{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T11:00:46Z","timestamp":1772362846031,"version":"3.50.1"},"reference-count":53,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T00:00:00Z","timestamp":1641859200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"NSF","award":["IIS-1718295"],"award-info":[{"award-number":["IIS-1718295"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Inf. Syst."],"published-print":{"date-parts":[[2022,10,31]]},"abstract":"<jats:p>\n            Search systems are often used to support learning-oriented goals. This trend has given rise to the \u201csearch-as-learning\u201d movement, which proposes that search systems should be designed to support learning. To this end, an important research question is: How does a searcher\u2019s\n            <jats:italic>type<\/jats:italic>\n            of learning objective (LO) influence their trajectory (or\n            <jats:italic>pathway<\/jats:italic>\n            ) toward that objective? We report on a lab study (N = 36) in which participants gathered information to meet a specific type of LO. To characterize LOs\n            <jats:italic>and pathways<\/jats:italic>\n            , we leveraged Anderson and Krathwohl\u2019s (A&amp;K\u2019s) taxonomy\u00a0[\n            <jats:xref ref-type=\"bibr\">3<\/jats:xref>\n            ]. A&amp;K\u2019s taxonomy situates LOs at the intersection of two orthogonal dimensions: (1)\n            <jats:italic>cognitive process<\/jats:italic>\n            (CP) (remember, understand, apply, analyze, evaluate, and create) and (2)\n            <jats:italic>knowledge type<\/jats:italic>\n            (factual, conceptual, procedural, and metacognitive knowledge). Participants completed learning-oriented search tasks that varied along three CPs (apply, evaluate, and create) and three knowledge types (factual, conceptual, and procedural knowledge). A\n            <jats:italic>pathway<\/jats:italic>\n            is defined as a sequence of\n            <jats:italic>learning instances<\/jats:italic>\n            (e.g., subgoals) that were also each classified into cells from A&amp;K\u2019s taxonomy. Our study used a think-aloud protocol, and pathways were generated through a qualitative analysis of participants\u2019 think-aloud comments and recorded screen activities. We investigate three research questions. First, in RQ1, we study the impact of the LO on pathway characteristics (e.g., pathway length). Second, in RQ2, we study the impact of the LO on the types of A&amp;K cells traversed along the pathway. Third, in RQ3, we study common and uncommon\n            <jats:italic>transitions<\/jats:italic>\n            between A&amp;K cells along pathways conditioned on the knowledge type of the objective. We discuss implications of our results for designing search systems to support learning.\n          <\/jats:p>","DOI":"10.1145\/3495222","type":"journal-article","created":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T06:04:22Z","timestamp":1642399462000},"page":"1-43","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Understanding the \u201cPathway\u201d Towards a Searcher\u2019s Learning Objective"],"prefix":"10.1145","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6140-6045","authenticated-orcid":false,"given":"Kelsey","family":"Urgo","sequence":"first","affiliation":[{"name":"School of Information and Library Science, University of North Carolina at Chapel Hill, Chapell Hill, North Carolina"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7645-0556","authenticated-orcid":false,"given":"Jaime","family":"Arguello","sequence":"additional","affiliation":[{"name":"School of Information and Library Science, University of North Carolina at Chapel Hill, Chapell Hill, North Carolina"}]}],"member":"320","published-online":{"date-parts":[[2022,1,11]]},"reference":[{"key":"e_1_3_4_2_2","volume-title":"Learning Factors and Determining Document-level Satisfaction In Search-as-Learning","author":"Abualsaud Mustafa","year":"2017","unstructured":"Mustafa Abualsaud. 2017. 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