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Philip Morris Records; newspaper article; extr, extra

"Super Scientist" Glen Beitmen, former Edison Winter Estates Wild Wizard, joins us to talk about why you should bring the whole family to STEMtastic on February 8th and he shows us a few science experiments that are cheap, easy, and fun! Audio only: https://soundcloud.com/leeschools/ep-41-glen-beitmen-on-making-science-fun

Dartford Grammar School is a selective academy and an International Baccalaureate World School with a strong, central international ethos. All 797 students in Key Stages 3 and 4 study two foreign languages up to GCSE level (including Chinese or Japanese) and all 537 students in the sixth form study at least one foreign language. To ensure a complete "learner journey" for the students, from Year 7 to Year 13 and beyond, and to help give purpose to their language learning, the school recognises the importance of providing international and expert careers advice. We have a range of initiatives to enable this to be achieved, but the main focus to provide key information to students, and to introduce them to the possible opportunities available in the future, is through our annual International Languages and Science Careers Fair. A short list of references and links is included. [For the complete volume, "Employability for Languages: A Handbook," see ED566902.]

Dartford Grammar School is a selective academy and an International Baccalaureate World School with a strong, central international ethos. All 797 students in Key Stages 3 and 4 study two foreign languages up to GCSE level (including Chinese or Japanese) and all 537 students in the sixth form study at least one foreign language. To ensure a complete "learner journey" for the students, from Year 7 to Year 13 and beyond, and to help give purpose to their language learning, the school recognises the importance of providing international and expert careers advice. We have a range of initiatives to enable this to be achieved, but the main focus to provide key information to students, and to introduce them to the possible opportunities available in the future, is through our annual International Languages and Science Careers Fair. A short list of references and links is included. [For the complete volume, "Employability for Languages: A Handbook," see ED566902.]

This paper deals with the organization of two important areas which interact strongly: information science and decision-making. Both are commonly and extensively used in a variety of ways and share an equally commonly and extensively used variety of definitions. This paper deals with the mutual interaction between information science and decision-making. In order to organize or to relate these two fields to each other, a number of important criteria must be considered. For example, the organization or interrelationship should have generality, applicability, utility, reality, and the potential for quantification. A generalized information system which satisfies all of these criteria is defined in detail. It consists of four interconnected components: an information source which acquires and disseminates information (IAD), a decision-maker which accepts the information from the source and disseminates courses of action on execution function which takes the courses of action and converts them into observables (the resultant of the courses or plan of action), and a transformation function which accepts the observables and transforms them into data which are fed to the IAD. (Author)

Originally introduced in several policy documents issued by different institutions belonging to the European Union (EU), the term responsible research and innovation (hereafter RRI) has gained considerable attention in recent years among researchers coming from different backgrounds and disciplines. RRI constitutes an attempt to articulate a theoretical framework that would shape the governance of science in Europe. While science education is mentioned in various EU policy documents as one of its strategic dimensions, the way in which RRI can actually be translated into science education is a topic that needs empirical investigation as well as theoretical elaboration. The overall aim of the paper is precisely to offer that. In the present article, we posit that RRI in science education can be experienced meaningfully by linking it to inquiry-based learning, which already stresses the importance of active participation as well as students' responsibility for discovering knowledge. To see this potential connection in practice, we conducted an ethnographic study involving seven Estonian science teachers, who agreed to be observed at least 3 times when they conducted inquiry-based learning lessons in their school. Specifically, the study aimed at acquiring a better understanding as to the meaning that the term responsibility can have during the different phases of inquiry-based lessons. The results of the ethnographic study allow us to come to the conclusion that RRI can be interpreted in science education as a type of meaningful engagement in and for an inquiry during which the students are given the opportunity to make meaningful decisions in the different inquiry phases and thus be able to take responsibility for the inquiry process.

This issue brief discusses how data science has emerged as a tool across all industries, resulting in a high demand for data-science experts and data analytics-enabled workers.

This issue brief discusses how data science has emerged as a tool across all industries, resulting in a high demand for data-science experts and data analytics-enabled workers.

This issue brief discusses how data science has emerged as a tool across all industries, resulting in a high demand for data-science experts and data analytics-enabled workers.

This issue brief discusses how data science has emerged as a tool across all industries, resulting in a high demand for data-science experts and data analytics-enabled workers.

This issue brief discusses how data science has emerged as a tool across all industries, resulting in a high demand for data-science experts and data analytics-enabled workers.

