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This research addresses high school students' understandings of the nature of models, and their interaction with model-based software in three science domains, namely, biology, physics, and chemistry. Data from 736 high school students' understandings of models were collected using the Students' Understanding of Models in Science (SUMS) survey as part of a large-scale, longitudinal study in the context of technology-based curricular units in each of the three science domains. The results of ANOVA and regression analyses showed that there were differences in students' pre-test understandings of models across the three domains, and that higher post-test scores were associated with having engaged in a greater number of curricular activities, but only in the chemistry domain. The analyses also showed that the relationships between the pre-test understanding of models subscales scores and post-test content knowledge varied across domains. Some implications are discussed with regard to how students' understanding of the nature of models can be promoted.

This study investigates young children's perspectives in explaining a selfregulating mobile robot, as they learn to program its behaviors from rules. We explore their descriptions of a robot in action to determine the nature of their explanatory frameworks: psychological or technological. We have also studied the role of an adult's intervention in their reasoning. The study was conducted individually with six kindergarten children along five sessions that included tasks, ordered by increasing difficulty. We developed and used a robotic control interface. We have found that the children employed two modes of explanation: ''engineering'' mode focused on the technological building blocks which make up the robot's operation; ''bridging'' mode tended to combine and align two explanatory frameworks -technological and psychological. However, this was not consistent across tasks. In the easiest tasks, involving one condition-action rule, most of the children used a technological perspective. When the task became more difficult, most children shifted to a psychological perspective. Further experience in programming was associated with a shift to technological or combined explanatory frameworks. The results are discussed with respect to developmental literature on children's explanatory frameworks, and with regard to educational implications of incorporating such learning environments in early childhood classes.Controlled self-regulated systems pervade our daily environment, embodying central concepts related to systems, adaptation and emergence. Robotic systems, which have been part of educational settings for over two decades, provide opportunities to interact with, and construct controlled adaptive behaviors (Papert 1980

This study explores young children's abstraction of the rules underlying a robot's emergent behavior. The study was conducted individually with six kindergarten children, along five sessions that included description and construction tasks, ordered by increasing difficulty. We developed and used a robotic control interface, structured as independent concurrent rules. To capture the children's changing knowledge representations, we have employed a framework that underscores the differences in generality between episodes, a unique sequence of events, scripts, which include repeating temporal patterns, triggered by an environmental condition and rules, atemporal associations between local environmental conditions and the robot's actions. Our data unravels the progression through which rules are constructed. From an episode that focuses on the robot's actions, noticing repeated sequences triggered by occasional environmental conditions emerges into scripts. Once both actions and conditions are attributed with similar importance, noticing the co-variance of environmental conditions with robot actions is made possible, bolstering abstraction of atemporal rules. In addition, we have supported the children's reasoning by helping them attend to relevant features, and compared their spontaneous and supported descriptions. We elaborate on the role of function and mechanism as invariants, and the support of ''concrete-abstractions'' in the interaction between cognitive schemas and object-embedded abstract schemas, for the children's evolving explanations of the robot's behavior.

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