Studying the users’ information-seeking behavior by recording brain waves activity with Electroencephalography method: A systematic Review

Despite the novelty in methodologies, User behavior study based on brain activity during information-seeking stages has become popular among information science researchers. This paper reviews scientific publications in which information-seeking behavior has been studied along with recorded brain activity to shed light on research status, challenges, and suggestions for future studies. Based on Kitchenham & Charters (2007) framework, a complete web search was performed in English and Persian scientific databases, and 22 publications in English were found as the final result, from 2007 to 2020. Review results demonstrate that exploring the user status (10 papers) and brain wave activity during information-seeking episodes (12 papers) were the most dominant subjective approaches in the field of user behavior studies. Cognitive load was found as an effective cognitive component on user status. With eye movement measurement and brain waves frequency study, 3 factors were found effective on cognitive load level generated during information searching and processing: searching media type, information representation, and text reading style. Brain wave activity and pupil dilation analysis were the most important measures in user status during search stages, and alpha and theta band waves were demonstrated as an index for cognitive load measurement during the information searching process. A correlation among eye data, search behavior, task complexity based on user experience, and cognitive style – as another effective factor on user status- led to results in different information searching behavior demonstrations. Also, 3 main stages were analyzed in the information-seeking process, based on brain wave activity: information exploring and query formulation, query reformulation and selection, relevance judgment, and decision making. Results showed a difference between brain activity areas, and differences in pupil dilation change level and alpha/beta frequency level during different search episodes. For future research, some suggestions were offered based on reviews. Finding relations between correlations among cognitive styles, task features, and domain knowledge during information searching process, personalized information retrieval improvement, more collaboration between information science and neurocognitive specialists, research in more user affective status like aggression and fatigue during the search process, using more economic methods and portable devices aiming to reduce research costs and expenses, facilitating larger sample studies and designing standard tasks were considered as a suggestion. Finally, some challenges were found based on reviewed studies. Some concepts like relevance feedback in information retrieval need more investigation. Also, it is necessary to investigate and explore user affections during the search process with multiple approaches

Comparative Study of Laptops and Touch-Screen PCs for Searching on the Web

This study compares the use of a laptop versus a touch-screen PC to perform web-based information search tasks. Thirty-six participants took part in a lab-based experiment. They were asked to use either a laptop or a touch-screen PC to seek information on the web and retrieve relevant pieces of information while their sessions were recorded. Cognitive load was measured through eyerelated data and cortical activity (EEG) along with a self-reported scale. Main results indicated that participants who used the laptop outperformed those who used the touch-screen PC, with more relevant webpages bookmarked (F = 9.678, p = .004) and more relevant elements retrieved (F = 6.302, p = .018). Participants with the touch-screen PC also spent more time on each webpage than their counterparts (F = 9.2141, p = .005). These results suggest that using the touch-screen PC required more mental effort, which is supported by cognitive load measurements. Linear mixed-model analyses showed significant differences across devices in both pupil size variation (F = 3.692, p = .05) and EEG-based cognitive load index (F = 5.181, p = .028). This study raises issues about whether touchscreen computers are suited for every computing needs.SCOPUS: cp.kinfo:eu-repo/semantics/publishe

Comparative study of laptops and touch-screen PCs for searching on the Web

info:eu-repo/semantics/nonPublishe