Abstract

School mathematics comprises a diversity of concepts whose cognitive complexity is still poorly understood, a chief example being fractions. These are typically taught in middle school, but many students fail to master them, and misconceptions frequently persist into adulthood. In this study, we investigate fraction comparison, a task that taps into both conceptual and procedural knowledge of fractions, by looking at performance of highly mathematically skilled young adults. Fifty-seven Chilean engineering undergraduate students answered a computerized fraction comparison task, while their answers and response times were recorded. Task items were selected according to a number of mathematically and/or cognitively relevant characteristics: (a) whether the fractions to be compared shared a common component, (b) the numerical distance between fractions, and (c) the applicability of two strategies to answer successfully: a congruency strategy (a fraction is larger if it has larger natural number components than another) and gap thinking (a fraction is larger if it is missing fewer pieces than another to complete the whole). In line with previous research, our data indicated that the congruency strategy is inadequate to describe participants’ performance, as congruent items turned out to be more difficult than incongruent ones when fractions had no common component. Although we hypothesized that this lower performance for congruent items would be explained by the use of gap thinking, this turned out not to be the case: evidence was insufficient to show that the applicability of the gap thinking strategy modulated either participants’ accuracy rates or response times (although individual-level data suggest that there is an effect for response times). When fractions shared a common component, instead, our data display a more complex pattern that expected: an advantage for congruent items is present in the first experimental block but fades as the experiment progresses. Numerical distance had an effect in fraction comparison that was statistically significant for items without common components only. Altogether, our results from experts’ reasoning reveal nuances in the fraction comparison task with respect to previous studies and contribute to future models of reasoning in this task.

Highlights

  • Rational numbers are key content in mathematics curricula throughout the world

  • The main question guiding this research was whether the conflicting results about congruency effects can be explained in a highly mathematically skilled population by gap thinking, namely, if experts’ lower performance in congruent than in incongruent fraction comparison items without common components can be explained by the use of this strategy

  • Performance was significantly better when fractions shared a common component [accuracy: 98% vs. 91%, t(55) = 10.0, p < 0.0001; response times (RTs): 2,795 ms vs. 4,009 ms, t(55) = 14.6, p < 0.0001]

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Summary

INTRODUCTION

Rational numbers are key content in mathematics curricula throughout the world. They are usually taught after natural numbers and constitute students’ first approach to concepts such as non-whole quantities and dense sets (Vamvakoussi and Vosniadou, 2004). Performance in fraction comparison, as well as its possible relation to a natural number bias, has been investigated in populations displaying a variety of knowledge level: middle school students (Van Hoof et al, 2013; Gómez and Dartnell, 2019), mathematics teachers (Siegler and LortieForgues, 2015), and experts (Bonato et al, 2007; Obersteiner et al, 2013; DeWolf and Vosniadou, 2015). The main question guiding this research was whether the conflicting results about congruency effects can be explained in a highly mathematically skilled population by gap thinking, namely, if experts’ lower performance in congruent than in incongruent fraction comparison items without common components can be explained by the use of this strategy. As a secondary research question, we tested the role of the numerical distance between fractions in predicting participants’ RTs after eliminating the applicability of the 1/2benchmark strategy, by using in all items only fractions below or above this value

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