162 p. : 23 cm

MAKING SCIENCE CHILD'S PLAY, HINDU 29.03.2017, ARTICLE ON ARVIND GUPTA, AKILA KANNADASAN

Political Darwinism explains why Leftists are making themselves extinct. NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we’re helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️Sign Up For Our Newsletter: https://www.naturalnews.com/Readerreg... ▶️Soundcloud: https://soundcloud.com/healthranger ▶️Download our app: https://www.naturalnews.com/App 🔴Bitchute: https://www.bitchute.com/channel/natu... 🔴 Steemit: https://steemit.com/@healthranger 🔴Gab: https://gab.ai/NaturalNews 🔴Twitter: http://www.twitter.com/healthranger 🔴 Facebook: https://www.facebook.com/HealthRanger 🔴 Mewe: https://mewe.com/i/health.ranger 🔴Pinterest: https://www.pinterest.com/naturalnews/ 🔴Diaspora: https://share.naturalnews.com/

In our everyday lives we are surrounded by advertising in its various forms. Thus in the school context it is not surprising that the issue of advertising is addressed by different subjects, with the main foci being advertising-specific language, images and illustrations, use of stereotypes, strategies of persuasion, etc. But advertising also contains factual information, being explicit or implicit, to make a campaign more credible and underline the effectiveness of a certain product. Dealing with the use of factual information in advertising critically is important for the consumer. For many products this information is derived from science and technology. Understanding the science in and behind advertising is necessary to become a critical consumer. Learning about the use of science in advertising also allows promoting societal-oriented communication and decision making skills in the science classroom. Unfortunately, only a few examples on the use of advertising in the science classroom exist. This paper provides a justification for the use of advertising in science education. Examples from the classroom developed in the framework of the PROFILES-project are provided by way of illustration.

Materi Integrasi Islam dan Sains

Materi Integrasi Islam dan Sains

We have developed a parallel data analysis algorithm for peptide classification, which is used for microbial identification. This algorithm was based on data generated from the commercially available algorithms SEQUEST and OMSSA. The outputs from those algorithms were analyzed to determine a probability score for the identified peptides and their associated proteins. The statistical analyses and data interpretation using our proposed approach showed that we can lower the false-discovery rate by using common proteins from both algorithms. This approach showed that the identification accuracy and reliable classification of microbes were improved without increasing the data analysis time. In summary, we have a higher confidence in the identification process and a reduced bottleneck in data analysis through the use of the new algorithm.

We have developed a parallel data analysis algorithm for peptide classification, which is used for microbial identification. This algorithm was based on data generated from the commercially available algorithms SEQUEST and OMSSA. The outputs from those algorithms were analyzed to determine a probability score for the identified peptides and their associated proteins. The statistical analyses and data interpretation using our proposed approach showed that we can lower the false-discovery rate by using common proteins from both algorithms. This approach showed that the identification accuracy and reliable classification of microbes were improved without increasing the data analysis time. In summary, we have a higher confidence in the identification process and a reduced bottleneck in data analysis through the use of the new algorithm.

We have developed a parallel data analysis algorithm for peptide classification, which is used for microbial identification. This algorithm was based on data generated from the commercially available algorithms SEQUEST and OMSSA. The outputs from those algorithms were analyzed to determine a probability score for the identified peptides and their associated proteins. The statistical analyses and data interpretation using our proposed approach showed that we can lower the false-discovery rate by using common proteins from both algorithms. This approach showed that the identification accuracy and reliable classification of microbes were improved without increasing the data analysis time. In summary, we have a higher confidence in the identification process and a reduced bottleneck in data analysis through the use of the new algorithm.

We have developed a parallel data analysis algorithm for peptide classification, which is used for microbial identification. This algorithm was based on data generated from the commercially available algorithms SEQUEST and OMSSA. The outputs from those algorithms were analyzed to determine a probability score for the identified peptides and their associated proteins. The statistical analyses and data interpretation using our proposed approach showed that we can lower the false-discovery rate by using common proteins from both algorithms. This approach showed that the identification accuracy and reliable classification of microbes were improved without increasing the data analysis time. In summary, we have a higher confidence in the identification process and a reduced bottleneck in data analysis through the use of the new algorithm.

We have developed a parallel data analysis algorithm for peptide classification, which is used for microbial identification. This algorithm was based on data generated from the commercially available algorithms SEQUEST and OMSSA. The outputs from those algorithms were analyzed to determine a probability score for the identified peptides and their associated proteins. The statistical analyses and data interpretation using our proposed approach showed that we can lower the false-discovery rate by using common proteins from both algorithms. This approach showed that the identification accuracy and reliable classification of microbes were improved without increasing the data analysis time. In summary, we have a higher confidence in the identification process and a reduced bottleneck in data analysis through the use of the new algorithm.

