Proposal Title

Quantitative Reasoning: Crossing Thresholds

Session Type

Workshop

Room

P&A Rm 117

Start Date

July 2015

Keywords

Quantitative reasoning; quantitative literacy; post-secondary science education; threshold concepts; interdisciplinary

Primary Threads

Teaching and Learning Science

Abstract

Conversations about teaching and student learning with faculty across many of the science disciplines will invariably lead to a number of shared concerns. One such concern typically revolves around quantitative reasoning, which can be defined as a competency and comfort in working with numerical data and applying such skills to solving quantitative problems within a range of contexts and everyday life situations (AACU 2010). Are such concepts threshold concepts? That is, are these troublesome concepts that are transformative, irreversible, and integrative (Meyer and Land, 2003), and typically involves a difficult passage through a “portal”, or threshold, as we master them? We see our students struggle with the execution of the range of quantitative techniques to analyze, represent and communicate data. We may know these students have taken mathematics courses, yet they struggle to transfer their learning from these courses to the real world problems and techniques within our disciplines. Addressing this concern from an interdisciplinary perspective may further inform how best to support student learning around quantitative reasoning within the disciplines.

In this workshop, through a sharing of our findings to date from interviews with undergraduate and graduate students, and faculty, collectively we will explore ways to incorporate and build quantitative reasoning skill development into our courses more effectively. Using examples of quantitative reasoning “problems” provided, as well as examples from their own teaching, participants will: (1) unpack the specific and general nature of quantitative reasoning within their disciplines; (2) identify specific or general bottlenecks for students; (3) highlight any misconceptions or other roadblocks; and (4) start to create a scaffolded approach that includes ample opportunity for students to practice such reasoning using “real world” examples. The aim is to collectively begin to build a toolbox of strategies and best practices that spark enhanced quantitative reasoning skills among our students.

AACU 2010. American Association of Colleges and Universities. Quantitative Literacy VALUE Rubric. Accessed on March 6, 2015 from http://www.aacu.org/value/rubrics/quantitative-literacy

Meyer, J.H.F. and Land, R., 2003. Threshold concepts and troublesome knowledge (1): linkages to ways of thinking and practising, in Rust, C. (ed.), Improving Student Learning – ten years on. Oxford: OCSLD.

Note: Participants may want to bring examples of quantitative problems or assignments that they use in their own first or second year undergraduate courses.

Elements of Engagement

Through examining quantitative reasoning examples and assignments from their own courses, and extending to look at examples from other disciplines, participants will examine the range of troublesome quantitative reasoning concepts and skills, engage in evaluating a variety of approaches to selected quantitative reasoning “problems”, share ideas around best practices, and develop new approaches to helping students develop their quantitative reasoning. Collectively, we aim to collate and create a set of activities and ideas to spark quantitative reasoning in our students.

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Jul 9th, 2:30 PM

Quantitative Reasoning: Crossing Thresholds

P&A Rm 117

Conversations about teaching and student learning with faculty across many of the science disciplines will invariably lead to a number of shared concerns. One such concern typically revolves around quantitative reasoning, which can be defined as a competency and comfort in working with numerical data and applying such skills to solving quantitative problems within a range of contexts and everyday life situations (AACU 2010). Are such concepts threshold concepts? That is, are these troublesome concepts that are transformative, irreversible, and integrative (Meyer and Land, 2003), and typically involves a difficult passage through a “portal”, or threshold, as we master them? We see our students struggle with the execution of the range of quantitative techniques to analyze, represent and communicate data. We may know these students have taken mathematics courses, yet they struggle to transfer their learning from these courses to the real world problems and techniques within our disciplines. Addressing this concern from an interdisciplinary perspective may further inform how best to support student learning around quantitative reasoning within the disciplines.

In this workshop, through a sharing of our findings to date from interviews with undergraduate and graduate students, and faculty, collectively we will explore ways to incorporate and build quantitative reasoning skill development into our courses more effectively. Using examples of quantitative reasoning “problems” provided, as well as examples from their own teaching, participants will: (1) unpack the specific and general nature of quantitative reasoning within their disciplines; (2) identify specific or general bottlenecks for students; (3) highlight any misconceptions or other roadblocks; and (4) start to create a scaffolded approach that includes ample opportunity for students to practice such reasoning using “real world” examples. The aim is to collectively begin to build a toolbox of strategies and best practices that spark enhanced quantitative reasoning skills among our students.

AACU 2010. American Association of Colleges and Universities. Quantitative Literacy VALUE Rubric. Accessed on March 6, 2015 from http://www.aacu.org/value/rubrics/quantitative-literacy

Meyer, J.H.F. and Land, R., 2003. Threshold concepts and troublesome knowledge (1): linkages to ways of thinking and practising, in Rust, C. (ed.), Improving Student Learning – ten years on. Oxford: OCSLD.

Note: Participants may want to bring examples of quantitative problems or assignments that they use in their own first or second year undergraduate courses.