Hellenic Open University, School of Science s & Technology,

1. Collaborative learning: Reasons that influence the participation of students in distance education fora Kiriakos Patriarcheas - Michalis Xenos Hellenic Open University, School of Sciences &Technology,

2. A key tool that supports communication in distance education is the electronic forum or e-forum. Distanec education e-forum

3. In recent years, the Hellenic Open University (HOU) has turned to the modeling of messages in order to classify the interventions of participants in its fora into large categories in order to detect where the subject of interest of the discussion is focused.

4. Content • Goal, When, For who, Where • Data • Method, Modelling in formal Language • Tool • Data analysis • Questions

5. Goal • This study focuses in the study of the reasons that influence the participation of students in a forum, by studying the causes that strengthen or discourage participation in the HOU fora.

6. When • For the academic years 2005-8 2006 2005 2006 2007 2007 2008

7. For who • Within the framework of a course module (INF10) of School of Sciences & Technology

8. Where In Patras, Greece.

9. Data • The data comprised of 423 discussion threads with 3,542 messages and 6,694 message content categories.

10. Method • This study uses a specific modelling developed for Hellenic Open University’s fora

11. Modelling in formal Language • There are two categories of communication’s carriers: a) Teachers, b) Students (For brevity reasons, teachers shall be symbolized with T and students with E) • As for the type of message, they are discerned to questions and replies (answers). Using the symbolsqand a respectively. • As for their content category, we use the symbols: M, X, P, I, F, D, J, G, V, L • The order in which appear the above symbols is: a) the message carrier, b) the type of message and c) the content category to which the message belongs.

12. Content categories • i) study of educational material (M), • ii) questions/answers for exercises – assignments (X), • iii) presentation of sample assignments by tutors (P), • iv) instructions (I), • v) assignment comments, corrections (F), • vi) student comments on assignments (D), • vii) sending – receiving assignments (J), • viii) sending - receiving grade marks (G), • ix) notification of advisory meeting (V) and • x) pointless message (L).

13. Rules • The grammar P: A set of rules of the form α → β, where α and β sequences containing terminal and non-terminal symbols and α is not an empty sequence, as follows:

14. An example • Sequence EqMEqXTaMX: Ε for the student’s capacity, q for the question, Μas it concerns the study of the educational material, Χfor the fact that the next message concerned an assignment, T for the teacher’s capacity, a for the fact that it is an answer, M for the fact that this reply concerns the study of educational material and Xfor the fact that the second part of the message concerns an assignment. According to the above, the sequence EqMEqXTaMX constitutes a sentence of the Language because: Rule: (1) (1) (1) (3) S —>ruS —>ruruS —>rururuS —>ruycruycruycS (4)(6)(8)(11) (4)(6)(8)(11) —————> EqMruycruycS —————> EqMEqXruycS (3) (2)(4)(5)(9)(10)(12) —>EqMEqXruycycS ————————> EqMEqXTaMX

15. The Tool According to this approach, it was developed a system of automatic classification, which comprised the following: • a) Data filtering: • b) Storage of roots files: • c) Strings’ production:

16. Data filtering • Where there are considered as input some web pages accommodating the discussion threads of a distance education forum of HOU (which include much data having no essential information concerning the educational procedure e.g. titles, images etc.) and creates a temporary file with the “useful” part (User name, date, message’s content) which may become a source of information for educational conclusions.

17. Storage of roots files • A dynamic way according to which word or phrases or symbols roots are stored, as well as the respective terminal symbols q if it is a question or a if it is an answer. The same thing was done also for the storage of information necessary for the determination of content category of a message, i.e. if it is about study, assignment, comment etc. or combination of them (e.g. a message concerning both the study and an assignment). To wit, it takes as input couples of information of the type root of a word or phrase and terminal symbol of the content category (M, X, P, I, F, D, J, G, V, L). The system provides the ability to add further content categories if necessary.

