Studies exploring how students learn and understand science processes such as diffusion and natural selection typically find that students provide misconceived explanations of how the patterns of such processes arise (such as why giraffes' necks get longer over generations, or how ink dropped into water appears to ''flow''). Instead of explaining the patterns of these processes as emerging from the collective interactions of all the agents (e.g., both the water and the ink molecules), students often explain the pattern as being caused by controlling agents with intentional goals, as well as express a variety of many other misconceived notions. In this article, we provide a hypothesis for what constitutes a misconceived explanation; why misconceived explanations are so prevalent, robust, and resistant to instruction; and offer one approach of how they may be overcome. In particular, we hypothesize that students misunderstand many science processes because they rely on a generalized version of narrative schemas and scripts (referred to here as a Direct-causal Schema) to interpret them. For science processes that are sequential and stage-like, such as cycles of moon, circulation of blood, stages of mitosis, and photosynthesis, a Direct-causal Schema is adequate for correct understanding. However, for science processes that are non-sequential (or emergent), such as diffusion, natural selection, osmosis, and heat flow, using a Direct Schema to understand these processes will lead to robust misconceptions. Instead, a different type of general schema may be required to interpret non-sequential processes, which we refer to as an Emergent-causal Schema. We propose that students lack this Emergent Schema and teaching it to them may help them learn and understand emergent kinds of science processes such as diffusion. Our study found that directly teaching students this Emergent Schema led to increased learning of the process of diffusion. This article presents a fine-grained characterization of each type of Schema, our instructional intervention, the successes we have achieved, and the lessons we have learned.Correspondence should be sent to Michelene T.

The goals of this study are to evaluate a relatively novel learning environment, as well as to seek greater understanding of why human tutoring is so effective. This alternative learning environment consists of pairs of students collaboratively observing a videotape of another student being tutored. Comparing this collaboratively observing environment to four other instructional methods-one-onone human tutoring, observing tutoring individually, collaborating without observing, and studying alone-the results showed that students learned to solve physics problems just as effectively from observing tutoring collaboratively as the tutees who were being tutored individually. We explain the effectiveness of this learning environment by postulating that such a situation encourages learners to become active and constructive observers through interactions with a peer. In essence, collaboratively observing combines the benefit of tutoring with the benefit of collaborating. The learning outcomes of the tutees and the collaborative observers, along with the tutoring dialogues, were used to further evaluate three hypotheses explaining why human tutoring is an effective learning method. Detailed analyses of the protocols at several grain sizes suggest that tutoring is effective when tutees are independently or jointly constructing knowledge: with the tutor, but not when the tutor independently conveys knowledge.

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There has been a national call for increased use of computers and technology in schools. Currently, however, little is known about how students use and learn from these technologies. This study explores how eighth-grade students use the Web to search for, browse, and find information in response to a specific prompt (how mosquitoes find their prey). A previous analysis (Roy, Taylor & Chi, 2003) found that boys performed significantly better on gaining target-specific (information directly related to the prompt) and target-related (information related to mosquitoes in general) knowledge than girls. The current article explores this difference further by examining how students searched the Web for information. Each student's search behavior was diagramed out and a series of six different "search moves" were derived. Statistical analysis of these search variables revealed that boys tended to employ a different search pattern from girls and that this variation in search behavior was related to the pattern of performance outcomes.

Of 3000+ raters, fewer than 0.3% have been identified as being extreme using the proposed criteria. Rater performance is being monitored on a regular basis, and the impact of these raters on candidate results will be considered before results are finalised. Extreme raters are contacted by the organisation to review their rating style. If this intervention fails to modify the rater's scoring pattern, the rater is no longer invited back. As more data are collected the organisation will assess them to inform the development of approaches to improve extreme rater performance.