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Learning the Language of Evolution: Lexical Ambiguity and Word Meaning in Student Explanations 总被引：1，自引：0，他引：1
Our study investigates the challenges introduced by students’ use of lexically ambiguous language in evolutionary explanations. Specifically, we examined students’ meaning of five key terms incorporated into their written evolutionary explanations: pressure, select, adapt, need, and must. We utilized a new technological tool known as the Assessment Cascade System (ACS) to investigate the frequency with which biology majors spontaneously used lexically ambiguous language in evolutionary explanations, as well as their definitions and explanations of what they meant when they used such terms. Three categories of language were identified and examined in this study: terms with Dual Ambiguity, Incompatible Ambiguity, and Unintended Ambiguity. In the sample of 1282 initial evolutionary explanations, 81 % of students spontaneously incorporated lexically ambiguous language at least once. Furthermore, the majority of these initial responses were judged to be inaccurate from a scientific point of view. While not significantly related to gender, age, or reading/writing ability, students’ use of contextually appropriate evolutionary language (pressure and adapt) was significantly associated with academic performance in biology. Comparisons of initial responses to follow-up responses demonstrated that the majority of student explanations were not reinterpreted after consideration of the follow-up response; nevertheless, a sizeable minority was interpreted differently. Most cases of interpretation change were a consequence of resolving initially ambiguous responses, rather than a change of accuracy, resulting in an increased understanding of students’ evolutionary explanations. We discuss a series of implications of lexical ambiguity for evolution education. 相似文献
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Understanding how situational features of assessment tasks impact reasoning is important for many educational pursuits, notably the selection of curricular examples to illustrate phenomena, the design of formative and summative assessment items, and determination of whether instruction has fostered the development of abstract schemas divorced from particular instances. The goal of our study was to employ an experimental research design to quantify the degree to which situational features impact inferences about participants’ understanding of Mendelian genetics. Two participant samples from different educational levels and cultural backgrounds (high school, n = 480; university, n = 444; Germany and USA) were used to test for context effects. A multi-matrix test design was employed, and item packets differing in situational features (e.g., plant, animal, human, fictitious) were randomly distributed to participants in the two samples. Rasch analyses of participant scores from both samples produced good item fit, person reliability, and item reliability and indicated that the university sample displayed stronger performance on the items compared to the high school sample. We found, surprisingly, that in both samples, no significant differences in performance occurred among the animal, plant, and human item contexts, or between the fictitious and “real” item contexts. In the university sample, we were also able to test for differences in performance between genders, among ethnic groups, and by prior biology coursework. None of these factors had a meaningful impact upon performance or context effects. Thus some, but not all, types of genetics problem solving or item formats are impacted by situational features. 相似文献
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Cognitive foundations for science assessment design: Knowing what students know about evolution 总被引：1，自引：0，他引：1
To improve assessments of academic achievement, test developers have been urged to use an “assessment triangle” that starts with research‐based models of cognition and learning [NRC (2001) Knowing what students know: The science and design of educational assessment. Washington, DC: National Academy Press]. This approach has been successful in designing high‐quality reading and math assessments, but less progress has been made for assessments in content‐rich sciences such as biology. To rectify this situation, we applied the “assessment triangle” to design and evaluate new items for an instrument (ACORNS, Assessing Contextual Reasoning about Natural Selection) that had been proposed to assess students' use of natural selection to explain evolutionary change. Design and scoring of items was explicitly guided by a cognitive model that reflected four psychological principles: with development of expertise, (1) core concepts facilitate long‐term recall, (2) causally‐central features become weighted more strongly in explaining phenomena, (3) normative ideas co‐exist but increasingly outcompete naive ideas in reasoning, and (4) knowledge becomes more abstract and less specific to the learning situation. We conducted an evaluation study with 320 students to examine whether scores from our new ACORNS items could detect gradations of expertise, provide insight into thinking about evolutionary change, and predict teachers' assessments of student achievement. Findings were consistent with our cognitive model, and ACORNS was revealing about undergraduates' thinking about evolutionary change. Results indicated that (1) causally‐central concepts of evolution by natural selection typically co‐existed and competed with the presence of naïve ideas in all students' explanations, with naïve ideas being especially prevalent in low‐performers' explanations; (2) causally‐central concepts were elicited most frequently when students were asked to explain evolution of animals and familiar plants, with influence of superficial features being strongest for low‐performers; and (3) ACORNS scores accurately predicted students' later achievement in a college‐level evolution course. Together, findings illustrate usefulness of cognitive models in designing instruments intended to capture students' developing expertise. © 2012 Wiley Periodicals, Inc. J Res Sci Teach 49: 744–777, 2012 相似文献
