Data Analysis and Interpretation in Physical Sciences of Next Generation Science Standards Data Analysis and Interpretation in Physical Sciences of Next Generation Science Standards MIYAMOTO, Naoki SUMMARY In this study, we focused on the Next Generation Science Standards in the United States, where viewpoints on instructions about analyzing and interpreting data are clearly shown. We have clarified the viewpoints on the stepwise development of the abilities for analyzing and interpreting data from the kindergarten to high-school levels. These viewpoints are as follows. 1 The analysis and interpretation of data are treated as basic skills for K-2 students, and are supposed to be developed in a stepwise manner, 2 The analysis and interpretation of data are associated with each other, and the abilities to analyze and interpret data are developed in a stepwise manner. 3 The analysis and interpretation of data are described by replacing the terms analysis and interpretation with expressions such as integration, evaluation, and translation. KEY WORDS: Data Analysis and Interpretation, Next Generation Science Standards 1 Introduction The study courses for science students in elementary schools focus on the development of the abilities of problem solving 1, whereas those for science students in junior high schools and high schools stipulate the development of the abilities of scientific investigation 2 3. In particular, in junior high and high schools, analysis and interpretation are emphasized among the investigation abilities4 5. In contrast, in elementary schools, although analysis and interpretation are not described, the investigation abilities for analysis and interpretation are essential in the process of problem solving and must be given importance. Despite such a situation, detailed Lecturer of the Faculty of Letters, Toyo University 361
descriptions for improvement described in the commentary of the science study courses in junior high schools, for example, state that we should enhance skills of problem solving that were obtained in the elementary school course, and develop abilities of scientific investigation such as to analyze and interpret results of observations and experiments 6. Furthermore, the detailed descriptions for improvement in the commentary of science study courses in junior high schools state that in observations, experiments, and investigations, we should further make much account of the learning activities such as to analyze and interpret results, to derive students own ideas, and to express them 7. From these examples, we observe that there are no viewpoints on stepwise development of the abilities of analysis and interpretation along with the progress of grades in Japan8. Therefore, teachers conducting science classes cannot have clear viewpoints to allow students to analyze and interpret experimental data9, and thus development of students abilities for analyzing and interpreting data cannot be expected. Moreover, as per our knowledge, there is no research about stepwise development of the abilities for analyzing and interpreting data from the elementary to high school levels. If we clarify the viewpoints to have students analyze and interpret data in a stepwise manner, we can obtain viewpoints to develop students abilities for analyzing and interpreting data. In a previous study on analyzing data interpretation skills for physics using an elementary science textbook Scott Foresman Science Grade1-6 in the United States, Miyamoto pointed out that they teach in a way so that students can obtain skills of interpreting data in a stepwise manner as grades are advanced 10. The study is based on an elementary level and only mentions data interpretation skills. It does not convey basic knowledge on stepwise development of the abilities for analyzing and interpreting data from the elementary to high school levels. NGSS, which In this study, we focus on the Next Generation Science Standards 11 are science standards in the United States, that clearly show viewpoints on instructions about analyzing and interpreting data. In addition, we clarify the viewpoints on stepwise development of the abilities for analyzing and interpreting data in Grades K-12 from kindergarten to high school. These NGSS were released in April 2013, and replaced the National Science Education Standards in the United States12. NGSS are based on A Framework for Science Education 13, and they are science education standards that are gaining considerable attention in the United States. Another set of standards called the Common Core State Standards CCSS are for math and language skills that 45 states in 362
