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Despite its proven added value, modeling‐based learning (MbL) in science is not commonly incorporated into the early grades. Our purpose in this descriptive case study was to enrich our understanding of how kindergarten children enact MbL by examining these children's constructed models and their accompanying oral descriptions of their models. For this purpose, we adopted a drawing‐based modeling approach in which children used annotated drawings to represent their models. The participants consisted of four groups of 5‐ to 6‐year‐olds (68 children total) who studied the solution of substances in water. We analyzed child‐developed models (artifact analysis) and their oral presentations (discourse analysis), seeking to provide rich, detailed descriptions of the characteristics of these models. Our findings suggest that children in the study developed five different types of models using three different depiction strategies. Our findings also suggest that when developing and presenting their models of a physical phenomenon, our kindergarten children tended to rely on analogical reasoning to identify similar, known situations corresponding to the phenomenon under study. They then invoked mechanistic reasoning to develop representations of the phenomenon under study based on the analogy they used. The spectrum of mechanistic reasoning used by the children, and the analysis of the structure and components of their constructed models serve as evidence suggesting that despite their limited experiences with formal science education, as well as with MbL in science, participating children could successfully engage in authentic MbL activities. We contend that this is aligned with the idea of modeling resources, suggesting that it is more productive to help children to develop more reliable access to modeling resources they already have, even though they are usually not aware of their connection to MbL, such as prior scientific knowledge, experience, and MbL skills. [ABSTRACT FROM AUTHOR]

According to the weak central coherence (CC) account individuals with autism spectrum disorders (ASD) exhibit enhanced local processing and weak part-whole integration. CC was investigated in the verbal domain. Adolescents, recruited using a 2 (ASD status) by 2 (language impairment status) design, completed an aural forced choice comprehension task involving syntactically ambiguous sentences. Half the picture targets depicted the least plausible interpretation, resulting in longer RTs across groups. These were assumed to reflect local processing. There was no ASD by plausibility interaction and consequently little evidence for weak CC in the verbal domain when conceptualised as enhanced local processing. Furthermore, there was little evidence that the processing of syntactically ambiguous sentences differed as a function of ASD or language-impairment status. [ABSTRACT FROM AUTHOR]

Although research has come to recognize the importance of studying classroom-based student–teacher discourse in science, the emphasis remains largely on teachers' abilities to ask questions and provide students with feedback, or on students' abilities to ask questions or engage in argumentative discourse. Consequently, little research has focused on the discourse elements relating to teacher–student discourse interactions. In this article, we argue for a shift of research attention toward describing what the teacher is responding to (Identification of student inquiry), the process of deciding how to respond (Interpretation—Evaluation of student inquiry), and how the teacher is responding (Response to student inquiry). We propose a new methodological approach for studying teacher discourse, which involves a framework we developed while analyzing 1,385 minutes of fifth grade, whole-class science conversations covering a 2-year period and facilitated by an experienced science teacher. Then, as a case in point, we applied our framework to the teacher discourse data of the study, aiming to show that the framework can be a useful tool for examining how a teacher supports students' inquiry. [ABSTRACT FROM PUBLISHER]

The purpose of this study was to investigate whole classroom discourse during modeling-based learning in science, seeking to describe the discourse's characteristics, its relation to the micro-context in which it took place and to the student-constructed models, and to ascertain when it becomes productive. Additionally, we aimed to describe how whole classroom modeling discourse in science may be better supported by the teacher as well as the role of the modeling tool. In doing so, we analyzed student conversations and student-constructed models from two groups of 11- to 12-year-old students. All students used a computer programming environment, namely Stagecast Creator, as a modeling tool. Findings revealed three distinct discourse types (modeling frames): (a) (initial) phenomenological description, (b) operationalization of the physical system's story, and (c) construction of algorithms. Finally, we discuss what we consider productive modeling discourse, as well as the contributions of the software and the teacher in this respect. © 2011 Wiley Periodicals, Inc. J Res Sci Teach 48: 919-951, 2011 [ABSTRACT FROM AUTHOR]

BackgroundAutism spectrum disorder (ASD) was once considered to be highly associated with intellectual disability and to show a characteristic IQ profile, with strengths in performance over verbal abilities and a distinctive pattern of ‘peaks’ and ‘troughs’ at the subtest level. However, there are few data from epidemiological studies.MethodComprehensive clinical assessments were conducted with 156 children aged 10–14 years [mean (s.d.)=11.7 (0.9)], seen as part of an epidemiological study (81 childhood autism, 75 other ASD). A sample weighting procedure enabled us to estimate characteristics of the total ASD population.ResultsOf the 75 children with ASD, 55% had an intellectual disability (IQ<70) but only 16% had moderate to severe intellectual disability (IQ<50); 28% had average intelligence (115>IQ>85) but only 3% were of above average intelligence (IQ>115). There was some evidence for a clinically significant Performance/Verbal IQ (PIQ/VIQ) discrepancy but discrepant verbal versus performance skills were not associated with a particular pattern of symptoms, as has been reported previously. There was mixed evidence of a characteristic subtest profile: whereas some previously reported patterns were supported (e.g. poor Comprehension), others were not (e.g. no ‘peak’ in Block Design). Adaptive skills were significantly lower than IQ and were associated with severity of early social impairment and also IQ.ConclusionsIn this epidemiological sample, ASD was less strongly associated with intellectual disability than traditionally held and there was only limited evidence of a distinctive IQ profile. Adaptive outcome was significantly impaired even for those children of average intelligence. [ABSTRACT FROM AUTHOR]

