Erin: Hi everyone.
I'm Erin Walker and I'm faculty at the University of Pittsburgh.
I'm here today to present a paper authored with my former student Shang
Wang on modeling student content mapping processes, and providing adaptive support.
Concept maps are diagrams that consists of nodes representing key concepts
in a domain and annotated links representing relationships between nodes.
When students are asked to create a content map from one or more sources,
they're required to reflect on the important concepts within a domain
and make connections between different concepts as part of creating the map.
And this tends to improve their understanding of the source.
However, students often need support and engaging in the
complex metacognitive processes required to create a concept map.
Some research has explored an intelligent tutoring style to support concept mapping
.This support in the context of concept mapping typically automatically scores a
completed concept map, and then provides feedback on the content of the map.
Um, and it's been shown to have some benefits for improving
student understanding.
However, we know that the process of and concept mapping is critical
to facilitating student learning.
Students learn more during concept mapping when engaging in comparative strategies.
Where they make connections and comparisons between the concepts
that they are adding to their maps.
Most of the computer-based adaptive efforts to support content mapping
have focused on outcome and not on this comparative process.
Therefore, our hypothesis is that adaptive feedback that targets both the process
of concept mapping and the content of the student's current map in progress might
be most effective at improving students' comparative strategies and learning.
To investigate this hypothesis we built a system called MindDot . MindDot
is an iPad app that allows students to build a concept map from a source text.
It provides an integrated text and content map view, um, and we've
populated MindDot for these studies with a chapter on biodiversity.
In MindDot, we give students combined process and content feedback.
One novel feature of MindDot that it provides adaptive feedback to students
on their content mapping via text box connected to an image of a light bulb.
Which you can see in the bottom right corner of this screenshot, as students
make their maps, MindDot extracts sequences of student actions and
determines whether the, sequences mapped to effective or ineffective
content mapping patterns that we've identified from our previous work.
It then uses this comparison to identify positive or negative process
feedback to give the students.
It further compares the content of students' concept maps to an expert-
authored map and uses that information to provide students with suggestions on
concepts that can be added to their map.
These suggestions connect to the process feedback that they had just received.
For example, we've identified reading three pages in a row without modifying
one's map is an ineffective pattern.
In response to this, the feedback suggested the learner, add
a node to their content map.
Uh, it then gives content feedback, suggesting possible concepts to
add based on relevant concepts.
Around that point in the book in the expert map .All told, MindDot
responds to three positive patterns and seven negative patterns.
To examine the potential benefits of the combined process in content
feedback, we conducted a study, comparing the combined feedback to process
feedback alone, and to no feedback.
Forty-six undergraduate students participated in this study.
They engaged in two different kinds of concept mapping tasks, 30 minutes
of concept mapping, where if they were in an adaptive support condition, they
received adaptive support and then a 10 minute transfer task in a different domain
where they made a concept map without the adaptive support for each task, we gave
students pre and post tests regarding, um, their comprehension of key facts
within that domain covered by the text.
More information on the assessments is available in the paper.
Some key findings from this study are that students who receive
combined feedback are more likely to immediately change their concept
mapping process to follow the feedback.
They exhibited higher frequencies of comparative strategies, such as
making links between concepts on different pages or navigating back
in the text to make a comparison.
This was true, both in the main session and in the transfer session.
Students who receive combined feedback also learn more in the main session, than
students who did not receive feedback, but this was not true in the transfer session.
And unlike in our previous studies, we did not find that comparative
strategies were correlated with learning across either session.
To summarize.
We built a system that modeled concept mapping and provided
adaptive process and content support.
Some conclusions we drew where that combined feedback did improve
concept mapping, possibly because it was more implementable by the
students than process feedback alone.
However it is possible the students went through the motions of implementing
comparative strategies as a result of the support, but not build knowledge
through this process in the same way as they would have if employing
comparative strategies, spontaneously.
Future work will investigate how adaptive support could be designed
to produce meaningful changes in student cognition in addition to
just changes in their strategies.