Data Analysis and Interpretation in Physical Sciences of Next Generation Science Standards the United States choose and follow. In CCSS and NGSS, it is stated that, Literacy skills are critical to building knowledge in science. To ensure the CCSS literacy standards work in tandem with the specific content demands outlined in the NGSS, the NGSS development team worked with the CCSS writing team to identify key literacy connections to the specific content demands outlined in the NGSS. 14 ; therefore, it is expected that NGSS and CCSS are related. Threfore, we will also discuss CCSS in this study. 2 Structure of NGSS NGSS are composed of the following three elements for each grade or each Disciplinary Core Ideas, and grade group15 : Science and Engineering Practices, Crosscutting Concepts. Furthermore, NGSS are composed of four domains: physical sciences ; life sciences ; earth and space sciences ; and engineering, technology, and applications of science. The expected learning achievements for students are mentioned clearly in each. In particular, the contents of analyzing and interpreting data are clearly stated in Science and Engineering Practices ; therefore, we focus on this element and proceed with its analysis. In general, analyzing and interpreting data were expressed as elements of science processes and inquiry ; however, in NGSS, they are expressed as elements of practices 16. Furthermore, it is mentioned that We use the term practices instead of a term such as skills to emphasize that engaging in scientific investigation 17 These practices are composed of the following eight items18. 1. Asking questions for science and defining problems for engineering 2. Developing and using models 3. Planning and carrying out investigations 4. Analyzing and interpreting data 5. Using mathematics and computational thinking 6. Constructing explanations for science and designing solutions for engineering 7. Engaging in argument from evidence 8. Obtaining, evaluating, and communicating information As aforementioned, analyzing and interpreting data are essential in practices. In the item Analyzing and interpreting data, as it is clearly stated that Students are also expected to improve their abilities to interpret data by identifying significant features 363
and patterns, use mathematics to represent relationships between variables, and take into account sources of error. 19, we can say that NGSS aim to develop students abilities. In this study, we consider that the abilities of analyzing and interpreting data are developed when the corresponding skills are improved. Inversely, the skills of analyzing and interpreting data are part of the elements of the abilities for analyzing and interpreting data, and are a major part of the abilities. The other elements of those abilities include inference and producing graphs. The next section highlights the learning achievements for analyzing and interpreting data that are expected of students. 3 Analyzing and interpreting data in NGSS Table 1 shows the analysis and interpretation of data described through grade groups along with the learning achievements that are expected for students. First, the table presents the learning achievements based on those for the previous grade group, as described in prior experiences in Grades K-2: K-2 experiences in Grades 3 5, K-5 experiences in Grades 6 8, and K-8 experiences in Grades 9 12. In particular, in Grades K-2 they are explicitly described as prior experiences. It is inferred that these are daily experiences in childhood. Therefore, there is stepwise development in the abilities for analyzing and interpreting data. Next, when we focus on analyzing data, as described in introducing quantitative approaches in Grades 3 5, quantitative data analysis is stipulated from the group. In addition, the use of basic statistics is explained in Table 1 Learning achievements expected for students about data analysis and interpretation Analyzing data in K 2 builds on prior experiences and progresses to collecting, recording, and sharing observations. Record information observations, thoughts, and ideas. Use and share pictures, drawings, and/or writings of observations. Grades K-2 Use observations firsthand or from media to describe patterns and/or relationships in the natural and designed world s in order to answer scientific questions and solve problems. Compare predictions based on prior experiences to what occurred observable events. Analyze data from tests of an object or tool to determine if it works as intended. Analyzing data in 3 5 builds on K 2 experiences and progresses to introducing quantitative approaches to collecting data and conducting multiple trials of qualitative Grades 3-5 observations. When possible and feasible, digital tools should be used. Represent data in tables and/or various graphical displays bar graphs, pictographs and/or pie charts to reveal patterns that indicate relationships. 364
Data Analysis and Interpretation in Physical Sciences of Next Generation Science Standards Analyze and interpret data to make sense of phenomena, using logical reasoning, mathematics, and/or computation. Compare and contrast data collected by different groups in order to discuss Grades 3-5 similarities and differences in their findings. Analyze data to refine a problem statement or the design of a proposed object, tool, or process. Use data to evaluate and refine design solutions. Analyzing data in 6 8 builds on K 5 experiences and progresses to extending quantitative analysis to investigations, distinguishing between correlation and causation, and basic statistical techniques of data and error analysis. Construct, analyze, and/or interpret graphical displays of data and/or large data sets to identify linear and nonlinear relationships. Use graphical displays e.g., maps, charts, graphs, and/or tables of large data sets to identify temporal and spatial relationships. Distinguish between causal and correlational