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## PART I  WEBINARS

### A.“But it’s a number, so it has to be true!”: An introduction to data literacy, Part I

This webinar is the first of two that cover the basic concepts of data and data literacy. Data literacy is about asking questions as one encounters numerical information in popular and scientific media. Numbers can be as fallible as any other source of information. This first in a two-part presentation will provide a concrete definition of data literacy, provide examples of the kinds of questions to raise when confronted with data, and give sources of information and types of assignments especially well-suited to building data literacy skills. This first part of the presentation will address the following concepts:

• Variables
• Averages (central tendencies)
• Percentages, percentiles, and percent change

Attendees will acquire the tools needed to begin similar conversations with students. Because working with numerical evidence is, as much or more, a mindset as it is a set of mathematical skills, the content will be helpful for teachers in all disciplines, not just math or science.

Time: Assume this activity will take 90 minutes, (36 minutes for the webinar itself and 54 minutes for a selection of activities and/or discussion questions).

Timeline:

• Quantitative literacy: 2:50
• Key statistical concepts: 9:10
• Variables: 9:40
• Percentages: 14:50
• Rates: 18:20
• Percent change: 20:20
• Averages: 22:35
• Averages activity: 25:30
• Statistic terms in the classroom: 28:20
• Recap: 34:48

Related webinar resources:

#### Discussion questions

1. What jumped out at you as knowledge already familiar to your students from existing curriculum practices?
2. What stood out as a data skills gap that needs to be addressed?
3. Should the skills you have identified be worked into someone’s existing curriculum, or should they be taught in a mini-lesson only if they should happen to arise in the classroom?
4. What problems can you or your students solve with the information in the webinar?
5. How can you highlight the differences between statistical literacy and math class for students?
6. What are some ways to show how data collection affects datasets?
7. How can you incorporate statistical literacy gracefully into a class?
8. What are some specific issues or concerns that could arise if you bring statistical literacy strategies into your classroom?
9. When might it be more advantageous to use a percent or a rate instead of a raw number when describing something?
10. How can you explain to students when they should look to use mean, median, or mode?

#### Recommended activities

1. Create a data literacy strategy of the week. Imagine that you could set aside five minutes a week — in your class, in the slideshow that plays in your school hallways, during a school broadcast, and/or in a family newsletter — to share a weekly data literacy strategy with the school. What would you pull out from this webinar to fill that weekly slot?
2. Brainstorm mean, median, and mode. Set a timer for five minutes. As individuals, brainstorm as many situations in which calculating the mean might be the best type of “average” to compute. Repeat with median and mode. Then pool your responses into a common document to share with other educators.
3. Explain percentile versus percentage to school parents. Create a newsletter blurb for parents and guardians explaining the difference between percentage and percentile that could be slipped into the report card envelope.

### B. “But it’s a number, so it has to be true!”: An introduction to data literacy, Part II

This second of two sessions dives further into data literacy concepts, touching on the nature of data, how you can incorporate statistical literacy into the classroom, and how variables play into data analysis and collection. Data literacy is all about asking questions as one encounters numerical information in popular and scientific media. Numbers can be as fallible as any other source of information. This second in a two-part presentation will provide a concrete definition of data literacy, provide examples of the kinds of questions to raise when confronted with data, and give sources of information and types of assignments especially well-suited to building data literacy skills. This second part of the presentation will address the following concepts more closely:

• Sampling
• Margin of error/confidence
• Correlation
• “Controlling” for ...
• Significance

Attendees will acquire the tools needed to begin similar conversations with students. Because working with numerical evidence is as much or more a mindset as it is a set of mathematical skills, the content should be helpful for teachers in all disciplines, not just math or science.

Time: Assume this activity will take 90 minutes, (43 minutes for the webinar itself and 47 minutes for a selection of activities and/or discussion questions).

Timeline:

• Recap of Part I: 1:10
• Key statistical concepts: 3:05
• Sampling and methodology: 3:48
• Margin of error: 13:20
• Correlation: 17:45
• Negative correlation activity: 27:10
• Statistical significance: 30:44
• In practice/Where to find examples: 35:09
• Recap: 40:35

Related webinar resources:

#### Discussion questions

1. What jumped out at you as knowledge already familiar to your students from existing curriculum practices?
2. What stood out as a data skills gap that needs to be addressed?
3. Should the skills you have identified be worked into someone’s existing curriculum, or should they be taught in a mini-lesson only if they should happen to arise in the classroom?
4. What problems can you or your students solve with the information in the webinar?
5. How can you emphasize the different aspects of good sample selection to students?
6. What are some ways you can demonstrate how question wording affects the answers on surveys?
7. Correlation versus causation is a key statistical concept. What are some ways to emphasize the difference between the two using activities the students conduct? What are some resources not in the slides that can be used to emphasize the difference between the two?
8. How can you incorporate statistical literacy gracefully into a class?
9. What are some specific issues or concerns that could arise if you bring statistical literacy strategies into your classroom?
10. How can you teach statistical language to students? What are some ways to emphasize that certain words have different meanings than students might be used to?

#### Recommended activities

1. Add to your list of weekly data literacy strategies. Think back to the weekly data literacy strategy list you made in Hoelter’s first webinar (Part I). What could you now add to your calendar of weekly data skills that you could promote in your class, in the slideshow that plays in your school hallways, during a school broadcast, and/or in a family newsletter? Swap ideas with others in the room so everyone leaves with a robust list.
2. Practice causation vs. correlation. Fold a paper in half and set a timer for five minutes. Individually, brainstorm lists of known causative relationships (e.g., smoking causes cancer). On the right hand side, brainstorm lists of correlative relationships (e.g., eating breakfast relates to higher test scores). Then discuss as a group to check your thinking.
3. Think about sample size in the real world. Think about the longtime Trident gum commercial tagline: “Four out of five dentists recommend Trident to their patients who chew gum.” What is really being said here? What sample size would make you feel more confident about this statement? Can you think of any other commercials or brands that use sample sizes to promote customer confidence?

### C. Where the rubber meets the road: Data literacy in the content areas

Data literacy is useful in all content areas, not just in math class. Having data literate students means you can use data visualizations and raw data to present material in different forms for different learners. Teaching students data literacy also helps prepare them for standardized testing and helps them understand other forms of literacy.

Time: Assume this activity will take 90 minutes (38 minutes for the webinar itself and 50 minutes for a selection of activities and/or discussion questions).

Timeline:

• Integrating data literacy: 2:10
• Data comprehension: 3:00
• Data visualization: 5:15
• Data as argument: 5:40
• Reasons for data literacy: 7:33
• GAP: 20:30
• Integration activities: 26:30
• Sources for data visualization: 30:15
• Developing informed citizens: 31:15

Related webinar resources:

#### Discussion questions

1. How can standards be addressed with schoolwide data literacy practice?
2. How do standardized test questions change your understanding of the need for cross-curricular data literacy skills?
3. What experiences can you share from your teaching related to student interactions with data and visualizations?
4. What are some ways to collect data in a non-science classroom?
5. How can you use data to present material in a new light?
6. What are some challenges you foresee from using data in this way?
7. What are good sources of data and data visualizations for classroom use?
8. Are there lessons for which you would not want to use data? Why?
9. Is there such a thing as using data-oriented lessons too much? Why or why not?
10. What would you need to adjust in your teaching to make room for discussions about data?
11. Do you see information here that would be helpful for colleagues in other subject areas? Which information? Why?

