1 Increase your broader impacts while improving science educationMelissa Kjelvik, Liz Schultheis, & Alexa Warwick Michigan State University BEACON Center for the Study of Evolution in Action

2 _ Who we are Alexa Warwick Science education postdoc.Biologist studying evolutionary biology. Melissa Kjelvik Co-founder of DNs and postdoc. Biologist studying animal behavior. 12pm: Start with introduction of ourselves Liz Schultheis Co-founder of DNs and postdoc. Biologist studying invasive plants.

3 Participant IntroductionsName Year in the graduate program Research area (brief) Career goal Why you came to the workshop Have participants go around and introduce themselves

4 Workshop Goals Help you get started creating a Data Nugget based on your own research Increase your outreach/broader impacts Bring your research into K-16 classrooms Improve communication of your research Help expand our program to include research from other disciplines We want to provide resources for teachers that reach outside of ecology, connect to other fields Frame the workshop. Goals for the day. (5-10 minutes)

5 Workshop Outline Introductions Lunch and jargon activityIntroduction to Data Nuggets Creating your own Data Nugget Most of the time will be spent actively creating your Data Nugget.

6 Activity 1: Jargon kills!_ 12:10pm: Lunch and jargon activity (20 minutes): Alexa

7 Hattaway Communications, Cutting Through the Jargon

8 Hattaway Communications, Cutting Through the Jargon

9 Tips for effective communicationJargon kills! Tips for effective communication _ Sit with a partner, exchange writing, and identify jargon Share with your partner – identify one sentence that needs improvement and work together to rewrite it Share your insights with the group – was there any part that was hard or easy? 12:10pm: Lunch and jargon activity (20 minutes): Alexa Have them sit with a partner, exchange writing, and identify jargon. Share with their partner. Work with partner to rewrite one sentence - partner IDs the sentence that needs work, and then the two work together to improve it. Ask them to share out with the group anything that came up through their conversations, was it easy or hard? Now we will move into telling you more about Data Nuggets, but keep this activity in mind as it is what you will use to create your DN Hattaway Communications, Jargon Kills! Tipsheet

10 What are Data Nuggets? _ LIZ SECTION

11 How Data Nuggets got their start_ Teachers concerned about performing inquiry in the classroom Students need practice working with messy data As early career scientists we had lots of messy data that students could use! Data Nuggets have been under development since 2011 and originated through conversations between science teachers and graduate students during the NSF GK-12 project “New GK- 12: Using the STEM Dimensions of Bioenergy Sustainability to Bring Leading-edge Graduate Research to K-12 Learning Settings” (NSF DGE ). This unique opportunity for collaboration between teachers and scientists led to the creation of teacher-inspired resources. Teachers shared that they were lacking educational resources that helped their students practice working with real, messy data like that collected during classroom inquiry-based projects. Graduate students in the sciences, however, have lots of practice working with messy data and surprising results.

12 Free activities that bring real data into the classroom, along with all its messiness and complexity Based on authentic cutting edge research Guide students through the entire process of science, including data analysis & interpretation Take minutes and follow familiar template

13 _ Data Nugget goals Increase quantitative literacyIntroduce students to the process of science Show scientists are approachable Engage students with the researcher themselves, discussing more than just research findings Build interest in science Current research may engage students more than classic textbook examples Could increase students’ desire to pursue a career in science The use of current research has the added benefit of capturing the attention of students by engaging them with more than just the conclusions of a study, but the story and process of the researcher behind the ideas and data. While using Data Nuggets, students get excited about a research topic while increasing their quantitative skills and competency with the scientific method.

14 All of our Data Nuggets can be found online at datanuggets. orgAll of our Data Nuggets can be found online at datanuggets.org. We have about a thousand visitors to our website every month, and hundreds of teachers using Data Nuggets in their classrooms.

15 We have over 40 Data Nuggets up on our website (as of today)We have over 40 Data Nuggets up on our website (as of today). They can all be found here in a searchable and sortable table.