relationships in data. Grades 6-8 Analyze and interpret data to provide evidence for phenomena. Apply concepts of statistics and probability including mean, median, mode, and variability to analyze and characterize data, using digital tools when feasible. Consider limitations of data analysis e.g., measurement error, and/or seek to improve precision and accuracy of data with better technological tools and methods e.g., multiple trials. Analyze and interpret data to determine similarities and differences in findings. Analyze data to define an optimal operational range for a proposed object, tool, process or system that best meets criteria for success. Analyzing data in 9 12 builds on K 8 experiences and progresses to introducing more detailed statistical analysis, the comparison of data sets for consistency, and the use of models to generate and analyze data. Analyze data using tools, technologies, and/or models e.g., computational, mathematical in order to make valid and reliable scientific claims or determine an optimal design solution. Apply concepts of statistics and probability including determining function fits to data, slope, intercept, and correlation coefficient for linear fits to scientific and Grades 9-12 engineering questions and problems, using digital tools when feasible. Consider limitations of data analysis e.g., measurement error, sample selection when analyzing and interpreting data. Compare and contrast various types of data sets e.g., self-generated, archival to examine consistency of measurements and observations. Evaluate the impact of new data on a working explanation and/or model of a proposed process or system. Analyze data to identify design features or characteristics of the components of a proposed process or system to optimize it relative to criteria for success. [Excerpts from Next Generation Science Standards: For States, By States, Volume2: Appendixes, Washington, DC: The National Academies Press, 2013. 57, Practice 4, analyzing and interpreting data including four domains ] 365
basic statistical techniques of data and error analysis in Grades 6 8. In particular, use of statistics and probability mean, median, mode, and variability is specified. Moreover, limitations of data analysis are mentioned in Consider limitations of data analysis e.g., measurement error. These points differ from the science curriculums in Japan, in which only the following are described. For example, in the contents of the first field of science Familiar physical phenomena and subfield Force and pressure, it is stated that when measurement results are treated, it is important to instruct students so that they can understand that measurement values always contain errors, and that they can find regularity with considering errors. In addition, it is important to have students master the basics of treating measurement values, including treatment of errors and drawing graphs 20. Moreover, in the contents of the first field of science Motion and Energy, it is stated that, when measurement results obtained by observations and experiments are treated, it is important to instruct students so that they can understand that measurement values always contain errors, and to instruct them by using tables and graphs so that students can find regularity with considering errors 21. Further, to express bar graphs, pictographs, and pie charts, the use of computers is stipulated from Grades 3 5, as observed in Analyze and interpret data to make sense of phenomena, using logical reasoning, mathematics, and/or computation in Grades 3 5. It is inferred that this is related to the introduction of the domain engineering, technology, and applications of science, which is explained later. In Grades 6 8, seek to improve precision and accuracy of data shows that data precision and accuracy are required. For interpreting data, Grades 3 5 provide a clear description of quantitative data analysis. In addition, as described in Grades 3 5; Compare and contrast data collected by different groups in order to discuss similarities and differences in their findings ; comparisons of similarities and differences are emphasized for data interpretation. Further, Represent data in tables and/or various graphical displays bar graphs, pictographs and/or pie charts to reveal patterns that indicate relationships in Grades 3 5 and Use graphical displays e.g., maps, charts, graphs, and/or tables of large data sets to identify temporal and spatial relationships in Grades 6 8, clearly state that students use graphic displays maps, charts, graphs, and/or tables to interpret data. Thus, the analysis and interpretation of data are related, and there is stepwise development in the abilities of analyzing and interpreting data. Therefore, we focus on Science and Engineering Practices of two domains of NGSS: physical sciences and engineering, technology, and applications of science, which are deeply related to physics domains. Note that physical 366
