Recognizing Opportunities for Mixed-Initiative Interactions based on the Principles of...
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Recognizing Opportunities for Mixed-Initiative Interactions based on the
Principles of Self-Regulated Learning
Jurika Shakya, Samir Menon, Liam Doherty, Mayo Jordanov, Vive KumarNovember 6, 2005
Simon Fraser University
AAAI-2005 Fall Symposia, Arlington, Virginia
2Outline
Outline
Motivation Self Regulatory Learning Theory Example MI-EDNA Architecture Future Direction
3Motivation
Motivation
Learning is viewed as an activity that students do for themselves in a proactive way rather than as a covert event that happens to them in reaction to teaching
The top performers are associated with self-regulatory capabilities.
Learners in the opposite end of the bell curve, could improve with some help in their learning style.
The goal of helping the learners learn with SRL theory-centric help can be best achieved through mixed-initiative approach.
Learner ScoreN
umbe
r of
lear
ners
Top Performers
Learner that can use help
in self regulating
their learning
4SRL
Self-Regulatory Learning Theory SRL is a theory that concerns how learners develop
learning skills and how they develop expertise in using learning skills effectively.
SRL theories Zimmerman’s 3 phase model
Forethought Phase Performance Phase Self-reflection Phase
Winne’s 4 state model Knowledge Goals Tactics and Strategies Product
5SRL
Self-Regulatory Learning Theory
Phases and Subprocesses of Self-Regulation. From B.J. Zimmerman and M. Campillo (in press), “Motivating Self-Regulated Problem Solvers.” In J.E. Davidson and Robert Sternberg (Eds.), The Nature of Problem Solving. New York: Cambridge University Press
6Example
Interactions
SRL guidance
MI-EDNA
7MI-EDNA Architecture
MI-EDNA System Architecture
HTTS.owlRules
CILT-Instantiated.owl
Facts
Inference Engine
Iden
tifie
d In
itiat
ive
Inte
ract
ion
(from
S
yste
m)
User
Inte
ract
ion
initia
ted
(by
user
)
Query Tool
Log_file.XMLXML Parser
CILT.owlInstantiator
CILT-Instantiated.owl Query Tool
(e.g. Protégé)
8Recognize MI
Recognition of Initiative Opportunities passively observes learner interactions
Instantiating the interactions into the CILT ontology recognizes opportunities for initiatives
Tracking interactions into learning tasks Mapping the learning tasks into tactics and strategies Inferring the activities involved in the SRL phases from the tactics and
strategies. actively initiates interactions
Based on the SRL principles Based on the scaffolding/Fading principles
DoThink
React
NoticeKnow
RegulateRecognizeRepresent
9recognize opportunities
Recognize Opportunities
JESSTranslator
OWL File(Instantiated
Domain Ontology)XSLT
(Owl2Jess)JESS FACTS
XSLT (Owl2Jess)
OWL File(Rules in SWRL) JESS RULES
Chat InterfaceJESS OUTPUT
QUERY JESS INPUT
10Outline
Actively Initiates Dissemination Categories
Content Scaffolds are based on the content that the learner is currently interacting within a session.
Process Scaffolds guide the learner to monitor his/her learning processes.
Learner Knowledge Scaffolds are based on the subject knowledge of the learner as modeled by the system.
Normative Scaffolds place their emphasis on the norms established by other learners in group-study or
class-room settings. The feedback offered here is expected to help a learner learn by emulating the tactics of others.
Context Scaffolds system provides relevant information when it is aware of the information required by a
learner in response to his/her interactions.
11Outline
Future workSome of the mixed-initiative aspects of this research is to Explore the suitable interfaces required for mixed-
initiative aspect of MI-EDNA An evaluation of the influence of mixed-initiative
interactions and interfaces Explanation-aware SRL modelling and scaffolding/fading
techniques The effects of MI approach SRL help on the learner Deploying the MI-EDNA system on various other
domains.
THANK YOU
Questions ?MI3 Team, SFU
(Liam Doherty, Mayo Jordanov, Sam Menon, Shilpi Rao, David Brokenshire, Pat Lougheed, Vive Kumar)
This research was funded by LearningKit project (SSHRC-INE)
LORNET project (NSERC)