Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | HT 2019 |
| Untertitel | Proceedings of the 30th ACM Conference on Hypertext and Social Media |
| Erscheinungsort | New York |
| Seiten | 123-132 |
| Seitenumfang | 10 |
| ISBN (elektronisch) | 9781450368858 |
| Publikationsstatus | Veröffentlicht - 12 Sept. 2019 |
| Veranstaltung | 30th ACM Conference on Hypertext and Social Media, HT 2019 - Hof, Deutschland Dauer: 17 Sept. 2019 → 20 Sept. 2019 |
Abstract
The ubiquitous accessibility of the world-wide web has led people to increasingly use web search to learn or acquire new knowledge. Recent research efforts have targeted the optimization of web search to satisfy learning related needs. However, there is little known about how one's search interactions differ across varying cognitive levels that correspond to one's learning. In this paper, we address this knowledge gap by investigating how the search interactions of 150 users vary across 6 search tasks corresponding to distinct cognitive levels. We also analyze how users' knowledge gain varies across the cognitive levels. Our findings suggest that the cognitive learning level of a user in a search session has a significant impact on the user's search behavior and knowledge gain. Estimating the cognitive level of users during their interactions with search systems will allow us to construct and improve learning experiences for the users. For example, learners can be served content that corresponds to their current cognitive level within their learning process.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Software
- Informatik (insg.)
- Artificial intelligence
- Informatik (insg.)
- Mensch-Maschine-Interaktion
- Informatik (insg.)
- Computergrafik und computergestütztes Design
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HT 2019: Proceedings of the 30th ACM Conference on Hypertext and Social Media. New York, 2019. S. 123-132.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Understanding user search behavior across varying cognitive levels
AU - Kalyani, Rishita
AU - Gadiraju, Ujwal Kumar
N1 - Funding information: We thank all the workers who participated in our experiments. This research has been supported in part by the Erasmus+ project DISKOW (grant no. 60171990).
PY - 2019/9/12
Y1 - 2019/9/12
N2 - The ubiquitous accessibility of the world-wide web has led people to increasingly use web search to learn or acquire new knowledge. Recent research efforts have targeted the optimization of web search to satisfy learning related needs. However, there is little known about how one's search interactions differ across varying cognitive levels that correspond to one's learning. In this paper, we address this knowledge gap by investigating how the search interactions of 150 users vary across 6 search tasks corresponding to distinct cognitive levels. We also analyze how users' knowledge gain varies across the cognitive levels. Our findings suggest that the cognitive learning level of a user in a search session has a significant impact on the user's search behavior and knowledge gain. Estimating the cognitive level of users during their interactions with search systems will allow us to construct and improve learning experiences for the users. For example, learners can be served content that corresponds to their current cognitive level within their learning process.
AB - The ubiquitous accessibility of the world-wide web has led people to increasingly use web search to learn or acquire new knowledge. Recent research efforts have targeted the optimization of web search to satisfy learning related needs. However, there is little known about how one's search interactions differ across varying cognitive levels that correspond to one's learning. In this paper, we address this knowledge gap by investigating how the search interactions of 150 users vary across 6 search tasks corresponding to distinct cognitive levels. We also analyze how users' knowledge gain varies across the cognitive levels. Our findings suggest that the cognitive learning level of a user in a search session has a significant impact on the user's search behavior and knowledge gain. Estimating the cognitive level of users during their interactions with search systems will allow us to construct and improve learning experiences for the users. For example, learners can be served content that corresponds to their current cognitive level within their learning process.
UR - http://www.scopus.com/inward/record.url?scp=85073329690&partnerID=8YFLogxK
U2 - 10.1145/3342220.3343643
DO - 10.1145/3342220.3343643
M3 - Conference contribution
AN - SCOPUS:85073329690
SP - 123
EP - 132
BT - HT 2019
CY - New York
T2 - 30th ACM Conference on Hypertext and Social Media, HT 2019
Y2 - 17 September 2019 through 20 September 2019
ER -