Session-based Search Behavior in Naturalistic Settings for Learning-related Tasks

Ghosh, Souvick; Shah, Chirag

doi:10.1145/3357384.3358098

Cited by 2 publications

(3 citation statements)

References 14 publications

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“…To better understand search as a learning process, researchers consider conceptualising learning as contexts or scenarios for searching, and accordingly they designed learning-related tasks [21][22][23]. Learning-related task emphasises search behaviours that are conducted to complete a work task with a/some learning goal(s).…”

Section: Related Work 21 Learning-related Tasksmentioning

confidence: 99%

“…They found the number of users' downloads are correlated across different search sessions, and the time gap until the next download session is negatively correlated with the number of queries. In addition, some studies regarding learning-related search focused on the relationship between users' interactions with learning outcomes or knowledge gain [21,33,34].…”

Section: Interaction Behaviours For Learning-related Tasksmentioning

confidence: 99%

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Characterising users’ task completion process in learning-related tasks:A search pace model

Liu

Song

Hansen

2021

Journal of Information Science

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This study investigated users’ searching, reading and writing interactions and their activity transitions during task completion process when users were collecting information for learning-related search tasks. Task completion process was defined as the process users started to search till the time when they have collected enough information to accomplish the search tasks. The data analysis was conducted from a new process perspective through synthesising macro- and micro-process levels. Four evenly distributed stages were divided according to the total task completion time in each search session. Our results demonstrated that users generally experienced three sub-processes during task completion process: exploration, accumulation and composition/reporting. Exploration sub-process is basically the first quarter of the total task completion time, during which users often issue more queries and visit more search engine result pages (SERPs) to collect information, and the dominant activity transition is switching between searching and reading; accumulation sub-process is mainly the second and third quarters of the total task completion time, during which they visit more unique content pages, have more revisits per content page, and they switch between reading and writing activities frequently; the last stage is composition/reporting sub-process, which is dominated by writing, and users often switch between writing and reading, and between writing and searching. Based on these findings, we propose a search pace model to describe how users proceed from the beginning to the end of task completion process in these three sub-processes. The methodology applied has been proved to be effective to examine users’ interaction behaviours from the process perspective on both the micro- and macro-levels. The findings of this article help us understand how users proceed their dynamic searching, reading and writing behaviours for learning-related tasks, and also have implications for the design of search systems that support learning-related tasks.

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Section: Related Work 21 Learning-related Tasksmentioning

confidence: 99%

Section: Interaction Behaviours For Learning-related Tasksmentioning

confidence: 99%

Characterising users’ task completion process in learning-related tasks:A search pace model

Liu

Song

Hansen

2021

Journal of Information Science

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“…Most of the studies belong to the latter category. These studies do not explicitly use the word ‘learning’, although implicitly they deal with this phenomenon.” Further, according to Reynolds et al (2018), searching and learning are not isolated but co‐occurring events, and the learning outcomes are often influenced by the cognitive complexity of the search tasks (Krathwohl, 2002), the choice of information sources (Rath et al, 2018), the affordances offered by search devices (chatbots, personal assistants), and the environment (Ghosh and Shah, 2019). The searchers’ topic knowledge, topic interest, and perceived task difficulty also affect the behavioral patterns and learning goals.…”

Section: Introductionmentioning

confidence: 99%

Search Systems and Artificial Intelligence: Enhancing Searching as Learning Approaches to Counter Misinformation

Ghosh,

Gwizdka,

Lewandowski

et al. 2023

Proceedings of the Association for Information Science and Tech

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Searching as a learning process implies that learning occurs during a search process and might happens incidentally, influenced by the context the search takes place and the system that is used. Searching and learning are not isolated but co‐occurring events. Research investigates how search systems can be improved to foster learning processes, integrate information literacy enhancing methods and support user's sense‐making of information. Regarding the advancement of AI algorithms and their implementation in search systems, the concept of searching as a learning process can help to better understand human‐computer interactions and future information‐seeking processes. The panel advances current research on search systems for learning in non‐formal settings, with a focus on investigating the relation between searching and learning processes that influence people's understanding, assessing and use of information. It will focus on the contributions of information science research and the expectations of future searching behavior with respect to emerging advances in AI.

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Session-based Search Behavior in Naturalistic Settings for Learning-related Tasks

Cited by 2 publications

References 14 publications

Characterising users’ task completion process in learning-related tasks:A search pace model

Characterising users’ task completion process in learning-related tasks:A search pace model

Search Systems and Artificial Intelligence: Enhancing Searching as Learning Approaches to Counter Misinformation

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