Data Analysis and Interpretation in Physical Sciences of Next Generation Science Standards sciences contains chemistry domains. 4 Analyzing and interpreting data in Science and Engineering Practices in physical sciences and engineering, technology, and applications of science Table 2 Data analysis and interpretation for each grade in Science and Engineering Practices in physical sciences Grade K 1 2 3 4 5 Description contents Analyzing data in K 2 builds on prior experiences and progresses to collecting, recording, and sharing observations. Analyze data from tests of an object or tool to determine if it works as intended. Motion and Stability: Forces and Interactions No description Analyzing data in K 2 builds on prior experiences and progresses to collecting, recording, and sharing observations. Analyze data from tests of an object or tool to determine if it works as intended. Matter and Its Interactions No description No description No description Analyzing data in 6 8 builds on K 5 experiences and progresses to extending quantitative analysis to investigations, distinguishing between correlation and causation, and basic statistical techniques of data and error analysis. Analyze and interpret data to determine similarities and differences in findings. Matter and Its Interactions Middle School Analyzing data in 6 8 builds on K 5 experiences and progresses to extending quantitative analysis to investigations, distinguishing between correlation and causation, and basic statistical techniques of data and error analysis. Construct and interpret graphical displays of data to identify linear and nonlinear relationships. Energy Analyzing data in 9 12 builds on K 8 experiences and progresses to introducing more detailed statistical analysis, the comparison of data sets for consistency, and the use of models High to generate and analyze data. School Analyze data using tools, technologies, and/or models e.g., computational, mathematical in order to make valid and reliable scientific claims or determine an optimal design solution. Motion and Stability: Forces and Interactions [Excerpts from Next Generation Science Standards: For States, By States, Volume1: The Standards-Arranged by Disciplinary Core Ideas and by Topics, Washington, DC: The National Academies Press, 2013. 4, 16, 57, 62, 95. The brackets show the contents of each domain.] 367
In K-5, that is, middle and high school physical sciences, analyzing and interpreting data is listed as one of the activities expected for students. Table 2 lists the content descriptions of data analysis and interpretation for each grade in Science and Engineering Practices in physical sciences. In Science and Engineering Practices in physical sciences, the contents that concretely describe data analysis and interpretation expected of students are only found as Motion and Stability: Forces and Interactions in Grade K and high school, Matter and Its Interactions in Grade 2, and Matter and Its Interactions, Energy in middle school. Other grade groups do not comprise any descriptions. However, each grade group describes learning achievements for analyzing and interpreting data expected of students, as shown in Table 1. Therefore, we can infer that it does not mean that data analysis and interpretation are not expected for those students. Table 3 shows the content descriptions of data analysis and interpretation for each grade in Science and Engineering Practices in engineering, technology, and applications of science. Table 3 Data analysis and interpretation for each grade in Science and Engineering Practices in engineering, technology, and applications of science Grade Description contents Analyzing data in K 2 builds on prior experiences and progresses to collecting, recording, K-2 and sharing observations. Analyze data from tests of an object or tool to determine if it works as intended. Engineering Design 3-5 No description Analyzing data in 6 8 builds on K 5 experiences and progresses to extending quantitative Middle School analysis to investigations, distinguishing between correlation and causation, and basic statistical techniques of data and error analysis. Analyze and interpret data to determine similarities and differences in findings. Engineering Design High School No description [Excerpts from Next Generation Science Standards: For States, By States, Volume1: The Standards-Arranged by Disciplinary Core Ideas and by Topics, Washington, DC: The National Academies Press, 2013. 23, 86. The brackets show the contents of each domain.] 368
Data Analysis and Interpretation in Physical Sciences of Next Generation Science Standards In Science and Engineering Practices in engineering, technology, and applications of science, the contents that concretely describe data analysis and interpretation expected of students are only found as Engineering Design in K-2 grade groups and middle school, and are not described in other grade groups. However, each grade group describes the learning achievements of analyzing and interpreting data expected for students, as shown in Table 1. Therefore, similar to Science and Engineering Practices in physical sciences, we can infer that the aforementioned does not indicate that data analysis and interpretation are not expected for those students. Furthermore, the contents of data analysis and interpretation in Table 2 clearly state that Analyze data using tools, technologies, and/or models e.g., computational, mathematical in order to make valid and reliable scientific claims or determine an optimal design solution, and in Table 3, the contents of domains such as Engineering Design are shown. 