1. Athabasca University School of Computing and Information Science
Effects of Individual Differences and Visual Information Seeking on Learning Strategies in Essay Writing
Nathan Laan
Athabasca University School of Computing and Information Science

2. Nathan Laan - Bio
IT Applications Manager for the Edmonton Police Service.
Background in Software Architecture, Design, and Development.
Working in Software Development and IT for 17 years.
Live in Edmonton Alberta with my wife and three kids, aged 3 through 9.
Education includes a BSc in Computing Science.

3. Supervisory Committee
Dr. Dunwei Wen
Associate Professor, School of Computing & Information Systems, Athabasca University
Dr. Dragan Gasevic
Professor, Schools of Education and Informatics, University of Edinburgh
Dr. Phil Winne
Associate Dean, Graduate Studies in Education, Simon Fraser University
Professor, Faculty of Education, Simon Fraser University

4. Purpose
Investigate effects of (1) individual differences and (2) information visualization on exploratory search when given the task of researching a topic and completing a short essay
Investigate how users explore topics
Explore how users construct search queries

5. Background Individual Differences Term-net / Concept Map Web Trace
The ways in which individuals differ in behavior.
The different processes that individuals follow or use.
Term-net / Concept Map
A graph providing a visualization of terms / concepts and the relationship between them.
Nodes (terms / concepts) and Edges (relationships).
Web Trace
Technique for instrumenting, analyzing, and visualizing user activity on the web.

6. Research Questions
What information seeking and learning strategies do learners use when interacting with conceptual maps to find and integrate information in writing an essay on a given theme?
What is the effect of individual differences on information seeking and learning strategies when interacting with conceptual maps to find and integrate information in writing an essay on a given theme?

7. Hypothesis
Expecting to see application of strategies via a careful analysis of web trace data
Selection and navigation.
Trial-and-error.
Indicators expected to include number of search keywords, page viewing times, page content, and the number of resources that participants make use of.
Expecting a correlation between
Relative level of motivation.
Amount of time spent applying strategies, using the search tools, and navigating through the concept map.

8. Materials Each participant will require: Computer workstation
Customized web browser
Internet access
Access to “custom search portal” tool

9. Method Laboratory experiment
Participants tasked with using a search tool (
Goal is to research and write a short word essay
Topic: “Identify a security technology that is used by people every day. Then, exploring the topics in the term-net, describe how a security exploit might impact someone.”

10. Experimental Process
Participants given overview of the study, and provided with informed consent.
Participants provided with anonymous login for the search tool and concept map.
Participants complete tutorial guiding them through the search tool and concept map.
Participants given achievement goal orientation questionnaire, as well as a pre-test Likert-scale questionnaire to evaluate their existing knowledge of the topic.
Participants given topic and associated concept map.
Participants provided with the essay question.
Participants instructed to conduct research using the concept map, and then write a short word essay response based on their research.
Participants asked to complete post-test tool evaluation and perceived usefulness questionnaires.

11. Measurement
Research method requires logging user activity for analysis.
Participants provided with a web-based search application.
Unique, anonymous Login ID.
Based on the Google Custom Search Engine (CSE) technology.
Allows us to target specific sets of data for the user to search.
Allows for precise logging of user activity.

12. Experimental Data Anonymous Login ID assigned to the participant
Pre-study Achievement Goal Orientation (AGO) Likert-scale answers
Pre-study Prior Knowledge Assessment Likert-scale answers
Need for Cognition questionnaire Likert-scale answers
The essays to the set theme to be prepared by the participant during the experiment
Web trace (log) data collected by the web search tool

13. Data Analysis Post-experimental analysis
Statistical data for web traces
Cluster analysis for graph (concept map) usage
Comparative analysis between graded essay responses and cluster analysis

14. Selected References
Butcher, Kirsten R., and Tamara Sumner. "Self-directed learning and the sensemaking paradox." Human– Computer Interaction (2011):
Hadwin, A., Nesbit, J., Jamieson-Noel, D., Code, J., & Winne, P. (2007). Examining trace data to explore self-regulated learning. Metacognition Learning, 2, 107–124.
Marchionini, Gary. "Exploratory search: from finding to understanding." Communications of the ACM (2006):
Novak, Joseph. "Concept mapping: A useful tool for science education." Journal of research in science teaching (1990):
Puustinen, Minna, and Jean-François Rouet. "Learning with new technologies: Help seeking and information searching revisited." Computers & Education 53.4 (2009):
Winne, P. (1982). Minimizing the black box problem to enhance the validity of theories about instructional effects. Instructional Science, 11,
Winne, P., & Perry, N. (2000). "Measuring self-regulated learning”.
Full references available on request.