By Jonathan Howell

Many instructors acknowledge the importance of quantitative literacy in non-STEM fields and may themselves use advanced tools for data analysis, statistics and visualization.  But how, if at all, does an instructor introduce quantitative methods into the classroom without overwhelming and disengaging students who may have been drawn to the field precisely because it has not traditionally required any skill or interest in science, technology, engineering or math?

This presentation describes, in a Goldilocks-style narrative, the evolution of an assignment for linguistics students in which they were asked to measure vowels from their own speech and to plot their measurements on a graph in order to re-create the standard organization of vowel sounds found in textbooks.  The first, low-tech iteration required students to make their visualization using paper and pencil.  The second, medium-tech iteration required students to use a familiar but restrictive software (Microsoft Excel).  The third iteration required students to use the powerful but overwhelming statistical computing environment R.  Finally, the fourth iteration required students to use an interactive, Web2.0-friendly application, which was easily created by the instructor using R, but required no knowledge of R by students.

In the second half of the talk, we compare the different versions of the assignment according to the Best Practices for Quantitative Reasoning Instruction published by the Numeracy Infusion Course for Higher Education, including:

      • real world applications and active learning, including discovery methods;
      • pairing QR instruction with writing and critical reading;
      • using technology, including computers;
      • collaborative instruction and group work;
      • pedagogy that is sensitive to differences in students’ culture and learning styles; and
      • scaffolding the learning process and providing rich feedback and opportunities for revision.


  • Quantitative literacy (like other literacies) is important across the curriculum
  • High-tech research tools can and should be used for instruction, but may require modification to accommodate student skill level

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