#### Recommended activities

1. Browse the data visualization lesson tips in the slide deck at http://datalit.sites.uofmhosting.net/2017/03/17/data-literacy-at-macul/ . Think about how these activities would be useful (or could be adapted to become useful) in your classroom. Share out with your group.
2. Do a search online for infographics related to your subject area. Check the creator and sources used for credibility. Send links to fellow educators. Brainstorm how you would use them in a lesson.
3. Browse your state or district learning standards. Where do they call for data skills? To find related standards, search for terms such as, visual, quantitative, claim, information, and bias. (Find links to national standards at the back of this book, as well as a link to a list of the data-related standards in those documents.) Make a table. In one column, list the standard’s number and text. In the next column, describe how your subject area will work to achieve that standard. Submit the completed document to your administrator, department head, and/or district administrator.

### D. Information literacy includes data literacy!

This presentation will provide a big-picture framing for data literacy as a component of information literacy. How do students move through the research process when they begin looking more attentively at how data is “read” and “written”? This webinar dives into the specifics of how you can use data literacy to help students evaluate and use statistics. The session focuses on real-world student activities to develop their ability to benchmark statistics and evaluate the sources of those statistics.

Time: Assume this activity will take approximately 90 minutes (30 minutes to view the webinar, and another hour to do the activities and discussion questions.)

Timeline:

 00:00 Introduction of presenter 00:50 Opening thoughts 2:00 Reference to 2007 Standards for the 21st-Century Learner (American Association of School Librarians) 3:00 Information literacy definition 3:35 Webinar goals 4:44 Step 1: Explore a new topic 7:01 How to use background reading 8:26 Benchmarking 10:54 Benchmarking activity 17:22 Step 2: Contextualize a statistic 18:41 Step 3: Use data as evidence 21:09 Data as evidence activity 25:47 How to interrogate a statistic

Related webinar resource:

#### Discussion questions

1. Seroff concentrates on three moments in the information literacy process in this webinar: exploring a new topic (“stepping stone reading”), evaluating an argument, and using data as evidence. Discuss each stage with fellow participants. What do you notice in student behavior at each of these stages? How do they currently respond to data?
2. How do you teach and respond at each stage?
3. How do Seroff’s experiences echo your own?
4. What is different from your experience?
5. What resources not mentioned in the webinar can students use to evaluate statistics used in arguments?
6. What exercises can you do with students to help them develop their statistical benchmarking skills?
7. What questions should students be able to ask of statistics while benchmarking them?
8. What role do different media outlets play in teaching students how to benchmark statistics?
9. What do you see students learning from the media about how to use statistics to support their arguments?
10. How can you help students avoid cherry-picking behavior?

#### Recommended activities

1. Explore information literacy and the inquiry process. Seroff references the 2007 Standards for the 21st-Century Learner, published by the American Association of School Librarians, available for download at http://ala.org/aasl/standards . Download a copy. Where do you see openings for bringing data literacy into those standards for students?
2. Learn more about write-arounds from Sara Kelley-Mudie. Seroff mentions Kelley-Mudie’s use of this technique in the first third of her webinar. Visit Kelley-Mudie’s blog post “Write arounds for topic selection” (http://kmthelibrarian.blogspot.com/2014/10/write-arounds-for-topic-selection.html) and discuss how this strategy might work with your students.
3. Brainstorm needed statistical benchmarks. At 11:00 into the webinar, Seroff modeled finding statistical benchmarks with live participants about video games and violence. Try her process using a topic that your students either study or research in your classroom or library. What kinds of reliable statistical benchmarks would be helpful in helping students contextualize the numerical data they will encounter with this topic? Is it the number of legal voters? The size of the U.S. population? The area of Great Britain and the United States? Then use resources such as http://census.gov, https://www.cia.gov/library/publications/the-world-factbook/, an encyclopedia, or an almanac to identify benchmarks that you can distribute or post for students to reference. What would a list of benchmarks look like if you added to this list throughout the year?

### E. Close reading: Unpacking the impact language has on how we understand statistics

How do the words we use to frame and describe statistics potentially change how readers perceive their meaning? Students often go looking for “some number” to use as evidence, but evocative language in which the statistics are often embedded may go unnoticed, even while it transforms the reader’s interpretation of a statistic’s meaning. Luckily, applying students’ formative skills in literary analysis can go a long way toward helping them move beyond initial responses to successfully analyzing and evaluating data. Come play with the language of statistics — this webinar addresses skills that can be used to assess the use of statistics in text. Bergson-Michelson relates them to the close reading skills many students are already familiar with from English class, before using headlines and an article to demonstrate some of those skills.

Time: Assume this activity will take 90 minutes, (42 minutes for the webinar itself and 48 minutes for a selection of activities and/or discussion questions).

Timeline:

• Language activity: 5:00
• Structure of statistical storytelling: 7:16
• Pure statistical storytelling: 11:00
• Correlation vs. causation: 11:54
• Causation and correlation activity: 13:20
• Language indicators: 25:00
• Questions: 26:47
• Emotionally evocative statistical storytelling: 30:05
• Recap: 40:41

Related webinar resources:

#### Discussion questions

1. What are your key takeaways from the webinar?
2. What do you make of Bergson-Michelson’s observations of how students approach numbers?
3. What rang particularly true given the students you work with?
4. What lessons can educators learn from English and literature teachers to apply to statistical reading?
5. How can you improve students’ statistical vocabulary?
6. Bergson-Michelson discusses the prevalence of field-specific vocabulary. What signs can students use to identify words that have a meaning different from what they are used to?
7. What can educators do to improve students’ knowledge of correlation words and causation words?
8. The webinar has lists of words associated with correlation and causation. What activities can you do with students to help them learn these words in an interesting way (e.g., not memorizing)?
9. Question marks are particularly important for indicating meaning in statistical writing. Sometimes they can be a hedge; other times they indicate a lack of causation. How can you tell the difference?
10. Tone is always difficult to convey in text but is one of the most important components of communication. How can students better learn to recognize tone in text?

#### Recommended activities

1. Start a collection of clickbait headlines related to statistics and data literacy. Start a physical or digital file in which you start collecting headlines that use statistics, causation instead of correlation, or other data tricks to entice the reader to click.
2. Explore language related to causation and correlation. Visit http://bit.ly/DataLitCloseReading. In small groups, invite participants to complete the first exercise, identifying which of the listed headlines indicate causation and which indicate correlation. Discuss your results as a larger group. What rules of thumb can you take away from this experience to share with students?
3. Discern the author’s perspective. Visit http://bit.ly/couldyourfastfoodburger and read over the article. Now look at the graphic on the last page at http://bit.ly/DataLitCloseReading. Discuss the article through addressing these three questions featured on the graphic (and also listed below). Think about how you would call on students to support their answers with evidence.

