Hausmann Study2

The Effects of Interaction on Robust Learning

Robert Hausmann and Kurt VanLehn

Abstract

It is widely assumed that an interactive learning resource is more effective in producing learning gains than non-interactive sources. It turns out, however, that this assumption may not be completely accurate. For instance, research on human tutoring suggests that human tutoring (i.e., interactive) is just as effective as reading a textbook (i.e., non-interactive) under very particular circumstances (VanLehn et al., in press). This rises the question, under which conditions should we expect to observe strong learning gains from interactive learning situations? The current project seeks to address this question by contrasting interactive learning (i.e., jointly constructing explanations) with non-interactive learning (i.e., individually constructing explanations).

Background and Significance

Several studies on collaborative learning have shown that it is more effective in producing learning gains than learning the same material alone. This finding has been replicated in many different configurations of students and across several different domains. Once the effect was established, the field moved into a more interesting phase, which was to accurately describe the interactions themselves and their impact on student learning (Dillenbourg, 1999). One of the hot topics in collaborative research is on the "co-construction" of new knowledge. Co-construction has been defined in many different ways. Therefore, the present study limits the scope of co-constructed ideas to jointly constructed explanations.

Evidence of the impacton jointly constructed explanations is sparse, but can be found in a study by McGregor and Chi (2002). They found that collaborative peers are able to not only jointly constructed ideas, but they will also reuse the ideas in a later problem-solving session. One of the limitations of their study is that it did not assess impact of jointly constructed ideas on individual, robust learning. In a related study, Hausmann and Chi (2004) found correlational evidence for learning from co-construction. To provide more stringent evidence for the impact of jointly constructed explanations, the present sutdy will manipulate the types of conversations dyads have by promtping for jointly constructed explanations and measuring the effect on robust learning.

Glossary

Jointly constructed explanation: a statement or set of statements, spread across two (or more) speakers, that makes explicit the causal or relational connection between concepts. Here is an example of a jointly constructed explanation in the domain of kinematics (from Hausmann & Chi, 2004):

Jill:	Force acting on block B, is different from force acting on block A.
Sara:	Ok. Because their mass, is different.
Jill:	Yeah. Because-yeah.

Jill presents a proposition (i.e., the forces are different) and Sara supplies the justification (i.e., because the masses are different).

Prompting: an explicit verbal reminder to engage in a specific interactive process, such as explaining.

Research question

How is robust learning affected by self-explanation vs. jointly constructed explanations?

Independent variables

Two variables were crossed:

• Interaction: singleton vs. dyad
• Engagement: natural vs. prompted

Hypothesis

The Interactive Hypothesis: collaborative peers will learn more than the individual learners because they benefit from the process of negotiating meaning with a peer, of appropriating part of the peers’ perspective, of building and maintaining common ground, and of articulating their knowledge and clarifying it when the peer misunderstands. In terms of the Intearctive Communication cluster, the hypothesis states that, even when controlling for the amount of knowledge components covered, the dyads will learn more than the individuals.

The Coverage Hypothesis: if both peers and singletons cover the same knowledge components, then they will learn the same amount.

Dependent variables & Results

• Near transfer, immediate: problems solved during the laboratory period.

• Near transfer, retention: homework preformance on electrodynamics problems that are isomorphic to the problems solved during the laboratory period.

• Far transfer, retention: homework preformance on electrodynamics problems that are not isomorphic to the problems solved during the laboratory period.

• Acceleration of future learning: homework preformance on magnetisim problems.

Explanation

This study is part of the Interactive Communication cluster, and its hypothesis is

References

VanLehn, K., Graesser, A. C., Jackson, G. T., Jordan, P., Olney, A., & Rose, C. P. (in press). When are tutorial dialogues more effective than reading? Cognitive Science.