16 Anatomy of a Data Nugget_ The goal of the Data Nugget is to take students through the entire process of science. And to do this in a way that is relatively quick so students can get repeated practice with all of these areas. HAND OUT STEM CELL DN SO THEY CAN FOLLOW ALONG

17 _ Research background Background information Question and HypothesisThe standard format of each Nugget provides a brief background about a researcher, their study system, and a real dataset from that work. Within each Nugget, students are challenged to answer a scientific question, are guided through the construction of graphs to facilitate data interpretation, and use data to support their claims. Data Nuggets serve to supplement existing science curriculum; because of their simplicity and flexibility, Data Nuggets can be used across grade levels and throughout the school year as students build confidence in their quantitative and scientific skills. Question and Hypothesis

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19 In addition we just added a “Meet the Scientists” page where we have a blurb about the scientist and their interests. There is also a link to their professional webpage and the Data Nuggets that they have created. This allows students to explore more about the work going on in the lab if they are interested in doing a follow up project on the Data Nugget.

20 Content levels _ These correspond with Flesch-Kincaid readability statistics and science content standards Graphing and multiple content levels allow for differentiated learning for students with any science or reading background.

21 Data and data visualization_ *NOTE this example if from Won’t you be my urchin? A Level 1 Data Nugget. There are no error bars on this graph because this is not something that students would typically be familiar with at that grade level. If using this DN in an upper grade level you can add a place in the table for students to calculate SD or SE, or you can just have students mark the range on the graph to stimulate discussion of variation.

22 _ Graphing levels Each activity is provided in each level (A-C)Graphing and multiple content levels allow for differentiated learning for students with any science or reading background. Each activity is provided in each level (A-C) As a Data Nugget author you only create the teacher version and we create these student versions

23 Constructing explanations_ Interpret the data: Make a claim that answers each of the scientific questions. What evidence was used to write your claim? Reference specific parts of the tables or graphs. Explain your reasoning and how the data supports your claim. Connect your reasoning back to what you learned about the habitat preferences of each bird species and how habitats change through forest succession.   Did the data support Sarah’s hypothesis? Use evidence to explain why or why not.  If you feel the data were inconclusive, explain why. THIS PART WE WILL ELABORATE IN THIS SESSION This one section of the DN we will go into more depth on and show you how to scaffold this part.

24 Scientist next steps _ For each DN we have a version that students can do by hand, but we also want teachers to be able to build students’ quantitative skills and expand to issues of calculating statistics and hypothesis testing.

25 Extra information for teachers_ At the end of each teacher guide we provide a list of additional resources related to each Data Nugget. These may include primary literature, videos that the scientist has made about their research, blog posts or other popular articles about the research included in the Data Nugget, or additional photos and images.

26 Making your own Data Nugget_ MELISSA LEADS

27 _ Why make a Data Nugget? Improve your communication skillsUncover the core message of your work Important to be able to explain your research to a variety of audiences PAUSE BEFORE SHOWING OUR THREE BULLET POINTS! Ask participants why they came and how they see Data Nuggets helping them. Creating a Data Nugget will help you think about the essence of your work and how it can be framed to captivate diverse audiences - from elementary students to fellow scientists. Data Nuggets are an avenue toward broader impacts as your research will be shared with K-16 audiences and improve the understanding of science in society.

28 If you can explain it to a 4th grader you can explain your work to fellow scientists and other members of society.

29 _ Why make a Data Nugget? Improve your communication skillsUncover the core message of your work Important to be able to explain your research to a variety of audiences Use them in your undergraduate teaching and/or public outreach Increase your broader impacts Needed for NSF grant funding Share your research findings broadly PAUSE BEFORE SHOWING OUR THREE BULLET POINTS! Ask participants why they came and how they see Data Nuggets helping them. Creating a Data Nugget will help you think about the essence of your work and how it can be framed to captivate diverse audiences - from elementary students to fellow scientists. Data Nuggets are an avenue toward broader impacts as your research will be shared with K-16 audiences and improve the understanding of science in society.

30 _ Broader Impacts 20,411 unique users to the website in the past yearEach Data Nugget gets its own page on our website We can provide you with Google Analytics information for your future grant proposals About 40% of those are return users

31 How to make a Data Nugget_ Take a 10 minute break! 12:50pm: Break, but make sure they are ready to actively be involved in next part (5-10 minutes)

32 Activity 2: The Story _ 1:00pm: Activity 1: Question and dataset/graphs - what is the one big theme from your research that you want to communicate? What is one question and graph that you want to use? (30-45 minutes +/-) Liz

33 “Science consists of millions of stories of cause and effect.”– E.O. Wilson It is convenient for science that our brain makes sense of information by creating stories. Since science is really a set of stories. Your data is the character, let it tell you what the narrative should be.

