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Comparative Study
| Published: September 30, 2023
Method of Loci, Deep Processing, and Shallow Processing: A Constructive Comparative Study of Memory Performance in Young Adults
Teaching Associate, Department of Psychology, JAIN (Deemed-to-be-University), India Google Scholar More about the auther
DIP: 18.01.407.20231103
DOI: 10.25215/1103.407
ABSTRACT
The method of loci is an ancient mnemonic strategy that is proven highly effective but at the same time possesses a high level of difficulty to master. In this study, an altered version of the classic method of loci (developed by the researcher) is tested by comparing it to two other mnemonic strategies – deep processing (animacy), and shallow processing (vowel counting). The purpose of this modification from the researcher is to determine whether a version of ‘method of loci’ is possible without excessive use of association, which is not an aspect of proficiency for all individuals. The study compared the memory performance of participants for three different mnemonic strategies – ‘method of loci’, ‘animacy’ (deep processing), and ‘shallow processing’ (vowel counting) with a wordlist containing 72 words (24 words per condition). The alternate hypothesis of this study is that the performance of participants with the method of loci condition would be higher than both animacy and shallow processing conditions. The results revealed that the performance of participants with the method of loci condition were higher than with the shallow processing condition but to some extent lower than the performance of participants with the animacy condition. This finding determined that further testing might be able to provide conclusive evidence regarding the efficiency of the altered method of loci strategy. The reasons for further testing are detailed in the study.
Keywords
Method of Loci, Mnemonic strategies, Memory Performance, Deep Processing, Shallow Processing
This is an Open Access Research distributed under the terms of the Creative Commons Attribution License (www.creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any Medium, provided the original work is properly cited.
© 2023, Shankaran, A.
Received: September 22, 2023; Revision Received: September 27, 2023; Accepted: September 30, 2023
Article Overview
ISSN 2348-5396
ISSN 2349-3429
18.01.407.20231103
10.25215/1103.407
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Published in Volume 11, Issue 3, July-September, 2023