Dashboards for Discovery & Learning Applications

Course Introduction:

This site has been developed as a supplemental resource page for your course.  (All readings and assignments will be available and submitted through Canvas.) In this course we will explore the emerging scholarship on dashboards in learning analytics. As a young area of research, many questions are unanswered, and as a human-center field, many questions have no single one right answer.  To make decisions, we will draw on research from a wide range of fields in and outside of the learning sciences and learning analytics community. 

This includes scholarship on:

• The field of Learning Analytics more broadly

• Data Visualization, Statistics, and the Visualization Sciences

• Universal Design, Neurodiversity, and Accessibility

• Semiotics and Cultural Metaphors

• Ethnomathematics and Sociocultural Differences in Learning and Visualization

• Number Sense, Data Literacy, etc.

• Algorithmic Biases

• Cognitive Biases

• Participatory Design, User/Ux Design

And, we may sometimes draw from fields like health communication, which has longer research traditions in both (a) data driven decision making and (b) communicating complicated data/processes to non-experts.

Table of Contents:

1. Tools: A wide range of tools have been assembled for you here as well, they include:

   • Data Vis Tools:

   • Pick a Chart/Feature:

   • Generating Faux Data:

   • Data Wrangling Resources:

   • Tableau YouTube Resources: This page has aggregated high-quality YouTube videos on how to use Tableau. Some of them will be specifically assigned to you over the course of the semester, but others are here for you on an as-needed basis.

   • Other Stats/Data Mining Resources:

2. DV Principles & Practice

   • Data VIsualization Principles: This page includes broad principles of dashboard design as well as research from the visualization sciences.

   • Data Vis Examples: This page includes a very short list of videos on how to read charts, alongside a longer list of both good and bad data visualizations that may help you to practice your critiquing skills.

3. Data Sources & Learning Environments: This page includes rescources that can help you to pick a learning environment for your final project.

4. Human Considerations in Dashboard Design: Includes an introduction to the goals we have for dashboards in this class.

   • Agency: This page introduces a working definition of agency and questions we should ask ourselves when we are designing a dashboard.

   • Motivation Theories: This page provides an exceptionally high level overview of some of the theories of motivation in education. Use this as a starting point for search terms any literature searches.

   • Self Regulated Learning (SRL): Provides an introduction to the COPES model of SRL

   • Additional Readings: Provides resources that might be relevant to course topics but were not assigned.

5.  About: This page has information about the course and also offers a link for you to suggest resources.