5 Relationship between CCSS and data analysis and interpretation The relationship between CCSS and Science and Engineering Practices is clearly described in Grades 6 1222. Table 4 lists these relationships to understand viewpoints for analyzing and interpreting data, in particular to focus on data analysis and interpretation in CCSS and Science and Engineering Practices23. Table 4 Relationship between CCSS and Science and Engineering Practices regarding data analysis and interpretation Supporting CCSS Literacy Anchor Standards and Relevant C o n n e c t i o n t o S c i e n c e a n d Portions of the Corresponding Standards for Science and Engineering Practice Technical Subjects CCR Reading Anchor #7: Integrate and evaluate content Scientists and engineers present presented in diverse formats and media, including visually and data in a myriad of visual formats in order to reveal meaningful patterns quantitatively, as well as in words. RST.6-8.7: Integrate quantitative or technical information and trends. Reading Standard 7 expressed in words in a text with a version of that speaks directly to the importance information expressed visually (e.g., in a flowchart, diagram, of understanding and presenting information that has been gathered model, graph, or table). RST.9-10.7: Translate quantitative or technical information in various formats to reveal patterns expressed in words in a text into visual form (e.g., a table and relationships and allow for or chart) and translate information expressed visually or deeper explanations and analyses. mathematically (e.g., in an equation) into words. RST.11-12.7:...evaluate multiple sources of information presented in diverse formats and media (e.g., quantitative data, video, multimedia) in order to address a question or solve a problem. 369
CCR Reading Anchor #9: Analyze how two or more texts S c i e n t i s t s a n d e n g i n e e r s u s e address similar themes or topics in order to build knowledge or technology to allow them to draw on multiple sources of information to compare the approaches the authors take. RST.6-8.9: Compare and contrast the information gained in order to create data sets. Reading from experiments, simulations, video, or multimedia sources Standard 9 identifies the importance with that gained from reading a text on the same topic. of analyzing multiple sources in RST.9-10.9: Compare and contrast findings presented in order to inform design decisions and a text to those from other sources (including their own create a coherent understanding of a experiments), noting when the findings support or contradict process or concept. previous explanations or accounts. RST.11-12.9: Synthesize information from a range of sources (e.g., texts, experiments, simulations) into a coherent understanding of a process, phenomenon, or concept, resolving conflicting information when possible. CCR Speaking and Listening #2: Integrate and evaluate Central to the practice of scientists information presented in diverse media and formats, including and engineers is integrating data drawn from multiple sources in visually, quantitatively, and orally. SL.8.2: Analyze the purpose of information presented in order to create a cohesive vision diverse media and formats (e.g., visually, quantitatively, of what the data means. Speaking and Listening Standard 2 addresses orally)... SL.9-10.2: Integrate multiple sources of information the importance of such synthesizing presented in diverse media or formats (e.g., visually, activities to building knowledge and quantitatively, orally) evaluating the credibility and accuracy defining and clarifying problems. This includes evaluating the of each source. SL.11-12.2:...evaluating the credibility and accuracy of each credibility and accuracy of data and source and noting any discrepancies among the data. identifying possible sources of error. CCR Speaking and Listening #5: Make strategic use of digital Presenting data for the purposes media and visual displays of data to express information and of cross- comparison is essential for identifying the best design solution enhance understanding of presentations. SL.8.5: Integrate multimedia and visual displays into or scientific explanation. Speaking presentations to clarify information, strengthen claims and and Listening Standard 5 stresses the importance of visual displays of evidence... SL.9-12.5: Make strategic use of digital media (e.g., data within presentations in order textual, graphical, audio, visual, and interactive elements) to enhance understanding of the in presentations to enhance understanding of findings, relevance of the evidence. That way others can make critical decisions reasoning, and evidence... regarding what is being claimed based on the data. [Excerpts from Next Generation Science Standards: For States, By States, Volume2: Appendixes, Washington, DC: The National Academies Press, 2013. 162] For example, in Table 4, Reading Anchor #9 as a viewpoint to interpret data, in which it is written, Compare and contrast the information gained from experiments, 370