34 Why stories? _ Stories are sticky – facts presented as stories (emotion) are much easier to remember Metaphors and analogies draw the student in and help tie the story to previous knowledge and experience Science consists of millions of. These accounts--some electrifying, most pedestrian--become science when they can be tested and woven into cause-and-effect explanations to become part of humanity's material worldview. But they also constitute a fascinating narrative, which can be the key to helping the non-scientist understand the great ideas of science.

35 What makes a story stick?_ Positive content that brings out emotion Stories that are surprising, interesting, and practically useful Facts that stir up emotions are quickly stored There was an article that you may have seen recently in the news. It analyzed hundreds of NYTimes articles and looked to see what makes some stories more likely to be shared than others. Why are certain pieces of online content (e.g., advertisements, videos, news articles) more viral than others? Using a unique data set of all the New York Times articles published over a three-month period, the authors examine how emotion shapes virality. The results indicate that positive content is more viral than negative content, but the relationship between emotion and social transmission is more complex than valence alone. Virality is partially driven by physiological arousal. Content that evokes high-arousal positive (awe) or negative (anger or anxiety) emotions is more viral. Content that evokes low-arousal, or deactivating, emotions (e.g., sadness) is less viral. These results hold even when the authors control for how surprising, interesting, or practically useful content is (all of which are positively linked to virality), as well as external drivers of attention (e.g., how prominently content was featured). Experimental results further demonstrate the causal impact of specific emotion on transmission and illustrate that it is driven by the level of activation induced. Taken together, these findings shed light on why people share content and how to design more effective viral marketing campaigns. Jonah Berger, Katherine L. Milkman (2012) What Makes Online Content Viral? Journal of Marketing Research: April 2012, Vol. 49, No. 2, pp

36 What makes a story stick?_ Lessons to take away: Relevant to a student’s experience Identify one big theme from your research Connect to the story of the researcher The results indicate that positive content is more viral than negative content, but the relationship between emotion and social transmission is more complex than valence alone. Virality is partially driven by physiological arousal. Content that evokes high-arousal positive (awe) or negative (anger or anxiety) emotions is more viral. Content that evokes low-arousal, or deactivating, emotions (e.g., sadness) is less viral. These results hold even when the authors control for how surprising, interesting, or practically useful content is (all of which are positively linked to virality), as well as external drivers of attention (e.g., how prominently content was featured). Experimental results further demonstrate the causal impact of specific emotion on transmission and illustrate that it is driven by the level of activation induced. Taken together, these findings shed light on why people share content and how to design more effective viral marketing campaigns. Jonah Berger, Katherine L. Milkman (2012) What Makes Online Content Viral? Journal of Marketing Research: April 2012, Vol. 49, No. 2, pp

37 _ Identify your story Work with a partner or someone from your labIdentify the one message that you would want someone to take away from your research GIVE THEM minutes to discuss with a partner and write it down. Then at ~1:15 have them go around and share with the group. What ideas are you thinking about for your story?

38 Identify your story and data_ What data is relevant to your message? What variables are important? How would you represent your data to communicate your message? In 1-2 sentences, write down your story and prepare to share out with larger group SHARE OUT WITH THE GROUP

39 Send us the following information:_ A summary of your story (1-2 sentences) Mock up a small data table Table can have unnecessary variables or data if you wish! Mock up a graph or visualization of the data that best illustrates your story. Liz at You can us the text or just snap a photo of your mock up

40 Activity 3: Writing the background_ 1:45pm: Activity 2: Spend time writing the research background for a DN. You could start by translating the abstract (or whatever research the dataset they selected addresses) to create a general summary words. (30-45 minutes) Melissa (overall lead)

41 Review stem cell Data Nugget_ What makes the background research easy to read? How did the researcher make his research appropriate for a K-12 audience? Have them read the stem cell DN again, what parts do you notice that make this different from a science text? Appropriate for the audience? Maybe take notes from what they mention on the whiteboard (if available) What to include or not to include [could have the students generate - we write on a whiteboard or just blank ppt slide]

42 Review stem cell Data Nugget_ Accessible writing: Includes a hook, catchy beginning Short, simple sentences Relatable, real-life connections Engaging story Minimal use of jargon or complicated words Have them read the stem cell DN again, what parts do you notice that make this different from a science text? Appropriate for the audience? Maybe take notes from what they mention on the whiteboard (if available) What to include or not to include [could have the students generate - we write on a whiteboard or just blank ppt slide]

