Cognitive Tutors ITS, Sept 30, 2004. Overview Production system models –For LISP, geometry, and algebra 8 principles from ACT theory Gains: 1/3 time to.

Slides:



Advertisements
Similar presentations
Performance Assessment
Advertisements

Instructional Decision Making
Modelling with expert systems. Expert systems Modelling with expert systems Coaching modelling with expert systems Advantages and limitations of modelling.
Direct Instruction Also called explicit instruction Widely applicable strategy that can be used to teach both concepts and skills Uses teacher explanation.
Chapter 10 Teaching and Learning Strategies
Dave_Congwu Tao March 26,  1. What is an intelligent tutor & intelligent tutoring system?  2.The related research on Intelligent tutoring system.
An Individualized Web-Based Algebra Tutor D.Sklavakis & I. Refanidis 1 An Individualized Web-Based Algebra Tutor Based on Dynamic Deep Model Tracing Dimitrios.
Supporting (aspects of) self- directed learning with Cognitive Tutors Ken Koedinger CMU Director of Pittsburgh Science of Learning Center Human-Computer.
Training & Development Definition –“The systematic acquisition of attitudes, concepts, knowledge, roles, or skills, that result in improved performance.
QA on Anderson et al Intro to CTAT CPI 494 & 598 Jan 27, 2009 Kurt VanLehn.
Training. Training & Development Definition “The systematic acquisition of attitudes, concepts, knowledge, roles, or skills, that result in improved performance.
Intelligent tutoring goes to school ITS- Sept 30, 2004.
The Silent Way.
Cognitive Processes PSY 334 Chapter 8 – Problem Solving May 21, 2003.
Theoretical Perspectives for Technology Integration.
TASK-BASED INSTRUCTION Teresa Pica, PhD Presented by Reem Alshamsi & Kherta Sherif Mohamed.
DED 101 Educational Psychology, Guidance And Counseling
CLT Conference Heerlen Ron Salden, Ken Koedinger, Vincent Aleven, & Bruce McLaren (Carnegie Mellon University, Pittsburgh, USA) Does Cognitive Load Theory.
Designing powerful learning environments and practical theories The knowledge integration environment Bat-Sheva Eylon, The Science Teaching Department,
1 Cognitive Principles in Tutor & e-Learning Design Ken Koedinger Human-Computer Interaction & Psychology Carnegie Mellon University CMU Director of the.
Intervention Resource Guide. Math Intervention Courses Address foundational math skills – Whole numbers – Addition, Subtraction, Multiplication, Division.
Learner Self-Correction in Solving Two-Step Algebraic Equations Brandy C. Judkins, School of Professional Studies in Education, Johns Hopkins University.
/ 181 InstrutionalMethods. Aim The purpose of this session is to increase the effectiveness of the trainings that are prepared by the participants, by.
Planning, Instruction, and Technology
1 New York State Mathematics Core Curriculum 2005.
31 st October, 2012 CSE-435 Tashwin Kaur Khurana.
Mathematics the Preschool Way
Concept Attainment Inquiry Lessons.  Is used to teach concepts, patterns and abstractions  Brings together the ideas of inquiry, discovery and problem-solving.
Learning & Teaching with Technology Claire O’Malley School of Psychology.
Click to edit Master title style  Click to edit Master text styles  Second level  Third level  Fourth level  Fifth level  Click to edit Master text.
NCTM Overview The Principles and Standards for Teaching Mathematics.
Inquiry learning How does IBL relate to our mathematics curriculum? Tool IG-1: The potential of IBL to meet curricular demands in mathematics.
Brunning – Chapter 10 Technological Contexts for Cognitive Growth Learning is influenced primarily by good instructional methods that takes advantage of.
Instructional software. Models for integrating technology in teaching Direct instructional approach Indirect instructional approach.
Becoming a Teacher Ninth Edition
Math rigor facilitating student understanding through process goals
The Administrative Webinar Series Modeling the Body-Brain Compatible Elements in Staff Meetings.
© 2013 University Of Pittsburgh Supporting Rigorous Mathematics Teaching and Learning Making Sense of Numbers and Operations Fraction Standards via a Set.
What is your perception of the Instructional Design & Technology field?
Encompasses a broad, overall approach to instruction.
CAPP ALGEBRA FORMATIVE ASSESSMENT GRANT Professional Development Aspect.
Academic Needs of L2/Bilingual Learners
Problem-Based Learning. Process of PBL Students confront a problem. In groups, students organize prior knowledge and attempt to identify the nature of.
Exploring Effective Teaching Methods Copyright © Notice: The materials are copyrighted © and trademarked ™ as the property of The Curriculum Center for.
Students with Learning Disabilities Mathematics. Math Skills Development Learning readiness –Number instruction Classification, ordering, one-to-one correspondence.
Overview Criteria Item Examples.  Create a sense of “measured urgency” ◦ Timeline is not immediate, but close ◦ Urgency in you and your teachers ◦ Difference.
Inquiry learning How does IBL relate to our mathematics curriculum? Tool IG-1: The potential of IBL to meet curricular demands in mathematics.
Cognitive apprenticeship Prasanth.P. According to Collins, Brown, & Newman, Cognitive apprenticeship focuses on “learning-through- guided-experience on.
Strategies for Teaching Students with Learning and Behavior Problems, 8e Vaughn and Bos ISBN: © 2012, 2009, 2006 Pearson Education, Inc. All.
Selecting and Designing Tasks
Problem-Solving Approach of Allied Health Learning Community.
711: Intelligent Tutoring Systems Week 1 – Introduction.
Minelli Weiland EDUC 5541 Gagne’s Conditions and Events of Learning Contemporary Learning Theory
Chapter Two The Technical Core Teaching & Learning.
Chapter 1 Integrating UBD and DI An Essential Partnership.
Competencia 16 Matematicas The teacher understands how children learn mathematical skills and uses knowledge to plan, organize, and implement instruction.
SESSION FIVE: MOTIVATION INSTRUCTION. MOTIVATION internal state or condition that activates behavior and gives it direction; *desire or want that energizes.
How people learn different ways to think about learning.
RULES Patty Nordstrom Hien Nguyen. "Cognitive Skills are Realized by Production Rules"
BENEFITS OF USING TESOL’S STANDARDS TO GUIDE INSTRUCTIONAL DESIGN IN THE CLASSROOM.
Performance Task and the common core. Analysis sheet Phases of problem sheet Performance task sheet.
Implementing PBIS in the Classroom Chapter 4 –Classroom Management: Systems & Practices.
Creative Curriculum and GOLD Assessment: Early Childhood Competency Based Evaluation System By Carol Bottom.
Using Cognitive Science To Inform Instructional Design
Roy B. Clariana, Assistant Professor The Pennsylvania State University
The Behavior of Tutoring Systems
Competency Based Instruction in CSI High Schools?
Theoretical Perspectives
Presentation transcript:

