Welcome to Maastricht University N@tschool gebruikers dag 2010 Keynote Online Communities Dr. Bart Rienties
Samenvatting Online Communities werken als: Duidelijk doel Kritische massa van participanten Sterke motivatie van participanten Sterke links Waardevolle links Kreatieve links
Wie is er lid van een online community? LinkedIn? Facebook? Hyves? Wiki? Newsgroup/discussion forum community?
LinkedIn vs Facebook for finding a new job Growing importance of internet on job-searcher s strategies (Fountain, 2005). Job-search strategies formal, informal and direct application. Informal job-search strategies include the use of personal contacts, such as relatives, friends and co-workers whom act as referrals and provide inside information on job openings. Informal search saves on search costs. Rienties, B., Tempelaar, D. T., Pinckaers, M., Giesbers, B., Lichel, L., (2010). The effects of online social networks sites on receiving job information, International Journal of Sociotechnology and Knowledge Development, XX (XX), p. XX-XX.
Theoretical framework I Strength of weak ties Granovetter (1974): strength of a social relationship or tie affects job-searchers by amount + quality of job-information. A tie is defined as weak when personal contacts see each other occasionally. Such a weak tie can have a bridging function. H1. SNS members who have received information about job openings via their SNS have a greater amount of weak ties in their SNS than SNS members who have not received information about job openings via their SNS. Rienties, B., Tempelaar, D. T., Pinckaers, M., Giesbers, B., Lichel, L., (2010). The effects of online social networks sites on receiving job information, International Journal of Sociotechnology and Knowledge Development, XX (XX), p. XX-XX.
Theoretical framework II Structural Holes Burt (1992):individuals gain more from social networks as structural hole Structural holes are those places in between networks where relations or bridges are absent and links do not exist, H2. SNS members who did receive information about job openings via their SNS have a higher network entrepreneur personality index than SNS members who have not received information about job openings via their SNS. Rienties, B., Tempelaar, D. T., Pinckaers, M., Giesbers, B., Lichel, L., (2010). The effects of online social networks sites on receiving job information, International Journal of Sociotechnology and Knowledge Development, XX (XX), p. XX-XX.
Theoretical framework III Social Capital Theory (Lin, 2001) Social Capital: value of the resources that off- or online social network ties hold: 1. Embedded resources facilitate information flows reducing transaction costs to find job opportunities. 2. Social ties may influence recruiters who play a critical role in decisions involving the job searcher. 3. Social ties may be conceived by a recruiter as certification of social credentials. 4. Provides emotional support but also public acknowledgement of one s accessibility to certain sources. H3. SNS members who have received a job offer via their SNS hold higher levels of resources then SNS members who have not received a job offer via their SNS. Rienties, B., Tempelaar, D. T., Pinckaers, M., Giesbers, B., Lichel, L., (2010). The effects of online social networks sites on receiving job information, International Journal of Sociotechnology and Knowledge Development, XX (XX), p. XX-XX.
Table 1 Descriptive statistics of SNS membership, network contacts and information about a job opening Students Non- Manager Manager F LinkedIn Members hip (in %) 49.38 81.81 89.86 35.064** Facebook Membership (in %) 87.65 75.00 52.53 20.287** Contacts in LinkedIn 63.77 78.14 120.29 3.882* Contacts in Facebook 184.07 120.72 122.45 4.360* W eak contacts in LinkedIn 41.55 57.04 91.37 3.473* Weak contacts in Facebook 149.35 94.50 99.55 3.975* Clos e contacts in LinkedIn 22.23 21.10 29.23 1.839 Close contacts in Facebook 34.72 26.23 22.50 1.801 Network Entrepeneur Personality Index 5.75 5.52 5.62 0.570 Job information received (in %) 22.22 32.95 42.39 5.554** ANOVA with students (N= 81), non-managers (n=88) and managers (n=217) **Coefficient is significant at the 0.01 level (2-tailed). *Coefficient is s ignificant at the 0.05 level (2-tailed). Rienties, B., Tempelaar, D. T., Pinckaers, M., Giesbers, B., Lichel, L., (2010). The effects of online social networks sites on receiving job information, International Journal of Sociotechnology and Knowledge Development, XX (XX), p. XX-XX.
