Cognitive Styles within an Exploratory Search System for Digital Libraries

Purpose – The purpose of this paper is to investigate the effects of cognitive style on navigating a large digital library of cultural heritage information; specifically, the paper focus on the wholist/analytic dimension as experienced in the field of educational informatics. The hypothesis is that wholist and analytic users have characteristically different approaches when they explore, search and interact with digital libraries, which may have implications for system design. Design/methodology/approach – A detailed interactive IR evaluation of a large cultural heritage digital library was undertaken, along with the Riding CSA test. Participants carried out a range of information tasks, and the authors analysed their task performance, interactions and attitudes. Findings – The hypothesis on the differences in performance and behaviour between wholist and analytic users is supported. However, the authors also find that user attitudes towards the system are opposite to expectations and that users give positive feedback for functionality that supports activities in which they are cognitively weaker. Research limitations/implications – There is scope for testing results in a larger scale study, and/or with different systems. In particular, the findings on user attitudes warrant further investigation. Practical implications – Findings on user attitudes suggest that systems which support areas of weakness in users’ cognitive abilities are valued, indicating an opportunity to offer diverse functionality to support different cognitive weaknesses. Originality/value – A model is proposed suggesting a converse relationship between behaviour and attitudes; to support individual users displaying search/navigation behaviour mapped onto the strengths of their cognitive style, but placing greater value on interface features that support aspects in which they are weaker

Thesaurus-assisted search term selection and query expansion: a review of user-centred studies

This paper provides a review of the literature related to the application of domain-specific thesauri in the search and retrieval process. Focusing on studies which adopt a user-centred approach, the review presents a survey of the methodologies and results from empirical studies undertaken on the use of thesauri as sources of term selection for query formulation and expansion during the search process. It summaries the ways in which domain-specific thesauri from different disciplines have been used by various types of users and how these tools aid users in the selection of search terms. The review consists of two main sections covering, firstly studies on thesaurus-aided search term selection and secondly those dealing with query expansion using thesauri. Both sections are illustrated with case studies that have adopted a user-centred approach

The role of human factors in stereotyping behavior and perception of digital library users: A robust clustering approach

To deliver effective personalization for digital library users, it is necessary to identify which human factors are most relevant in determining the behavior and perception of these users. This paper examines three key human factors: cognitive styles, levels of expertise and gender differences, and utilizes three individual clustering techniques: k-means, hierarchical clustering and fuzzy clustering to understand user behavior and perception. Moreover, robust clustering, capable of correcting the bias of individual clustering techniques, is used to obtain a deeper understanding. The robust clustering approach produced results that highlighted the relevance of cognitive style for user behavior, i.e., cognitive style dominates and justifies each of the robust clusters created. We also found that perception was mainly determined by the level of expertise of a user. We conclude that robust clustering is an effective technique to analyze user behavior and perception

Contextualised Browsing in a Digital Library's Living Lab

Contextualisation has proven to be effective in tailoring \linebreak search results towards the users' information need. While this is true for a basic query search, the usage of contextual session information during exploratory search especially on the level of browsing has so far been underexposed in research. In this paper, we present two approaches that contextualise browsing on the level of structured metadata in a Digital Library (DL), (1) one variant bases on document similarity and (2) one variant utilises implicit session information, such as queries and different document metadata encountered during the session of a users. We evaluate our approaches in a living lab environment using a DL in the social sciences and compare our contextualisation approaches against a non-contextualised approach. For a period of more than three months we analysed 47,444 unique retrieval sessions that contain search activities on the level of browsing. Our results show that a contextualisation of browsing significantly outperforms our baseline in terms of the position of the first clicked item in the result set. The mean rank of the first clicked document (measured as mean first relevant - MFR) was 4.52 using a non-contextualised ranking compared to 3.04 when re-ranking the result lists based on similarity to the previously viewed document. Furthermore, we observed that both contextual approaches show a noticeably higher click-through rate. A contextualisation based on document similarity leads to almost twice as many document views compared to the non-contextualised ranking.Comment: 10 pages, 2 figures, paper accepted at JCDL 201

