In this study, a semantic web bookmarking tool called Twine was used in a graduate level course for K-12 educators. It was found that collaborative teams using the semantic web application developed high levels of expertise. Andrew Lumpe David Wicks

1. Andrew Lumpe David Wicks Seattle Pacific University Evaluation of the Use of Semantic Web Technology in a Collaborative Learning Environment

2. OBJECTIVES Describe the application of a semantic web application in a collaborative learning environment. Report the results on student learning. Provide recommendations for future research and applications of semantic web technologies in educational environments.

3. Overall Goal of Education The overall goal of education is to develop expertise Expert learners vs. Novice learners Have greater access to content Are more skilled at retrieving content Are better at adapting, changing, and recognizing when to apply knowledge Semantic technologies MAY be one way to help develop expertise (Bransford et al, 1999)

4. dullhunk

6. Collaborative Learning Research (Dillonbourg et al, 1996)

7. Personal Learning Networks Holotescu&Grosseck, 2009

8. TWINE

11. How is [Twine] different than other social bookmarking tools like Delicious? “The difference between {the system} and most bookmarking services is that {the system} attempts to identify the resource the page is describing, rather than just recording the location of the page itself. “ (Clarke & Greig, 2009)

12. Context Online graduate education course with weekly, interactive modules –Blackboard 9 N=60 Module 1 General overview of course topics Data used as preTest TWINE not used Modules 2-6 Specific Topics = Advance Organizers, Collaborative Learning, Inquiry/Induction, Conceptual Understanding, Multiple Intelligences TWINE used throughout Data used at postTest

13. Methods Quasi Experimental Design Experimental group used TWINE Data sources = All text posts - discussion posts, blog entries, research papers, TWINE comments WordStat 5.1 – “a text mining tool for fast extraction of themes and trends” Build Dictionaries Related Words and Phrases Word exclusion list Key Word in Context (KWIC) MANCOVA IV = group assignment DV = module posts by five categories Covariate = pretest posts

14. Results Incoming GPAs not different (F = .22, p = .64) Students posted many resources and comments in their twines These resources were regularly used in students’ posts Others outside the course joined and contributed to the twines 356,322 total words used in posts 8,612 related words/phrases included in analyses Equal variances on all DVs (Levene's Test)

15. COLLABORATION

16. a. R Squared = .331 (Adjusted R Squared = .060) b. R Squared = .461 (Adjusted R Squared = .243) c. R Squared = .461 (Adjusted R Squared = .243) d. R Squared = .390 (Adjusted R Squared = .143) e. R Squared = .718 (Adjusted R Squared = .604)

18. Conclusions Use of a Personal Learning Network (TWINE) helped students develop richer, more coherent expertise in 3 out of 5 content categories. TWINE served as a collaborative repository of resources, ideas, and connections. The impact of the semantic nature of TWINE was not apparent.

20. Extended use may be needed in order for semantic technologies to learn interests and provide recommendationsContinue to explore the use of collaborative, semantic technologies to enhance learning Twine T2? http://www.opencalais.com/ http://www.puffinwarellc.com/ (iMetaSearch) http://www.stumpedia.com/ http://imindi.com/

21. Questions?