• What does the author say (topic)?
• What does the author think (opinion)?
• What does the author want me to do or say (call to action)?

### F. Real world data fluency: How to use raw data

High school students don’t often get to work with raw data. The collection or generation of data may seem monolithic and unquestionable. Students are more likely to confront data through headlines crafted to entice reader curiosity and stress novelty. This webinar shares several tools and tips for dealing with raw data. In addition to discussing how to deal with raw datasets, this webinar gives participants many resources that have publicly available datasets which are easy to access for students.

Time: Assume this activity will take 90 minutes, (47 minutes for the webinar itself and 50 minutes for a selection of activities and/or discussion questions).

Timeline:

• Thinking computationally: 8:36
• Finding existing datasets: 21:31
• Presenting data responsibly: 39:41
• Recap: 46:00

Related webinar resources:

#### Discussion questions

1. What are the key themes of the webinar (e.g., the categories of sites she recommends)?
2. What advice from the presenter did you find most resonant?
3. Why does the presenter advocate for using existing datasets instead of just letting kids explore online?
4. Which sites have you used before? Which have been valuable?
5. Which sites might be the most valuable for colleagues and classroom teachers you know?
6. Which dataset do you think would be best for introducing students to datasets in general? Why?
8. What criteria are you using to determine “best” datasets?
9. Which dataset do you find the most interesting?
10. Which do you think students would find the most interesting?

#### Recommended activities

1. Explore the sites Steadman Stephens hand-selected. View the list of tools at http://tinyurl.com/datafluent. Divide participants into groups, with each exploring one source. Have each group prepare a one-minute tour of their chosen site.
2. Recommend a dataset to a colleague. Pass out blank stationery to the group. Ask each person to think of someone else in her building who might be able to benefit from either a site or a dataset within a site. Write them a note letting them know about the dataset and why it might be useful.
3. Add a dataset to your resource page. Choose at least one dataset to add to your library or class’s web page, social media page, and/or resources page. As an extension, consider adding one site a week to your “data of the week” project you started with Lynette Hoelter’s two webinars on statistical literacy. How close are you now to having a year’s worth of strategies and resources?

### G. Gathering data via action research: A plan for librarians, classroom teachers, and students

In today’s data-driven world, librarians and educators are under increasing pressure to show that their efforts yield measurable results. Action research (AR) is a flexible framework in which educators can design interventions with assessment in mind, implement those changes, measure the impact, and share the results. This practitioner-friendly approach puts you in the driver’s seat. You don’t need a Ph.D. in statistics to gather data that matters! In this presentation, you’ll learn more about the AR cycle and its power to help you measure and communicate what matters. Once you have used it yourself, you’ll be able to teach your students to design their own AR!

This webinar provides an overview of how to use research to benefit your professional life and development. It touches on data collection and analysis techniques, and discusses how you can best adapt research practices to different professional roles and scenarios.

Time: Assume this activity will take 90 minutes (38 minutes for the webinar itself and 50 minutes for a selection of activities and/or discussion questions).

Timeline:

• What is action research (AR)?: 2:18
• AR to foster collaboration and self reliance: 6:14
• Advantages to action research: 7:25
• Connection to data literacy: 9:25
• Getting started: 13:05
• Action research proposal: 13:22
• Data usage: 22:06
• Reporting the data: 31:20
• Application with students: 32:50
• Summary and recap: 36:50

#### Discussion questions

1. What appeals to you about action research (AR) as a pathway to gathering data and insights as an educator?
2. What kinds of data are you asked to demonstrate to your administrator, department chair, district coordinator, or other stakeholders? Which kinds might be conducive to AR?
3. What appeals to you about AR as a technique for students? In what kinds of classes or projects might AR be a useful way for students to collect data?
4. What is a topic, issue or area of interest that you could use AR to study and learn about in order to “take action” in your own classroom or library?
5. What rules of thumb can you take away from this webinar?
6. How can you effectively frame an AR question for yourself? For a student? For another stakeholder?
7. What are some ways you can limit qualitative variables while doing AR in a school environment?
8. What are some best practices for presenting your research results to stakeholders?
9. What presentation styles or formats are preferred by your administration, board, and/or trustees?
10. What are some things to avoid while presenting results?

#### Recommended activities

1. Review your school’s strategic plan. Each school or district has a long-term plan, often called a strategic plan, in which areas to receive additional or particular focus are outlined. Identify those priorities.
2. Identify opportunities for research related to your district’s needs or those of your classroom or library. Are there issues that could be studied via AR that could be useful not only for your classroom but in service toward the larger strategic plan? Brainstorm possibilities.
3. Read and discuss this case study. Prior to retirement from Londonderry (NH) School District, Susan D. Ballard was on a team to use AR to research the impact and effectiveness of professional development and practice related to interactive whiteboards. Read the report at http://datalit.sites.uofmhosting.net/2017/05/14/action-research-example/ and discuss how AR illuminated their practice.

### H. Data literacy and voting

This webinar discusses the importance of data literacy on many different aspects of the 2016 U.S. presidential campaign, and politics in general. It addresses the difficulties in assessing electorate polls by exploring how they are created and manipulated before diving into some misuses of data visualizations and some statistical issues related to news coverage of candidates and races.

Time: Assume this activity will take two hours (48 minutes to view the webinar, and another hour to do the activities and discussion questions).

Timeline:

• Agenda: 0:00-1:31
• News media perception: 1:32
• 2016 presidential election summary: 3:07
• Rule of thumb 1: Knowing polls work: 4:39
• How polls trip us up: 7:09
• Indications of a good poll: 13:20
• Poll examples: 15:32
• Rule of thumb 2: Apply statistical skills: 26:46
• Statistical skills example: 28:37
• Rule of thumb 3: Apply data visualization skills: 32:05
• Data visualization skills examples: 33:41
• Rule of thumb 4: Look at multiple sources: 42:25
• Good sources: 43:43

Slide deck: https://goo.gl/weGb3p

#### Discussion questions

1. Think ahead to the 2018 midterm elections or other upcoming elections in your area. How might framing data literacy as an election issue be useful in your school community?
2. What experiences have you had as an educator that relate to the webinar?
3. How would you address the issue of media bias (perceived and real) with students?
4. Which kind of poll do you think is the most accurate?
5. Which do you think is the most reliable?
6. What bearing does this information have on lessons since major elections happen only every four years.
7. What statistical questions could you ask of polls that are not included in the slides?
8. What is the relevance of polling and poll modeling on students’ day-to-day lives?
9. What are some other circumstances where non-geographically aligned maps could help students learn about a complex topic?