Data Analysis and Interpretation in Physical Sciences of Next Generation Science Standards simulations, video, or multimedia sources with that gained from reading a text on the same topic, clearly emphasizes comparison and contrast. In other words, data analysis and interpretation are performed visually, and are considered processes of practice in which knowledge is created using charts, models, graphs, and tables, which show quantitative relationships, and by comparing and contrasting data obtained through experiments and information from multimedia. In addition, in Speaking and Listening anchors, data analysis and interpretation are comprehensively judged according to claims and evidence on the credibility and accuracy. On the other hand, data analysis and interpretation are concretely described using expressions such as integration, evaluation, and translation. Thus, in CCSS, data analysis and interpretation are considered from viewpoints of comparison and contrast ; comprehensive judgment based on claims and evidence with the credibility and accuracy ; and integration, evaluation, and translation. 6 Conclusion In this study, we focused on NGSS, which clearly describes viewpoints on analyzing and interpreting data, and clarified viewpoints on stepwise development of abilities for analyzing and interpreting data in Grades K-12 from kindergarten to high school. The following points have been identified: data analysis and interpretation are treated as basic skills because they are described in Grades K-2 and are supposed to be developed in a stepwise manner ; data analysis and interpretation are associated with each other and are developed in a stepwise manner ; and data analysis and interpretation are concretely written by replacing the terms with expressions such as integration, evaluation, and translation. In conclusion, although the development of abilities for interpreting data is not highlighted in the study courses for kindergarten, elementary schools, junior high schools, and high schools in Japan, the explanation of the aforementioned viewpoints and development of the abilities for analyzing and interpreting data in a stepwise manner will be necessary in Japan. 371
References, and Notes 1 Ministry of Education, Culture, Sports, Science and Technology: Courses of Study for Elementary Schools, 2008 61. 2 Ministry of Education, Culture, Sports, Science and Technology: Courses of Study for Junior High Schools, Higashiyama Shobo, 2008 57. 3 Ministry of Education, Culture, Sports, Science and Technology: Courses of Study for High Schools, Higashiyama Shobo, 2009 64. 4 Ministry of Education, Culture, Sports, Science and Technology: Commentary to the Courses of Study for Junior High Schools: Science, Dainippon Tosho, 2008 17. 5 Ministry of Education, Culture, Sports, Science and Technology: Commentary to the Courses of Study for High Schools: Science, Science and Mathematics, Dainippon Tosho, 2009 126. 6 Ministry of Education, Culture, Sports, Science and Technology: Courses of Study for Junior High Schools, Higashiyama Shobo, 2008 5. 7 Ministry of Education, Culture, Sports, Science and Technology: Courses of Study for High Schools, Higashiyama Shobo, 2009 4. 8 In Courses of Study for Elementary Schools: Science ; Commentary to the Courses of Study for Junior High Schools: Science ; and Commentary to the Courses of Study for High Schools: Science, Science and Mathematics, no viewpoints are described about stepwise development of the abilities for data analysis and interpretation. 9 Analyzing and interpreting data describes analysis and interpretation of data that have qualitative and quantitative aspects. In contrast, analysis and interpretation is an expression used in the Courses of Study for junior high schools and high schools for science, which includes analyzing and interpreting data that do not have qualitative and quantitative aspects. 10 MIYAMOTO Naoki The Skill to Understand Data of Physics Unit in a Textbook on Science for American Elementary Schools, Journal of the Physics Education Society of Japan, 61 4, 2013 181-186. 11 Next Generation Science Standards: For States, By States, Volume1: The Standards-Arranged by Disciplinary Core Ideas and by Topics, Volume2: Appendixes, Washington, DC: The National Academies Press, 2013. 12 Namio Nagasu eds. : National Science Education Standards, Azusa Syuppan, 2001, 139. 13 National Research Council: A Framework for K-12 Science Education Practices, Crosscutting Concepts, and Core Ideas, The National Academies Press, 2011. 14 Next Generation Science Standards: op. cit. 11, Volume2, 158. 372
Data Analysis and Interpretation in Physical Sciences of Next Generation Science Standards 15 Grades and groups of grades in NGSS, which are expressed as K-12, for example, correspond to grades from kindergarten to high school in Japan. 16 Next Generation Science Standards: op. cit.11, Volume2, 48. 17 Ibid. 18 Ibid. 19 Next Generation Science Standards: op. cit. 11, Volume2, 56. 20 Ministry of Education, Culture, Sports, Science and Technology: Courses of Study for Junior High Schools, Higashiyama Shobo, 2008 27. 21 Ibid., 44. 22 Next Generation Science Standards: op. cit. 11, Volume2, 158-169. 23 Ibid., 163. 373
Next Generation Science Standards の Physical Science におけるデータ分析 解釈 文学部教育学科講師 宮本 直樹 本研究では データ分析 解釈に関する指導の視点が明確に示されている米国のNext Generation Science Standardsを中心に 幼稚園から高等学校までのデータ分析 解釈する 能力育成の視点を明らかにした その結果 以下に示すことが主に明らかとなった 1 データ分析 解釈は K-2学年に記述されていることから 基礎的スキルとしての扱い があり 段階的に育成するようになっている 2 データ分析とデータ解釈を関連させ 段階的にデータ分析 解釈を育成している 3 統合 評価 変換 といった表現に置き換えて データ分析 解釈を明示している 374