Fostering Strategy #3: Instructor teaches formal attributes and affordances of a standard type of visualization

(most recent update 24jan2018) (return to workshop front page)

Contributors: Kim Kastens, Tim Shipley

Description:

  • Instructor (or instructional material) didactically explains specific attributes of certain kinds of standard visualizations, what they are used for, and how they work to represent an aspect of the world.
  • Typically, these are data-driven visualizations, but one can think of non-data-driven examples as well (for example, architects' elevations, section, axonometric, and isometric visualizations of not-yet-built buildings)
  • Typically, students then interpret or create examples of the types of visualizations just taught.

Examples:

Examples of topics suitable for this approach:

  • Map projections: example from Peter H. Dana at the University of Colorado
  • Coordinate systems: example from Math Planet
  • Types of graphs: example from Statistics Canada
  • Earthquake focal mechanisms ("beach ball diagrams"): video example from IRIS

Examples of activities to build or assess mastery of formal attributes and affordances:

  • "I do--We do--You do" (Model, Coach, Practice): Instructor demonstrates, the class applies the new formalism together; then students do further examples on their own.
  • Students find examples of professionally-created visualizations that use various of the just taught visualization formalisms (for example, different types of graphs), and explain why this was an effective (or ineffective) way to represent the phenomenon. Sources for students to mine:
    • hhmi BioInteractive: Provides access to a wide range of visualizations, professionally vetted, in life sciences.
  • Liben (1997) lays out methods for assessing children's mastery of how maps work. Two of these methods seem potentially generalizable to all types of visualizations:
    • Representational correspondance methods: learner or subject is asked to relate, in some way, one representation to another representation of the same phenomenon. To explore understanding of the formal attributes, learner can be asked to articulate the "transform function" whereby each of two types of visualizations represent the referent system, and why two different types of visualizations are needed or useful.
    • Meta-representational methods: learner or subject is asked to describe or reflect on one or more relations between the representation and the referent. For example: what are the different ways to indicate the scale of a map, and what are the advantages and disadvantages of each?

Affordances of this strategy/what it is good for:

  • Less time is needed for the instructor to explain this kind of material than would be required for a more student-centered discovery learning process. Especially for learners who are already committed to learning in the discipline, this approach can be very efficient.
  • Instructor can position the material in the context of the field being taught, can emphasize the conventions used in the domain, and can explain what problem the convention was developed to solve.
  • Understanding formal conventions prepares the learner to read and understand the literature in the field.
  • This strategy can also develop students' and teacher's awareness of why visual conventions are useful in general: they can make the graphic language more efficient and more effective.
  • Mastery of the normative representational language of the discipline is prerequisite to achieving "Level 4: Semantic Use of Formal Representations" in Kozma & Russel's (2007) articulation of Representational Competence Levels.

Potential pitfalls & challenges:

  • If the material is taught in one context, students may not successfully transfer it to a different context (classic problem of techniques learned in math not transferring to science class.)
  • Modern technology allows learners to create visualizations that look good (especially to the novice eye), even if the learner hasn't understood the underlying way in which the visualization works to represent the referent (e.g. using a line graph for nominal data where a bar graph would be suitable). Such lack of understanding can be hard to diagnose.
  • Even though it can be quick to state or read or view an exposition about the affordances and attributes of a type of visualization, it can take a much longer time for learners to actually internalize how and when to use a type of visualization, and how to make best use of all of its features. Instructors tend to under-estimate how much time will be needed for this.

Emergent insights:

  • Instructors may think their work is done after they have presented this material in a clear and well-organized fashion. However, experience shows that are many ways that learners' understanding can be incomplete:
    • Learners may have procedural knowledge (for example, be able to explain how various map projections differ), but still struggle to apply this knowledge to practical situations.
    • Learners may have grasped how the visualization was created from the data (for example, how the map projection works) but failed to understand attribute of how the data were collected (for example, the difference in resolution between satellite-based bathymetry and ship-based bathymetry).
    • Learners may be able to repeat what the instructor said, but their understanding can be "brittle" and fall apart when faced with the need to transfer to a slightly different situation.
  • This viability of this strategy may be dependent on the learners' initial familiarity with the phenomenon being represented and the content being taught. If the content is unfamiliar and can only be accessed via representation, it might make no sense to contemplate teaching the formal attributes of the representational system independent of the conceptual content.
    • Case 1: Phenomenon is familiar: map projections. All that a student needs to know to begin to learn about map projections is that the globe is roughly spherical and maps are planar. That's enough knowledge about the referent to open a conversation about map projections. Virtually all students walk in the classroom door with this knowledge, and instruction can build from there.
    • Case 2: Phenomenon is partially familiar: Beach balls diagrams for Earthquake first motion direction: This specialized representation shows direction of motion of blocks of the Earth's crust in 3-D space relative to position on the Earth's surface. Although the notion that pieces of the Earth move may be unfamiliar, the general concept that things (cars, people) move relative to each other, and that it can be meaningful and informative to know the direction of motion, is familiar.
    • Case 3: Phenomenon is unfamiliar: Various representations of molecules: People have no direct lived experience with molecules, and so the only route to learn about the molecular nature of matter, molecular interactions, and other chemical concepts is via representations. In this case, it may not be possible to separate teaching about the representation from teaching about the referent.

Research Questions:

  • When learners have been taught the formal attributes of an unfamiliar visualization type in the abstract, what then has to happen for the learners to be able to apply this knowledge practically, e.g. to solve a problem, answer a question, or defend a line of reasoning?
  • What is gained by encountering visualizations of similar format across multiple domains? Does awareness of the utility of formal properties arise from being exposed to such pedagogy across a range of data types/science domains?

References & Credits:

  • Clark, A. C., & Wiebe, E. N. (2000). Scientific visualization for secondary and post-secondary schools. Journal of Technology Studies, 26(1).
  • Kozma, R., & Russel, J. (2007). Students becoming chemists: Developing representational competence. In J. K. Gilbert (Ed.), Visualization in Science Education (pp. 121-146): Springer.
  • Liben, L. S. (1997). Children's understanding of spatial representations of place: Mapping the methodological landscape. In N. Foreman & R. Gillett (Eds.), Handbook of Spatial Research Paradigms and Methodologies, Volume 1: Spatial cognition in the child and adult (pp. 41-82). East Sussex, UK: The Psychology Press (Taylor & Francis Group).