#### Recommended activities

1. Compare electoral maps. Ask small groups to find and compare electoral maps from the 2016 Clinton-Trump election to that of Obama-Romney in 2012. Where in the country did the biggest voting shifts happen? What happens if you make comparisons even further back in recent history?
2. Explore presidential approval ratings over time. Invite participants to explore Gallup.com, the site of the well-known polling company, and particularly the site dedicated to daily monitoring of presidential job approval ratings for recent presidents:

Ask them to choose a president and tinker with various time ranges. Can they manipulate the way the data looks merely by changing the time period sampled? What time period might make their selected president look particularly strong? Particularly weak? What do they make of this ability to change the message of a graph merely by selecting different dates?

3. Compare polling data. Go to http://www.publicpolicypolling.com/, a site that tracks presidential polling. Choose the most recent poll from the home page. Compare it to the poll conducted immediately following the 2016 Clinton-Trump election. The week President Trump was inaugurated? What patterns do you notice? What can you learn from reading the summary? The methodology? The raw data?

### I. Making sense of data visualization

Data visualization is first and foremost a sense-making process; it is a means by which we extract meaning from complex datasets. This presentation will explore the ways that data can be transformed into visual representations and how we can make sense of these visualizations. Discussion will include a variety of types of visualizations and when they are most effective. This talk will briefly include information about tools for making data visualizations, but the focus will be on how to read and understand them. The conclusion will discuss ways in which data visualization and data literacy can be taught in the classroom.

Time: Assume this activity will take 90 minutes, (36 minutes for the webinar itself and 54 minutes for a selection of activities and/or discussion questions).

Timeline:

• What is data: 3:50
• Drawn/non computational data visualization: 6:10
• Understanding data visualization: 7:20
• US Census data visualizations: 7:50
• Breakdown of data visualization options: 15:45
• Information density: 21:30
• Recognizing patterns: 26:25
• Teaching data visualization: 29:08
• Making visualizations: 32:00
• Recap: 34:45

Related webinar resources:

Slide deck: https://goo.gl/byYVoX

#### Discussion questions

1. What forms of data visualization were familiar to you? Unfamiliar?
2. Why might we want to have rules of thumb for students on data visualization? Which strategies strike you as most urgent?
3. What experiences have you had as an educator that relate to the webinar?
4. What kinds of data do you think are best suited to visualization?
5. One important point in the presentation is that data is not neutral: the way it is collected affects the datasets. How can you educate students on this point?
6. Aside from color and type of visualization, what other design choices are most important for displaying data? Why?
7. How might color accidentally communicate unintended emotion in data visualizations? For example, in a visualization about gender, what would be the impact if both genders were represented in hues of pink?
8. How do you know how much data in a visualization is too much? Too little?
9. Mapping data to geographic location is not always the best way visualize data. Brainstorm: When would you want to use a map to visualize data, and when would you not want to?
10. Joque concludes by presenting some questions to ask yourself when viewing any visualization. What questions would you add?

#### Recommended activities

1. List and prioritize rules of thumb for visualizations. In small groups, use a piece of chart paper to brainstorm the rules of thumb or helpful hints that Joque presents in his webinar. Now sort them into groups according to high, medium, and low priority for instruction. Which are “must knows” for students?
2. Start a collection of sample visualizations. Browse past issues of newspapers or news journals either in print or online. Create an informal scrapbook of more and less effective visualizations. What makes a visualization weaker? Stronger?
3. Writearound with visualizations. WTF Visualizations, despite its non-school-friendly title, gathers weird or awkward visualization examples that can lead to great discussions. Visit http://viz.wtf. Browse until you find a handful of visualizations that are particularly awkward. Print them out and place each in the middle of a large piece of chart paper. Place each at a separate table. Divide the participants into small groups and have them rotate between tables adding comments, feedback, and questions to each visualization. (This is known as a “writearound” activity.) Then pull the group together to discuss. Optional extension: Assign one commented visualization to each group and ask them to remake it so it is more accurate or more effective.

### J. DataBasic.io: Tools & activities that help introduce newcomers to data storytelling

There has been a proliferation of tools created to assist novices in gathering, working with, and visualizing data. The problem is that many of these tools prioritize creating flashy pictures without scaffolding a learning process for newcomers to data analysis and storytelling. In this talk, we showcase the motivations behind creating the free, online platform DataBasic.io. We will demo the tools and activities that DataBasic offers as well as discuss the learning goals that they fulfill. We’ll kick off the webinar by talking about creative data literacy and the DIY Art project.

Time: Assume this activity will take 90 minutes (46 minutes for the webinar itself and 50 minutes for a selection of activities and/or discussion questions).

Timeline:

• Creative data literacy: 2:43
• Data mindset: 3:45
• Creative data literacy in a library context: 8:38
• Beyond Databasic: 11:32
• Databasic.io: 18:14
• 5-minute activity: 20:40
• WordCounter: 25:22
• Other Databasic tools: 32:11
• Sum up for tools: 37:03
• Conclusion and questions: 39:58

#### Discussion questions

1. How do the presenters define “creative data literacy”?
2. What are some datasets that might be conducive to creative data literacy? What are some methods you can use to make these datasets more accessible and meaningful to non-number thinkers?
3. There are many options for entertaining datasets that will interest your students. How can you pull these datasets into meaningful data visualizations that feed into learning and curriculum goals?
4. What types of teaching styles are more conducive to this creative approach to building data literacy skills? How might you market these skills to your education community?
5. Which curriculum areas are conducive to creative data literacy projects?
6. How can you get a community involved in thinking about how to use data creatively? What kinds of community organizations could you involve?
7. How can you tailor creative data literacy activities to meet different learning styles and different working styles?
8. DataBasic is a powerful tool to teach creative data literacy. What are some of the limitations with the website? What can you do as an educator to overcome these limitations?
9. How might you assess students’ work when they use the tools at DataBasic?
10. When would you consider exposing students to broader, more powerful tools, such as Excel or even professional tools like R?

#### Recommended activities

1. Divide participants up into four groups. Assign a different tool from http://databasic.io to each. Ask each group to preview a tool and brainstorm possible curriculum connections. After 15-20 minutes, bring the group back together to swap ideas. Appoint a note taker to record everyone’s thoughts and email them to the group.
2. Spend some time looking throughhttps://itsliteracy.org/diy-data-art-activity-guide/. What activities are suited to your age group or learning goals? What are the cost barriers for these projects? Which educators in your community will be interested in various activities?
3. Host a one-chapter book club. Go to http://dataliteracy.si.umich.edu/book and read Creating Data Literate Students’ Chapter 5, “Manipulating Data in Spreadsheets,” by Martha Stuit. How could DataBasic serve as an on-ramp to Excel-based data manipulation?

### K. Data presentation: Showcasing your data with charts and graphs

Learn to use charts and graphs to answer questions about data! Get answers to questions like: What are some rules of thumb for creating impactful charts? When is it best to use one chart type over another? and, which will readers find easier to swallow, a pie chart or a waffle chart? This webinar addresses how you can present data thoughtfully and effectively in chart and graph form. It discusses aspects of data presentation like color choice, graph type selection, general design decisions, and why certain charts are better for certain kinds of data. Discover new types of charts and rediscover old ones while learning how to put them to use most effectively.

