integrated collaborative learning environments with dynamic support
DESCRIPTION
Integrated Collaborative Learning Environments with Dynamic Support. Carolyn Penstein Ros é Language Technologies Institute/ Human-Computer Interaction Institute. Design Principle Know what problem you are trying to solve!!. Passivity in Class Discussions. Accountable Talk. - PowerPoint PPT PresentationTRANSCRIPT
Integrated Collaborative Learning Environments with Dynamic Support
Carolyn Penstein Rosé
Language Technologies Institute/
Human-Computer Interaction Institute
Design Principle
Know what problem you are trying to
solve!!
Passivity in Class Discussions
Accountable Talk A codified set of moves that
Ts and Ss can be taught that build effective language in the classroom
Press individuals to explain and elaborate Require individuals to listen and respond to
each other Reveal misunderstandings, incomplete ideas.. Let Ss know how others are “hearing them” Spread participation through the group
Transactivity
Students explicitly display their reasoning
Students orient their contributions towards previous contributions May be competitive or
non-competitive May be representational
operational May be oriented
towards self or other
Student 1: Alright, we put that the negative and positive whole numbers.
Teacher: Alright, other ideas you want to add on, yes Mario.
Student 2: I put a um numbers that doesn't include decimal points or fractions but they include, they can include negative signs or positive signs.
Accountable Talk Move Corresponding Transactivity Move
Revoicing Clarification, Competitive Clarification, Refinement
Restate Request Paraphrase, Competitive Paraphrase
Reasoning Application Request
Extension, Competitive Extension, Contradiction, Reasoning Critique
Prompting for Further Participation.
Extension, Completion, Clarification
Request for Elaboration Extension, Completion
Challenge orRequest for Counter-Example
Competitive Paraphrase, Contradiction, Competitive Extension
Accountable Talk elicits Transactivity in group discussion
Accountable Talk elicits Transactivity in group discussion
Eddie: Well, i don't think it matters what order the numbers are in. You still get the same answer. But three times four and four times three seem like they could be talking about different things.
Teacher: Rebecca, do you agree or disagree with what Eddie is saying?Rebecca: Well, I agree that it doesn't matter which number is first,
because they both give you twelve. But I don't get what Eddie means about them saying different things.
Teacher: Eddie, would you explain what you mean?Eddie: Well, I just think that like three times four can mean three groups
of four things, like three bags of four apples. And four times three means four bags of three apples, and those don't seem like the same thing.
Tiffany: But you still have the same number of apples, so they are the same!
Teacher: OK, so we have two different ideas here to talk about. Eddie says the order does matter, because the two orders can be used to describe different situations. So Tiffany, are you saying that three times four and four times three can't be used to describe two different situations?
Reasoning Application RequestJustification Request
Request for ElaborationClarification
Reasoning Critique
Revoicing
Unequal Participation
Wizard-of-Oz Setup
Tutor
Student Student
Problem Solving Interface
Interface allowsstudents to submitIncorrect solutions
Reflection Interface
Scaffolding for Collaboration
• Prompts to encourage the instructionally beneficial behavior of students– Explanations– Equal contributions
Explanation Prompt
(Student 1 corrects the answer for the confederate learner without offering any explanation)
Student1: c is 1Auto-Prompt (to student 1): Help the student understand your correction. Student2 : what does c mean? Student1 : constant Student2 : okStudent1 : the constant in front of the variable which in our case is variable t Student2 : okStudent1 : now for the second part we use the constant function
Equal Contribution Prompt
(After the participant makes 5 correct problem actions without confederate student’s contribution)
Auto-Prompt: It seems like the other student has not contributed lately. Why don’t you see if they need help? Student1: you want to do the other half?Student2: ok
Learning effect
Significant benefit for prompting on student learning with pretest as a covariate F(1,39) = 4.47, p < .05, effect size .58
Process Losses
Another Domain: Earth Sciences
Collaborative idea generation in the Earth Sciences domain
Chinese TagHelper learns hand-coded topic analysis Human agreement .84
Kappa TagHelper
performance .7 Kappa Trained models used in
follow-up study to trigger interventions and facilitate data analysis
Example Dialogue
SpeakerSpeaker TextText
Student 1Student 1 People stole sand and stones to use for construction.People stole sand and stones to use for construction.
VIBRANTVIBRANT
Yes, steeling sand and stones may destroy the balance and Yes, steeling sand and stones may destroy the balance and thus make mountain areas unstable. Thinking about thus make mountain areas unstable. Thinking about development of mountain areas, can you think of a kind of development of mountain areas, can you think of a kind of development that may cause a problem? development that may cause a problem?
Student 2Student 2 Development of mountain areas often causes problems.Development of mountain areas often causes problems.
Student 1Student 1 It is okay to develop, but there must be some constraints.It is okay to develop, but there must be some constraints.
