%0 Journal Article %1 doi:10.1080/10494820903281999 %A Toikkanen, Tarmo %A Lipponen, Lasse %D 2011 %J Interactive Learning Environments %K Freeman's analysis degree density inquiry learning network networked progressive social %N 4 %P 365-379 %R 10.1080/10494820903281999 %T The applicability of social network analysis to the study of networked learning %U http://www.tandfonline.com/doi/abs/10.1080/10494820903281999 %V 19 %X Studying networked learning (NL) by applying social network analysis (SNA) has gained popularity in recent years. However, it appears that in the context of NL the choice of SNA indices is very often dictated by using easily achievable SNA tools. Most studies in this field only involve a single group of students and utilise simple indices, such as density and Freeman's degree centrality. This study uses data collected from 23 groups of pupils and correlates various SNA indices with the pupils' experiences of the learning process, thus identifying SNA indices that actually relate to the experiences of a learning process. The results show that density is not very useful in studying NL, and Freeman's degree centrality is meaningful only in certain cases. Further, the study points out several potentially better suited indices for use in further studies of NL.

@article{doi:10.1080/10494820903281999, abstract = { Studying networked learning (NL) by applying social network analysis (SNA) has gained popularity in recent years. However, it appears that in the context of NL the choice of SNA indices is very often dictated by using easily achievable SNA tools. Most studies in this field only involve a single group of students and utilise simple indices, such as density and Freeman's degree centrality. This study uses data collected from 23 groups of pupils and correlates various SNA indices with the pupils' experiences of the learning process, thus identifying SNA indices that actually relate to the experiences of a learning process. The results show that density is not very useful in studying NL, and Freeman's degree centrality is meaningful only in certain cases. Further, the study points out several potentially better suited indices for use in further studies of NL. }, added-at = {2011-08-23T12:55:26.000+0200}, author = {Toikkanen, Tarmo and Lipponen, Lasse}, biburl = {https://www.bibsonomy.org/bibtex/28084400a4ca446acd43a951c33f7d214/enricostano}, doi = {10.1080/10494820903281999}, eprint = {http://www.tandfonline.com/doi/pdf/10.1080/10494820903281999}, interhash = {d2d1b4b134c7727063ff0fb12989d1ac}, intrahash = {8084400a4ca446acd43a951c33f7d214}, journal = {Interactive Learning Environments}, keywords = {Freeman's analysis degree density inquiry learning network networked progressive social}, number = 4, pages = {365-379}, timestamp = {2011-08-23T12:55:26.000+0200}, title = {The applicability of social network analysis to the study of networked learning}, url = {http://www.tandfonline.com/doi/abs/10.1080/10494820903281999}, volume = 19, year = 2011 }