Time: Assume this activity will take 100 minutes (40 minutes for the webinar itself and 60 minutes for a selection of activities and/or discussion questions).

Timeline:

• Data visualization warm up: 00:55
• General rules of thumb: 2:20
• Chart and graph types: 11:19
• Pie chart: 11:33
• Waffle chart: 15:48
• Bar chart: 19:03
• Dot plot: 22:02
• Line chart: 25:45
• Histogram: 29:26
• Google Public Data Explorer: 33:40

Related webinar resources:

Slide Deck: https://goo.gl/RS40TV

#### Discussion questions

1. What information jumped out at you as being particularly significant, important, or even urgent to you? To your students?
2. What forms of representing data were new to you? Familiar?
3. How do they relate to the experiences your students already have with charts and graphs?
4. What are some examples of rules of thumb about visualizing data that you can take away from this webinar?
5. What are some advantages to adding complex aesthetics to a visualization? What are some risks?
6. Discuss as a group which types of charts you prefer for different types of data, and why.
7. Are there any chart types you would always avoid? Are there any that you think are almost always effective?
8. Which is your favorite chart type? Why?
9. Which visualization types do you consider essential? Which would you consider optional considering your student population and curriculum needs?

#### Recommended activities

1. Convert to another visualization type. Find a chart or graph in a newspaper, magazine, or journal. Convert it to another visualization type, including labels. How many different kinds of visualization can your group create? Host a gallery walk to see the variety.
2. Add to your data of the week list. If you viewed Lynette Hoelter’s two webinars, we encouraged you start making a list of “data of the week” strategies and resources that you could share out via newsletters, school broadcasts, posters, in-school slideshows, etc. What from this webinar could you add to that set? How close to a year or semester’s worth of data could you get?
3. Explore available software. Open Microsoft Excel or Google Sheets software and explore the kinds of data visualization types that are available to you and your students by default. Become familiar with the options. Alternatively, visit Beam (https://beam.venngage.com/) and play with the default data on coffee consumption. How does the same data look different when different chart styles and color palettes are available? What would you want students to know before they began exploring these visualization tools?

### L. Using Social Explorer to help students gain insight

Helping students gain context for data can be a challenge. But SocialExplorer.com, which has both free and paid features, can unlock insights by mapping data to a U.S. Map. There’s nothing to download — the project is browser-based. Because it has many historical datasets from the U.S. Census and similar sources, and a variety of styles for visualizing data, students spend less time tinkering and more time analyzing data. We will cover both how to export tables and create maps using the built-in tools in Social Explorer. We will pay especially close attention to the visualization and mapping options and discuss possible ways to integrate Social Explorer into assignments. Come learn some strategies from U-M’s data visualization librarian for how you can use this tool to scaffold students’ data explorations and reveal new insights.

Time: Assume this activity will take about 100 minutes (53 minutes for the webinar itself and 50 minutes for a selection of activities and/or discussion questions).

Timeline:

• Introduction: 0:34
• Census data: 2:42
• Thinking about and choosing data: 5:51
• Social Explorer: 13:56
• Raw data: 16:30
• Visualization: 23:10
• Questions set I: 40:12
• Lesson plans: 46:35
• Recap and questions: 48:25

#### Discussion questions

1. What are the challenges of working with census data? How might technology help with these challenges? Can technology enhance our capability to gather this kind of information? Why or why not?
2. How does using the United States map to represent data change how you interact with data presented about the U.S.?
3. What are some advantages and limitations of only having access to the 2000 census data in the free version of SocialExplorer.com?
5. When would you recommend students use the different visualization styles (for example dots vs. hotspots) of the Social Explorer map?
6. When would you recommend students use different categories of data (for example, gender, income, ethnicity, mean or median, etc.) in Social Explorer?
7. How much guidance would you give students when they use Social Explorer? What are the features that are useful to know versus essential to know?
8. How might a history class, a science class, or an English class benefit from using Social Explorer?
9. Predict and discuss how census data has changed over time.
10. Can maps ever mislead you about data? Read https://www.washingtonpost.com/news/politics/wp/2017/05/13/at-last-an-electoral-map-thats-to-the-proper-scale/ . All of the maps shown are accurate, yet each tells a different story. How does changing the level of detail at which data was collected (e.g., precinct versus state-level) or adjusting the map’s size to represent the impact of votes change how you react to the data?

#### Recommended activities

1. Some of Social Explorer’s mapping capabilities are present in the U.S. Census Bureau’s free tools athttps://www.census.gov/censusexplorer/ . Ask participants to explore this site and discuss possible curriculum connections.
2. There are many additional Census tools online at http://census.gov. Divide the participants into groups and assign one group to each of these sites to explore and report back to the group.

3. Explore the Census’ visualizations available athttps://www.census.gov/library/visualizations.html .

### M. Infographics: An instructional lens

Visuals and data are ubiquitous in teens’ lives; they use them to make decisions every day, in and out of school. For us, they are a call to action. The first part of this webinar focuses on how to read and analyze infographics in a critical manner. Discussions include how to forward an effective visual argument, as well as tips and tricks for breaking down the different elements of effective and ineffective infographics. The second half of this webinar on infographics shares strategies for creating infographics as visual arguments, showing the steps students can take to know how much — and which — data will be needed to tell the intended story through an infographic. Students designers can storyframe data and images to create a visual draft of the infographic design that can be finished by hand or translated into a digital design using a computer graphics application. Presenters include an evaluation checklist and suggest strategies and opportunities for how to begin integrating infographics into your teaching.

The presenters stop occasionally to respond to attendees. While the chat window does not appear in the archived version, feel free to pause the video for discussion in lieu of the live chat.

Time: This was a two-part webinar, so please allow extra time. Assume this activity will take three hours (2 hours 5 minutes to view the two-part webinar and another hour to do the activities and discussion questions).

Timeline:

• Introduction of presenter: 00:00 - 3:48
• Definition of an infographic: 3:49
• Goals for teaching infographics: 6:45
• Posters vs. infographics: 8:03
• Making arguments with infographics: 12:15
• Evaluating infographic arguments: 38:47
• Data stories: Finding context for data: 45:21
• Curating data for context: 59:43
• How to teach disciplinary writing and thinking: 1:07:50
• Start of Part II Reading vs. creating infographics: 1:11:41
• Good infographic structures: 1:21:11
• Choosing arguments to present with infographics: 1:28:43
• Storyframes: 1:33:05
• Using infographics for synthesis: 1:42:26

Related webinar resources:

#### Discussion questions

Part I: Rationale and framework for teaching infographics

1. Infographics are not part of learning standards or most required curriculum. What interested your group in studying infographics as a pedagogical tool or strategy?
2. How does the webinar differentiate between a poster and an infographic? How does that difference resonate with you as you consider older digital formats like slide decks?
3. How does this use of claims and arguments change your understanding of infographics?
4. How can “reading from the bottom up” help students think more critically about an infographic?
5. How can you teach Tufte’s recommendations for graphical excellence to students?
6. The webinar includes an anecdote about counting the unemployment rate. How could population numbers be used in your class?
7. How can you encourage yourself and your students to look beyond cognitive biases?
8. What resources come to mind right now for “in the wild” infographics?
9. How can you teach benchmarking for data? Brainstorm benchmarks for other topics or questions.
10. While teaching benchmarking, how can you effectively teach heuristics?