* Feedback during idea generation increases learning and idea generation productivity (except during the first 5 minutes) (Wang et al., 2007)
Pairs+Feedback
Individuals+NoFeedback
Pairs+NoFeedback
Individuals+Feedback
Process Analysis
Process loss Pairs vs Individuals:F(1,24)=12.22, p<.005, 1 sigma Process loss Pairs vs Individuals:
F(1,24)=4.61, p<.05, .61 sigmaNegativeNegative effect of Feedback: effect of Feedback:F(1,24)= 7.23, p<.05, -1.03 F(1,24)= 7.23, p<.05, -1.03
sigmasigmaPositivePositive effect of feedback: effect of feedback:F(1,24)=16.43, p<.0005, 1.37 sigmaF(1,24)=16.43, p<.0005, 1.37 sigma
0 5 10 15 20 25 30
02
46
810
12
Time Stamp
#Uni
que
Idea
s
Unique Ideas
Nom+NNom+FReal+NReal+F Pairs+Feedback
Individuals+NoFeedback
Pairs+NoFeedback
Individuals+Feedback
Pairs+Feedback
Individuals+NoFeedback
Pairs+NoFeedback
Individuals+Feedback
Deficient Help Exchange
Why study help?
Offering of deep help and elaborated explanations predicts post test performance (e.g., Webb et al., 2002)
Help behavior mediates learning (e.g., Gweon et al., 2006; Gweon et al., 2007)
Exchanging help in the context of collaborative learning increases identification with a learning community and motivation, and improves race relations (Sharan, 1980)
Providing help leads to feelings empowerment for “low status” students (Elbers & Hann, 2004)
How can we prompt helping behavior? DIRECT: Explicit prompts (Gweon et al., 2006) LESS DIRECT: Manipulating availability of help
from problem solving environment (Gweon et al., 2007) Girls offered more help with delayed feedback from
environment Boys offered more help with immediate help from the
environment SUBTLE: Conversation agents inject humor
(Kumar et al., 2007) Positive effects on perceived help exchange (p<.05),
effective help exchange (p<.1), and Learning (p=.06)
Collaborative Problem Solving Environment
Jan packed several books to amuse herself on along car ride to visit her grandma. After 1/5 ofthe trip she had already finished 6/8 of the booksshe brought. How many times more books shouldshe have brought than what she packed?
Extraneous Entertainment?
Coding Scheme (Gweon et al., 2007) Help provision mediates learning (Gweon et al.,
2006; Gweon et al., 2007)
(R) Help Requests: “Help me”, “I’m stuck”, “I don’t get it.”
(P) Help Provisions: “Find the common denominator”, “Try the flip and multiply strategy”
(C) Can’t help: “I don’t know”, “I’m stuck too” (D) Deny help: “ask the teacher”, “you’re an idiot”,
“press the help button” (N) Nothing
Examples[R] Student 1: What do we put on top of the fraction?[P] Student 2: Did you find a common denominator?<student 1 correctly finds the common denominator>
[R] Student 1: I don’t get it[D] Student 2: hold on<then student 1 tried something and got negative feedback from the problem solving
environment.><finally student 1 tried something else, which was correct, and got positive feedback
from the problem solving environment>
[R] Student 1: Why 16?[C] Student 2: I don’t know.
[R] Student 1: I don’t get it<student 2 tries something and gets negative feedback from the problem solving
environment><student 2 tries something else and gets negative feedback from the problem solving
environment><student 2 clicks on the help button><student 1 tries something that is correct and gets positive feedback from the problem
solving environment>
Big findings:
More help related episodes in experimental condition
More episodes where people got help, and then managed to solve
the problem themselves in the experimental condition
Vision
Vision Support for collaborative
learning is like training wheels
Effective support allows learners to achieve better collaboration
Unnecessary support can be demotivating
Fading support is ideal But too little support can be
detrimental as well Trained human facilitators
are able to achieve the right balance
Vision Support for collaborative
learning is like training wheels
Effective support allows learners to achieve better collaboration
Unnecessary support can be demotivating
Fading support is ideal But too little support can be
detrimental as well Trained human facilitators
are able to achieve the right balance
Vision Support for collaborative
learning is like training wheels
Effective support allows learners to achieve better collaboration
Unnecessary support can be demotivating
Fading support is ideal But too little support can be
detrimental as well Trained human facilitators
are able to achieve the right balance
Vision Support for collaborative
learning is like training wheels
Effective support allows learners to achieve better collaboration
Unnecessary support can be demotivating
Fading support is ideal But too little support can be
detrimental as well Trained human facilitators
are able to achieve the right balance
Vision Support for collaborative
learning is like training wheels
Effective support allows learners to achieve better collaboration
Unnecessary support can be demotivating
Fading support is ideal But too little support can be
detrimental as well Trained human facilitators
are able to achieve the right balance
Support for collaborative learning is like training wheels
Effective support allows learners to achieve better collaboration
Unnecessary support can be demotivating
Fading support is ideal But too little support can be
detrimental as well Trained human facilitators
are able to achieve the right balance
Vision
Architecture for Dynamic Collaboration Support
VMT-Basilica
** Students learn up to 1.25 standard deviations more when interactive support is provided in the environment.
Basilica Architecture
A channel filter collects all of the
events that occur at the interface from
all students involved in the conversation
Basilica Architecture
Events are then channeled to
special purpose filters such as a text
processing filter
Other filters may keep track of time
or other factors not related to student
behavior
Basilica Architecture
Filters that are related to decision making for specific
types of interventions
receive notifications from the analysis filters and pass
notifications on to the Actors, which are responsible to
launching interventions
Basilica Architecture
Actors of different types produce
events that are sent to the Outgoing
Message Spooling Filter
From there, events are sent through the
Presence Actor to the interface.
Issues to consider What problem are you trying to solve?
Formulate analysis scheme
When should you intervene?Use technologies like TagHelper and SIDE to
track interaction and trigger support
What should the intervention be?Technologies like TuTalk can be used to offer
support
Questions?