Understanding Novice Users\u27 Help-seeking Behavior in Getting Started with Digital Libraries: Influence of Learning Styles

Users\u27 information needs have to be fulfilled by providing a well-designed system. However, end users usually encounter various problems when interacting with information retrieval (IR) systems and it is even more so for novice users. The most common problem reported from previous research is that novice users do not know how to get started even though most IR systems contain help mechanisms. There is a deep gap between the system\u27s help function and the user\u27s need. In order to fill the gap and provide a better interacting environment, it is necessary to have a clearer picture of the problem and understand what the novice users\u27 behaviors are in using IR systems. The purpose of this study is to identify novice users\u27 help-seeking behaviors while they get started with digital libraries and how their learning styles lead to these behaviors. While a novice user is engaged in the process of interacting with an IR system, he/she may easily encounter problematic situations and require some kind of help in the search process. Novice users need to learn how to use a new IR environment by interacting with help features to fulfill their searching needs. However, many research studies have demonstrated that the existing help systems in IR systems cannot fully satisfy users\u27 needs. In addition to the system side problems, users\u27 characteristics, such as preference in using help, also play major roles in the decision of using system help. When viewing help-seeking as a learning activity, learning style is an influential factor that would lead to different help-seeking behaviors. Learning style deeply influences how students process information in learning activities, including learning performance, learning strategy, and learning preferences. Existing research does not seem to consider learning style and help-seeking together; therefore, the aim of this study is to explore the effects of learning styles on help-seeking interactions in the information seeking and searching environment. The study took place in an academic setting, and recruited 60 participants representing students from different education levels and disciplines. Data were collected by different methods, including pre-questionnaire, cognitive preference questionnaire, think-aloud protocol, transaction log, and interview. Both qualitative and quantitative approaches were employed to analyze data in the study. Qualitative methods were first applied to explore novice users\u27 help-seeking approaches as well as to illustrate how learning styles lead to these approaches. Quantitative methods were followed to test whether or not learning style would affect help-seeking behaviors and approaches. Results of this study highlight two findings. First, this study identifies eight types of help features used by novice users with different learning styles. The quantitative evidence also verifies the effect of learning styles on help-seeking interactions with help features. Based on the foundation of the analysis of help features, the study further identified fifteen help-seeking approaches applied by users with different learning styles in digital libraries. The broad triangulation approach assumed in this study not only enables the illustration of novice users\u27 diversified help-seeking approaches but also explores and confirms the relationships between different dimensions of learning styles and help-seeking behaviors. The results also suggest that the designs and delivery of IR systems, including digital libraries, need to support different learning styles by offering more engaging processing layouts, diversified input formats, as well as easy-to-perceive and easy-to-understand modes of help features

Beyond The Book: Promoting Effective Research

In the past library professionals have primarily collected and provided access to materials; however, this paper will argue that we must now go beyond access or Beyond the Book. One way to do this is to learn about the information search process and then assume a new and more assertive role as a research advisor. We need to change our patrons \u27expectations so that they see us as knowledgeable about sources, yes, but also as experts on effective research as a process of discovery. Three relevant information search process models are covered, as well as the way people vary in their learning styles and thus approaches to research

The contribution of data mining to information science

The information explosion is a serious challenge for current information institutions. On the other hand, data mining, which is the search for valuable information in large volumes of data, is one of the solutions to face this challenge. In the past several years, data mining has made a significant contribution to the field of information science. This paper examines the impact of data mining by reviewing existing applications, including personalized environments, electronic commerce, and search engines. For these three types of application, how data mining can enhance their functions is discussed. The reader of this paper is expected to get an overview of the state of the art research associated with these applications. Furthermore, we identify the limitations of current work and raise several directions for future research

Encountering on the road to Serendip? Browsing in new information environments

Considers the continuing relevance of the ideas of browsing, serendipity, information encountering, and literature discovery in a digital information environment