Part II: Understanding the story behind the design

1. At the very start of Part II, we hear Susan Smith talking about four different charts containing the same data. Why should we be cautious about our students jumping right into chart/graph generators or infographics software?
2. How does Connie Williams define storyframing? Are there other projects in which storyframing on paper could be used as a rough draft for the design?
3. Timelines are a visualization structure students are familiar with from elementary school. What questions and strategies might you pull from this familiar form of visualization and bring into your students’ work with infographics?
4. What strategies might you use to help students learn to build story elements into their infographics?
5. What kinds of questions might you suggest that students learn to ask themselves when constructing an infographic?
6. What questions should instructors ask themselves before assigning an infographic?
7. How can storyframing help students check their claim or argument?

#### Recommended activities

1. Find and analyze flawed infographics. Set the timer for five to ten minutes and divide your staff into teams. Go on a flawed infographics hunt. Compete in small teams to find the worst infographic. What makes it so bad? Awkward layout? Lack of claim? Confusing colors or design? Poor or missing sources? More poster than argument?
2. Apply a rubric. Read Williams and Abilock’s “Recipe for an Infographic” (available at https://goo.gl/n9cvDd) and consider the rubric at the end of the article. Use the rubric to evaluate your group’s chosen infographic as if it were student work. How does the rubric as an instructional tool for students help you? How effectively does it serve as an evaluation tool? What other questions arise as you deconstruct your flawed infographic. For example, who might want to use it and why, even if it does not meet your standards for excellence? Why might someone use this infographic to bolster their claim, and what might that claim look like? What strategies might the “bad” infographic use to make it more appealing to viewers?
3. Draft an infographics assignment. Based on what you now know about structuring an infographics project and distinguishing it from a poster, brainstorm three ideas for an infographics assignments. If you have existing infographics assignments, consider how you might update them based on the strategies from this webinar.

### N. Tools for preserving your personal and intellectual privacy

Have you ever searched for something out of idle curiosity only to have targeted advertisements follow you around online? How can you combat the ever-increasing number of corporate entities looking to scrape your (and your students) online browsing information? This session will explore a range of tools to preserve your privacy, including Tor, Ghostery, DuckDuckGo, StartPage, and HTTPS Everywhere, with practical and low-effort options for preserving your personal privacy while maintaining the spirit of inquiry.

Time: Assume this activity will take 120 minutes (60 minutes for the webinar itself and 60 minutes for a selection of activities and/or discussion questions).

Timeline:

• Introduction: 3:32
• Concept of privacy: 5:51
• Chat exercise: 18:23
• Privacy tools: 21:37
• Personal privacy strategies: 33:14
• Chat exercise on strategies: 37:39
• Recap and questions: 40:24

#### Discussion questions:

1. What is your general definition of privacy? How does that definition change (or remain unchanged) when you consider the “real world” versus digital world?
2. Do you use social media sites? What advantages do you see for using these sites? How do they impact privacy? Are you mindful of what you post online? Why?
3. What are your experiences with online tracking? Do you think those experiences were advantageous or an invasion of your privacy?
4. What are your own personal needs in regards to digital privacy?
5. What are some of the issues surrounding encrypting email? How might that manifest in your educational environment?
6. What are some strategies you use for protecting your personal information online?
7. What are some methods you could use to find out how a service you use manages security and privacy?
8. Stephens mentions many different tools that can help with digital privacy. Which one, if any, is best suited for your needs? Why?
9. Stephens mentions unroll.me and the controversy surrounding the sale of personal data (see pages 172-175 for a case study on Unroll.me). The company claims that its terms of service allow the sale of this data. Since users rarely read and/or understand terms of service, do companies have any responsibilities to make invasive practices better-known to consumers? Why or why not?
10. Stephens states that no one is ever really anonymous on the web. Is that true? Why or why not?

#### Recommended activities

1. Pick one of the tools that Stephens describes and determine whether you could implement it regularly in your school.
2. In small groups, design a digital privacy awareness lesson plan for your students.

• Poitras, Laura. 2015. Citizenfour. [United States]: RADiUS TWC.
• boyd, danah. 2014. It’s Complicated: the Social Lives of Networked Teens. New Haven: Yale University Press.
• Brunton, Finn, and Helen Fay Nissenbaum. 2015. Obfuscation: a User’s Guide for Privacy And Protest. Cambridge, Massachusetts: MIT Press.
• Pariser, Eli. 2011. The Filter Bubble: What the Internet Is Hiding From You. New York: Penguin Press.

### O. Big Data and you: Normalizing the practices of privacy

You may have heard of Big Data, the process of collecting millions of pieces of data and drawing conclusions from them. From the metadata that is attached to photographs by default to the kinds of information your browser can reveal, we want you and your students to be aware of the kinds of data being quietly collected in the online and digital world so that you can make savvy, informed decisions. Seroff will share tools and resources to help you engage students and inspire active decision-making about digital privacy.

Time: Assume this activity will take 115 minutes (55 minutes for the webinar itself and 60 minutes for a selection of activities and/or discussion questions).

Timeline:

• Introduction: 0:52
• Make it meaningful: 1:30
• Pwned data activity: 7:10
• Browsers and ISP activity: 15:50
• Privacy and security: 19:10
• Apps and permissions: 25:14
• Encryption: 33:06
• Ethics of personal data privacy: 41:43
• Conclusion and questions: 49:20

#### Discussion questions

1. What are the benefits of being more aware of the data being collected about you? Can you imagine why some people feel they’d rather not know these details?
2. Which kind of password practice (e.g., setting up a password manager, making a list, stringing recognizable words together) feels like the best match for you? Why? How would you rank them in terms of practicality, security, and overall viability in your work and life?
3. Consider the photo metadata section of the webinar. Go through your phone and find your camera and photo settings. Make any adjustments that better fit your needs. Consider why you made the changes you did.
4. Go to the slide showing apps and their encryption in a Venn Diagram. Does anything on that slide change how you feel about the apps you use? Why or why not?
5. Do you see this content having a role in your school’s curriculum, family-school engagement, and/or after-school programs? What might that look like? Which ideas are the most important to communicate? What are potential areas of tension, politicking, etc., that you would want to look out for before initiating this activity with minors?
6. During the webinar, Seroff mentioned two tools that make you aware of what kind of browser behaviors can be tracked. You experimented during the webinar with http://clickclickclick.click. Now visit the second site — http://webkay.robinlinus.com — and scroll down to see what the site claims to know about you. How does this reinforce or shift your thinking? How, if at all, does the information change if you use a different browser? What might the impact be if you used a VPN (virtual private network) such as the one built into the Opera browser?
7. Some phone apps only function when given full access to the user’s personal information. Thus, when users try to change their privacy settings the app no longer works. How do you feel about the all or nothing nature of these apps? Why do you think companies have this practice? What factors do you consider to determine whether the service offered by the app is worth the breach in privacy? Where is the tipping point — the moment where you would be willing to purchase the app in lieu of sharing your information?
8. Where would you start a discussion with your students about balancing the ethics of consumer protection with the values of a free market?
9. What do you know about the history of protecting individuals’ privacy? How do those historical standards apply in the digital world?
10. A tool like ProtonMail uses extra encryption to protect your messages. What would incentivize you to switch over to an account there? What downsides might you envision? What are the potential downsides of continuing to use unencrypted email?

