Data Products - Badge

LASER Institute Foundation Learning Lab 4

The final activity for each learning lab provides space to work with data and to reflect on how the concepts and techniques introduced in each lab might apply to your own research.

To earn a badge for each lab, you are required to respond to a set of prompts for two parts:

• In Part I, you will reflect on your understanding of key concepts and begin to think about potential next steps for your own study.

• In Part II, you will create a simple data product in R that demonstrates your ability to apply a data analysis technique introduced in this learning lab.

Part I: Reflect and Plan

Use the institutional library (e.g. NCSU Library), Google Scholar or search engine to locate a research article, presentation, or resource that applies learning analytics analysis to an educational context or topic of interest. More specifically, locate a study that makes use of one of the data structures we learned today. You are also welcome to select one of your research papers.

1. Provide an APA citation for your selected study.

2. What educational issue, “problem of practice,” and/or questions were addressed?

3. What maked this a “good” data product?

4. In your self-selected article, who were the intended beneficiaries of the work and what “change ideas” might the result imply for them?

5. Finally, how were modeling used to support analysis, if at all? Were these practices new to you?

Draft a new research question of guided by the the phases of the Learning Anlytics Workflow. Or use one of your current research questions.

1. What educational issue, “problem of practice,” and/or questions is addressed?

2. Briefly describe how you might “polish” a data visualization for the educators you will share it with?

3. How might you include education practitioners (e.g teachers, admin, policymakers, etc) to be involved in the study?

Part II: Data Product

We have completed the phases of the Learning Analytics Workflow but really have only scratched the surface with the power of tidyverse in each of these phases.

1. Select. Communicating what one has learned involves selecting among those analyses that are most important and most useful to an intended audience, as well as selecting a form for displaying that information, such as a graph or table in static or interactive form, i.e.a “data product.”

2. Polish. After creating initial versions of data products, research teams often spend time refining or polishing them, by adding or editing titles, labels, and notations and by working with colors and shapes to highlight key points.

3. Narrate. Writing a narrative to accompany the data products involves, at a minimum, pairing a data product with its related research question, describing how best to interpret the data product, and explaining the ways in which the data product helps answer the research question.

Using one of the data sets provided in the data folder, your goal for this lab is to complete a data product.

You have two options for completing the Data Product portion:

• Create a Data Story with our current data set
  • Develop a research question
  • Add ggplot visualizations
  • Modeling visualizations
  • add a short write up for the intended stakeholders
  • flexdashboard_template.rmd in lab4 folder if needed.
  • Create a data product using your own data.
• Make sure to publish the dashboard and share that link in here

FLEX DASHBOARD published link below:

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Share code:

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Knit & Submit

Congratulations, you’ve completed your Foundation Badge on Learning Analytics Data Product! Complete the following steps to submit your work for review by: Congratulations, you’ve completed your Data Sources Badge!

Complete the following steps to submit your work for review by:

Complete the following steps to knit and publish your work:

1. First, change the name of the author: in the YAML header at the very top of this document to your name. The YAML header controls the style and feel for knitted document but doesn’t actually display in the final output.

2. Next, click the knit button in the toolbar above to “knit” your R Markdown document to a HTML file that will be saved in your R Project folder. You should see a formatted webpage appear in your Viewer tab in the lower right pan or in a new browser window. Let’s us know if you run into any issues with knitting.

3. Finally, publish your webpage on on Posit Cloud by clicking the “Publish” button located in the Viewer Pane after you knit your document. See screenshot below.

Foundations Learning Badge 4

Congratulations, you’ve completed Foundations Learning Badge 4! To receive credit for this assignment and earn the an official Foundations LASER Badge, share the link to published webpage under an empty Badge Artifact column on the 2023 LASER Scholar Information and Documents spreadsheet: https://go.ncsu.edu/laser-sheet. We recommend bookmarking this spreadsheet as we’ll be using it throughout the year to keep track of your progress.

Once your instructor has checked your link, you will be provided a physical version of the badge below!