43 _ What was the hook? Hattaway Communications, Jargon Kills! TipsheetWhat is the hook, how do you capture your audience’s attention? (Refer back to the stem cell Data Nugget example) You can use these criteria to craft language that is memorable and motivating. The criteria are based on research suggesting the most powerful language will 1) create emotional reactions, 2) be both familiar and easy to understand and 3) evoke visual images in the mind. You also want the message to spread on the internet and via word-of-mouth, so you should use words that people will retain and repeat. Hattaway Communications, Jargon Kills! Tipsheet

44 Hattaway Communications, Cutting Through the Jargon

45 Write simply & remove jargon_ Remember: jargon distracts the reader, and they are less likely to trust writing they have to work to understand. What are example sentences in the stem cell Data Nugget that have more or less jargon? What types of sentences are found before or after the introduction of terms? Can you find any instances of analogies or metaphors? What do you think makes a sentence harder to read? Ask the group before showing the three bullet points

46 Write simply & remove jargon_ Flesch–Kincaid Score: represents readability of text in terms of U.S. grade levels. What factors make F-K scores higher? Long sentences Complex sentence structures Long or jargon words Stringing long words together What do you think makes a sentence harder to read? Ask the group before showing the three bullet points NY TIMES IS A F-K of 10th GRADE https://www.online-utility.org/english/readability_test_and_improve.jsp

47 Write simply & remove jargon_ Take a second to look at the F-K score on your original writing samples. You can check the F-K score as you write to monitor the level of your writing. Paste text into free online readability calculators Microsoft Word will calculate for you, need to turn on this function Word > Preferences > Spelling and grammar > show readability statistics checkbox (MAC) File > Options > Proofing tab > show readability statistics checkbox (PC) My tool of preference is in Microsoft Word.  The major readability statistics are Flesch Reading Ease and Flesch-Kincaid Grade Level. For the Flesch Reading Ease and Flesch-Kincaid Grade Level statistics to come up in the “Spelling & Grammar” review of your content you will need to enable those statistics. To do this select “File” then “Options” next go to the “Proofing” tab and check the box that says “Show readability statistics.”

48 Make scientists relatable!_ Scientists are still overwhelmingly white and male (Pollack 2015). Ethnic minority students are more likely to see themselves as scientists if they are exposed to role models that they can identify with (Price 2010). Overcome scientist stereotypes. Scientists are still overwhelmingly white and male (Pollack 2015). This homogeneity excludes talented individuals and reduces productivity that can be achieved with increased workplace diversity (Reagans & Zuckerman 2001, Stahl et al. 2010). Barriers for underrepresented groups in STEM fields are often rooted in social rather than academic factors, such as negative stereotypes and a lack of same­race peers (Strayhorn 2010). These social constructs are reinforced by the stereotypical depiction of scientists in the media and popular culture (Dudo et al. 2011). Two common tropes include the “mad scientist” (e.g., in superhero movies) and the “awkward geek” (e.g., The Big Bang Theory ); neither is very approachable or appealing as a role model, and both are typically white men. Ethnic minority students are more likely to see themselves as scientists if they are exposed to role models that they can identify with (e.g., their teachers, Price 2010). By redefining what a scientist looks like, we hope to encourage participation in science by all interested students.

49 Activity 3: Writing the background_ Begin writing your Data Nugget background Keep in mind: Minimize jargon and write simply Focus on the story Include a hook Be relatable

50 Activity 4: The Template_ 1:45pm: Activity 2: Spend time writing the research background for a DN. You could start by translating the abstract (or whatever research the dataset they selected addresses) to create a general summary words. (30-45 minutes) Melissa (overall lead)

51 Filling out the template_ Finalize your Nugget by filling in all components of the template (text in red) You are making the teacher copy and we will make the student versions – feel free to include any additional information you think would be helpful and we can add this in as notes to the teacher! materials to Liz or Melissa

52 Evaluation Forms Anonymous feedback about the workshop overallNon-anonymous feedback about your progress: Fill out the half-page form us a photo of your Data Nugget so far us a photo of your jargon activity Frame the workshop. Goals for the day. (5-10 minutes)

