collaborative learning

Collaborative and Non-collaborative Learning of small groups in virtual environments Elisa Guidi*^ and Cristina Cecchini*^ *Department of Information Engineering, University of Florence ^Interdepartmental Centre for the Study of Complex Dynamics, University of Florence

BACKGROUND

INTRODUCTION Recent Research:

Interdepartmental Center for the Study of Complex Dynamics (CSDC)

Departments University of Florence

Virtual community: Social dynamics VIRTHULAB

Collaborative learning (Francescato et al., 2007) Civic participation Mutual support (Blanchard & Markus, 2004)

Education Prevention Health promotion

Web-based experimental interventions (Bennett & Glasgow, 2009)  www.sostanze.info  Laboratory Of Virtual Community Psychology -University of Rome

AIMS

METHOD

Virtual environment: Small group effects on collaborative learning  not complex tasks 1. Gender differences and group composition (Homo, Hetero, Prevalent gender)

Participants N= 144 (Male 50%) Age: M = 29.28, SD = 10.698 Education: M = 14.66 years, SD = 3.946

CHAT

Deese/Roediger-McDermott Paradigm (DRM) Individuals, Nominal groups and Collaborative groups in simple memory tasks (Roediger, 2010)

2. Communication/information (Abstracted Vs Concrete words) and experimental condition (Individual, Nominal group and Collaborative group)

Instruments •List of words A: Abstracted (e.g. Anger) •List of words B: Concrete (e.g. Guitar)

3. Social interactions in virtual collaborative groups

DATA ANALYSIS: SPSS; Linguistic Inquiry and Word Count (LIWC)

RESULTS Independent-samples t-Test analysis by homogeneous gender (female groups vs male groups)

2. Communication/Experimental condition

8,09 INDIVIDUAL: Correct Answers

1. Gender Differences

7,09

Female Groups

8,14 7,25

NOMINAL: Correct Answers

Independent-samples t-Test analysis by prevalent gender (females Vs males)

Collaborative group  Greater number of correct answers Male Groups

List B (Concrete words: e.g. musical instruments) is easier to learn than List A (Abstracted words: e.g. emotions)

1,77 COLLABORATIVE: False Memories

8 INDIVIDUAL: Correct Answers

6,79

Prevalent Females

0

Prevalent Males

1

2

7,02

1

2

3

4

5

6

7

4

5

6

7

8

9

1,79 2,38

NOMINAL: False Memories 0

3

Analysis of Collaborative Group Chat: Correlations among False Memories, Correct Answers and LIWC variables

Independent-samples t-Test analysis by heterogeneous Vs homogeneous gender

7,93 NOMINAL: Correct Answers

3. Social Interactions

2,91

Heterogeneous Groups

8

7,64 8,7

COLLABORATIVE: Correct Answers

Homogeneous grouos

9,679 11,046

COLLABORATIVE: Number of responses

0

2

4

6

8

10

12

DISCUSSION COMMUNICATION OF CONSTRUCTS Concrete terms: more effective  Computer Supported Collaborative Learning (CSCL). GROUP COMPOSITION Female groups: better performance  Fewer mistakes, more correct answers. Heterogeneous groups: better males performance  Females’ answers + Certainty–based communication (Michailidou & Economides, 2007; Paulus et al., 2002). EXPERIMENTAL CONDITION Collaborative group: better performance  Greater participation (i.e. Higher chat interaction) + All members-addressed communication (e.g., "What do you think, guys?") In-group perception better performance.

Contacts: [email protected] [email protected]

BIBLIOGRAPHY • Bennett, G. G., & Glasgow, R. E. (2009). The delivery of public health interventions via the Internet: actualizing their potential. Annual review of public health, 30, 273-292 •Blanchard, A. L., & Markus, M. L. (2004). The experienced sense of a virtual community: Characteristics and processes. ACM SIGMIS Database, 35(1), 64-79. •Francescato, D., Mebane, M., Porcelli, R., Attanasio, C., & Pulino, M. (2007). Developing professional skills and social capital through computer supported collaborative learning in university contexts. International Journal of Human-Computer Studies, 65, 140–152. • Michailidou, A., & Economides, A.A. (2007). Gender and Diversity in Collaborative Virtual Teams. In K. L. Orvis, A.L.R. Lassiter (ed.), Computer Supported Collaborative Learning: Best Practices and Principles for Instructors (pp. 199-224). IGI Global. • Paulus, P. B., Legett, K., Dzindolet, M. T., Coskun, H., & Putman, V. L. (2002). Social and cognitive influences in group brainstorming: Prediction of production gains and losses. In W. Stroebe, e M. Hewstone, (ed.), European review of social psychology (pp. 299–325). London, United Kingdom: 7 Wiley. • Roediger, H. L. (2010). Reflections on intersections between cognitive and social psychology: A personal exploration. European Journal of Social Psychology, 40(2), 189-205.