#OnThisDay 1984: "Creating a monster like a Tripod involves an awful lot of television trickery." Sarah Greene chatted to Mike Ellis of the BBC Special Effects department, about making the challenging science fiction series, The Tripods. https://t.co/6md8EGja6m Source: https://twitter.com/BBCArchive/status/1174001819065806848 Uploader: BBC Archive

Pt. 2 dated 1845

Pt. 2 dated 1845

Pt. 2 dated 1845

Donald F. and Mildred Topp Othmer Library of Chemical History, Othmer MS 1. Bergamo?, Milan?, Pavia?, Como?, Northwestern Italy, Probably before 22 December 1438. This manuscript contains a recipe collection with more than 520 different recipes on topics ranging from alchemy and medicine to solutions for simple household problems such as fleas, with an extensive alphabetical index.

These appendices accompany the report "Final Report of the i3 Impact Study of Making Sense of SCIENCE, 2016-17 through 2017-18." Science education has experienced a significant transition over the last decade, catalyzed by a re-envisioning of what students should know and be able to do in science. That re-envisioning culminated in the release of the Next Generation Science Standards (NGSS) in 2013. The new standards set off a chain reaction of standards adoption and implementation across states, districts, and schools, including steps taken toward transforming science professional learning, instruction, curriculum, and assessment. It was in this dynamic context that Empirical Education conducted an impact evaluation, as part of an Investing in Innovation (i3) grant, of WestEd's Making Sense of SCIENCE project, a teacher professional learning model aimed at raising students' science achievement through improving science instruction. Under this grant, WestEd and Empirical Education also partnered with Heller Research Associates (HRA) to conduct an implementation study and a scale-up study of Making Sense of SCIENCE. The impact evaluation, which is the focus of this report, was a two-year cluster-randomized control trial (RCT) that took place in California and Wisconsin across seven school districts and 66 elementary schools in the 2016-17 and 2017-18 school years. The study randomized schools to either receive the Making Sense of SCIENCE professional learning or to the business-as-usual ("control") group, which received the professional learning (delayed-treatment) after the study ended. The study found that Making Sense of SCIENCE had a positive impact on teacher content knowledge (effect size = 0.56, p = .006) and a positive impact on a holistic scale of teacher pedagogical content knowledge (effect size = 0.41, p = 0.026). The study also yielded positive and significant impacts on the amount of time teachers spent on science instruction (effect size = 0.40, p = 0.015) and on the emphasis that teachers placed on NGSS-aligned instructional practices, with statistically significant effect sizes ranging from 0.40 to 0.49 standard deviations. This suggestive evidence that Making Sense of SCIENCE changes classroom science learning experiences in ways that align with expectations in NGSS, which is a hypothesized precursor to measuring impacts on student achievement, deserves notice. In regard to student science achievement, the study did not find statistically significant results for the full sample of students (effect size = 0.06, p = 0.494), or for the sample of students in the bottom third of incoming math and English Language Arts achievement, with effect sizes of 0.22 standard deviations (p = 0.099) and 0.073 standard deviations (p = 0.567), respectively. Notably, with the exception of one negative effect size, additional analyses on student achievement using different measures and samples yielded positive, but not statistically significant, effect sizes ranging from 0.02 to 0.12 standard deviations. Evaluators offer three potential contributors to the findings of limited impact on student science achievement. First, given the timing of the study in relation to the release of the NGSS in 2013, finding a suitable NGSS-aligned student science assessment was a challenge. Second, most study schools and districts had not yet adopted NGSS-aligned curricula and did not have access to NGSS-aligned curriculum resources. Third, the sample of teachers was unstable across the two years, with the percentage of teachers leaving the school congruous to the percentage observed at the national level. [For the full report, see ED609253; for the research summary, see ED609256.]

