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MILO Mobile: An iPad App to Measure Search Performance in Multi-Target Sequences
This article introduces a mobile app version of the Multi-Item Localization (MILO) task. The MILO task was designed to explore the temporal context of search through a sequence and has proven useful in both basic and applied research settings. Here, we describe the basic features of the app and how...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7307404/ https://www.ncbi.nlm.nih.gov/pubmed/32612800 http://dx.doi.org/10.1177/2041669520932587 |
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author | Thornton, Ian M. Horowitz, Todd S. |
author_facet | Thornton, Ian M. Horowitz, Todd S. |
author_sort | Thornton, Ian M. |
collection | PubMed |
description | This article introduces a mobile app version of the Multi-Item Localization (MILO) task. The MILO task was designed to explore the temporal context of search through a sequence and has proven useful in both basic and applied research settings. Here, we describe the basic features of the app and how it can be obtained, installed, and modified. We also provide example data files and present two new sets of empirical data to verify that previous findings concerning prospective planning and retrospective memory (i.e., inhibitory tagging) are reproducible with the app. We conclude by discussing ongoing studies and future modifications that illustrate the flexibility and potential of the MILO Mobile app. |
format | Online Article Text |
id | pubmed-7307404 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-73074042020-06-30 MILO Mobile: An iPad App to Measure Search Performance in Multi-Target Sequences Thornton, Ian M. Horowitz, Todd S. Iperception Methods This article introduces a mobile app version of the Multi-Item Localization (MILO) task. The MILO task was designed to explore the temporal context of search through a sequence and has proven useful in both basic and applied research settings. Here, we describe the basic features of the app and how it can be obtained, installed, and modified. We also provide example data files and present two new sets of empirical data to verify that previous findings concerning prospective planning and retrospective memory (i.e., inhibitory tagging) are reproducible with the app. We conclude by discussing ongoing studies and future modifications that illustrate the flexibility and potential of the MILO Mobile app. SAGE Publications 2020-06-20 /pmc/articles/PMC7307404/ /pubmed/32612800 http://dx.doi.org/10.1177/2041669520932587 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/ Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Methods Thornton, Ian M. Horowitz, Todd S. MILO Mobile: An iPad App to Measure Search Performance in Multi-Target Sequences |
title | MILO Mobile: An iPad App to Measure Search Performance in
Multi-Target Sequences |
title_full | MILO Mobile: An iPad App to Measure Search Performance in
Multi-Target Sequences |
title_fullStr | MILO Mobile: An iPad App to Measure Search Performance in
Multi-Target Sequences |
title_full_unstemmed | MILO Mobile: An iPad App to Measure Search Performance in
Multi-Target Sequences |
title_short | MILO Mobile: An iPad App to Measure Search Performance in
Multi-Target Sequences |
title_sort | milo mobile: an ipad app to measure search performance in
multi-target sequences |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7307404/ https://www.ncbi.nlm.nih.gov/pubmed/32612800 http://dx.doi.org/10.1177/2041669520932587 |
work_keys_str_mv | AT thorntonianm milomobileanipadapptomeasuresearchperformanceinmultitargetsequences AT horowitztodds milomobileanipadapptomeasuresearchperformanceinmultitargetsequences |