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dc.contributor.authorCai, Carrie Jun
dc.contributor.authorMiller, Robert C
dc.contributor.authorRen, Anji
dc.date.accessioned2017-12-01T14:37:33Z
dc.date.available2017-12-01T14:37:33Z
dc.date.issued2017-03
dc.date.submitted2016-12
dc.identifier.issn1073-0516
dc.identifier.urihttp://hdl.handle.net/1721.1/112331
dc.description.abstractThe busyness of daily life makes it difficult to find time for informal learning. Yet, learning requires significant time and effort, with repeated exposures to educational content on a recurring basis. Despite the struggle to find time, there are numerous moments in a day that are typically wasted due to waiting, such as while waiting for the elevator to arrive, wifi to connect, or an instant message to arrive. We introduce the concept of wait-learning: automatically detecting wait time and inviting people to learn while waiting. Our approach is to design seamless interactions that augment existing wait time with productive opportunities. Combining wait time with productive work opens up a new class of software systems that overcome the problem of limited time. In this article, we establish a design space for wait-learning and explore this design space by creating WaitSuite, a suite of five different wait-learning apps that each uses a different kind of waiting. For one of these apps, we conducted a feasibility study to evaluate learning and to understand how exercises should be timed during waiting periods. Subsequently, we evaluated multiple kinds of wait-learning in a two-week field study of WaitSuite with 25 people. We present design implications for wait-learning, and a theoretical framework that describes how wait time, ease of accessing the learning task, and competing demands impact the effectiveness of wait-learning in different waiting scenarios. These findings provide insight into how wait-learning can be designed to minimize interruption to ongoing tasks and maximize engagement with learning.en_US
dc.language.isoen_US
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.isversionofhttps://doi.org/10.1145/3044534en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMilleren_US
dc.titleWaitSuite: Productive Use of Diverse Waiting Momentsen_US
dc.typeArticleen_US
dc.identifier.citationCai, Carrie J. et al. “WaitSuite: Productive Use of Diverse Waiting Moments.” ACM Transactions on Computer-Human Interaction 24, 1 (March 2017): 1–41 © 2017 Association for Computing Machinery (ACM)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.approverMiller, Robert C.en_US
dc.contributor.mitauthorCai, Carrie Jun
dc.contributor.mitauthorMiller, Robert C
dc.contributor.mitauthorRen, Anji
dc.relation.journalACM Transactions on Computer-Human Interactionen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsCai, Carrie J.; Ren, Anji; Miller, Robert C.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-9421-7128
dc.identifier.orcidhttps://orcid.org/0000-0002-0442-691X
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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