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Xiaoming Zhai Kevin C. Haudek Lehong Shi Ross H. Nehm Mark Urban-Lurain 《科学教学研究杂志》2020,57(9):1430-1459
This study develops a framework to conceptualize the use and evolution of machine learning (ML) in science assessment. We systematically reviewed 47 studies that applied ML in science assessment and classified them into five categories: (a) constructed response, (b) essay, (c) simulation, (d) educational game, and (e) inter-discipline. We compared the ML-based and conventional science assessments and extracted 12 critical characteristics to map three variables in a three-dimensional framework: construct, functionality, and automaticity. The 12 characteristics used to construct a profile for ML-based science assessments for each article were further analyzed by a two-step cluster analysis. The clusters identified for each variable were summarized into four levels to illustrate the evolution of each. We further conducted cluster analysis to identify four classes of assessment across the three variables. Based on the analysis, we conclude that ML has transformed—but not yet redefined—conventional science assessment practice in terms of fundamental purpose, the nature of the science assessment, and the relevant assessment challenges. Along with the three-dimensional framework, we propose five anticipated trends for incorporating ML in science assessment practice for future studies: addressing developmental cognition, changing the process of educational decision making, personalized science learning, borrowing 'good' to advance 'good', and integrating knowledge from other disciplines into science assessment. 相似文献
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A large body of research has examined students' conceptions of evolution and their relationships to acceptance of evolution. Proficiency in statistical and probabilistic reasoning has long been considered to be an essential feature of evolutionary reasoning, yet almost no empirical work has explored these putative connections. The RaPro instruments have recently been developed to measure statistical reasoning in the contexts of mathematics (RaProMath) and evolution (RaProEvo). Our study provides additional validation of these instruments using Rasch analysis and quantifies the contribution of statistical reasoning to both understanding and accepting evolution. We recruited a large sample (N = 564) of undergraduate students enrolled in an introductory biology course at a large public research university in the United States. Students completed a suite of published instruments that assessed statistical reasoning, evolutionary understanding, and evolutionary acceptance. Our findings indicate that validity inferences derived from RaPro scores generalized to the new sample, and that proficiency in statistical reasoning explained 28% of the variance in evolutionary knowledge and 19% of the variation in evolutionary acceptance. The inclusion of demographic variables into the model significantly increased the explained variance in acceptance. Notably, the variance in evolution acceptance explained by statistical reasoning was comparable to that of thinking dispositions or evolutionary knowledge reported in the literature. This work provides the first large-scale evidence of the role of statistical reasoning in evolutionary knowledge and acceptance and motivates future work to explore how statistical literacy should be integrated into evolution education efforts. 相似文献
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The growing importance of genomics and bioinformatics methods and paradigms in biology has been accompanied by an explosion of new curricula and pedagogies. An important question to ask about these educational innovations is whether they are having a meaningful impact on students’ knowledge, attitudes, or skills. Although assessments are necessary tools for answering this question, their outputs are dependent on their quality. Our study 1) reviews the central importance of reliability and construct validity evidence in the development and evaluation of science assessments and 2) examines the extent to which published assessments in genomics and bioinformatics education (GBE) have been developed using such evidence. We identified 95 GBE articles (out of 226) that contained claims of knowledge increases, affective changes, or skill acquisition. We found that 1) the purpose of most of these studies was to assess summative learning gains associated with curricular change at the undergraduate level, and 2) a minority (<10%) of studies provided any reliability or validity evidence, and only one study out of the 95 sampled mentioned both validity and reliability. Our findings raise concerns about the quality of evidence derived from these instruments. We end with recommendations for improving assessment quality in GBE. 相似文献
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Ross H. Nehm 《Science & Education》2013,22(5):1291-1294
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