53 Thank you! _ NIMBioS Working Group: Expanding Data Nuggets Meeting 1 participants (L to R): Louise Mead, Melissa Kjelvik, Molly Stuhlsatz, Laurel Hartley, Julie Morris, Paul Strode, Kristin Jenkins, Elizabeth Schultheis, Jeremy Wojdak, Ariel Cintron-Arias, Robert Mayes, Gordon Uno

54 EXTRA SLIDES

55 Quantitative literacy_ Quantitative literacy: way of viewing the world through “mathematical eyes” and approaching every day problems with confidence and logical reasoning (Piatek-Jimenez et al. 2012, Vacher 2014) Critical need in STEM education Students are graduating unable to apply quantitative knowledge to situations (Wilkins 2010) Students with poor quantitative literacy more likely to drop out of school, experience unemployment, earn less (McMillan & Marks 2003, Marks et al. 2005, Rumberger & Lamb 2003) It turns out that the needs of our GK-12 teachers addressed a broad national need as well. Quantitative literacy covers a variety of skills, including the ability to understand quantitative information such as graphs, tables, mathematical relations, and descriptive statistics; as well as exhibit coherent and logical thinking about quantitative information. Through this collaboration, Data Nuggets were created to bring real data from current and ongoing research into the classroom and take students through the process of science, from the inception of ideas to the analysis and interpretation of data.

56 Your next step as a scientist: Become curious Ask questions Develop hypothesis Research background: Become curious Ask questions Develop hypothesis Interpret the data: Collect data to answer question Graph and interpret data Support or refute hypothesis Interpret the data: Build knowledge Satisfy curiosity Data Nuggets were designed to take students through the entire scientific process. Template has been updated to incorporate feedback from Understanding Science Your next step as a scientist: Discuss with colleagues Come up with further questions

57 Jonah Berger, Katherine LJonah Berger, Katherine L. Milkman (2012) What Makes Online Content Viral? Journal of Marketing Research: April 2012, Vol. 49, No. 2, pp

58 What makes a good scientific question?_ Make it broad Can not be answered with a yes or no Are testable – it can be answered by direct observation or experimentation Can be answered with a hypothesis statement Interesting! If you have having trouble coming up with a good hypothesis, it could be that you are not starting with a good question. Think broader.

59 What makes a good hypothesis?_ How would you define a hypothesis? How textbooks define hypothesis: A proposed explanation for an observation. Wilbraham A.C. et al. (Pearson Prentice Hall 2008) Chemistry: the Molecular Nature of Matter and Change A reasonable explanation for observations - one that can be tested with additional experiments. Serway and Faughn (Holt, Reinhalt, and Winston 2009) A tentative answer to a well-framed question - an explanation on trial. Campbell and Reece (2008) Biology, 8th Ed.:

60 What makes a good hypothesis?_ Give us an idea of why a particular phenomenon occurs (explanatory power). Testable because they generate expectations about what we should observe in different situations. Which is best? Table salt will dissolve in water more quickly than rock salt. The surface area of a dissolvable substance determines the rate that it dissolves. Salt with more surface area will dissolve more quickly in water than salt with less surface area.

61 What makes a good hypothesis?_ Critique & improve the following hypotheses: If the farmer burns the prairie, then the next year will produce taller plants in his field then the previous year. H: Prairie fires replenish soil nutrients. If marsh grass receives nitrogen fertilizer, then it will grow to be bigger than plants that do not receive fertilizer. H: Marsh grass growth is limited by available nitrogen. Examples are from Paul Strode. All these examples lack a mechanism. The exercise is can the participants reword them to become a hypothesis.

62 What makes a good hypothesis?_ “If _____, then _____” statements are a common way that hypotheses are taught incorrectly in classrooms. These are just simply a method followed by a prediction and gives no statement on what mechanism is being tested. Be sure to state your hypothesis clearly and not as a prediction Phrasing as a prediction shifts students’ mindsets away from investigating cause and toward simply confirming an observation. Start with a good scientific question, and your hypothesis is the proposed answer to that question ex. how to salmon navigate to their home stream? Hypothesis – they use the earth’s magnetic field WRONG: If we do this, then we see this – method followed by prediction ex. if we add fertilizer to plants, then they will grow larger CORRECT: If (mechanism/hypothesis), and we do this (method), we will see this (prediction) ex. if lack of nutrients is inhibiting plant growth, and we add fertilizer to plants, then they will grow larger