My areas of teaching include research methods and statistics, Web search engines and Web data mining, information retrieval, database management systems, and informetrics.
I particularly enjoy teaching statistics and have been teaching this subject in various disciplines at levels from undergraduate to doctoral. I use logical reasoning rather than mathematical deduction to explain statistical concepts and tests. Most students in my classes have very little mathematical background and many enter the course with feelings of fear and nervousness. However, they were pleasantly surprised at how painless statistics can be and how exciting it is to understand a subject that was once mysterious and foreign to them. Based on my decade of experience teaching statistics, I published a book called Statistical
Methods for the Information Professional: A Practical, Painless Approach to
Understanding, Using, and Interpreting Statistics. The book received highly positive reviews published in major journals such as Journal of Documentation, International Journal of Information Management, and Library & Information Science Research.
Currently, the focus for my research is the World Wide Web, including Web data mining, evaluation of Web search engines and Webometrics (the analysis of Web-related information using quantitative methods). My research projects on Web data mining for business intelligence have been funded by the Social Sciences and Humanities Research Council of Canada. A paper from the project titled "Mapping Business Competitive Positions Using Web Co-link Analysis" (co-authored with J. You) won the Best Paper Award in Applied Bibliometrics at the 10th International Conference of the International Society for Scientometrics and Informetrics, held in Stockholm, Sweden, July 26, 2005.