{"id":215215,"date":"2016-05-01T00:00:00","date_gmt":"2016-05-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/impact-chain-reactions-the-of-order-on-microtask-chains\/"},"modified":"2018-10-16T21:42:19","modified_gmt":"2018-10-17T04:42:19","slug":"impact-chain-reactions-the-of-order-on-microtask-chains","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/impact-chain-reactions-the-of-order-on-microtask-chains\/","title":{"rendered":"Chain Reactions: The Impact of Order on Microtask Chains"},"content":{"rendered":"
Microtasks are small units of work designed to be completed individually, eventually contributing to a larger goal. Although microtasks can be performed in isolation, in practice people often complete a chain of microtasks within a single session. Through a series of crowd-based studies, we look at how various microtasks can be chained together to improve efficiency and minimize mental demand, focusing on the writing domain. We find that participants completed low-complexity microtasks faster when they were preceded by the same type of microtask, whereas they found high-complexity microtasks less mentally demanding when preceded by microtasks on the same content. Furthermore, participants were faster at starting high-complexity microtasks after completing lower-complexity microtasks, but completion time and quality were not affected. These findings provide insight into how microtasks can be ordered to optimize transitions from one microtask to another.<\/p>\n<\/div>\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
Microtasks are small units of work designed to be completed individually, eventually contributing to a larger goal. Although microtasks can be performed in isolation, in practice people often complete a chain of microtasks within a single session. Through a series of crowd-based studies, we look at how various microtasks can be chained together to improve […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13554],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-215215","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"ACM - Association for Computing Machinery","msr_edition":"CHI 2016","msr_affiliation":"","msr_published_date":"2016-05-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"225466","msr_publicationurl":"","msr_doi":"10.1145\/2858036.2858237","msr_publication_uploader":[{"type":"file","title":"chi16-chains.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/05\/chi16-chains.pdf","id":225466,"label_id":0},{"type":"doi","title":"10.1145\/2858036.2858237","viewUrl":false,"id":false,"label_id":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"text","value":"Carrie J. Cai","user_id":0,"rest_url":false},{"type":"user_nicename","value":"shamsi","user_id":33592,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=shamsi"},{"type":"user_nicename","value":"teevan","user_id":33975,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=teevan"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[356726],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":356726,"post_title":"Microproductivity","post_name":"microtasks-and-microproductivity","post_type":"msr-project","post_date":"2017-01-23 12:01:04","post_modified":"2018-10-19 12:57:21","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/microtasks-and-microproductivity\/","post_excerpt":"As people\u2019s time becomes increasingly fragmented, getting tasks accomplished becomes more and more challenging. In this project we are investigating ways of decomposing larger tasks into smaller microtasks that leverage the micromoments that exist sporadically during a person\u2019s day. Our goal is to provide new ways of accomplishing smaller goals that contribute towards larger productivity, instead of setting aside large chunks of uninterrupted time. 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