Seventeen scholarly papers and twelve abstracts comprise the content of the twentieth annual Brick & Click Libraries Conference, held annually at Northwest Missouri State University in Maryville, Missouri. The twentieth Brick & Click Libraries Conference was held virtually. The proceedings, authored by academic librarians and presented at the conference, portray the contemporary and future face of librarianship. The 2020 paper and abstract titles include: (1) From the Wild West to Teamwork: Faculty Driven Acquisitions (Randyn Heisserer-Miller, Stephanie Hallam, and Brad Reel); (2) Student Engagement: Exploring Primary Sources in the Library of Congress in an Online Course (Peggy Ridlen); (3) Object Oriented vs Functional Programming - Library Instruction in a Bite-Sized Functional Model (Billy Moore); (4) When People Count: Leveraging Internal Resources to Develop a Program for Tracking Building Usage (Terra Feick); (5) Interactive Introductions for International Students: Reworking How We Teach Information Literacy Skills (Kelly Hovinga); (6) Fostering Success for New Faculty Librarians (Karen Bleier); (7) We Did It, You Can Do It, Too: In-House Digital Preservation (Samantha Henning); (8) Stacking it Up: A Textbooks on Reserve Program (Katharine Baldwin and Jenise Overmier); (9) Teaching into the Gray Areas: Designing Learning Activities That Encourage Higher Order Thinking and Research Skills (Virginia L. Cairns); (10) Building a Teaching Strategy Toolkit to Engage Learners (Courtney Mlinar); (11) Cracking the Code: Building an Assessment Plan with Student Discussion Boards (Anthony Rodgers and Courtney Strimel); (12) Making the Most of LibApps (Kayla Reed); (13) Neither Rain, Nor Sleet, Nor Gloom of Night: Maintaining Library Services During a Medical State of Emergency (Rob Withers); (14) Psychological Safety and Building Effective Teams (Kara Whatley, Deborah Caesar, Amanda Watson, and Molly Nystrom); (15) Summer in the Stacks: A Weeding Experience Between Faculty and Library (Kayla Reed and Hong Li); (16) Puppies and Kitties Oh My!: Partnering with a Local PETPALS Organization (Leila June Rod-Welch and Jordan A. Newburg); (17) Unlocking Online Escape Rooms for Library Instruction (Sean Cordes); (18) Spectral Tales: Lessons Learned from Being Ghosted by Faculty (Tammi M. Owens, Meghan Salsbury, and Heidi Blackburn); (19) The Librarian's Guide to Zines for Classroom and Community (Claire Du Laney, Monica Maher, and Amy C. Schindler); (20) Professionalizing Student Employment: The Library Associates Program at Hendrix College (Janice Weddle); (21) Making It Easy to Read Harder: Implementing a Reading Challenge at Community College (Amy Fortner, Anthony Rodgers, and Gwen Wolfe); (22) Beyond the Humanities: Archives Instruction for Science and Medicine (Laurinda Weisse); (23) Library Collaboration with the Smithsonian: World War I Lessons and Legacies Exhibit (Leila June Rod-Welch and Julie Ann Beddow); (24) The Genesis of a Conduct Policy in a Medium-Sized Academic Library (John Baken); (25) Universal Design and Accessibility: A Checklist for LibGuides and Online Tutorials (Courtney Mlinar); (26) Anti-vaxxers, Sasquatch DNA and Other "Scientific" Findings: Actively Engaging Distance Students in Media Literacy (Joanna Nemeth); (27) All Good Things Must Come to an End: When Library Staff Pass Away (Rob Withers); (28) If "They" Build it, "They" Will Come (Martha Allen); and (29) Save the Earth - Earth Day Game Drive: Small Steps, Big Impact (Leila June Rod-Welch). [For the 2019 proceedings, see ED600185.]

Text classification has allowed researchers to analyze natural language data at a previously impossible scale. However, a text classifier is only as valid as the the annotations on which it was trained. Further, the cost of training a classifier depends on annotators' ability to quickly and accurately apply the coding scheme to each text. Thus, researchers need guidance on how to generate training data with optimal efficiency and accuracy. To this end, this study proposes the single-case study design as a feasible and causally-valid research design for empirical decision-making in annotation projects. The key strength of the design is its ability to generate causal evidence with as few as one annotator. In this paper, we demonstrate the application of the single-case study in an applied experiment and argue that future researchers should incorporate the design into the pilot stage of annotation projects so that, over time, a causally-valid body of knowledge regarding the best annotation techniques is built. [This paper will be published in the "Journal of Data Science." The published article is titled: "Improving the Science of Annotation for Natural Language Processing: The Use of the Single-Case Study for Piloting Annotation Projects"]

This guide outlines the initial work and includes recommendations for schools and districts on how to implement an integrated science program. Chapters include: (1) "What Is Integrated Science and What Does It Look Like at the High School Level?"; (2) "Coherence in High School Science" (F. James Rutherford); (3) "Thinking about Change: What Will It Take to Implement an Integrated Science Program?"; (4) "Supporting Change through Professional Development" (Rodger W. Bybee and Susan Loucks-Horsley); (5) "How Do We Assess Learning in Integrated Science?" (Kathy Comfort); (6) "Thinking about Implementation: The Road Ahead"; (7) "How Have Others Done It?"; (8) "California Scenario" (Marilyn Perron); (9) "Utah Scenario" (Sue Faibisch); and (10) "Florida Scenario" (Ginger Davis and Raul Montes). Appendices include: (1) "Using the Concerns-Based Adoption Model When Implementing Integrated Science Programs"; (2) "A Short Cut for Model IV"; (3) "A Needs Assessment for Integrated Science"; (4) "Next Step Questions to Consider Before Making a Decision"; (5) "The Integrated Science Program at Your School: Guidelines for Writers"; (6) "Frequently Asked Questions about Integrated Science at the High School Level"; (7) "List of Curriculum Materials for Integrated Science and Survey Results." (Contains 50 references.) (YDS)

