Cognitive styles and search engine preferences: Field dependence/independence vs holism/serialism

Purpose – Cognitive style has been identified to be significantly influential in deciding users' preferences of search engines. In particular, Witkin's field dependence/independence has been widely studied in the area of web searching. It has been suggested that this cognitive style has conceptual links with the holism/serialism. This study aims to investigate the differences between the field dependence/independence and holism/serialism.Design/methodology/approach – An empirical study was conducted with 120 students from a UK university. Riding's cognitive style analysis (CSA) and Ford's study preference questionnaire (SPQ) were used to identify the students' cognitive styles. A questionnaire was designed to identify users' preferences for the design of search engines. Data mining techniques were applied to analyse the data obtained from the empirical study.Findings – The results highlight three findings. First, a fundamental link is confirmed between the two cognitive styles. Second, the relationship be...

[1]  R. Riding,et al.  Cognitive Styles and Learning Strategies , 2013 .

[2]  Amanda Spink,et al.  A study of results overlap and uniqueness among major Web search engines , 2006, Inf. Process. Manag..

[3]  G. Pask STYLES AND STRATEGIES OF LEARNING , 1976 .

[4]  Peter Clark,et al.  The CN2 Induction Algorithm , 1989, Machine Learning.

[5]  Xiaohui Liu,et al.  An Integrated Approach for Modeling Learning Patterns of Students in Web-Based Instruction: A Cognitive Style Perspective , 2008, TCHI.

[6]  David Miller,et al.  The role of individual differences in Internet searching: an empirical study , 2001 .

[7]  Haibin Liu,et al.  Combined mining of Web server logs and web contents for classifying user navigation patterns and predicting users' future requests , 2007, Data Knowl. Eng..

[8]  Harm J. A. Biemans,et al.  Differences between novice and experienced users in searching information on the World Wide Web , 2000 .

[9]  Jamshid Beheshti,et al.  Design criteria for children's Web portals: The users speak out , 2002, J. Assoc. Inf. Sci. Technol..

[10]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[11]  Klaus Nordhausen,et al.  Modeling successful performance in Web searching , 2006 .

[12]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .

[13]  Nigel Ford,et al.  Individual differences, hypermedia navigation, and learning: an empirical study , 2000 .

[14]  C. J. van Rijsbergen,et al.  A Non-Classical Logic for Information Retrieval , 1997, Comput. J..

[15]  Richard Riding,et al.  Cognitive style, gender and learning from multi-media materials in 11-year-old children , 1999, Br. J. Educ. Technol..

[16]  P. Stephen,et al.  Simple Statistics for Library and Information Professionals , 1995 .

[17]  Xiaohui Liu,et al.  Mining students' behavior in web-based learning programs , 2009, Expert Syst. Appl..

[18]  Melody Y. Ivory,et al.  Evolution of web site design patterns , 2005, TOIS.

[19]  Judit Bar-Ilan,et al.  Comparing rankings of search results on the Web , 2005, Inf. Process. Manag..

[20]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[21]  Nigel Ford,et al.  Matching/mismatching revisited: an empirical study of learning and teaching styles , 2001, Br. J. Educ. Technol..

[22]  Kyung-Sun Kim,et al.  Effects of emotion control and task on Web searching behavior , 2008, Inf. Process. Manag..

[23]  David Miller,et al.  Web search strategies and human individual differences: Cognitive and demographic factors, Internet attitudes, and approaches , 2005, J. Assoc. Inf. Sci. Technol..

[24]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques with Java implementations , 2002, SGMD.

[25]  Nigel Ford,et al.  Learning Styles and Strategies of Postgraduate Students , 1985 .

[26]  Pankoo Kim,et al.  A Comparison of Web Searching Strategies According to Cognitive Styles of Elementary Students , 2004, ICCSA.

[27]  Jaekyung Yang,et al.  Optimization-based feature selection with adaptive instance sampling , 2006, Comput. Oper. Res..

[28]  Daniel E. Rose,et al.  Understanding user goals in web search , 2004, WWW '04.

[29]  Alvaro Soto,et al.  Using data mining techniques to predict industrial wine problem fermentations , 2007 .

[30]  Xiaohui Liu,et al.  Combining multiple classifiers for wrapper feature selection , 2008, Int. J. Data Min. Model. Manag..

[31]  Ian Witten,et al.  Data Mining , 2000 .

[32]  Robert D. Macredie,et al.  Cognitive Modeling of Student Learning in Web-Based Instructional Programs , 2004, Int. J. Hum. Comput. Interact..

[33]  Yoon Ho Cho,et al.  A personalized recommender system based on web usage mining and decision tree induction , 2002, Expert Syst. Appl..

[34]  Heikki Mannila,et al.  Principles of Data Mining , 2001, Undergraduate Topics in Computer Science.

[35]  Ian J. Deary,et al.  Examining wholistic–analytic style using preferences in early information processing , 2006 .

[36]  J. M. Porcel,et al.  A decision tree for differentiating tuberculous from malignant pleural effusions. , 2008, Respiratory medicine.

[37]  Amanda Spink,et al.  Information seeking and mediated searching. Part 4. Cognitive styles in information seeking , 2002, J. Assoc. Inf. Sci. Technol..

[38]  Amanda Spink,et al.  Searching the Web: the public and their queries , 2001 .

[39]  Xiaohui Liu,et al.  The role of human factors in stereotyping behavior and perception of digital library users: a robust clustering approach , 2007, User Modeling and User-Adapted Interaction.

[40]  Cheng-Lung Huang,et al.  A GA-based feature selection and parameters optimizationfor support vector machines , 2006, Expert Syst. Appl..

[41]  C. A. Moore,et al.  Field-Dependent and Field-Independent Cognitive Styles and Their Educational Implications , 1977 .

[42]  Yazdan Mansourian,et al.  Web searchers' attributions of success and failure: an empirical study , 2007, J. Documentation.

[43]  Yen-Liang Chen,et al.  Constructing a multi-valued and multi-labeled decision tree , 2003, Expert Syst. Appl..

[44]  Li-Yen Chang,et al.  Data mining of tree-based models to analyze freeway accident frequency. , 2005, Journal of safety research.