Adaptive Learning: Effectively Integrating Technology into the Classroom (181417971)

7/27/2019 Adaptive Learning: Effectively Integrating Technology into the Classroom (181417971)

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Adaptive Learning:

Effectively Integrating Technologyinto the Classroom

Rahim S. Rajan

Senior Program Officer

Postsecondary Success

October 17th

Educause 2013



Adapt ive Learning:

Effect ively Integrating Techno logy into

the Classroom

Panelists:• Adam Newman, Managing Partner, Education Growth Advisors

• Joseph E. Beck, Assistant Professor, Worcester PolytechnicInstitute

• Deb Bushway, CAO & VP Academic Innovation, Capella University

• Scott Dalrymple, Dean, School of Liberal Arts, Excelsior College

Moderated by:• Rahim Rajan, Senior Program Officer, Postsecondary Success, Bill

& Melinda Gates Foundation

November 1, 2013 © 2013 Bill & Melinda Gates Foundation | 2




Bill & Melinda Gates Foundation’s

PERSONALIZED Strategy

Students learn best wheneducation is targeted to their needsand goals. Our partners areexploring how all students—not justthose who are able to attend themost elite, expensive colleges—

can get the best, most

personalized education at areasonable price, using integratedtechnologies with outstandingteaching.



Benefits of Personalized & Adaptive Learning

November 1, 2013

We believe that well implemented personalized & adaptive learning has the potential todramatically improve student outcomes

Potential Pedagogical Benefits*

Formative Evaluation (d=.90)

Acceleration (.88)

Effective Feedback (.73)

Meta-cognition (.69)

Mastery Based Learning (.58)

Concept Mapping (.57)

Interactive content (.52)

*Source: John Hattie’s Visible L earnin g

800+ meta analysis onachievement

Standard deviation is effectsize where d = 1.0

(i.e. improvement of learningby at least 50%)

Average effect size d=.40

When d is > .40

excellent achievement gains

4



An Emerging Evidence Base:

Research on mastery based learning and digital tutors – Bloom’s 2 sigmafindings (B. Bloom, 1984); recent research that argues intelligent tutors arenow nearly as effective as 1:1 human tutors (K. Van Lehn, 2011).

Randomized controlled study by ITHAKA conducted with six publicuniversities w/ statistically reliable control and treatment groups, found nodifference in learning between the blended and face to face groups, with OLIstudents completing approximately 25% faster.

Previous research by CMU of CMU students documented that studentsachieved the same or better learning outcomes on an independent third partyassessment while completing the course 50% faster.

Knewton / ASU partnership on re-designed emporium and mastery basedmath courses – pass rates increased by 18% and withdrawals dropped by

more than 47% -- reducing drops to ~240 and saving ASU an estimated$12,000,000 in lost tuition.

Cal State Northridge (Next Generation Learning Challenges Wave 1winner) - a 67% increase in Math 103 pass rates (from 45% to 75%).

November 1, 2013 5



6

The Adaptive Learning Market

November 1, 2013

X

CurrentMarket State

X

Innovators Early Adopters Early & LateMajority

How do weaccelerate the

market to reachhere?

• The adaptive learning market inpost secondary education isdiverse, yet embryonic.

• Only the most innovativeinstitutions are experimentingwith these solutions privately.

• It may take many years toadvance and refine thesesolutions and see themimplemented broadly



Adaptive Learning Market AcceleratorGrant Program


14 Grants involving

17colleges, universities

9 Adaptive Learning Platforms

30 Courses in12 Disciplines

32,358 Total Students Enrolled (across 3 terms)

44% Average % of Pell eligible students at grantees

4 yr.Institutions

2 yr.Institutions

For Profit

Gen Ed

Dev Ed

OnlineBlended

Blended /Emporium



Adam Newman

Managing Director,Education Growth Associates

Joseph E. Beck,

Assistant Professor,

Worcester Polytechnic Institute

Deb Bushway,CAO & VP Academic Innovation,

Capella University

Scott Dalrymple,Dean, School of Liberal Arts, Excelsior College


Adapt ive Learning :

Effect ively Integrat ing Techno logy into the Classro om


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Preamble – Starting a Conversation about the

Direction and Implications for Adaptive Learning

• In the future, institutions may not own the student learning experience,

but may only contribute to a portion of it, even within the context of a

student earning a specific degree

9

2000 2025

Institutional Needs

Student Needs

Learning

Experience

“Drivers” Workforce Needs



Where Is “Adaptive Learning” on the Hype Cycle for Education?

10

Adaptive

Learning

MOOCs

SocialLearning

Platforms

E-Textbooks



Working Definition of Personalized Learning, of

which “Adaptive Learning” Is a Subset

• A pedagogical method that draws on observation to inform tailored educational

interventions designed to increase the likelihood of student success

• Technology is not essential, but it facilitates personalization at scale

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• Embedded

• Portfolio

• Standardizedcontentconnected

• Standardizedcontent

• PedagogicalProfile

• LearnerProfile

Observe Instruct

AssessRemediate

F o u n d a t i o n a l E l e

m e n t s

F o u n d a t i o n a l E l e m e n t s

Personalization Process

DRAFT



Clarifying Use of “Personalized Learning” and “Adaptive”

• Personalized learning is an umbrella term incorporating various methods for

enabling more individualized instruction

• Adaptive and/or adaptivity is used in reference to product-level attributes

– Adaptive products/solutions are technology based, enabling scale

– Solutions leverage research across a host of areas such as:

• Intelligent tutoring systems

• Machine learning

• Knowledge space theory

• Memory

• Cognitive load theory

• Adaptive products/solutions represent one approach for enabling

personalized learning models

12

http://www.virtualnerd.com/



PL Landscape: Suppliers Are Converging on Models

from Different Vantage Points

13

“Established” Publishers

• Migration to content plustech and services

• Homework solutions

Alternative

Institutional Models

• Social

• Scale

• Unaccredited

Adaptive Platform

Providers• PL “infrastructure”

• Content-agnostic

• Learner analytics

PL

“Emergent” Publishers

• Beyond the book

• Immersive experiences





14

Adaptive TAXONOMY Framework Sample Overview



Education Growth Advisors © 2013

Adaptive Solution MATURITY Framework Sample Overview

15




Selected Observations

• “Adaptive” is one flavor of personalized learning that supports a range

of emerging approaches:

– Digital tutors and academic support

– Competency-based instruction

– Analytics and outcomes measurement that drives continuous improvement

• At surface level, suppliers may look similar; reality is that meaningful

differences exist in approach and potential use case

– Institutions need to clearly define their own needs vs. available use cases

• Suppliers are eager to engage with institutions and partners to secureguidance and align future development efforts

• Tracking supplier market evolution should be an ongoing activity

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http://edgrowthadvisors.com/research/

17

Adam Newman

Managing Partner617-447-9073

[email protected]


mailto:[email protected]

mailto:[email protected]




Adam Newman

Managing Director,Education Growth Associates

Joseph E. Beck,

Assistant Professor,

Worcester Polytechnic Institute

Deb Bushway,CAO & VP Academic Innovation,

Capella University

Scott Dalrymple,Dean, School of Liberal Arts, Excelsior College


Adapt ive Learning :

Effect ively Integrat ing Techno logy into the Classro om



Thank you!


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Adaptive Learning: Effectively Integrating Technology into the Classroom (181417971)