This guide outlines the initial work and includes recommendations for schools and districts on how to implement an integrated science program. Chapters include: (1) "What Is Integrated Science and What Does It Look Like at the High School Level?"; (2) "Coherence in High School Science" (F. James Rutherford); (3) "Thinking about Change: What Will It Take to Implement an Integrated Science Program?"; (4) "Supporting Change through Professional Development" (Rodger W. Bybee and Susan Loucks-Horsley); (5) "How Do We Assess Learning in Integrated Science?" (Kathy Comfort); (6) "Thinking about Implementation: The Road Ahead"; (7) "How Have Others Done It?"; (8) "California Scenario" (Marilyn Perron); (9) "Utah Scenario" (Sue Faibisch); and (10) "Florida Scenario" (Ginger Davis and Raul Montes). Appendices include: (1) "Using the Concerns-Based Adoption Model When Implementing Integrated Science Programs"; (2) "A Short Cut for Model IV"; (3) "A Needs Assessment for Integrated Science"; (4) "Next Step Questions to Consider Before Making a Decision"; (5) "The Integrated Science Program at Your School: Guidelines for Writers"; (6) "Frequently Asked Questions about Integrated Science at the High School Level"; (7) "List of Curriculum Materials for Integrated Science and Survey Results." (Contains 50 references.) (YDS)

This guide outlines the initial work and includes recommendations for schools and districts on how to implement an integrated science program. Chapters include: (1) "What Is Integrated Science and What Does It Look Like at the High School Level?"; (2) "Coherence in High School Science" (F. James Rutherford); (3) "Thinking about Change: What Will It Take to Implement an Integrated Science Program?"; (4) "Supporting Change through Professional Development" (Rodger W. Bybee and Susan Loucks-Horsley); (5) "How Do We Assess Learning in Integrated Science?" (Kathy Comfort); (6) "Thinking about Implementation: The Road Ahead"; (7) "How Have Others Done It?"; (8) "California Scenario" (Marilyn Perron); (9) "Utah Scenario" (Sue Faibisch); and (10) "Florida Scenario" (Ginger Davis and Raul Montes). Appendices include: (1) "Using the Concerns-Based Adoption Model When Implementing Integrated Science Programs"; (2) "A Short Cut for Model IV"; (3) "A Needs Assessment for Integrated Science"; (4) "Next Step Questions to Consider Before Making a Decision"; (5) "The Integrated Science Program at Your School: Guidelines for Writers"; (6) "Frequently Asked Questions about Integrated Science at the High School Level"; (7) "List of Curriculum Materials for Integrated Science and Survey Results." (Contains 50 references.) (YDS)

This guide outlines the initial work and includes recommendations for schools and districts on how to implement an integrated science program. Chapters include: (1) "What Is Integrated Science and What Does It Look Like at the High School Level?"; (2) "Coherence in High School Science" (F. James Rutherford); (3) "Thinking about Change: What Will It Take to Implement an Integrated Science Program?"; (4) "Supporting Change through Professional Development" (Rodger W. Bybee and Susan Loucks-Horsley); (5) "How Do We Assess Learning in Integrated Science?" (Kathy Comfort); (6) "Thinking about Implementation: The Road Ahead"; (7) "How Have Others Done It?"; (8) "California Scenario" (Marilyn Perron); (9) "Utah Scenario" (Sue Faibisch); and (10) "Florida Scenario" (Ginger Davis and Raul Montes). Appendices include: (1) "Using the Concerns-Based Adoption Model When Implementing Integrated Science Programs"; (2) "A Short Cut for Model IV"; (3) "A Needs Assessment for Integrated Science"; (4) "Next Step Questions to Consider Before Making a Decision"; (5) "The Integrated Science Program at Your School: Guidelines for Writers"; (6) "Frequently Asked Questions about Integrated Science at the High School Level"; (7) "List of Curriculum Materials for Integrated Science and Survey Results." (Contains 50 references.) (YDS)

'Data Data everywhere but nor anytime to think' is a possible mantra for the problems of scientific data overload. The CombeChem Project (http://www.combechem.org) takes a holistic approach to the undertaking of scientific laboratory research with a view to improve the quality, accessibility and re-use of chemical information. The project is investigating the use of e-Science technologies based on the idea of Publication @ Source. It is the researchers responsibility to collect the scientific data with the fullest possible context at the start and then ensure that none of the material is lost as the data is processed, refined, analyzed and disseminated. I will illustrate how the e-Science ideas such as the 'Semantic Web and Grid, Web 2.0, can be applied to the use of tablet PCs as electronic laboratory notebooks, laboratory blogs, enhancing remote monitoring & control of smart laboratories, and repository based dissemination of chemical data. I will highlight areas where improved transport of information between commonly used software would make a huge difference to the efficiency of scientific data handling and the useful dissemination and discussion of this information. ©2007 Microsoft Corporation. All rights reserved.