#### Recommended activities

1. Download a browser extension like Ghostery (https://www.ghostery.com/products/) that is designed to inform you about the tools tracking your browser history. Ghostery works with browsers including Firefox, Chrome, Safari, and Internet Explorer. Now go to five of your favorite websites. How many trackers are on those sites? Which, in Ghostery’s pull-down menu, do you decide to keep? Which do you block? How did you decide? Discuss as a group.
2. Spend ten minutes updating your online passwords, creating an account with a password manager service (like LastPass, 1Password, or KeePass), and/or setting up two-factor authentication. Make a recurring reminder in your calendar to do this again every three to six months.
3. Take a stand on one of the privacy decisions discussed in this webinar. Then:

• Create an elevator pitch (a short, 15- to 30-second talk) in which you argue for a position on that issue or advocate for a course of action.
• Create a public service announcement (live, podcast, or video) encouraging people to adopt a privacy behavior you endorse.
• Create a slide for a school’s display screens about the privacy behavior you endorse.
• Create a tutorial for how your peers can take action for the privacy behavior you endorse (e.g., walk them through how to change an Android’s photo settings).

### P. The right to obscurity vs. the digital Eye of Sauron

In Tolkien’s Lord of the Rings, the Eye of Sauron was able to surveille the unsuspecting inhabitants of Middle Earth and using the information he gathered, subject them to his will.  As we learned, it was left to Hobbits — rather shy, retiring sorts — to finally set things right and thwart his evil intentions! This session will focus on how the use of data has made it almost impossible for the average person to maintain a low profile in a high tech world. While we value the ability to connect with friends and colleagues via social media and use eCommerce with increasing regularity, do we want those interactions and transactions monitored, collected and used to scrutinize and manipulate our lives? Conversely, has the ability for us to also easily access data and information about others turned us into opportunists who “hack” into other people’s personal spaces, or even worse, do we exhibit voyeuristic tendencies and a lack of empathy for others by secretly invading their privacy. What would a hobbit do? We’ll discuss strategies to guard your right to obscurity and be more understanding of the need to appreciate this right for others, too.

Time: Assume this activity will take 90 minutes (46 minutes for the webinar itself and 50 minutes for a selection of activities and/or discussion questions).

Timeline:

• Introduction: 2:45
• Privacy vs. obscurity: 4:29
• Obscurity vs. security: 11:09
• Security vs. surveillance: 18:22
• “The Right to Be Forgotten”: 24:24
• Conclusion and questions: 30:35

#### Discussion questions

1. What is the difference between privacy and obscurity? What are the advantages and disadvantages of each?
2. What are some of the benefits to having your data online?
3. Since the early 1900s, companies have been using personal information about individuals to target them for advertising. How are the practices in the current day different and similar?
4. Do you own any loyalty cards? How do you decide whether to sign up for a loyalty card? What has been the advantage of using those cards? How do you balance that advantage with sharing personal information about your consumer habits?
5. Where do you as an individual draw a line with privacy? Consider how necessary Facebook or Linkedin can be to participate in a modern society. For example, school reunions and neighborhood associations often communicate through Facebook. How can a line be drawn to factor in the advantages some people see in social media use?
6. What information do you think is acceptable to have online and openly available? What information should be private? How would legislators successfully create a distinction?
7. Have you or someone you know ever had your personal information compromised? Describe the experience, the result, and how you addressed the situation.
9. What does the Right to be Forgotten mean for those who have passed on? What does it mean for their loved ones?
10. How do the issues of digital privacy fit (or not fit) into your school’s culture, practices, and curriculum?

#### Recommended activities

1. Explore the kinds of consumer information available, in part, by merging consumer and other data. Visit ESRI Tapestry at http://www.esri.com/landing-pages/tapestry and type in your zip code. How does the information resonate with what you know about your area? Are there errors or overgeneralizations?
2. Consider the kinds of mail you receive each week. Ask yourself how you may have ended up on that mailing list: from credit reports or other consumer data? From shared catalog lists? Visit the website of the Federal Trade Commission (FTC) at https://www.consumer.ftc.gov/articles/0262-stopping-unsolicited-mail-phone-calls-and-email and read about how you can minimize unsolicited contacts.
3. Schedule a time to check your credit report, which you can do annually at no cost and with no impact on your credit score. Visit https://www.usa.gov/credit-reports to learn more.

### Q. Student data privacy: Protecting the personal information that informs instruction

Using student data to develop and inform school curricula and classroom instruction is useful and effective, but we need to weigh the benefits of using this data for school improvement with the dangers of exposing students’ personal information. If we understand student data privacy we can be better stewards of our students’ personal information.

Time: Assume this activity will take 100 minutes (50 minutes for the webinar itself and 50 minutes for a selection of activities and/or discussion questions).

Timeline:

• Introduction: 0:41
• Student data: 1:08
• Types of student data: 3:45
• What is done with student data: 10:20
• Threats to student data: 15:27
• How to protect student data: 20:46
• National level: 21:04
• State level: 25:06
• Local level: 27:20
• Personal plan of action: 31:20
• Conclusion and questions: 38:04

#### Discussion questions

1. What kinds of student data do you collect? Where do you store it? Where do school officials and/or district store it?
2. How long is student data retained in your school district? Why do you think the data is retained for that time period? If you do not know how long student data is retained, how would you find out? What do you think is a reasonable amount of time to save student data?
3. Many teachers and librarians use apps and web-based software that have not been through a district-wide vetting process such as blogging software and web-based educational games. Do you sign your students up for third-party accounts or require that they do? What kind of information is collected about your students by those companies?
4. What do you do to protect your students’ data?
5. Consider the information about state laws and student privacy found in the Center for Democracy & Technology’s State Student Privacy Law Compendium (https://cdt.org/files/2016/10/CDT-Stu-Priv-Compendium-FNL.pdf). Look up the state laws for your state and consider how you would communicate those laws to your students, parents, administrators, and community. Several states do not have student privacy laws. If you live in one of those states, how might you use other state laws to influence your state legislature?
6. Do we need to collect as much student data as we do? Why or why not? What kinds of data should be time-limited and purged on a regular, scheduled basis? What kinds should be maintained? How did you come up with your decisions?
7. Are students aware of the data you collect about them? Why or why not? How might students become more aware of this data?
9. What kind of student data is stored on your own devices? How is it protected?
10. Could you do a data dump to remove student data from your devices? What would you do to perform a data dump? What can you do to encourage others to protect and remove student data from their own devices?

