Educ 206: Data Visualization For All
Fall 2025 Syllabus
Our course meets in-person on Mondays and Wednesdays 11:30am-12:45pm in classroom TBA
Instructors
- Professor Jack Dougherty, Trinity College, Hartford CT. Email me a quick question or schedule a Zoom appointment on my calendar.
- Teaching Assistant Nellie Conklin ‘26 - contact and scheduling info on Moodle
- Research Assistant Ali MacDougall ‘26 - contact and scheduling info on Moodle
Course description: How can charts and maps tell meaningful stories? How can they mislead us from the truth? In this introductory hands-on course, we will create data visualizations in order to better understand design principles and develop a critical analysis of the field. Students will learn skills in both quantitative reasoning and digital storytelling as we advance from beginner tools to editing code templates. For the community learning component, our class will build interactive charts and maps on a public policy issue with a Hartford-area partner organization. No coding experience is necessary, but curiosity is required.
- Fulfills Numerical and Symbolic Reasoning (NUM) requirement.
- Fulfills Research Methods requirement for Ed Studies majors.
- Cross-referenced with Community Learning, Public Policy & Law, Writing & Rhetoric, Urban Studies.
- Enrollment limited to 19 students.
Community Learning Project
Our project and Hartford-area community learning partner this semester:
School Based Health Centers: Melanie Wilde-Lane (Executive Director) and Isabel Gonillo (Program Assistant) from the Connecticut Association for School Based Health Centers. Their nonprofit organization advocates for medical, dental, and mental health services that are provided in over 300 public schools across the state. They have asked us to create data stories to help them answer questions such as: How does access to these health centers vary by family income and school district funding? How does free preventive care improve long-term health outcomes and reduce government costs for emergency room visits?
Intro video for CT Association of School Based Health Centers project, Fall 2025
Course Materials and Tools
- Two open-access books are freely available online (or you can purchase print editions).
- Jack Dougherty and Ilya Ilyankou, Hands-On Data Visualization: Interactive Storytelling from Spreadsheets to Code (O’Reilly Media, Inc., 2021), https://HandsOnDataViz.org.
- Catherine D’Ignazio and Lauren F. Klein, Data Feminism (MIT Press, 2020), https://data-feminism.mitpress.mit.edu.
- Bring a laptop computer (Mac, Windows, or Chromebook) to every class. Install more than one browser (such as Firefox, Safari, Chrome) for testing purposes. Tell me if you need a temporary laptop loaner.
- You will need to sign up for several free web services (such as Google Drive, Datawrapper, GitHub). See my list of recommended free digital tools in this course.
Learning Goals and Assessments
In this course you will demonstrate the knowledge and skills you have developed to meet 12 broad learning goals (with more specific sub-goals listed in the schedule further below):
- Strengthen Your Spreadsheet Skills
- Find and Question Your Data
- Clean Up Messy Data
- Make Meaningful Comparisons
- Chart Your Data
- Map Your Data
- Transform Your Map Data
- Edit and Host Leaflet Code on GitHub
- Detect Lies and Reduce Bias
- Explore Leaflet Map Code Templates
- Tell and Show Your Data Story
- Embed on the Web
Your progress toward these learning goals will be assessed in three ways:
A. Open-Book Weekly Quizzes
- The purpose is to demonstrate your knowledge and skills through questions that emphasize conceptual understanding and how to apply it in new contexts. You will have more than one opportunity to successfully complete each quiz while working independently with your notes, readings, and any web resources.
- Each week, select any 2-hour period during the quiz window (typically a four-day window from Wednesday afternoon to Sunday 9pm) to complete a Moodle quiz of around 5 questions on the designated learning goal. You may see different versions of questions than other students, but all questions address the same goal.
- Students can make at least two quiz attempts during the typical four-day window. Short-answer questions will be scored automatically by the computer, and show-your-work questions will be scored manually by the instructor. If you respond incorrectly to an auto-scored question, the quiz will offer advice and allow you to try again. If you respond incorrectly to a manually-scored question, the instructor will offer advice via email or a meeting and allow you to try again before the quiz window closes, if sufficient time remains.
- HINT: Start your quiz by Friday 12 noon if you want to receive the instructor’s feedback on show-your-work questions before the quiz window typically closes on Sunday 9pm. If you wait until the last minute and don’t start your quiz until Saturday or Sunday, you may not receive feedback from the instructor in time to do a second attempt.
- Before you start the quiz, prepare by reading assigned chapters, doing practice exercises, and discussing the material with classmates who have not yet started it.
- When you start the typical 2-hour quiz period, you may use your materials (including your notes, the online book, and any Internet content or tools), but you must work independently and you may not communicate about the quiz content in any way (except with the instructors) until the quiz has closed. See the Intellectual Honesty and Artificial Intelligence policy further below.
