Modelling the Accuracy Rates of Spatial Relational Reasoning Problems: An Analysis Facilitating ACT-R and PRISM Theory
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This thesis models the effects of errors of omission and commission due to increased working memory demands on accuracy rates of spatial relational reasoning problems. The questions modelled are taken from the Multidimensional Relational Reasoning Task (Cortes et al., 2021). Four models were created using Python ACT-R and PRISM theory which demonstrated the negative relationship of increased premises and dimensions per problem on accuracy rates. Results highlight the need for future modelling to consider the individual differences in micro-strategy preferences, how reasoning processes may be affected by different memory errors, and how future measures may be constructed to better address raised concerns.
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Copyright © 2022 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
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- 2022
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turcas-modellingtheaccuracyratesofspatialrelational.pdf | 2023-05-05 | Public | Download |