Table 3 Comparison of receivers of information about a job opening and non-receivers Students Non- Manager Manager LinkedIn M embership (in %) 2.832** 2.578* 3.904** Facebook Membership (in %) Contacts in LinkedIn 3.414** 3.061** Contacts in Facebook W eak contacts in LinkedIn 2.683* 3.205** 2.304* Weak contacts in Facebook Close contacts in LinkedIn 2.272* 2.285* 4.357** Close contacts in Facebook Network Entrepeneur Personality Index 1.756 2.681** A NOVA F-v alu e o f jo b -in fo receiv ed v s n o jo b -in fo receiv ed with students (N= 81), non-managers (n=88), and managers (n=217) * * Co efficien t is s ig n ifican t at th e 0.01 lev el (2-tailed ). * Co efficien t is s ig n ifican t at th e 0.05 lev el (2-tailed ). Coefficient School of Business is significant and at Economics the 0.10 level (2-tailed). Rienties, B., Tempelaar, D. T., Pinckaers, M., Giesbers, B., Lichel, L., (2010). The effects of online social networks sites on receiving job information, International Journal of Sociotechnology and Knowledge Development, XX (XX), p. XX-XX.
Thus. For LinkedIn members: close ties (b = 0.20) and weak ties (b = 0.18) The structural holes hypothesis is rejected in our sample. Neither tie-strength nor network entrepreneurial personality index good predictor for students For non-managers, weak-ties (b = 0.44) significantly predict receiving information about job openings For managers it is primarily close ties (b = 0.27) Thus use LinkedIn and your close contacts to find a new job Rienties, B., Tempelaar, D. T., Pinckaers, M., Giesbers, B., Lichel, L., (2010). The effects of online social networks sites on receiving job information, International Journal of Sociotechnology and Knowledge Development, XX (XX), p. XX-XX.
Agenda School of Business and Economics 1. Wat zijn nu online communities? 2. Hoe werken online communities in praktijk 3. Wat zijn gekende problemen van communities of learning? 4. Welke vormen van communities of learning werken wel? Resultaten van 2 studies 5. Conclusie en discussie
+ e-book system
3. Common problems in community of learning learning 1. Dynamics of community of learning are complex (De Laat et al. 2007; Ahuja et al. 2003) 2. Most community of learnings actually perform differently than anticipated (Alexander, 2006; Giesbers, Rienties, et al., 2009) De Laat & Lally, 2004; Schellens & Valcke, 2005, Rienties et al., 2009). 3. High degree of informal communication. Because of a lack of formal rules, procedures, clear reporting relationships, and norms, more extensive informal communication is required (Ahuja et al. 1999, Rienties et al., 2009) 4. How to establish team cohesiveness, identity and ego involvement (Van de Bossche et al., 2006)? 5. Role of learner complex (Williamson et al. 2006, Rienties et al., 2009, Tempelaar et al., 2009) 6. Role of teacher in community of learning complex (Anderson & Rourke, 2001), De Laat et al. 2007)
4. Major Research findings Effectiveness team problem solving is determined by how well team members are communicating with each other (Jonassen & Kwon, 2001, Rienties et al., 2009) Barron (2003) found that successful teams are able to create a joint problem-solving space Focus of discourse should be broader than just cognitive perspectives (Arts, Gijselaers, & Segers, 2002; Garrison, Anderson, & Archer, 2000; Roschelle & Teasley, 1995; Van den Bossche, Gijselaers, Segers, & Kirschner, 2006) teams have to make an effort in order to establish a dualproblem space, where participants simultaneously contribute both to the content space as well as the relational space (Barron, 2003)
Study 1 Role of Motivation in CSCL Subjects 100 participants were randomly assigned in six groups. The six groups had an average of 13.66 members (SD= 2.16, range = 11-17) per team. The average age was 19 years and 45% of the learners were female. Rienties, B., Tempelaar, D. T., Van den Bossche, P., Gijselaers, W. H., & Segers, M. (2009). The role of academic motivation in CSCL. Computers in Human Behavior, 25(6), 1195-1206.
Social interaction in week 1: With whom are learners interacting? Jonas central after 1st week of discussions 9 students participate, 6 do not participate
Jonas, Veronica and Tutor 3 central in 6 weeks of discussions 14 students have participated, 1 student does not participate Several students on outer ring of social interaction (Bernard, Felix, Philip, Christina, Elena, Sandra, Jonathan, Bart) Social interaction in week 1-6
METHOD: integrated multi-method approach Individual contribution to discourse using Content Analysis Content Analysis on social and cognitive discourse of Veerman & Veldhuis-Diermanse (2001), whereby a distinction is made between non-task related (Veerman NTR: 1 planning; 2 technical; 3 social; 4 non-sense) and task-related discourse activity (Veerman TR: 5 facts; 6 experience/opinion; 7 theoretical ideas; 8 explication; 9 evaluation). Three coders independently coded all messages based on unit of meaning Students posted 2307 messages of which 2075 (90%)were considered as codeable (90%). The Cronbach alpha (α) 0.928, the Cohen s kappa was 0.71, 0.71 and 0.68 Position of individual within team using Social Network Analysis Degree of centralisation of each individual of all communication as well as higher cognitive communication; Size of ego density network of each individual. Higher cognitive degree of centralisation using results CA Higher cognitive size of ego density network using CA Academic motivation Scale of Vallerand et al. (1992): Three aspects of intrinsic motivation (IMTK, to know; IMTA, to accomplish; IMES, to experience stimulation) Four other scales of decreasing level of intrinsic, and an increasing level of extrinsic motivation (EMID, identified regulation; EMIN, introjected regulation; EMER, external regulation; AMOT, amotivation). Response-rate 93%, Cronbach alpha for the seven items ranged from.760 to.856 Learners who are high on intrinsic motivation relative to all other students as intrinsically motivated learners. Learners who are relatively high on extrinsic motivation are labelled as extrinsically motivated learners. Learner can have both high levels of intrinsic as well as extrinsic motivation.(90%). Rienties, B., Tempelaar, D. T., Van den Bossche, P., Gijselaers, W. H., & Segers, M. (2009). The role of academic motivation in CSCL. Computers in Human Behavior, 25(6), 1195-1206.