This study evaluated an approach to professional development for middle school science teachers by closely examining one grade 8 course that embodies that approach. Using a cluster-randomized experimental design, the study tested the effectiveness of the Making Sense of SCIENCE[TM] professional development course on force and motion (Daehler, Shinohara, and Folsom 2011) by comparing outcomes for students of teachers who took the course with outcomes for students of control group of teachers who received only the typical professional development offered in their schools and districts. The study estimated impacts on student science achievement for all grade 8 students in the study sample as well as for the subsample of English language learners. It also estimated impacts on teacher science and pedagogical knowledge. Results for the primary confirmatory analyses indicate that after adjusting for multiple comparisons, there were no statistically significant differences between the test results on science content of students in intervention group classrooms and students in control group classrooms. Intervention group students in neither the full sample (effect size = 0.11) nor the English language learner subsample (effect size = 0.31) scored significantly higher on the ATLAST Test of Force and Motion than did their control group counterparts. Similarly, intervention group students in neither the full sample (effect size = 0.03) nor the English language learner subsample (effect size =0 .09) scored higher on the physical science reporting clusters of the California Standards Test than did their control group counterparts. Results for the intermediate confirmatory analyses indicate that after adjusting for multiple comparisons, teachers who received the professional development course outscored their control group counterparts on the ATLAST Test of Force and Motion for Teachers (effect size = 0.38), as well as on their ratings of confidence in their ability to teach force and motion (effect size = 0.49). With one exception, the study findings were not sensitive to variations in specification of the estimation models. The exception is that, for teacher content knowledge, inclusion of the pretest in the impact analysis model (basic model plus pretest) decreased the point estimate from 9.8 to 6.1 and the effect size from 0.61 to 0.38. In exploratory analyses, the study investigated whether there were differential impacts on student and teacher content knowledge outcomes across the six research sites. The estimated impacts were most pronounced at two of the six sites. For the full sample of students, point estimates for student and teacher content knowledge of force and motion followed exactly the same rank order at all sites. There are three main limitations of this study. First, there was high sample attrition: 48 of the 181 teachers who were randomly assigned to intervention and control groups left the study before data collection was completed. However, there is no evidence that attrition resulted in significant differences at the baseline between the intervention and control samples used in the analysis. Second, the study did not include analyses of classroom implementation of course-related practices. As a result it is not possible to infer whether the lack of student effects is due to a failure of treatment group teachers to modify classroom practices or a failure of modified practices to affect student outcomes. Third, the findings are based on volunteer teachers and students whose parents provided consent. It is possible that the findings would have been different had teachers been required to participate in the intervention, and all students been tested. Appended are: (1) Study power estimates; (2) Procedure for assigning blocks for recruited sample and final analytic sample; (3) Teacher agreement to protect the study; (4) Teacher survey responses related to contamination across groups; (5) Parent consent form; (6) California content standards in physical science reporting clusters; (7) Student data obtained from district administrative records; (8) Survey items used to measure teacher confidence; (9) Course session video recording protocol; (10) Course session attendance sheet; (11) Student test administration instructions for proctors; (12) Teacher test administration instructions for site coordinators; (13) Baseline equivalence of teacher demographics in intervention and control group samples; (14) Class selection worksheet; (15) Sensitivity analysis for nesting of students within teachers or classes within teachers; (16) Impact estimation methods; (17) Missing item--level data; (18) Schedule and content goals of Making Sense of SCIENCE[TM] professional development course on force and motion; and (19) Sensitivity analyses based on different models and analytic samples. (Contains 51 tables, 4 figures and 8 footnotes.)

It is typically expected that when people work together, they can often accomplish goals that are difficult or even impossible for individuals. We consider this notion of the group achieving more than the sum of all individuals’ achievements to be the synergic effect (the whole greater than the sum of all) in collaboration. Similar expectation exists for people working in collaboration for information seeking tasks. We, however, lack a methodology and appropriate evaluation metrics for studying and measuring the synergic effect. In this talk I will present details from a large-scale lab study we did to understand the productivity of collaborators in different situations. I will discuss several traditional and novel approaches to evaluate such productivity, and show how certain conditions provide (or lack of) support for optimizing the outcome of collaboration in an information seeking project. While these conditions are primarily based on location and communication channels, I will also brush upon asynchronous vs. synchronous collaboration based on our experiments. As a part of this talk, I will also demo our collaborative system, called Coagmento. ©2011 Microsoft Corporation. All rights reserved.

It is typically expected that when people work together, they can often accomplish goals that are difficult or even impossible for individuals. We consider this notion of the group achieving more than the sum of all individuals’ achievements to be the synergic effect (the whole greater than the sum of all) in collaboration. Similar expectation exists for people working in collaboration for information seeking tasks. We, however, lack a methodology and appropriate evaluation metrics for studying and measuring the synergic effect. In this talk I will present details from a large-scale lab study we did to understand the productivity of collaborators in different situations. I will discuss several traditional and novel approaches to evaluate such productivity, and show how certain conditions provide (or lack of) support for optimizing the outcome of collaboration in an information seeking project. While these conditions are primarily based on location and communication channels, I will also brush upon asynchronous vs. synchronous collaboration based on our experiments. As a part of this talk, I will also demo our collaborative system, called Coagmento. ©2011 Microsoft Corporation. All rights reserved.