Cognitive Tutors ITS, Sept 30, 2004

Overview Production system models –For LISP, geometry, and algebra 8 principles from ACT theory Gains: 1/3 time to mastery Evolved to view of ITS as non-human tool or “teacher assistant” New development model

ACT theory of skill acquisition Procedural-declarative distinction –Cognitive skill: convert declarative knowledge into production rules Knowledge compilation –Employing declarative knowledge in problem- solving context Strengthening –Knowledge acquires strength with practice

Resulting instruction Initial brief declarative knowledge presentation Guided practice Note: complexity of learning a cognitive skill is inherit in domain, not the process of cognitive skill acquisition

Declarative v. Procedural Side-angle-side theorem Skills: –Placing triangles into correspondence –Determining the included angle –Setting subgoals –Making inferences

Model-tracing approach Model production rules of skill Recognize on-path actions Focus instruction on getting students back on path when off Error feedback and help

8 principles 1.Rep. student competence as production set 2.Communicate goal structure 3.Provide instruction in problem-solving context 4.Promote abstract understanding 5.Minimize working memory load 6.Provide immediate error feedback 7.Adjust grain size with learning 8.Facilitate successive approx. to target skill

Initial results Geometry tutor –+14 points on 80 point test –Project teacher only one with + results LISP tutor –30% faster learning, one std. dev. + Algebra tutor –Hierarchical knowledge shown –Skills transfer not effective

Predicting learning 1.Production practice 2.Within-problem practice effects (strengthening) 3.Acquisition factor 4.Retention factor

Knowledge tracing Bayesian probability a rule was learned Successfully predicted post-test results Applies for measuring mastery

Locus of feedback control Immediate Error-flagging Demand None First three better than last

Feedback content Error flagging (Short) explanatory feedback –Fewer errors per production –More likely to correct error on first attempt No long-term effect except time & perception of tutor Carefully crafted => long-term effect

Impractical? Didn’t address curriculum What happens after tutors? Inflexible in application How to support deployment?

New development model 1.Interface construction 2.Curriculum specification 3.Cognitive modeling 4.Design of instruction 5.Classroom deployment