The learning process and its outcomes depend greatly on the social interaction between teachers and students and, in particular, on the proficient and focused use of language through written text or discussions. Our overarching goal in this project is to better understand how to make automated tutorial dialogues effective and adaptive to student characteristics, such as prior knowledge. The specific goal of our current project is to develop an adaptive, natural-language tutoring system, driven by a student model, which can effectively carry out reflective conversations with students after they solve physics problems. Towards this end, we continue our work in identifying linguistic features of tutoring that predict learning gains, and extend it by characterizing the “level of support” to provide to students based on their current level of understanding particular physics concepts and principles, as dynamically captured by the student model. In this talk, I will describe the features of dialogic discourse underlying “level of support” that we have identified through the analysis of human-to-human tutorial dialogues as well as the construction and application of a coding scheme for the characterization of the “level of support”. I will present initial teacher feedback on dialogues that apply these features to coach students at different levels. I will also discuss how this line of research affects the authoring of tutorial dialogues used by an intelligent tutoring system for students who exhibit different levels of understanding.

1. Hello world!

2. Hello world  I am Irene!
Postdoc @ HCII since
April, 2016!

3. Hello world  I am Irene!
PhD: Methods and tools for the evaluation of collaborative learning
activities using time series (2014, University of Patras)
Greece!!!

4. “Linking Dialogue with Student
Modeling to Create an Enhanced
Micro-adaptive Tutoring System”
University of Pittsburgh (LRDC)
&
CMU (HCII)

5. Dialogue as a means for learning
• We aim to develop an adaptive tutorial dialogue
system, guided by a student model that will support
students in learning physics

6. Research questions
• RQ1: What makes tutorial dialogues successful?
Teachers’ adapt the level of discussion to the
student’s “zone of proximal development”
(Vygotsky)
• RQ2: How do tutorial dialogues adapt to different
student characteristics and prior knowledge?
Degree of Teacher Control (van de Pol)
Contingent Tutoring (Pino-Pasternak)
Cognitive Complexity (Nystrand, Graesser)
Research Objective:
What makes some tutor’s help
generous or stingy, easy or
challenging, straightforward or
“cognitively complex”?
Level of Support
(LOS)

7. An example would be nice….
RQ: What minimum acceleration must the
climber have in order for the rope not to
break while she is rappelling down the
cliff? (You do not have to come up with a
numerical answer. Just solve for "a"
without any substitution of numbers.)
S: a = f / m
T: what's f ?
S: f = mg
T: just mg ? how many forces act on the
climber ?
S: mg + T
T: is mg down or up ?
S: down and T is up
T: ok so now solve for a again plugging in T
and mg
RQ: What minimum acceleration must the
climber …….
S: 500/55 kg=a m/s^2
T: I don't agree - that's the acceleration
that just the pull from the rope would
produce (well once the units are
straightened out it would be). Think a little
more. What is the general rule for finding
acceleration from forces?
S: F/m=a
T: and what is the F there?
S: tension?
T: No.. the F in F=ma is always the net force
on the object (or group of objects). The
vector sum of all the forces on the object. I
prefer to say "Sum of F= ma" because it's
easier to get it right. So.. if she is sliding
down and the rope is just short of breaking,
what is the *net* force on her?
High performer

8. [How] can we group the features of instructional
dialogue to differentiate the “levels of support” (LOS)?
• Analyze human-to-human tutorial dialogues
• Build a coding scheme to operationalize Level of
Support
• Set up Tutorial Dialogue Authoring Guidelines
• Adapt tutorial dialogue system to LOS
support
• And then… what a great time for studies!
Work in progress!

9. The end.
If you want to know more, get in touch!
NSH 2602K
ichounta@cs.cmu.edu
(plus cat pictures!)