3. Adaptive learning
Objectives…
At the end of the session, you will be able
to-
Describe Adaptive Learning.
State applications of Adaptive
Learning.
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4. Adaptive learning
Introduction…
‘Adaptive Learning’ is a style of learning
that focuses on prior successes and the
use of these as the basis for developing
future strategies and successes.
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5. Adaptive learning
Introduction…
• Interactive teaching device.
• Responses indicate the student’s learning
need.
• Computers gauge and adapt the presentation
of the material.
• Incorporating the interactivity of one-to-one
basis in electronic education. (e-education).
• Aspects from the fields of Computer
Science, Education and Psychology.
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6. Adaptive learning
Introduction…
• Increase is due to the realization of the
fact that traditional non-adaptive
approaches cannot help in customizing
learning on a large-scale.
• The aim is to change the learner from
being a passive receptor of information
to being a partner/team member.
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7. Adaptive learning
Introduction…
• Adaptive Educational Hypermedia
• Computer-Based Learning
• Adaptive Instruction
• Intelligent Tutoring Systems
• Computer Based Pedagogical Systems
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8. Adaptive learning
History…
• Artificial Intelligence Movement, 1970s
• Computers gaining the human ability to
adapt
• Intelligent tutoring
• Cost and size of computers
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9. Adaptive learning
History…
• ‘AutoTutor’, Institute of Intelligent System
• Grasser said, ‘Spoken computational
environments may foster social
relationships that may enhance learning.’
• More classrooms becoming computerized
has led to a steady increase in ALS
companies
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10. Components Adaptive learning
Expert Model…
• Stores information
• Simple – solution to question sets, lessons
and tutorials
• Complex – expert methodologies
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11. Components Adaptive learning
Student Model…
• Simple student models involve algorithms
• CAT (Computer Adaptive Testing)
• Learner answers the questions based on their
level of difficulty, presumed skill level of the
subject
• As test advances, the computer selects
questions from a narrower range of difficulty
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12. Components Adaptive learning
Student Model…
• Complex Model algorithms provide a more
extensive diagnosis
• Indicates conceptual strengths and
weaknesses
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13. Components Adaptive learning
Instructional Model…
• Incorporate the best educational tools with
the expert teacher advice for presentation
methods
• The level of complexity of Instructional Model
depends on the level of Student Model
• ‘Feedback’ in the form of ‘hints’ or ‘popup’
suggestions also fall under this Model
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