Paul, Jonas and Chris central in higher cognitive discourse in week 1-6 Higher Cognitive Discourse in week 1-6: Who interacts with whom on a higher cognitive level? 11 students contribute to higher cognitive discourse, 4 students and 1 tutor do not.
Overall findings study 1 1. Large differences between students with respect to amount and quality of discourse 2. Differences in contributions explained (in part) by motivation 1. Intrinsically motivated students contribute more to task-related communication 2. Intrinsically motivated students have more connections 3. Intrinsically motivated students are more in the center of the social network 4. Extrinsically motivated students contribute on average but lower on social contributions, which is important for group development (Barron, 2003) 5. Extrinsically motivated students are scattered throughout the network Rienties, B., Tempelaar, D. T., Van den Bossche, P., Gijselaers, W. H., & Segers, M. (2009). The role of academic motivation in CSCL. Computers in Human Behavior, 25(6), 1195-1206.
Study 2 Increasing learning satisfaction with webvideoconference Cohort 1 as described above (82 participants in 6 groups) Cohort 2: weekly videoconferences + discussion forums 69 participants in 5 groups Instruments Academic Motivation Scale Prior Expectations of the course Perceived usefullness of course 33 questions of seven categories: assessment (four items), course design (six items); course materials (three items); goals and tasks (four items); group collaboration (five items); instruction by teacher (five items); and learning satisfaction (five items). Giesbers, B., Rienties, B., Gijselaers, W. H., Segers, M., & Tempelaar, D. T. (2009). Social presence, web-videoconferencing and learning in community of learnings. Industry and Higher Education, 23(4), 301-310.
Videoconferences vs. discussion forums Discussion Forum Videoconference t-test Cohen M SD M SD difference d-value Assessment 14.80 2.41 14.23 2.60 Course Materials 11.29 1.66 10.65 1.80.058.37 Course Design 24.69 2.59 23.76 2.48.064.36 Group Collaboration 18.24 3.34 17.42 3.28 Goals and Tasks 15.15 2.51 15.40 1.82 Instruction 19.53 2.13 20.57 2.09.012* -.50 Learning Satisfaction 19.83 2.50 19.27 2.73 Independent sample T-test (2-sided) of Discussion forum (n=59) vs. Videoconference and Discussion forum (n= *Coefficient is significant at the.05 level (2-tailed). Coefficient is significant at the.10 level (2-tailed). Giesbers, B., Rienties, B., Gijselaers, W. H., Segers, M., & Tempelaar, D. T. (2009). Social presence, web-videoconferencing and learning in community of learnings. Industry and Higher Education, 23(4), 301-310.
Overall findings study 2 1. Students videoconference not more satisfied than students discussion forums 2. Students videoconference less satisfied with course materials and course design 3. Students videoconference more satisfied with instructional support Giesbers, B., Rienties, B., Gijselaers, W. H., Segers, M., & Tempelaar, D. T. (2009). Social presence, web-videoconferencing and learning in community of learnings. Industry and Higher Education, 23(4), 301-310.
5. Conclusies 1. 80-20 rule 2. Sociale interactie in community of learnings complex 3. Persoonlijkheid (motivatie) 4. Meer Social presence leidt niet automatisch tot meer tevredenheid 5. Rol docent bepalend maar complex complex
5. Aanbevelingen 1. Kreeer een veilige omgeving vanaf het begin 2. Wees een actieve coach van het begin 3. Let op persoonlijkheidsverschillen! 4. Kreeer een community voor verschillende lerenden 5. Gebruik SNA en log-in data als early warning system
Samenvatting Online Communities werken als: Duidelijk doel Kritische massa van participanten Sterke motivatie van participanten Sterke links Waardevolle links Kreatieve links
Keynote adres Online Communities 18 juni 2010, Rotterdam Bart.Rienties@maastrichtuniversity.nl http://www.personeel.unimaas.nl/bart.rienties