- If you do not begin a quiz or demonstrate sufficient effort during the quiz window, a 20 percent late penalty will be deducted for every 12-hour period beyond the deadline. Exceptions are granted only for documented health or family emergencies.
- 12 learning goals x 5 points per quiz (but no quiz for Goal #11) = 55 points
B. Building Data Stories
- The purpose is to show your original work in building different stages of data visualizations and written narratives that explain why and how it matters to our community partners. See the Intellectual Honesty and Artificial Intelligence policy further below.
- Depending on the stage of the build, your work will be evaluated by the instructor, your peers, or guest experts, based on a rubric.
- 8 stages x 5 points = 40 points. A 20 percent late penalty will be deducted for every 12-hour period beyond the deadline, with exceptions granted only for documented health or family emergencies.
C. Class Participation
- The purpose is to encourage active learning and accountability. Each student begins the course with 5 participation points. During class, you may be randomly called on to discuss a concept in our reading, or to share your computer screen for everyone to view while we learn tools and build data stories. You do not necessarily need to know the correct answer. But if you are not present or not able to participate when called, one point will be deducted each time from your participation score.
- Exceptions will be granted for any pre-scheduled absences (such as religious observations or any pre-planned events, if you email me at least one week ahead of time), or health or family emergencies (if you email me at least one hour before class). If you have health concerns that prevent you from attending class in person (such as Covid or other illness), email me at least one hour before class, and if feasible, request permission to participate remotely. Learning on Zoom is not as good as learning in real life, but it’s better than not attending at all. Last-minute requests will not be granted.
Summary
55 points quizzes + 40 points data stories + 5 class participation = 100 total points. In this course, unsatisfactory work (below 70%) falls in the D or F range, adequate work (70-79%) in the C range, good work (80-89%) in the B range, and outstanding work (90 to 100%) in the A range. Each range is divided into equal thirds for minus (-), regular, and plus (+) letter grades. For example, 80 to 83.33% = B-, 83.34 to 86.67 = B, and 86.68 to 89.99 = B+. Access your individual assessments on the password-protected Moodle site for this course at https://moodle.trincoll.edu.
Intellectual Honesty and Artificial Intelligence
- You are responsible for following the Intellectual Honesty policy as described in the Trinity Student Handbook.
- Artificial intelligence tools are not prohibited in this course, but think carefully before using any technology that might interfere with your learning. Large Language Models (LLMs), such as ChatGPT by OpenAI or Claude by Anthropic, can be helpful for repetitive coding tasks or proofreading paragraphs you’ve already composed. But LLMs also create plausible-sounding text with invented facts and bad calculations. LLMs also raise ethical questions about unpaid labor, energy usage, harmful biases, and safety for humanity. Don’t cheat yourself out of an education by substituting LLM-generated responses in place of authentic learning.
- For online quizzes, you may use your materials (including your notes, the online book, and any Internet content or tools), but you must work independently and you may not communicate about the quiz content in any way (except with the instructors) until the quiz has closed. If any doubts arise, the instructor may require you to show your work, retake a quiz under direct supervision, or refer a case to the Honor Council.
- For build assignments, You (and your partner) are expected to create all original content (text and visualizations), with proper citations to any paraphrased or quoted text written by others, image credits to any visuals produced by others, and a methods section that describes all tools used and how. If any doubts arise, the instructor may require you to show your work, or independently reproduce content under direct supervision, or refer a case to the Honor Council.
Academic accommodations
Please notify me before our third class session, and schedule an appointment on my calendar to discuss how we will implement your approved plan. For those students with accommodations approved after the start of the semester, a minimum of 10 days’ notice is required. Learn more at the Student Accessibility Resource Center.
How to Succeed in this Course
- Bookmark this online syllabus and check it for important updates, which will appear in bold.
- Keep a calendar (paper or digital) to manage your time and meet deadlines.
- Bring a laptop (with a fully-charged battery) to every class, and turn off distractions to help you (and others) focus on learning. Set notifications on digital devices to “Do Not Disturb.”
- Use a password manager to keep track of your digital accounts. See my introduction to Bitwarden, an open-source password manager with free core features for Windows/Mac/Linux computers, all major web browsers, and iOS and Android mobile devices.
- Take initiative and ask questions: during or after class, via email, or by appointment on my calendar. If you don’t understand something, other students probably are puzzled, too. Go ahead and ask.
- Meet up with other students outside of class. Create a small study group to review the course material and work together. The secret to success in college is teaching yourselves how to learn new material.
- If anything is interfering with your learning, email or talk with me. I care about how you’re doing in life, not just in our classroom.