SDP Winter Workshop 2025

** This session is open to both C15 and C16 fellows **

PREWORK: None

SESSION DESCRIPTION:
Managing your own data projects is challenging, but as your career progresses, you may also take on the responsibility of managing people within data teams. This adds a new layer of complexity, particularly in the K-12 education sector, where navigating union and non-union employer groups can present unique challenges.
This session focuses on the strategies, tools, and leadership skills needed to build and lead high-performing data teams that consistently deliver impactful results. It is designed to help early-career data professionals gain a clear understanding of the tools, approaches, and mindset required for supervising staff effectively. By the end of the session, attendees will be better equipped to transition into leadership roles and set themselves—and their teams—up for success.

SESSION MATIERALS:

** This session is open to both C15 and C16 fellows **

PREWORK: None

SESSION DESCRIPTION:
Clustering is a fundamental component of data science’s machine learning toolbox. This session will explore the foundational concepts of clustering, and, through practical examples, provide insights into how it may be useful for analyzing education-related data. As part of this session, an R-based Jupyter notebook will be provided to participants as a reference if they wish to implement k-means clustering in their work.

What is clustering?

• In which situations would clustering be helpful/appropriate?
• How do you conduct a clustering analysis and interpret the results?
• Use some examples from ETSU’s work to walk through the process

SESSION MATERIALS:

** This session is open to both C15 and C16 fellows **

PREWORK: ** Submission Required ** 

Submit your own data or problem prior and we will pick a couple to use as a walk-through example of the process. submit your work to this folder here by January 31.

Those interested in walking through the process of narrowing their data focus can submit their data set, or a description of what their data is, along with anything they are being asked to do with the data, or any information they have about why they are using the data.

SESSION DESCRIPTION:

This session invites participants to submit their data sets or describe their data challenges, providing a hands-on experience in narrowing down data focus effectively. Learn the importance of honing in on the right data parameters before diving into analysis, and discover the research-backed 6 Steps to streamline your data focus for more impactful results. Additionally, explore why data literacy and strategic thinking are crucial components to implement alongside data tools. Join us to enhance your data strategy and make informed, data-driven decisions with confidence.

SESSION MATIERALS: See below

** This session is open to both C15 and C16 fellows **

PREWORK: ** No Submission Required ** 

Come with access to your LLM of choice. A paid account is not required for most use cases.

SESSION DESCRIPTION:
This workshop showcases the many ways that other fellows are integrating LLMs into their day-to-day work right now. This session pushes beyond abstractions and demonstrates practical applications proven effective by fellows in our cohort. We will highlight applications across quantitative, qualitative, and mixed-methods work. Examples include named entity recognition for user tracking, developing evaluative rubrics aligned with standards, and theorizing counter-arguments for high-stakes presentations. Participants will learn practical techniques to adapt LLMs for automating processes, generating insights, and enhancing workflows, while small-group collaboration will provide support for brainstorming and developing personalized use cases. Attendees will leave with actionable ideas and a clear starting point for leveraging LLMs in their own work.

SESSION MATIERALS:

** This session is open to both C15 and C16 fellows **

SESSION RECORDING: To Be Posted

PRE WORK:
Participants should complete the brief pre-session survey here by January 29th. Responses will help inform facilitation of the session. 

SESSION DESCRIPTION:
The journey to impactful change begins with the end in mind, and it's helpful to have a map to guide the way. Learn about how Guilford County Schools developed and applied the Roadmap to Success framework to systemically support strategic implementation and progress monitoring. Participants will leave with proven tools and processes, including Theories of Change, Logic Models, and Progress Monitoring Plans, to foster continuous improvement. Grounded in implementation science, the session emphasizes strategic alignment and data use to prevent "initiative-itis" - a focus on busyness over productivity. Through interactive discussions and reflection, participants will explore practical applications and uncover opportunities to build systemic progress monitoring in their own contexts, ensuring meaningful and sustainable results.

SESSION MATERIALS:

SESSION RECORDING: To Be Posted

PREWORK:

STEP 1: Please rank your top two choices of the above Ethics Breakout Sessions by January 24th.  You will be assigned to your session by Friday, January 31st. You will need to complete the pre-reading based on the session you are assigned (if applicable) before the breakouts on February 10th.

Survey: https://forms.office.com/r/dHGhsZmUur

STEP 2: Complete by January 31st . Please accept 3 $10 Donors Choose gifts that you can distribute to any project(s) you want. Donors Choose is a nonprofit organization that allows you to donate directly to public school classroom projects. Your first step is to search Donors Choose for the projects you wish to invest in. Then, find your name in this spreadsheet and use the three assigned gift codes next to your name to make three ten-dollar donations. You can allocate all of them in any configuration (all to one project, for example), but they must be in 10$ increments. Add the name of the project you supported with each code and the link to the cause. Enjoy!

STEP 3: Complete after Day 1 Session on February 4. Complete this self-assessment and submit the copy of your responses to this folder prior to the Day 2 session on February 10.

SESSION DESCRIPTION:
The rapid pace of data innovation has not been matched by a parallel growth in the analysis of the ethical implications of our work. Data analytics has been long conceived to be value-neutral, a technocrat's endeavor. However, working with education data is ultimately a human endeavor, beset with choices that will have real implications for students, educators, and families.

