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Byrne, Tang, Tang, Tranduc

Byrne, Tang, Tang, Tranduc Web 2.0 Electronic Teaching and Tutoring Assistant (eTA) Products and their Distribution Potential Research Products: the Electronic Tutoring and Teaching Assistant (eTA) Suite: Research in Online Education Mittal, Ankush , 2006; Chen, Nian-Shing, 2008

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Byrne, Tang, Tang, Tranduc

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  1. Byrne, Tang, Tang, Tranduc Web 2.0 Electronic Teaching and Tutoring Assistant (eTA) Products and their Distribution Potential

  2. Research Products: the Electronic Tutoring and Teaching Assistant (eTA) Suite:

  3. Research in Online Education Mittal, Ankush , 2006; Chen, Nian-Shing, 2008 Subset of Text Mining = Semantic Analysis Richard Landauer Technique = Latent Semantic Analysis Application = Automated Essay Scoring (Burstein, 2004) Text Mining as Core Technique

  4. A client based and server computer application to detect plagiarism Key word function to download Web Pages Compares up to 100 student papers Uses author’s semantic algorithm to eliminate noise Fast and stable ePaperCompare

  5. automated student essay scorer to assess student writing Algorithms based on: Flesch Kincaid Equations Latent Semantic Analysis Proprietary semantic algorithm Initial Beta Testing = 70-85% correlation between machine and human reader eGrader

  6. application to improve reading speed, comprehension and retention Traditional speed reading scroll bar Allows student to: Translate text to speech Increase speech speed Highlight important parts of text Generate reports Print out of highlighted words and phases List of frequency of important names and concepts Vector context of frequent names and concepts eReader/eSpeaker

  7. Academic Research Search Engine Key word function to download Web hits Compares template articles with Web articles Automatically filters out and selects relevant articles based on: Content/ lack of Writing sophistication congruency/ in-congruency Redundancy eResearcher

  8. Text and Exercises to improve IQ Online Interactive Tutorial Meta Method to improve ability to take standardized tests ACT, SAT, LSAT, GMAT, GRE Semantic Algorithms reduced to Boolean Logic Possible AI applications IQ Enhancer (iqE)

  9. Method: Bibliometrics Developed by library scientists: Ball, 2006 Method to measure frequency of publications as indicator of interest. Interest in “Online Learning Software” According to Google = general interest (in hundreds) According to ERIC = education interest Market Analysis

  10. Results Chart shows: • a rise in interest from 1998 to 2001, • a decline from 2001 to 2003, • and an increase again from 2005 to 2008. • Decline from 2001-2003 = f (IT Bubble Bust?)

  11. Interest in Specific Online Learning Products

  12. Current Levels of Interest • Hits correlate well with our previous bibliometric analyses with high interest in • reading improvement • online tutoring May 15, 2009 Google News Hits

  13. “Online study groups’ as a subset of “online tutoring groups.” Received hits for the first time Chaker, 2009 Cramster.com eduFire.com TutorVista.com Unexpected Results

  14. Founded by: Sean McCleese and Nikhil Sreenath (aged 25) (http://studentoffortune.com/) Average: $15 Fee/transaction Revenue in millions at a 12.5% WEEKLY increase Users make money Top tutor: college senior $60,000 per year Source: http://www.guardian.co.uk/business/feedarticle/8517937. May 10, 2009) Student of Fortune

  15. Rank of interest in applications 1. reading improvement software 2. online tutoring software 3. plagiarism detection software 4. critical thinking software 5. academic search engines 6. automated writing scoring machines Conclusion

  16. Potential areas of needed research 1. emerging education social networks for the student market 2. possible social networks for the teaching market If education social networks become prominent online tutoring software could have great commercial potential Effect on assessment given tutoring software Ethical issues More Research Needed

  17. Comments Marketing suggestions? Call for participation: All applications described are or will be open source. • Would anyone like to work on any of our research projects? • Would anyone be interested in testing any of the products? • Please contact Michael Tang at: Michael.tang@ucdenver.edu. Discussion

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