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    Appendix Materials for "Development and Evaluation of Search Tasks for IIR Experiments using a Cognitive Complexity Framework"

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    In recent years, the “search as learning” community has argued that search systems should be designed to support learning. We report on a lab study in which we manipulated the learning objectives associated with search tasks assigned to participants. We manipulated learning objectives by leveraging Anderson and Krathwohl’s taxonomy of learning (A&K’s taxonomy) [2], which situates learn-ing objectives at the intersection of two orthogonal dimensions: the cognitive process and the knowledge type dimension. Participants in our study completed tasks with learning objectives that varied across three cognitive processes (apply, evaluate, and create) and three knowledge types (factual, conceptual, and procedural knowledge). We focus on the effects of the task’s cognitive process and knowledge type on participants’ pre-/post-task perceptions and search behaviors. Our results found that the three knowledge types considered in our study had a greater effect than the three cognitive processes. Specifically, conceptual knowledge tasks were perceived to be more difficult and required more search activity. We discuss implications for designing search systems that support learning

    Veebi otsingumootorid ja vajadus keeruka informatsiooni jÀrele

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    VĂ€itekirja elektrooniline versioon ei sisalda publikatsioone.Veebi otsingumootorid on muutunud pĂ”hiliseks teabe hankimise vahenditeks internetist. Koos otsingumootorite kasvava populaarsusega on nende kasutusala kasvanud lihtsailt pĂ€ringuilt vajaduseni kĂŒllaltki keeruka informatsiooni otsingu jĂ€rele. Samas on ka akadeemiline huvi otsingu vastu hakanud liikuma lihtpĂ€ringute analĂŒĂŒsilt mĂ€rksa keerukamate tegevuste suunas, mis hĂ”lmavad ka pikemaid ajaraame. Praegused otsinguvahendid ei toeta selliseid tegevusi niivĂ”rd hĂ€sti nagu lihtpĂ€ringute juhtu. Eriti kehtib see toe osas koondada mitme pĂ€ringu tulemusi kokku sĂŒnteesides erinevate lihtotsingute tulemusi ĂŒhte uude dokumenti. Selline lĂ€henemine on alles algfaasis ja ning motiveerib uurijaid arendama vastavaid vahendeid toetamaks taolisi informatsiooniotsingu ĂŒlesandeid. KĂ€esolevas dissertatsioonis esitatakse rida uurimistulemusi eesmĂ€rgiga muuta keeruliste otsingute tuge paremaks kasutades tĂ€napĂ€evaseid otsingumootoreid. AlameesmĂ€rkideks olid: (a) arendada vĂ€lja keeruliste otsingute mudel, (b) mÔÔdikute loomine kompleksotsingute mudelile, (c) eristada kompleksotsingu ĂŒlesandeid lihtotsingutest ning teha kindlaks, kas neid on vĂ”imalik mÔÔta leides ĂŒhtlasi lihtsaid mÔÔdikuid kirjeldamaks nende keerukust, (d) analĂŒĂŒsida, kui erinevalt kasutajad kĂ€ituvad sooritades keerukaid otsinguĂŒlesandeid kasutades veebi otsingumootoreid, (e) uurida korrelatsiooni inimeste tava-veebikasutustavade ja nende otsingutulemuslikkuse vahel, (f) kuidas inimestel lĂ€heb eelhinnates otsinguĂŒlesande raskusastet ja vajaminevat jĂ”upingutust ning (g) milline on soo ja vanuse mĂ”ju otsingu tulemuslikkusele. Keeruka veebiotsingu ĂŒlesanded jaotatakse edukalt kolmeastmeliseks protsessiks. Esitatakse sellise protsessi mudel; seda protsessi on ĂŒhtlasi vĂ”imalik ka mÔÔta. Edasi nĂ€idatakse kompleksotsingu loomupĂ€raseid omadusi, mis teevad selle eristatavaks lihtsamatest juhtudest ning nĂ€idatakse Ă€ra katsemeetod sooritamaks kompleksotsingu kasutaja-uuringuid. Demonstreeritakse pĂ”hilisi samme raamistiku “Search-Logger” (eelmainitud metodoloogia tehnilise teostuse) rakendamisel kasutaja-uuringutes. Esitatakse sellisel viisil teostatud uuringute tulemused. LĂ”puks esitatakse ATMS meetodi realisatsioon ja rakendamine parandamaks kompleksotsingu vajaduste tuge kaasaegsetes otsingumootorites.Search engines have become the means for searching information on the Internet. Along with the increasing popularity of these search tools, the areas of their application have grown from simple look-up to rather complex information needs. Also the academic interest in search has started to shift from analyzing simple query and response patterns to examining more sophisticated activities covering longer time spans. Current search tools do not support those activities as well as they do in the case of simple look-up tasks. Especially the support for aggregating search results from multiple search-queries, taking into account discoveries made and synthesizing them into a newly compiled document is only at the beginning and motivates researchers to develop new tools for supporting those information seeking tasks. In this dissertation I present the results of empirical research with the focus on evaluating search engines and developing a theoretical model of the complex search process that can be used to better support this special kind of search with existing search tools. It is not the goal of the thesis to implement a new search technology. Therefore performance benchmarks against established systems such as question answering systems are not part of this thesis. I present a model that decomposes complex Web search tasks into a measurable, three-step process. I show the innate characteristics of complex search tasks that make them distinguishable from their less complex counterparts and showcase an experimentation method to carry out complex search related user studies. I demonstrate the main steps taken during the development and implementation of the Search-Logger study framework (the technical manifestation of the aforementioned method) to carry our search user studies. I present the results of user studies carried out with this approach. Finally I present development and application of the ATMS (awareness-task-monitor-share) model to improve the support for complex search needs in current Web search engines

    Una teorĂ­a cognitiva integral para la recuperaciĂłn de informaciĂłn: saliendo del entorno del laboratorio

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    The paper demonstrates how the Laboratory Research Framework fits into the integrated Cognitive Framework for IR. It first discusses the Laboratory Framework with emphasis on its underlying assumptions and known limitations. This is followed by a view of interaction and relevance phenomena associated with IR evaluation and central to the understanding of IR. The ensuing section outlines how interactive IR is viewed from a Cognitive Framework, and ‘light’ interactive IR experiments are suggested performed by drawing on the latter framework’s contextual possibilities. These include independent variables drawn from a collection, matching principles in a retrieval system, and the searcher’s situation and task context. The paper ends with concluding points of summarization of issues encountered.Este artĂ­culo demuestra cĂłmo el marco de investigaciĂłn en laboratorio encaja bien dentro del marco cognitivo integral para la RecuperaciĂłn de informaciĂłn. Se discute primero el marco de investigaciĂłn en laboratorio, con Ă©nfasis en sus asunciones y limitaciones. Se analizan los fenĂłmenos de la interacciĂłn y relevancia asociados con la evaluaciĂłn en RI., asĂ­ como el modo de desarrollar experimentos interactivos de RecuperaciĂłn de informaciĂłn dentro del marco cognitivo, considerando la situaciĂłn del investigador y el contexto de la tarea llevada a cabo
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