It is typically expected that when people work together, they can often accomplish goals that are difficult or even impossible for individuals. We consider this notion of the group achieving more than the sum of all individuals’ achievements to be the synergic effect (the whole greater than the sum of all) in collaboration. Similar expectation exists for people working in collaboration for information seeking tasks. We, however, lack a methodology and appropriate evaluation metrics for studying and measuring the synergic effect. In this talk I will present details from a large-scale lab study we did to understand the productivity of collaborators in different situations. I will discuss several traditional and novel approaches to evaluate such productivity, and show how certain conditions provide (or lack of) support for optimizing the outcome of collaboration in an information seeking project. While these conditions are primarily based on location and communication channels, I will also brush upon asynchronous vs. synchronous collaboration based on our experiments. As a part of this talk, I will also demo our collaborative system, called Coagmento. ©2011 Microsoft Corporation. All rights reserved.

It is typically expected that when people work together, they can often accomplish goals that are difficult or even impossible for individuals. We consider this notion of the group achieving more than the sum of all individuals’ achievements to be the synergic effect (the whole greater than the sum of all) in collaboration. Similar expectation exists for people working in collaboration for information seeking tasks. We, however, lack a methodology and appropriate evaluation metrics for studying and measuring the synergic effect. In this talk I will present details from a large-scale lab study we did to understand the productivity of collaborators in different situations. I will discuss several traditional and novel approaches to evaluate such productivity, and show how certain conditions provide (or lack of) support for optimizing the outcome of collaboration in an information seeking project. While these conditions are primarily based on location and communication channels, I will also brush upon asynchronous vs. synchronous collaboration based on our experiments. As a part of this talk, I will also demo our collaborative system, called Coagmento. ©2011 Microsoft Corporation. All rights reserved.

It is typically expected that when people work together, they can often accomplish goals that are difficult or even impossible for individuals. We consider this notion of the group achieving more than the sum of all individuals’ achievements to be the synergic effect (the whole greater than the sum of all) in collaboration. Similar expectation exists for people working in collaboration for information seeking tasks. We, however, lack a methodology and appropriate evaluation metrics for studying and measuring the synergic effect. In this talk I will present details from a large-scale lab study we did to understand the productivity of collaborators in different situations. I will discuss several traditional and novel approaches to evaluate such productivity, and show how certain conditions provide (or lack of) support for optimizing the outcome of collaboration in an information seeking project. While these conditions are primarily based on location and communication channels, I will also brush upon asynchronous vs. synchronous collaboration based on our experiments. As a part of this talk, I will also demo our collaborative system, called Coagmento. ©2011 Microsoft Corporation. All rights reserved.

It is typically expected that when people work together, they can often accomplish goals that are difficult or even impossible for individuals. We consider this notion of the group achieving more than the sum of all individuals’ achievements to be the synergic effect (the whole greater than the sum of all) in collaboration. Similar expectation exists for people working in collaboration for information seeking tasks. We, however, lack a methodology and appropriate evaluation metrics for studying and measuring the synergic effect. In this talk I will present details from a large-scale lab study we did to understand the productivity of collaborators in different situations. I will discuss several traditional and novel approaches to evaluate such productivity, and show how certain conditions provide (or lack of) support for optimizing the outcome of collaboration in an information seeking project. While these conditions are primarily based on location and communication channels, I will also brush upon asynchronous vs. synchronous collaboration based on our experiments. As a part of this talk, I will also demo our collaborative system, called Coagmento. ©2011 Microsoft Corporation. All rights reserved.

It is typically expected that when people work together, they can often accomplish goals that are difficult or even impossible for individuals. We consider this notion of the group achieving more than the sum of all individuals’ achievements to be the synergic effect (the whole greater than the sum of all) in collaboration. Similar expectation exists for people working in collaboration for information seeking tasks. We, however, lack a methodology and appropriate evaluation metrics for studying and measuring the synergic effect. In this talk I will present details from a large-scale lab study we did to understand the productivity of collaborators in different situations. I will discuss several traditional and novel approaches to evaluate such productivity, and show how certain conditions provide (or lack of) support for optimizing the outcome of collaboration in an information seeking project. While these conditions are primarily based on location and communication channels, I will also brush upon asynchronous vs. synchronous collaboration based on our experiments. As a part of this talk, I will also demo our collaborative system, called Coagmento. ©2011 Microsoft Corporation. All rights reserved.