18. Strings’ production • Receiving as input the temporary file with the “useful” information (User name, date, message’s content) and the files with the couples of roots words/ phrases/ symbols and terminal symbols and presents (and stores) the respective strings with the relative extensible file, so as the results to be kept for further exploitation. EqMEqXTaMX

19. Input

20. Output • Representation of discussion thread in simple string

21. Output after the addition of User names and dates.

22. Data analysis • Based on the above methodology, if for each discussion thread we take into account who starts it (Tutor or Student) then it is apparent that the threads started by a tutor have more messages: 10.97 messages/thread versus 5.06 in threads started by students. TABLE I The ratio of messages per discussion thread in INF 10 of HOU during years 2005-8

23. Data analysis • It should be noted however that this phenomenon does not have the same intensity throughout the academic year, but there is a rising trend in the months October through December, a fact that means the gradually increasing participation of students in the forum in the first months of the academic year, followed (in January) by a decline of the effect of the phenomenon, a sharp rise in February and then an ongoing decline until the end of the academic year.

24. Data analysis TABLE II The ratio of messages/discussion thread in total (A) and in threads started by the Tutor (B) per month

25. Data analysis

26. Data analysis • The period when a discussion thread is started plays a definite role, and we can distinguish 4 distinct periods: a) high participation in the first active months (October-December), peaking in November, b) followed by a period of decline (January-March), with a peak in February and c) lower participation period (April - May), with the threads started by the tutor always having preponderance over the total number and d) very low participation (June - September), with the exception of June, something which is mostly due to the fact that exam results are announced and explained by the tutor and the students have a relevant discussion.

27. Data analysis • We should also take into account in the above that in the months November and February the 2 first written assignments are submitted, a fact that explains (proportionally) the two peaks of participation.

28. Data analysis TABLE III Number of discussion threads and messages in total and in threads started by the Tutor per month

29. Data analysis • With regard to which subject categories are the focus of the discussion, based on this methodology, it arises that categories questions/answers for exercises - assignments (X) and study of educational material (M) are the most popular.

30. Data analysis • An important category also is student comments on assignments (D) which comes in 3rd totally with 919 appearances, a fact that shows that students like to comment on assignments of other students and make observations. Furthermore, the great difference in category instructions (I) in threads started by the tutor compared to those started by students (110 versus 42) shows that the basic “channel” in the provision of instructions passes through the tutor, and despite the tutor's encouragement for the exchange of opinions between students, they continue to trust their tutor in the provision of instructions throughout the academic year.

31. Data analysis • The low appearance of the “functional” categories sending - receiving assignments (J), sending - receiving grade marks (G) and notification of advisory meeting (V), appears as expected, even though here we see the phenomenon of declining participation, a fact that means that from January and onwards students turn to more traditional forms for functional procedures (email, conventional mail, etc.).

32. Data analysis • It is finally remarkable that the category pointless message (L) mostly related to messages with wishes for holidays, vacations, etc, is 5th in threads started by students and 10th in threads started by teachers, a fact that means that socialization in the student group is a strong parameter and is (proportionately) high in their ranking during their participation in the forum.

33. Data analysis TABLE IV Number of appearances of message content categories based on modeling in years 2005-8 in INF10 of HOU

34. Data analysis • If the above approach is analyzed at the monthly time level, we have the following results per message content category. TABLE V

35. TABLE VI Number of appearances of message content categories based on modeling in years 2005-8 in INF10 of HOU per month in the threads started by tutors

36. Data analysis

37. Data analysis There is a similar picture when it comes to threads started by students related to the subject categories on which the discussion’s interest focuses (table VII) but with different intensity.

38. TABLE VII Number of appearances of message content categories based on modeling in years 2005-8 in INF10 of HOU per month in the threads started by students

39. Data analysis

40. TABLE VIII Ratios of number of message content categories of threads started by tutors to the total number and the messages respectively

41. Data analysis – Conclusion In the middle of the academic year aphenomenonisobserved where participation in threads started by the Tutor declines more than participation in threads started by students, both in quantity (in number of messages) and in quality (in appearances of content categories) a fact that means that fewer students stay in the forum, but that they are more active.

42. Data analysis – Conclusion Thus, the middle of the academic year functions as a “cross-road” where many students (most of them, because total participation falls) cease to participate, while others (fewer ones, because the B/C ratio declines both in Appearance Number level and in Messages Number level) participate more actively.

43. TABLE IX Ratios of number of message content categories of threads started by tutors to threads started by students and messages respectively

44. Data analysis

45. Data analysis • The above results which arise from all the data for years 2005-8, are verified at the annual level, as well as for the current and previous year, meaning that they are recurrent phenomena.

46. Questions? Thank you! http://quality.eap.gr xenos@eap.gr