Design

 

Research: Bob Dolan

Photo of Bob Dolan

“Expert learners decide for themselves which content, contexts, and supports work best. Even when curricula, instruction, and materials adhere to UDL principles and provide flexibility, it is daunting for students to make effective choices. An excellent way to support students in building the metacognitive skills foundational for expert learning is through modeling. This is where effective adaptive learning systems can best operate—and why they must operate transparently. Adaptive learning solutions that indicate why choices and recommendations are made can scaffold students in making effective choices, Allowing students to override system decisions further provides opportunities for self-agency. In the end, students are provided not only with improved learning opportunities for proximal goals, they’re supported in becoming expert learners.”

Bob Dolan, CAST Senior Innovation Scientist

 

Instructional Design: Kristin Robinson

“In biology, an adaptive feature is something that allows a living thing to thrive and grow. I think of that definition when I consider adaptivity in Clusive. Adaptivity means that learners have the unique set of features that allow them to grow, and these change as a learner and their environment changes. And UDL adaptivity means that the learners see, clearly, how they are learning, what things they need to grow, and how their challenges and strengths change over time and conditions.”

Kristin Robinson, CAST Instructional Designer & Research Associate

Screen capture of Clusive recommendation panel.

A game-like word challenge gathers information about users and informs Clusive recommendations.

What adaptivity features does Clusive currently contain?

Adaptive dictionary and glossary. When Clusive users open a learning object, they can opt to do a game-like word challenge that evaluates their current word knowledge and allows them to set goals. Inside a text, learners can look up words, view their previous word activity, and add any word or term to their personal Clusive Word Bank, a full list of words collected by a learner.

What adaptivity features are we working on now?

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