Taking advantage of automated assessment of student‐constructed graphs in science

Vitale, Jonathan M.; Lai, Kevin; Linn, Marcia C.

doi:10.1002/tea.21241

Cited by 25 publications

(20 citation statements)

References 42 publications

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“…Indeed, sometimes, the argument may be made explicitly. In a study exploring the assessment of student-generated graphs in science, Vitale, Lai andLinn (2015, p. 1438) suggested that "relatively high values of Cronbach's α (six items, pre-test: α = 0.70; post-test: α = 0.77) suggest that these items all, at least partially, measured the same factor^(emphasis added). Depending on how the authors intend the qualifier "at least partially", this claim is either misleading or trivial.…”

Section: Misuse Of Alpha To Imply Unidimensionalitymentioning

confidence: 99%

The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education

2017

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Cronbach's alpha is a statistic commonly quoted by authors to demonstrate that tests and scales that have been constructed or adopted for research projects are fit for purpose. Cronbach's alpha is regularly adopted in studies in science education: it was referred to in 69 different papers published in 4 leading science education journals in a single year (2015)-usually as a measure of reliability. This article explores how this statistic is used in reporting science education research and what it represents. Authors often cite alpha values with little commentary to explain why they feel this statistic is relevant and seldom interpret the result for readers beyond citing an arbitrary threshold for an acceptable value. Those authors who do offer readers qualitative descriptors interpreting alpha values adopt a diverse and seemingly arbitrary terminology. More seriously, illustrative examples from the science education literature demonstrate that alpha may be acceptable even when there are recognised problems with the scales concerned. Alpha is also sometimes inappropriately used to claim an instrument is unidimensional. It is argued that a high value of alpha offers limited evidence of the reliability of a research instrument, and that indeed a very high value may actually be undesirable when developing a test of scientific knowledge or understanding. Guidance is offered to authors reporting, and readers evaluating, studies that present Cronbach's alpha statistic as evidence of instrument quality.

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Section: Misuse Of Alpha To Imply Unidimensionalitymentioning

confidence: 99%

The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education

2017

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“…Thus, for critique as for comprehension many students drew on superficial criteria (such as readability) and failed to incorporate their knowledge of the science (such as climate trends) into their response. Instructional studies that emphasize knowledge integration show that it is possible to improve the ability to critique graphs (Chang and Linn 2013;Svihla and Linn 2012;Vitale et al 2015).…”

Section: Critique Itemsmentioning

confidence: 98%

“…To implement this type of item, we took advantage of the WISE graphing tool that provided students with a predefined set of axes and an intuitive point-plotting interface as well as a method for designing automated scoring of the resulting graph (Vitale et al 2015). Since the axes were predefined for the students, the automatic scoring only scored the actual lines the students constructed, and not the other basic graph elements (e.g., axes, axes titles).…”

Section: Graph Construction Itemsmentioning

confidence: 99%

“…Additionally, graph construction activities can expose students' non-normative ideas about scientific concepts (Vitale et al 2015). For example, if students depict cooling as a linear relationship between temperature and time, they demonstrate an incomplete knowledge of the science.…”

Section: Constructionmentioning

confidence: 99%

“…Students appeared to implement an intuitive idea about the narrative, rather than focusing on elements of the graph, such as the meaning of the axes. Instructional studies demonstrate that students can learn to integrate their intuitions about the narrative and their knowledge of graphs to represent a complex sequence of actions and incorporate a series of constraints (Vitale et al 2015).…”

Section: Graph Construction Itemsmentioning

confidence: 99%

See 2 more Smart Citations

Measuring Graph Comprehension, Critique, and Construction in Science

et al. 2016

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Interpreting and creating graphs plays a critical role in scientific practice. The K-12 Next Generation Science Standards call for students to use graphs for scientific modeling, reasoning, and communication. To measure progress on this dimension, we need valid and reliable measures of graph understanding in science. In this research, we designed items to measure graph comprehension, critique, and construction and developed scoring rubrics based on the knowledge integration (KI) framework. We administered the items to over 460 middle school students. We found that the items formed a coherent scale and had good reliability using both item response theory and classical test theory. The KI scoring rubric showed that most students had difficulty linking graphs features to science concepts, especially when asked to critique or construct graphs. In addition, students with limited access to computers as well as those who speak a language other than English at home have less integrated understanding than others. These findings point to the need to increase the integration of graphing into science instruction. The results suggest directions for further research leading to comprehensive assessments of graph understanding.

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Qualitative graphing in an authentic inquiry context: How construction and critique help middle school students to reason about cancer

Matuk

Zhang²,

et al. 2019

J Res Sci Teach

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Inquiry instruction often neglects graphing. It gives students few opportunities to develop the knowledge and skills necessary to take advantage of graphs, and which are called for by current science education standards. Yet, it is not well known how to support graphing skills, particularly within middle school science inquiry contexts. Using qualitative graphs is a promising, but underexplored approach. In contrast to quantitative graphs, which can lead students to focus too narrowly on the mechanics of plotting points, qualitative graphs can encourage students to relate graphical representations to their conceptual meaning. Guided by the Knowledge Integration framework, which recognizes and guides students in integrating their diverse ideas about science, we incorporated qualitative graphing activities into a seventh grade web‐based inquiry unit about cell division and cancer treatment. In Study 1, we characterized the kinds of graphs students generated in terms of their integration of graphical and scientific knowledge. We also found that students (n = 30) using the unit made significant learning gains based on their pretest to post‐test scores. In Study 2, we compared students' performance in two versions of the same unit: One that had students construct, and second that had them critique qualitative graphs. Results showed that both activities had distinct benefits, and improved students' (n = 117) integrated understanding of graphs and science. Specifically, critiquing graphs helped students improve their scientific explanations within the unit, while constructing graphs led students to link key science ideas within both their in‐unit and post‐unit explanations. We discuss the relative affordances and constraints of critique and construction activities, and observe students' common misunderstandings of graphs. In all, this study offers a critical exploration of how to design instruction that simultaneously supports students' science and graph understanding within complex inquiry contexts.

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Taking advantage of automated assessment of student‐constructed graphs in science

Cited by 25 publications

References 42 publications

The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education

The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education

Measuring Graph Comprehension, Critique, and Construction in Science

Qualitative graphing in an authentic inquiry context: How construction and critique help middle school students to reason about cancer

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