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