Applying web analytics in a K-12 resource inventory

Purpose – This paper seeks to investigate how to use a web analytics tool to conduct deep analysis of users' web behaviors. This study aims to focus on examining whether the types of traffic sources and temporal fluctuation influence the web visitors' performance on the web portal of a K‐12 resource inventory.Design/methodology/approach – One year's data were collected via the Advanced Segmentation function of Google Analytics. To compare visitors' behavior from different types of traffic recourses with the intervention of temporal effect, clickstream data of three visitor segments were collected.Findings – Traffic sources and temporal effect have been found to influence web site visitors' performance interactively. Search engines seemed good at bringing a significantly large amount of traffic to the eThemes site, but most visitors are likely “information encounters”. However, visitors from direct traffic (bookmark/typed URLs) seemed to visit the eThemes site purposefully – stay for a long time on the sit...

[1]  Mimi Recker,et al.  Using web metrics to analyze digital libraries , 2008, JCDL.

[2]  Arun Sen,et al.  Current trends in web data analysis , 2006, CACM.

[3]  Mimi Recker,et al.  Perspectives on Teachers as Digital Library Users: Consumers, Contributors, and Designers , 2006, D Lib Mag..

[4]  Andy Phippen,et al.  An evaluative methodology for virtual communities using web analytics , 2004 .

[5]  Brian Clifton,et al.  Advanced Web Metrics with Google Analytics , 2008 .

[6]  Ophir Frieder,et al.  Temporal analysis of a very large topically categorized Web query log , 2007 .

[7]  Ming-der Wu,et al.  Elementary schoolteachers' use of instructional materials on the web , 2008, Electron. Libr..

[8]  Jennifer LeClaire,et al.  Web Analytics For Dummies , 2007 .

[9]  Anita Sundaram Coleman,et al.  Developing a Web Analytics Strategy for the National Science Digital Library , 2004 .

[10]  Yun Chi,et al.  Structural and temporal analysis of the blogosphere through community factorization , 2007, KDD '07.

[11]  Steven Furnell,et al.  A practical evaluation of Web analytics , 2004, Internet Res..

[12]  M Wjst.  When Air Is Rare: Behind the Scenes of an Asthma Web Site , 2001, The Journal of asthma : official journal of the Association for the Care of Asthma.

[13]  M. Volman,et al.  The Web as an Information Resource in K–12 Education: Strategies for Supporting Students in Searching and Processing Information , 2005 .

[14]  Paul Alpar,et al.  Measuring the Efficiency of Web Site Traffic Generation , 2001, Int. J. Electron. Commer..

[15]  Kent J. Crippen,et al.  The Sites Teachers Choose: A Gauge of Classroom Web Use , 2007 .

[16]  Marshall Breeding.  An analytical approach to assessing the effictiveness of Web-based resources , 2008 .

[17]  Carol Tenopir,et al.  What deep log analysis tells us about the impact of big deals: case study OhioLINK , 2006, J. Documentation.

[18]  Mary L. Gillaspy,et al.  Factors Affecting the Provision of Consumer Health Information in Public Libraries: The Last Five Years , 2005, Libr. Trends.

[19]  John Wedman,et al.  eThemes: An Internet Instructional Resource Service. , 2001 .

[20]  Jason J. Jung.  Collaborative Web Browsing Based on Semantic Extraction of User Interests with Bookmarks , 2005, J. Univers. Comput. Sci..

[21]  Jerri Ledford,et al.  Google Analytics 2.0 , 2007 .

[22]  Philip M. Davis.  Information-seeking behavior of chemists: A transaction log analysis of referral URLs , 2004, J. Assoc. Inf. Sci. Technol..