-
Zhang, Y.; Wu, D.; Hagen, L.; Song, I.-Y.; Mostafa, J.; Oh, S.; Anderson, T.; Shah, C.; Bishop, B.W.; Hopfgartner, F.; Eckert, K.; Federer, L.; Saltz, J.S.: Data science curriculum in the iField (2023)
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- Abstract
- Many disciplines, including the broad Field of Information (iField), offer Data Science (DS) programs. There have been significant efforts exploring an individual discipline's identity and unique contributions to the broader DS education landscape. To advance DS education in the iField, the iSchool Data Science Curriculum Committee (iDSCC) was formed and charged with building and recommending a DS education framework for iSchools. This paper reports on the research process and findings of a series of studies to address important questions: What is the iField identity in the multidisciplinary DS education landscape? What is the status of DS education in iField schools? What knowledge and skills should be included in the core curriculum for iField DS education? What are the jobs available for DS graduates from the iField? What are the differences between graduate-level and undergraduate-level DS education? Answers to these questions will not only distinguish an iField approach to DS education but also define critical components of DS curriculum. The results will inform individual DS programs in the iField to develop curriculum to support undergraduate and graduate DS education in their local context.
- Date
- 12. 5.2023 14:29:42
- Footnote
- Beitrag in einem Special issue on "Data Science in the iField".
- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.6, S.641-662
-
Hendahewa, C.; Shah, C.: Implicit search feature based approach to assist users in exploratory search tasks (2015)
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- Source
- Information processing and management. 51(2015) no.5, S.643-661
-
Shah, C.: Collaborative information seeking (2014)
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- Abstract
- The notions that information seeking is not always a solitary activity and that people working in collaboration for information intensive tasks should be studied and supported have become more prevalent in recent years. Several new research questions, methodologies, and systems have emerged around these notions that may prove to be useful beyond the field of collaborative information seeking (CIS), with relevance to the broader area of information seeking and behavior. This article provides an overview of such key research work from a variety of domains, including library and information science, computer-supported cooperative work, human-computer interaction, and information retrieval. It starts with explanations of collaboration and how CIS fits in different contexts, emphasizing the interactive, intentional, and mutually beneficial nature of CIS activities. Relations to similar and related fields such as collaborative information retrieval, collaborative information behavior, and collaborative filtering are also clarified. Next, the article presents a synthesis of various frameworks and models that exist in the field today, along with a new synthesis of 12 different dimensions of group activities. A discussion on issues and approaches relating to evaluating various parameters in CIS follows. Finally, a list of known issues and challenges is presented to provide an overview of research opportunities in this field.
- Date
- 29. 1.2014 16:08:31
- Series
- Advances in information science
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.2, S.215-236
-
Le, L.T.; Shah, C.: Retrieving people : identifying potential answerers in Community Question-Answering (2018)
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- Date
- 29. 9.2018 13:18:09
- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.10, S.1246-1258
-
Shah, C.; Anderson, T.; Hagen, L.; Zhang, Y.: ¬An iSchool approach to data science : human-centered, socially responsible, and context-driven (2021)
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- Abstract
- The Information Schools, also referred to as iSchools, have a unique approach to data science with three distinct components: human-centeredness, socially responsible, and rooted in context. In this position paper, we highlight and expand on these components and show how they are integrated in various research and educational activities related to data science that are being carried out at iSchools. We argue that the iSchool way of doing data science is not only highly relevant to the current times, but also crucial in solving problems of tomorrow. Specifically, we accentuate the issues of developing insights and solutions that are not only data-driven, but also incorporate human values, including transparency, privacy, ethics, fairness, and equity. This approach to data science has meaningful implications on how we educate the students and train the next generation of scholars and policymakers. Here, we provide some of those design decisions, rooted in evidence-based research, along with our perspective on how data science is currently situated and how it should be advanced in iSchools.
- Source
- Journal of the Association for Information Science and Technology. 72(2021) no.6, S.793-796
-
Wang, Y.; Shah, C.: Investigating failures in information seeking episodes (2017)
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- Date
- 20. 1.2015 18:30:22
-
Shah, C.; Marchionini, G.: Awareness in collaborative information seeking (2010)
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- Footnote
- Erratum in: Journal of the American Society for Information Science and Technology, 61(2010) no.11, S.2377.
- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.10, S.1970-1986
-
Shah, C.; Kitzie, V.: Social Q&A and virtual reference : comparing apples and oranges with the help of experts and users (2012)
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- Source
- Journal of the American Society for Information Science and Technology. 63(2012) no.10, S.2020-2036
-
Shah, C.: Effects of awareness on coordination in collaborative information seeking (2013)
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- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.6, S.1122-1143
-
González-Ibáñez, R.; Shah, C.; White, R.W.: Capturing 'Collabportunities' : a method to evaluate collaboration opportunities in information search using pseudocollaboration (2015)
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- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.9, S.1897-1912
-
Choi, E.; Shah, C.: User motivations for asking questions in online Q&A services (2016)
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- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.5, S.1182-1197
-
Shah, C.; Hendahewa, C.; González-Ibáñez, R.: Rain or shine? : forecasting search process performance in exploratory search tasks (2016)
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- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.7, S.1607-1623
-
Radford, M.L.; Connaway, L.S.; Mikitish, S.; Alpert, M.; Shah, C.; Cooke, N.A.: Shared values, new vision : collaboration and communities of practice in virtual reference and SQA (2017)
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- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.2, S.438-449
-
González-Ibáñez, R.; Esparza-Villamán, A.; Vargas-Godoy, J.C.; Shah, C.: ¬A comparison of unimodal and multimodal models for implicit detection of relevance in interactive IR (2019)
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- Source
- Journal of the Association for Information Science and Technology. 70(2019) no.11, S.1223-1235
-
Wang, Y.; Shah, C.: Authentic versus synthetic : an investigation of the influences of study settings and task configurations on search behaviors (2022)
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- Source
- Journal of the Association for Information Science and Technology. 73(2022) no.3, S.362-375
-
Shah, C.: Collaborative information seeking : the art and science of making the whole greater than the sum of all (2012)
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