intelligent adaptive learning - an essential element of 21st century teaching and learning

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Providing truly differentiated, individualized instruction has been a goal of educators for decades, but new technologies available today are empowering schools to implement this form of education in a way never before possible. Intelligent adaptive learning software is able to tailor instruction according to each student’s unique needs, understandings and interests while remaining grounded in sound pedagogy. Attend this web seminar to hear the latest findings from Cheryl Lemke, of the research firm Metiri Group, about how intelligent adaptive learning works, the role the technology can play in raising student achievement, and the research base required for districts to invest wisely in these new tools.

TRANSCRIPT

Intelligent Adaptive Learning

The What

The Learning

The R&D

Prototyping

- U.S. Department of Education

The

Curriculum sequencing Multiple experiences Customized presentation Individualized pace

Intelligent Adaptive Learning

Intelligent Adaptive Learning

Cognitive Modeling

Intelligent analysis data

Interactive problem solving support

Why now?

Intelligent Adaptive Learning

Intelligent adaptive learning (IAL) is defined as digital learning that: • immerses students in modular learning

environments

• where every decision a student makes is captured, considered in the context of sound learning theory, and

• is used to guide the student’s learning experiences, to adjust the student’s path and pace within and between lessons, and to provide formative and summative data to the student’s teacher.

The Learning

Frustration or confusion

Boredom

Task

Complexity

Skill Level

1

2

Based on: Csíkszentmihályi’(1991, 2000), Vgotsky (1978), Murray & Arroyo (2002) & Arroyo (2003)

Next Generation Digital Learning

Staker and Horn 2012

Staker and Horn 2012

Next Generation Digital Learning

Intelligent Adaptive Learning

Student

Database of

Student Data

Continuous capture and

storing of data

Cognitive Model/

Data Analysis

Continuous data feed

*Designed pedagogically to engage students.

Classroom

Intelligent feedback

to student

Data on student progress

Adapt sequencing, navigation, pace, pedagogy,

and presentation*

Intelligent feedback to system

Modular Curriculum*

Learning Activities*

Embedded, Adaptive, Continuous Assessment*

Real-time data capture

of student actions,

solutions, and

explorations online

Teacher

The

IAL Design Elements

1) Tutoring

2) Sequencing

3) Pacing

4) Regulating cognitive load

5) Engaging through gaming

… In the context of the cognitive model

Design Element: Tutoring • Tutoring, whether on the computer or in-person,

when done well, is twice as effective as classroom learning

• The secret sauce in tutoring is targeted feedback

• Targeted feedback has been found to increase the average student’s learning by 27 percentile points

Researchers have found that students receive little if any feedback in the classroom. Intelligent adaptive learning systems can change that.

Feedback

Learning Principles

• “An understanding is a learner realization about the power of an idea.”

• “Understandings cannot be given; they have to be engineered so that learners see for themselves the power of an idea for making sense of things.”

p. 113, Schooling by Design, Wiggins & McTighe, ©2007

Division with Remainders

Division with Remainders

?

Division with Remainders

Design Element: Sequencing

• Sequenced curriculum and learning activities based on student’s prior knowledge and skill levels

• Choice, challenge, engagement, and motivation

Frustration or confusion

Boredom

Task

Complexity

Skill Level

1

2

Based on: Csíkszentmihályi’(1991, 2000), Vgotsky (1978), Murray & Arroyo (2002) & Arroyo (2003)

Plan Backward from 6th Grade

The Distributive Property

(c + 9) × (n + 1)

cn + 1c + 9n + 9

25

26

3rd Grade Students learn conceptually why (2 + 4) × 6 = 6 × 6

27

3rd Grade

28

4th Grade

29

4th Grade

30

4th Grade

31

5th Grade

6th Grade

32

Design Element: Pacing

• Mastery learning works. Average student gains 22 percentile points in academic achievement over results from conventional classroom

• The use of computers is more effective when the student is in control of the pacing, time allocations for mastery, sequencing and pacing of instructional materials, choice of practice items, and review process

Primary Engagement Environment

Intermediate Engagement Environment

Design Element: Regulating Cognitive Load

• Working memory is limited to: ~ 7 things in verbal working memory ~ 4 things in visual working memory

• Manage cognitive load

Working Memory

Thinking: • Integrating • Diagnosing • Analyzing • Sense making • Schema developing

Long-term Memory

Visual Working Memory

Visuals/Video

Verbal Working Memory

Talk/Sound

Manage Cognitive Load

• Organization of information on screen

• Alignment of visual and verbal information

• Screen design

• Schema building

29 + 72 = ?

13

12´

2

3= ?

Design Element: Engaging through Gaming

• Student engagement can be increased through: • Logical sequencing of curriculum • Novelty and variety • Student choice • Intellectual safety • Clarity of goals

NON-INTERACTIVE

Multimodal Learning

INTERACTIVE Multimodal Learning

BASIC SKILLS HIGHER ORDER SKILLS

Average Student

**Percentile Ranking on Higher Order or Transfer Skills

*Percentile Ranking on Retention of Basic Skills

MULTIMODAL VS. TRADITIONAL, UNIMODAL LEARNING

+9 Percentile* increase for average student

II.

+32 Percentile** increase for average student

III.

+21 Percentile* increase for average student

I.

+20 Percentile** increase for average student

IV.

Gaming

Five principles of effective gaming also serve as important elements of intelligent adaptive learning systems:

• Sequenced challenges

• “Just in time” and “on demand” information

• Performance before competence

• Motivation and attention

• Timely and specific feedback

– Gee 2003

Motivation & Performance

44

Sequenced Challenges

45

Timely, Specific Feedback

46

In summary

• Think research-based

• Think blended learning

• Think “next generation” cognitive modeling

• Think big data – learning analytics

• Think prototyping

Prototyping

- U.S. Department of Education

Purchasers of digital learning resources and those who mandate their use should seek out and use evidence with respect to the claims made about each resource’s capabilities, implementation, and effectiveness.

Bottom Line

• Definitive research studies are underway

• In the meantime, the design of intelligent adaptive learning systems is research based and warrants a serious look, use, and prototyping by educators

• In doing so, it is critical that the cognitive model upon which the IAL is based aligns with the school’s pedagogical approach

DreamBox Combines Three Essential Elements to Accelerate Student Learning

50

For more information visit:

www.dreambox.com

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