#### Recommended activities

1. Create a graphic describing how specific student data “travels” through your own school district.
2. Pick one of the items on the slide labeled “Plan of Action: What Can You Do Now?” Choose one of the action plans and apply it to your class/school/school district.
3. The Electronic Frontier Foundation published a 2017 report on student data and privacy that includes several real-world examples. Download Spying On Students: School-Issued Devices and Student Privacy at https://www.eff.org/wp/school-issued-devices-and-student-privacy and choose a few of the page-long case studies for discussion. In small groups, discuss how your school or district would respond to each situation. When uncertain, circle back to administration for answers. Over the course of a few additional meetings, come up with protocols to address these concerns in your organization.

### R. DataRefuge: Preserving data and growing literacy

Schell discusses the origins and continued efforts of the DataRefuge movement. Born out of fears of widespread removal of environmental and other governmental data that citizens and corporations alike rely on, DataRefuge has assisted in coordinating more than 40 “Data Rescue” events, bringing together librarians, developers, scientists, archivists, and other concerned citizens to archive a variety of federal data. The project has evolved into a multi-field conversation about the importance, and uneven vulnerability, of data. One of the main lessons of this project is the variety of ways that people can get involved in such preservation efforts. Schell will discuss a number of ways that participants and their students can assist in the project.

Time: Assume this activity will take 100 minutes (50 minutes for the webinar itself and 50 minutes for a selection of activities and/or discussion questions).

Timeline:

• What is DataRefuge: 2:52
• First iteration: 3:50
• Support and pre-existing programs: 6:12
• Questions before working: 7:34
• Questions I: 11:34
• Workflow: 16:46
• Results: 25:22
• Questions II: 26:09
• Current iteration of DataRefuge: 28:04
• How you can help: 34:11
• Recap and questions: 40:19

#### Discussion questions

1. How does Schell define data? How would you define or redefine data given the purpose of Data Rescue events?
2. When selecting materials to undergo a Data Rescue project, which criteria are important for selection? Why do you think those criteria are important?
3. What are some of the limitations and benefits to letting data rescue participants choose which websites they focus on?
4. How might surveys to scientists asking them to identify valuable government datasets be a useful method of prioritization? How might it limit archival practices?
5. What are some of the workflow difficulties discovered during early DataRefuge events? How do the workflow parameters influence how people can participate in this type of data rescue?
6. Where should data rescuers draw the line when they have to choose between preserving important versus vulnerable data?
7. Is the data rescue movement more effective as a bottom-up grassroots movement or as a top-down organized movement? Why?
8. If the movement is going to rely on grassroots volunteerism, how can we frame the complexities of data rescue into an activity in which novices can contribute successfully?
9. How might your classroom or school become more aware of the importance of federal data? What can you do at a classroom level to help with this effort within your broader curriculum?
10. Is there data you work with that you think is vulnerable? If so, what steps can you take to make it less vulnerable and/or more accessible? How does student privacy factor into your decision-making?

#### Recommended activities

1. Go to the Wayback Machine (https://archive.org/web/) and type in some common URLs. Explore archived versions of three to five websites. Compare those websites to the current version of those sites. What is different? What is the same? Why do you think it was important for those websites to be archived?
2. The data rescue movement has focused on preserving data at the federal level. Is there data at your community level that is vulnerable? How can your school work to preserve it?
3. Make a plan for how your school or classroom could participate in rescuing data in some way.

### S. Science in the wild: How to make the most of citizen science projects at your school

Abilock, Smith, and Williams invite you explore the many ways that citizen science projects can fit into your classroom in order to build student skills, collaboration, and confidence. Together we will explore the process of incorporating citizen science projects into a specific course or curricular area.  We will review university, governmental, and non-profit portals that offer projects, and the pros and cons of the formats and goals. We will also discuss how to discern an organization’s perspective, identify funding and scientific oversight, and how to best match your curricular objectives to a project.

Time: Assume this activity will take 120 minutes (55 minutes for the webinar itself and 60 minutes for a selection of activities and/or discussion questions).

Timeline:

• Introduction: 1:30
• Hypothetical projects: 5:10
• Citizen science definitions: 7:23
• Classroom integration: 12:25
• Classroom assessment: 16:14
• Creating or finding a project: 22:52
• Education/curriculum standards: 34:14
• Fun vs. engaging projects for your classroom: 36:16
• Recap and questions: 42:24

#### Discussion questions

1. How might citizen science projects contribute to your students’ understanding of science? How might humanities teachers use crowdsourcing projects designed for use in citizen science online portals?
2. What elements would need to be in place, and what might students learn, in an ideal citizen science or crowdsourcing project?
3. How might citizen science projects contribute to your students’ sense of community or global engagement?
4. What “soft skill,” service learning, or socioemotional benefits might accrue from participation in citizen science projects?
5. Discuss how much expertise you think is needed to participate in different types of citizen science projects.
6. What are the advantages and disadvantages of letting students pick their own projects versus committing a class to the same single project?
7. How do you think that screen-based projects differ from “in the field” projects in terms of student engagement and learning?
8. Consider Susan Smith’s discussion about how to plan your citizen science project. Are there scientists or other people outside of your school who might want to partner with you? How might you find a local partner and establish a collaborative partnership?
9. What methods might you use to assess citizen science projects in your classroom or school? Why?
10. Citizen science can be deployed during class time, but also consider it as a community outreach activity. Imagine what it would look like to add a citizen science tag-a-thon activity — a time when volunteers come together to label online content — to your school calendar? Would you invite families? Community members? Partners from not-for-profit communities? Combine it with an existing event like parent-teacher conferences or Science Fair or create a standalone? How would you organize it?

#### Recommended activities

1. Browse the physical or virtual citizen science projects curated at Scientific American (https://www.scientificamerican.com/citizen-science/). Apply the presenters’ method for deciding on a project to your own context. What, if anything, do you think you need from your educational community in order for your class/your school to start or participate in a citizen science project? (Note: If you find a project that interests you, be sure to click through to see if it currently needs volunteer support.)
2. We often ask our K-12 students to engage in inquiry about the natural world. Zoom over to Zooniverse.org, another digital portal to numerous online citizen science efforts. Take a look at the Michigan ZoomIn project, a University of Michigan project which features motion-activated photographs of Michigan wildlife. Which animals are familiar to you from your own area? How does that familiarity impact the way you approach the identification work? Now take a look at another wildlife project on the site like Penguin Watch, Wildwatch Kenya, or Elephant Expedition (all were active at press time). How does your curiosity react differently to these less familiar surroundings and species? What kinds of inquiry-oriented questions arise by engaging in various habitats? How might those kinds of “aha moments” make their way into your classroom?
3. Take a look at the Smithsonian Institution’s transcription project at http://transcription.si.edu, where several text-based artifacts from the museum’s collection await volunteer transcription. How do the currently-available projects resonate with you as potentially useful as an academic or service learning project? Try transcribing an item or two. How much time does each item take? What coding structures did you need to acquire prior to use?