ASTE 2014 CSCS & NGSS

Next Generation Science Standards (NGSS)

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Engaging Students in the Science and Engineering Practices of the Next Generation Science Standards (NGSS) with Computer Supported Collaborative Science (CSCS)

Norman Herr, Mike Rivas

Department of Secondary Education

California State University, Northridge

Abstract:

Computer Supported Collaborative Science (CSCS) is a methodology that uses collaborative cloud-based resources to engage all learners in the collection, analysis, and interpretation of individual data in the context of whole-class data. CSCS turns hands-on classroom activities into more authentic scientific experiences, engaging students in the science and engineering practices specified in Dimension-1 of the Next Generation Science Standards (NGSS). During this workshop, participants will learn how to engage students in the science and engineering practices mentioned in Dimension-1 of the NGSS using the Computer Supported Collaborative Science (CSCS) approach.

Science and Engineering Practices in the NGSS

In 2013, Achieve Inc, operating on behalf of the twenty-six states and partners, published the Next Generation Science Standards (Achieve, Inc., 2013). It is anticipated that the vast majority of states will adopt these standards. The Standards recommend that science education be built around three dimensions: (1) scientific and engineering practices, (2) cross cutting concepts that have common application across fields, and (3) core ideas in four disciplinary areas: physical sciences; life sciences; earth and space sciences; and engineering, technology, and applications of science. The Standards draws upon ideas set forth in earlier reform documents such as Project 2061 (American Association for the Advancement of Science, 1993), and the National Science Education Standards (NRC, 1996) but are destined to be more influential since most states have already adopted the Common Core Standards (National Governors Association, 2012) in mathematics and English and have expressed an intent to adopt the Next Generation Science Standards as well. The Next Generation Science Standards will provide a roadmap for reforming science education and will create a need for new teaching strategies to traverse this map. Fortunately, recent advances in collaborative cloud-based computing have provided the technological tools which allow the implementation of new teaching methodologies for engaging students in the scientific and engineering practices specified in Dimension-1 of the NGSS.

Continuous Formative Assessments (CFA) in Science Instruction

Computer Supported Collaborative Science (CSCS) is a teaching methodology that uses collaborative web-based resources to engage all learners in the collection, analysis, and interpretation of individual data in the context of whole-class data. CSCS fosters scientific inquiry by using collaborative online resources to assess prior knowledge, collect and analyze student ideas, data, and comments, and provides instructors the opportunity to perform continuous formative assessments to inform and reform their own instruction. CSCS turns hands-on classroom activities into more authentic scientific experiences -- shifting the focus from cookbook data collection to thoughtful data analysis. (d'Alessio, & Lundquist, 2013; Herr, Rivas, Chang, Tippens, Vandergon, d’Alessio, & Nguyen-Graff, 2013; Herr, Rivas, Foley, Vandergon & Simila 2013). The CSCS model engages all students in learning science and provides experience in how science is actually done. The CSCS model provides a pedagogical framework for science teachers seeking to implement the goals of the NGSS.

• Prior Knowledge and Student Engagement. Often, science lessons ignore prior knowledge and cultural influences, complicating the challenge of teaching in a diverse classroom (Brown, 2004). CSCS uses online surveys to assess students’ initial understanding of new topics. This allows teachers to learn about preconceptions to be addressed and helps students to become aware of their naïve conceptions. Students remain engaged when they are regularly asked to commit responses to formative assessment. (Herr et.al, 2012)

• Collecting large data sets. In traditional classes, lab groups collect data independent from other lab teams. By combining data sets online, students recognize patterns that are only visible when students pool their data. Students compute averages, plot data together and gain firsthand experience for what it means for an experiment to be repeatable.

• Focusing on interpretation. In verification labs, experiments stop once data are collected because the results are known before they start. In CSCS, students post collaborative lab reports online linking to relevant data and graphs. Shared conclusions allow for further discussion and the consensus building that is essential for inquiry (Berland & Reiser, 2009). Automated graphing of data using CSCS tools can reduce the load on working memory, allowing for more cognitive resources to be devoted to data analysis (Hmelo-Silver, Duncan, & Chinn, 2007).

Focus and Value for ASTE Members

The National Research Council has stated that current science education in the United States “does not provide students with engaging opportunities to experience how science is actually done.” (NRC, 2012). The CSCS model, employing new collaborative web-based document technology, provides students and teachers the opportunity to readily collect and analyze large sets of data from multiple lab groups and class sections. Such resources may be used to create an environment that more closely resembles the collaborative environment of a professional scientific research community in which researchers develop hypothesis and explanations in light of their own findings and those of their colleagues. The CSCS Model emphasizes scientific inquiry in an evidence-rich, collaborative environment that places greater emphases on interpretation, evaluation, and explanation. The CSCS model replaces traditional “cookbook” verification activities in which students work in isolated lab groups, with discovery activities using student-generated procedures working in collaboration with multiple lab groups. The CSCS model provides an opportunity for students to experience how science is actually done by engaging in the scientific and engineering practices advocated in Dimension 1 of the NGSS, namely (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.

