Why do some groups succeed where others fail? We hypothesise that collaborative success is achieved when the relationship between the dyad's prior expertise and the complexity of the task creates a situation that affords constructive and interactive processes between group members. We call this state the zone of proximal facilitation in which the dyad's prior knowledge and experience enables them to benefit from both knowledge-based problem-solving processes (e.g., elaboration, explanation, and error correction) andcollaborative skills (e.g., creating common ground, maintaining joint (...) attention to the task). To test this hypothesis we conducted an experiment in which participants with different levels of aviation expertise, experts (flight instructors), novices (student pilots), and non-pilots, read flight problem scenarios of varying complexity and had to identify the problem and generate a solution with either another participant of the same level of expertise or alone. The non-pilots showed collaborative inhibition on problem identification in which dyads performed worse than their predicted potential for both simple and complex scenarios, whereas the novices and experts did not. On solution generation the non-pilot and novice dyads performed at their predicted potential with no collaborative inhibition on either simple or complex scenarios. In contrast, expert dyads showed collaborative gains, withdyads performing above their predicted potential, but only for the complex scenarios. On simple scenarios the expert dyads showed collaborative inhibition and performed worse than their predicted potential. We discuss the implications of these results for theories of collaborative problem solving. (shrink)

Peer interaction has been found to be conducive to learning in many settings. Knowledge co-construction has been proposed as one explanatory mechanism. However, KCC is a theoretical construct that is too abstract to guide the development of instructional software that can support peer interaction. In this study, we present an extensive analysis of a corpus of peer dialogs that we collected in the domain of introductory Computer Science. We show that the notion of task initiative shifts correlates with both KCC (...) and learning. Speakers take task initiative when they contribute new content that advances problem solving and that is not invited by their partner; if initiative shifts between the partners, it indicates they both contribute to problem solving. We found that task initiative shifts occur more frequently within KCC episodes than outside. In addition, task initiative shifts within KCC episodes correlate with learning for low pre-testers, and total task initiative shifts correlate with learning for high pre-testers. As recognizing task initiative shifts does not require as much deep knowledge as recognizing KCC, task initiative shifts as an indicator of productive collaboration are potentially easier to model in instructional software that simulates a peer. (shrink)

The proposed multilevel framework of discourse comprehension includes the surface code, the textbase, the situation model, the genre and rhetorical structure, and the pragmatic communication level. We describe these five levels when comprehension succeeds and also when there are communication misalignments and comprehension breakdowns. A computer tool has been developed, called Coh-Metrix, that scales discourse (oral or print) on dozens of measures associated with the first four discourse levels. The measurement of these levels with an automated tool helps researchers track (...) and better understand multilevel discourse comprehension. Two sets of analyses illustrate the utility of Coh-Metrix in discourse theory and educational practice. First, Coh-Metrix was used to measure the cohesion of the text base and situation model, as well as potential extraneous variables, in a sample of published studies that manipulated text cohesion. This analysis helped us better understand what was precisely manipulated in these studies and the implications for discourse comprehension mechanisms. Second, Coh-Metrix analyses are reported for samples of narrative and science texts in order to advance the argument that traditional text difficulty measures are limited because they fail to accommodate most of the levels of the multilevel discourse comprehension framework. (shrink)