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TagHelper Track Overview Carolyn Penstein Rosé Carnegie Mellon University Language Technologies Institute & Human-Computer Interaction Institute School.

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Presentation on theme: "TagHelper Track Overview Carolyn Penstein Rosé Carnegie Mellon University Language Technologies Institute & Human-Computer Interaction Institute School."— Presentation transcript:

1 TagHelper Track Overview Carolyn Penstein Rosé Carnegie Mellon University Language Technologies Institute & Human-Computer Interaction Institute School of Computer Science

2 TagHelper Tools and SIDE TagHelper Tools uses text mining technology to automate annotation of conversational data SIDE facilitates rapid prototyping of reporting interfaces for group learning facilitators Define Annotations Annotate Data Visualize Annotated Data

3 ? 3 But what can you do with it?

4 Identifying types of conversational moves 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?

5 ? 5 But why would you want to do that?

6 Why automatically monitor conversations? 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 Ideal support is adaptive and context sensitive 6

7 Triggering Support as Needed Integrated with several collaborative learning environments Evaluated in several Learning Studies Positive effects on learning in comparison with no support control conditions –(Kumar et al., 2007; Wang et al., 2007; Chaudhuri et al., 2008) 7

8 Projects from Previous Years Identifying types of helping behavior Identifying argumentation moves Identifying correct and incorrect physics explanations Identifying grammatical errors in non-native English speakers’ essays 8

9 Tracking Valuable Conversational Behavior TagHelper Tools Project –445 users from 55 countries Some success in automating transactivity analysis –Rosé et al., in press; Joshi & Rosé, 2007 Limitations –Highly controlled settings –Limited generalizability 9

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13 Tracking Valuable Conversational Behavior TagHelper Tools Project –445 users from 55 countries Some success in automating transactivity analysis –Rosé et al., in press; Joshi & Rosé, 2007 Limitations –Highly controlled settings –Limited generalizability 13

14 14 Any questions? Download tools at: http://www.cs.cmu.edu/~cprose/TagHelper.html http://www.cs.cmu.edu/~cprose/SIDE.html


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