Title
The Cross-Modal Relationship Between Language and Mathematics: A Bi-Directional Training Paradigm
Document Type
Undergraduate Thesis
Publication Date
Spring 5-2022
Journal
Undergraduate Honours Theses
Abstract
The cross-modal relationship between language and mathematics is extensively debated (see for review, Peng et al., 2020). The present research examined the nature of this cross-modal relationship across three experiments. Experiment 1 examined whether training participants in linguistic problem-solving facilitates performance in mathematical problems. Participants were 156 adults recruited using Amazon Mechanical Turk and randomly assigned to one of three linguistic training conditions (i.e., linguistic reasoning, structural priming, or no-training) and tested on mathematical problems. No significant difference in mathematical performance was found across training conditions [F(2, 153) = 1.69, p = .18]. Experiment 2 examined whether training participants to solve mathematical problems facilitates performance in linguistic problems. Participants were 144 adults assigned to one of three mathematical training conditions (i.e., mathematical reasoning, structural priming, or no-training) and tested on linguistic problems. Results showed a significant difference in linguistic performance across training conditions [F(2, 142) = 3.86, p = .02, η2 = .05]. Post-hoc analysis revealed a significant difference between the structural priming (M = 9.37, SD = 1.99) and no-training conditions (M =8.04, SD=2.66). Experiment 3 examined whether the explicitness of mathematical training differently impacts linguistic problem-solving. Participants were 75 undergraduate students assigned to one of three mathematical training conditions (i.e., explicit training, structural priming, or no-training) and tested on linguistic problems. A significant difference between training conditions was found [F(2, 72) = 5.40, p = .006, η2 = .13]. Post-hoc analysis showed a significant difference between explicit instruction (M = 9.00, SD = 2.61) and no-training (M =7.32, SD=2.88), as well as structural priming (M = 9.40, SD = 1.32) and no training (M =7.32, SD=2.88). Implications of these results and avenues for future research are discussed.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Notes
Thesis Advisor(s):
Dr Christine Tsang, Dr Stephen Van Hedger