Data Across Disciplines

THINKING ABOUT DATA ACROSS THE DISCIPLINES

Data is interdisciplinary and thus shows up across our curriculum. However, sometimes we use the same words but mean different things, in each of our disciplines. And sometimes we use different words but mean the same thing. This can make it particularly challenging for novice data users (aka our learners) to apply and integrate their data skills cohesively. Let’s explore some examples:

Discussing Relationships:

• Math: direction of relationship (mathematical +/-); slope; type of function = form of relationship (e.g., linear); relation/relationship = input + multiple possible output variables

• Science: positive, what does that mean for variables; what does slope tell us about variables; no relationship = constant; continuity = no breaks over time/space; patterns over time, in space; type of relationship in terms of pattern (shape)

• Social Studies: beneficial vs detrimental of outcomes of trend; consistent/continuity in time/space

Discussing Direction of Patterns in Data:

• Math: value goes up/down

• Science: value goes up/down

• Social Studies: not often used

POSITIVE/NEGATIVE:

• Math: when one variable values increase the other variable values increase

• Science: when one variable values increase the other variable values increase

• Social Studies: when there are beneficial outcome(s)

FLUCTUATES:

• Math: not often used

• Science: variable values changes over no consistent pattern or period

• Social Studies: inconsistent/volatile

CYCLICAL:

• Math: variable values increase and decrease not over a fixed/consistent period

• Science: variable values increase and decrease not over a fixed/consistent period

• Social Studies: things go up and down

PERIODIC:

• Math: fit a periodicity function to the increase and decrease of values over a fixed/consistent range

• Science: variable values increase and decrease over a fixed/consistent period of time

• Social Studies: periods of time in history

Other aspects of data:

• Linear: A straight line

• Non-linear: A non-straight line (e.g., exponential, polynomial)

CAUSE & EFFECT: WHEN DISCUSSING WHAT CAN DRIVE A RELATIONSHIP...

• Math - causation, correlation with r2; input/output; explanatory vs. response variables

• Science - independent/dependent variable interaction

• Social Studies - cause & effect

PROOF/PROVE: WHEN DISCUSSING WHAT THE DATA SHOW....

• Math - step-by-step sequence, make assertion and support with rules to support conclusion (not by example, only by variables/logic)

• Science - never use this term (rather all about evidence justifying conclusions)

• Social Studies - credibility/bias of evidence of examples; sequence of events/timeline