The most important and challenging choices SDP fellows will face are not necessarily about coding or models, nor will they be straight-forward options between good and bad. This session will focus on four traditional frames of ethical deliberation and apply them to common data ethics scenarios. SDP Fellows will attend one of the following breakout sessions:

Ethics of Gaming – Michael LaMont, Cohort 7 on the Atlanta Public Schools Cheating Scandal

Ethics of Experimentation – Cara Jackson, Cohort 5 on when it is okay and not okay to experiment with students

Ethics of Privacy – Marika Pfefferkorn, Twin Cities Innovation Alliance to present on data sharing early warning indicator data across public agencies

Other Session Materials:
- Data Ethics Scenarios
- Data Ethics Workbook

** Note this session is for C15 Fellows. Please indicate your preference for your breakout session here. Fellows will be assigned a breakout session **

SESSION RECORDING:

PREWORK: ** No Submission Required **

• Wrong Answer, New Yorker
• Optional: The Long‐Run Effects of Teacher Cheating on Student Outcomes
• Optional: Black Lives and the Spectacle of the Atlanta Cheating Scandal

SESSION DESCRIPTION:
Ethics of Gaming – Michael LaMont, Cohort 7 on the Atlanta Public Schools Cheating Scandal

Examine the case of the cheating scandal in Atlanta (and others). What happens when you discover something that looks suspicious in the data? What risks do you face when you discover a colleague is doing something fishy? What should you do?

SESSION MATERIALS:

SESSION RECORDING: To Be Posted

​​​​PREWORK:
Fellows should read chapter 5- Identification from The Effect by Nick Huntington-Klein.

SESSION DESCRIPTION:
In this session, you’ll review the fundamentals of causal inference and learn about common quantitative research designs that, given the right circumstances, can produce causal estimates. We will in particular discuss the key assumptions that must be met to support identification so you leave equipped with the knowledge needed to conduct your own rigorous research as well as to be a critical consumer of research literature/causal claims. Come prepared with your capstone question or other research question for ongoing work, as this session will be interactive and will include time for you to plan your upcoming analyses.

SESSION MATERIALS:

SESSION RECORDING: To Be Posted

PREWORK: ** Submission Required **

1. Please submit one survey item that you wish to focus on. It may be your own work, something your organization has produced, or something from the wider field. Submit to this folder.
2. Consider the larger survey that this item is embedded within and write 2-3 brief sentences about the survey’s strengths and how it might be improved. Please include what you aim to assess with this tool (e.g., teacher satisfaction, student engagement, school climate).
3. Please submit 1 & 2 with a link, screenshot, or other upload of your survey or survey item.

SESSION DESCRIPTION:
In this session we'll frame surveys as “conversations” designed to better understand and take the perspective of constituents in your school community. Through that lens, we will discuss key principles of effective survey design, including how to decide whether to use an off-the-shelf survey, adapt an existing measure, or develop your own from scratch. Surveys adhering to best practices not only yield reliable data and actionable insights that form the backbone of sage institutional decision-making, but they can help foster stronger relationships within the community when respondents feel heard. By contrast, traditional surveys (that are often riddled with substantial measurement error) can cost schools in dollars, morale, and credibility as they often result in misguided policies and interventions.

After discussing these key principles, we will then apply them to a variety of survey questions. To that end, we ask that you prepare for this session by reflecting on surveys already in use in your organization. If possible, please share an item with us that you would like to improve, think is pretty good already, and/or would like feedback on.

Your survey may be selected for us to workshop collectively during the session. If you would prefer your visual not be used in the presentation or if the survey cannot be made public, please just let us know in your submission.

SESSION MATERIALS:

SESSION RECORDING: To Be Posted

PREWORK: **Submission Required**:

Submit a visual to this folder and read about a critique tool.

Please find one visual (one chart/graph/table, or one element of a larger dashboard) that you wish to reflect upon. It may be your own work, something your organization has produced, or something from the wider field.

Consider the visual, and write 2-3 brief sentences about what are the strong elements of the visual, and what you think may be improved. Please submit these sentences with a screenshot of the visual itself, by January 31. You may upload these together or separately.

Note, please make sure that any sensitive data in your visual is redacted. Your visual may be referenced or discussed in the session. If you would prefer your visual not be used in the presentation, please state this in your submission.

You should also read one of the two articles linked below. Each article represents a different way of reflecting on how well data visualizations accomplish their goal. The Few article is more holistic or big picture in its approach. The We All Count blog post is more recent and zooms in on one more specific aspect of a data visualization—its legend—as a way to reflect on its effectiveness. Please read the one article you feel suits you best (though you may read both if you desire):

• We All Count’s Reverse Reverse-Engineered Legend 
• Stephen Few’s Data Visualization Effectiveness Profile 

SESSION DESCRIPTION:
In the workshop session Principles of Effective Data Visualization, we'll discuss some key principles of effective data visualization, and through this build a common language for what makes an effective visual. We will then apply these lessons to our own visuals and those of our peers. Though this is a non-technical session, it will nonetheless be hands-on through feedback and dialogue.