Adaptive technologists develop online STEM course of the future

Online courseware provider used by edX is re-imagining what online STEM could look like

cerego-personalized-coursewareUsing “the science of memory,” and recent advances in personalized learning, an adaptive courseware provider is developing a STEM course aimed at engaging and retaining at-risk students.

A recent recipient of the the Bill & Melinda Gates Foundation Next Generation Courseware ChallengeCerego says its future course, StatsPL, will allow for such personalization of STEM learning that the course could reach more than 1 million low-income students by 2018.

The courseware provider not only plans to reach these students through what it calls the science of memory, but in allowing for students’ personal passions to dictate the course…even if it’s a statistics 101 course.

“We’re a group of scientists and technologists,” said Cerego executive chairman and co-founder Andrew Smith Lewis. “We’re not content experts, but we work with them in order to personalize knowledge acquisition.”

Founded in 2000, Cerego incorporates what it says is long-standing research on the science of memory, which the company felt was often under-utilized, in order to improve learning efficiency and ensure that crucial concepts are never forgotten.

Specifically, Cerego says the adaptive platform focuses on helping users master foundational knowledge by focusing on recency, frequency, and patterns of prior exposure so that students are shown information again whenever they are on the cusp of forgetting.

“At the end of the day, the goal is that everyone masters the concepts,” Smith Lewis said. “A one size fits all model of instruction doesn’t work as well as a personal tutor.”

After becoming the first third-party developer to join with edX, Cerego now hosts hundreds of courses on their website from a multitude of developers including Cerego themselves, many of which are used by major online institutions including HarvardX and MITx.

The courseware being developed now, though, might be Cerego’s most innovative and ambitious project yet. The course, which is called StatsPL, will bring in a host of collaborators from many different fields in order to create a highly personalized experience.

(Next Page: How Cerego’s StatsPL will take personalized learning to a new level in STEM)

Thanks to funding they received for being a finalist in the Bill & Melinda Gates’ Next Generation Courseware Challenge, Cerego plans to develop their cutting edge statistics STEM course as a cross “between personalized learning solutions and real-life statisticians in an effort to make it much more approachable and enjoyable,” Smith Lewis said.

In an effort to make the course more engaging to students, Cerego will implement sections focusing on “statistics in action,” where students will be able to learn about concepts using examples of their choice from a host of specific topics including sports statistics, underwater exploration, and exoplanet searches, to name a few.

This tactic aims to elevate the course into a truly personalized experience, as well as a highly collaborative one, and Smith Lewis hopes it will “inspire students to notice interesting fields” in statistics that they may not have sought out beforehand.

More than merely a supplement, StatsPL is being developed to play a major role in introductory statistics courses, with features that could help lecturing teachers more easily grasp how their students are doing in the course, said the company.

So far, partners for the development of the courseware include OpenStax, edX, NYU Create, BBC Worldwide Learning, the SETI Institute, Fabien Cousteau’s OceanLearningCenter, and CUNY’s Center for Advanced Study in Education.

Cerego hopes StatsPL will be fully completed by 2018. The first beta rollout is expected as early as next fall, where the course will be piloted at schools affiliated with the Columbia College network.

If StatsPL is a success, Cerego hopes they can take what they learn from the course and make personalized learning into a generalized model that can then be applied to other 101 courses in the future.

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