Workshop Activities

During this workshop, participants will learn how to engage students in the science and engineering practices mentioned in Dimension-1 of the NGSS using the Computer Supported Collaborative Science (CSCS) approach. Participants will gain experience developing resources that they can use to help their own students master these skills. We will conclude by having participants brainstorm additional ways the CSCS model can be used to help teachers improve student mastery of the Dimension-1 skills of NGSS.

Expertise of workshop presenters - The CSCS team at CSUN consists of faculty from the departments of secondary education, physics, geology, biology, and chemistry, as well as secondary school science teachers. We have developed a series of online activities that are used in CSCS workshops, credential and masters courses, undergraduate science classes, and secondary school science classrooms. Each member of this workshop team has been involved in developing and refining this model. This model is presently being used in the science teacher preparation program at CSUN, one of the largest producers of science teachers in the nation, and is the subject of research studies by university faculty and graduate students. (Herr et. al, 2011a, 2011b, 2010a, 2010b, 2010c)

References

American Association for the Advancement of Science. (1993). Benchmarks for Science Literacy. Project 2061. New York: Oxford University Press.

American Association for the Advancement of Science. (2007). Atlas of Science Literacy, Volumes 1 and 2. Project 2061. Washington, DC: Author.

Bransford, D., Brown, E., and Cocking, R. (eds.) (1999). How People Learn: Brain, Mind, Experience, and School. Committee on Developments in the Science of Learning, National Research Council. Washington, D.C.: National Academy Press

d'Alessio, Matthew, and Loraine Lundquist (2013). Computer Supported Collaborative Rocketry: Teaching students to distinguish good and bad data like an expert physicist. The Physics Teacher

Herr, N.; Rivas, M..; Chang, T.; Tippens, M.; Vandergon, V.; d’Alessio, M.; Nguyen-Graff, D. (2013). Continuous formative assessment (CFA) during blended and online instruction using cloud-based collaborative documents. In Koç, S; Wachira, P.; Liu, X. Assessment in Online and Blended Learning Environments. Chapter submitted for publication.

Herr, Foley, Rivas, d'Alessio, Vandergon, Simila, Nguyen-Graff, Postma (2012). Employing Collaborative Online Documents for Continuous Formative Assessments. Proceedings of the Society for Information Technology and Teacher Education (SITE). Austin, TX. March 5-9.

Herr, Norman, Mike Rivas, Brian Foley, Virginia Vandergon,and Gerry Simila (2011) Using Collaborative Web-based documents to Instantly Collect and Analyze Whole Class Data. Proceedings of the 9th Annual Hawaii International Conference on Education, January 3-7, Honolulu, Hawaii.

Herr, Norman, Mike Rivas, Brian Foley, Virginia Vandergon, Gerry Simil, Matthew d'Alessio, and Henk Potsma (2011) Computer Supported Collaborative Education - Strategies for Using Collaborative Web-Based Technologies to Engage All Learners. Proceedings of the 9th Annual Hawaii International Conference on Education, January 3-7, Honolulu, Hawaii.

Herr, Norman and Mike Rivas (2010). Teaching the Nature of Scientific Research by Collecting and Analyzing Whole-Class Data Using Collaborative Web-Based Documents. Proceedings of the Association for the Advancement of Computing in Education, October 18-22, 2010, Orlando, Florida.

National Governors Association Center for Best Practices, Council of Chief State School Officers (2010). Common Core State Standards. Washington D.C. National Governors Association Center for Best Practices, Council of Chief State School Officers,

National Research Council. (1996). National Science Education Standards. National Committee for Science Education Standards and Assessment. Washington, DC: National Academy Press.

National Research Council. (2012). A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas. Committee on a Conceptual Framework for New K-12 Science Education Standards. Board on Science Education, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

Achieve, Inc. (2013) Next Generation Science Standards. Achieve, Inc. on behalf of the twenty-six states and partners that collaborated on the NGSS

Program abstract

Proceedings Abstract

The CSCS Model emphasizes scientific inquiry in an evidence-rich, collaborative environment that places greater emphases on interpretation, evaluation, and explanation. The CSCS model replaces traditional “cookbook” verification activities in which students work in isolated lab groups, with discovery activities using student-generated procedures working in collaboration with multiple lab groups. The CSCS model provides an opportunity for students to experience how science is actually done by engaging in the scientific and engineering practices advocated in Dimension 1 of the NGSS, namely (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.

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