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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

Ashwin Shankaran

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.

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Responding Author Information

Ashwin Shankaran @ s.ashwin@jainuniversity.ac.in

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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