BackgroundAutism spectrum disorder (ASD) was once considered to be highly associated with intellectual disability and to show a characteristic IQ profile, with strengths in performance over verbal abilities and a distinctive pattern of ‘peaks’ and ‘troughs’ at the subtest level. However, there are few data from epidemiological studies.MethodComprehensive clinical assessments were conducted with 156 children aged 10–14 years [mean (s.d.)=11.7 (0.9)], seen as part of an epidemiological study (81 childhood autism, 75 other ASD). A sample weighting procedure enabled us to estimate characteristics of the total ASD population.ResultsOf the 75 children with ASD, 55% had an intellectual disability (IQ<70) but only 16% had moderate to severe intellectual disability (IQ<50); 28% had average intelligence (115>IQ>85) but only 3% were of above average intelligence (IQ>115). There was some evidence for a clinically significant Performance/Verbal IQ (PIQ/VIQ) discrepancy but discrepant verbal versus performance skills were not associated with a particular pattern of symptoms, as has been reported previously. There was mixed evidence of a characteristic subtest profile: whereas some previously reported patterns were supported (e.g. poor Comprehension), others were not (e.g. no ‘peak’ in Block Design). Adaptive skills were significantly lower than IQ and were associated with severity of early social impairment and also IQ.ConclusionsIn this epidemiological sample, ASD was less strongly associated with intellectual disability than traditionally held and there was only limited evidence of a distinctive IQ profile. Adaptive outcome was significantly impaired even for those children of average intelligence. [ABSTRACT FROM PUBLISHER]

The purpose of this study was to develop a framework for analyzing and evaluating student-constructed models of physical phenomena and monitoring the progress of these models. Moreover, we aimed to examine whether this framework could capture differences between models created using different computer-based modeling tools; namely, computer-based programming environments which, in prior research, were found to differ in various aspects of the models constructed through them. We analyzed 220 computer-based models of physical phenomena developed by two groups of elementary-school students. Using open coding we developed a framework that includes five elements of scientific models that code for representations of: (i) the physical objects; (ii) the physical entities; (iii) the object behaviors; (iv) the interactions among physical objects, physical entities, and object behavior(s); and (v) the accuracy of the phenomenon depiction. The implementation of this framework confirmed that it can differentiate student-generated models according to their sophistication and structural components, independent of the computer-based programming environments used to create the models. [ABSTRACT FROM AUTHOR]

Background: Recent studies have indicated that many children with autism spectrum disorders present with language difficulties that are similar to those of children with specific language impairments, leading some to argue for similar structural deficits in these two disorders. Aims: Repetition of sentences involving long-distance dependencies was used to investigate complex syntax in these groups. Methods & Procedures: Adolescents with specific language impairments (mean age = 15;3, n = 14) and autism spectrum disorders plus language impairment (autism plus language impairment; mean age = 14;8, n = 16) were recruited alongside typically developing adolescents (mean age = 14;4, n = 17). They were required to repeat sentences containing relative clauses that varied in syntactic complexity. Outcomes & Results: The adolescents with specific language impairments presented with greater syntactic difficulties than the adolescents with autism plus language impairment, as manifested by higher error rates on the more complex object relative clauses, and a greater tendency to make syntactic changes during repetition. Conclusions & Implications: Adolescents with specific language impairments may have more severe syntactic difficulties than adolescents with autism plus language impairment, possibly due to their short-term memory limitations. [ABSTRACT FROM AUTHOR]

This is an interpretive case study seeking to develop detailed and comparative descriptions of how two groups of fifth-grade students used two different Computer-based Programming Environments (CPEs) (namely Microworlds Logo and Stagecast Creator) during scientific modelling. The primary sources of data that were used in this 4-month study include videotaped students' group work and whole-class discussions, and the instructors' reflective journals. For the data analysis, contextual inquiry was used in conjunction with analysis of student conversation in order to gain better insight into students' activity and conversation patterns while working with CPEs. Findings highlight the differences in the ways that the students used the two CPEs in the context of developing models of natural phenomena with respect to three distinct phases that emerged from data analysis, which include student approaches to (i) planning, (ii) writing and debugging code, and (iii) using code to represent the phenomenon under study. Lastly, findings highlight which aspects of students work during the three phases can be productive for scientific modelling, proposing possible relationships between student work and CPE features. [ABSTRACT FROM AUTHOR]