It is typically expected that when people work together, they can often accomplish goals that are difficult or even impossible for individuals. We consider this notion of the group achieving more than the sum of all individuals’ achievements to be the synergic effect (the whole greater than the sum of all) in collaboration. Similar expectation exists for people working in collaboration for information seeking tasks. We, however, lack a methodology and appropriate evaluation metrics for studying and measuring the synergic effect. In this talk I will present details from a large-scale lab study we did to understand the productivity of collaborators in different situations. I will discuss several traditional and novel approaches to evaluate such productivity, and show how certain conditions provide (or lack of) support for optimizing the outcome of collaboration in an information seeking project. While these conditions are primarily based on location and communication channels, I will also brush upon asynchronous vs. synchronous collaboration based on our experiments. As a part of this talk, I will also demo our collaborative system, called Coagmento. ©2011 Microsoft Corporation. All rights reserved.

It is typically expected that when people work together, they can often accomplish goals that are difficult or even impossible for individuals. We consider this notion of the group achieving more than the sum of all individuals’ achievements to be the synergic effect (the whole greater than the sum of all) in collaboration. Similar expectation exists for people working in collaboration for information seeking tasks. We, however, lack a methodology and appropriate evaluation metrics for studying and measuring the synergic effect. In this talk I will present details from a large-scale lab study we did to understand the productivity of collaborators in different situations. I will discuss several traditional and novel approaches to evaluate such productivity, and show how certain conditions provide (or lack of) support for optimizing the outcome of collaboration in an information seeking project. While these conditions are primarily based on location and communication channels, I will also brush upon asynchronous vs. synchronous collaboration based on our experiments. As a part of this talk, I will also demo our collaborative system, called Coagmento. ©2011 Microsoft Corporation. All rights reserved.

Both the global research community and federal governments are embracing a move toward more open sharing of the products of research. Historically, the primary product of research has been peer-reviewed journal articles and published technical reports. However, advances in information technology, new 'open access' business models, and government policies are working to make publications and supporting materials much more accessible to the general public. These same drivers are blurring the distinction between the data generated through the course of research and the associated publications. These developments have the potential to significantly enhance the value of both publications and supporting digital research data, turning them into valuable assets that can be shared and reused by other researchers. The confluence of these shifts in the research landscape leads one to the conclusion that technical publications and their supporting research data must be bound together in a rational fashion. However, bringing these two research products together will require the establishment of new policies and a supporting data infrastructure that have essentially no precedent in the materials community, and indeed, are stressing many other fields of research. This document raises the key issues that must be addressed in developing these policies and infrastructure and suggests a path forward in creating the solutions.

Both the global research community and federal governments are embracing a move toward more open sharing of the products of research. Historically, the primary product of research has been peer-reviewed journal articles and published technical reports. However, advances in information technology, new 'open access' business models, and government policies are working to make publications and supporting materials much more accessible to the general public. These same drivers are blurring the distinction between the data generated through the course of research and the associated publications. These developments have the potential to significantly enhance the value of both publications and supporting digital research data, turning them into valuable assets that can be shared and reused by other researchers. The confluence of these shifts in the research landscape leads one to the conclusion that technical publications and their supporting research data must be bound together in a rational fashion. However, bringing these two research products together will require the establishment of new policies and a supporting data infrastructure that have essentially no precedent in the materials community, and indeed, are stressing many other fields of research. This document raises the key issues that must be addressed in developing these policies and infrastructure and suggests a path forward in creating the solutions.

Both the global research community and federal governments are embracing a move toward more open sharing of the products of research. Historically, the primary product of research has been peer-reviewed journal articles and published technical reports. However, advances in information technology, new 'open access' business models, and government policies are working to make publications and supporting materials much more accessible to the general public. These same drivers are blurring the distinction between the data generated through the course of research and the associated publications. These developments have the potential to significantly enhance the value of both publications and supporting digital research data, turning them into valuable assets that can be shared and reused by other researchers. The confluence of these shifts in the research landscape leads one to the conclusion that technical publications and their supporting research data must be bound together in a rational fashion. However, bringing these two research products together will require the establishment of new policies and a supporting data infrastructure that have essentially no precedent in the materials community, and indeed, are stressing many other fields of research. This document raises the key issues that must be addressed in developing these policies and infrastructure and suggests a path forward in creating the solutions.

Scientists are trying to communicate their research all the time to the general public, sometimes with great success, but sometimes the research can come across as difficult to understand, difficult to relate to, or difficult to convey its importance. But what if there was another way to not only communicate your research but also make [...]Read More... from Making Science into Comedy

Scientists are trying to communicate their research all the time to the general public, sometimes with great success, but sometimes the research can come across as difficult to understand, difficult to relate to, or difficult to convey its importance. But what if there was another way to not only communicate your research but also make [...]Read More... from Making Science into Comedy