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Knowledge Science & Engineering Institute, Beijing Normal University, Analyzing Transcripts of Online Asynchronous.

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Presentation on theme: "Knowledge Science & Engineering Institute, Beijing Normal University, Analyzing Transcripts of Online Asynchronous."— Presentation transcript:

1 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Analyzing Transcripts of Online Asynchronous Discussion Groups with VINCA Yanyan Li Knowledge Science & Engineering Institute, School of Education Technology, Beijing Normal University liyy1114@gmail.com

2 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Outline Existing tools VINCA introduction Further development

3 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Existing Tools Annotation aids Nvivo (http://www.qsrinternational.com/)http://www.qsrinternational.com/ Atlas-ti (http://www.atlasti.de).http://www.atlasti.de Dictionary-based content analysis CATPAC LIWC (http://www.erlbaum.com)http://www.erlbaum.com Development environments Profiler Plus DIMAP (http://www.clres.com)http://www.clres.com

4 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Shortcomings of the tools Not integrated Coding process is largely manual Not learnable Display coding results in text or tables Lack of freestanding content analysis packages incorporating text mining.

5 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Our goal Can we design and implement an integrated tool to assist identifying features of interaction and provide feedbacks to facilitate the collaboration in CSCL?

6 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Implementing a Tool to Support Discussion Transcripts Analysis

7 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Multidimensional Analysis How do the students talking with others? What are the students talking about? Who are talking to whom? Process Pattern Speech Topics Member Relationship Interaction Discourse Keywords in context Semi-auto Coding Statistics for Social Network Analysis

8 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Tool Design Framework

9 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Vinca ‘ s Features Learnable semi-automatic coding support Analyze text in Chinese (traditional and simplified) Utilize computational language & text mining technologies Support assessing for CKB Underlying technologies Syntax analysis Domain ontology Association rules mining

10 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn 1) Data preparation Data preparation to convert Knowledge Forum (KF platform) discourse in html to database format  From Version 3.4  From Version 4.5

11 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn 2) Annotation Aids Edit Coding Scheme  New, Modify, Delete Associate feature keywords to specific codes Annotation  Support segment & merge  *Automatic discover the code hint, highlight it and attach possible codes with confidence probability.  During the process of coding, users are allowed to select the hint to mark the final coding. View Coding Result Suggested codes

12 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn 3) Text Analysis Keywords retrieval & frequency counting Concordance *Discourse pattern discovery *Category analysis  Similarity Computation *Text clustering Ontology-based assessing for CKB

13 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Word Frequency (Keywords Retrieval) Select Data  From KF  From Speech File  From Single Text File Exclusive List  Special  Common Tag Filter Picked List Find Keywords in Word List Export Keywords & User Keywords Distribution Import user ’ s lexicon Select exclusive list Select the words with specified tags

14 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn 14 Concordance List of extracted keywords Concordance

15 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Check the original text

16 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Discourse Pattern Discovery Pattern configuration interface Frequent pattern mining results

17 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Category Analysis Open Category File Search Para Synonyms in Interaction Text Based on Similarity Computation Category List Lexicon specified by tutors and auto-found synonyms

18 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Text Clustering Select Data.. Get Keywords.. Set Option Export Result of Text Clustering

19 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn 19 Assessing for CKB Group Performance Member Contribution Topic similarity between members Domain ontology

20 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn 4) Data Export for SNA Export KF Data Export Relation Matrix Export Coding Result Export Coding Matrix Export Coding Frequency

21 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Annotation aids  Semi-automatic coding with enhanced precision Text analysis  Category analysis for topic recognition  Discourse Pattern discovery Visualization  Topic space  Social network Further Development

22 Knowledge Science & Engineering Institute, Beijing Normal University, http://ksei.bnu.edu.cnhttp://ksei.bnu.edu.cn Thanks! Welcome Questions and Comments


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