@article {9269, title = {Does a Formal Wiki Event contribute to the Formation of a Network of Practice? A Social Capital Perspective on the Potential for Informal Learning}, journal = {Interactive Learning Environments}, year = {2017}, pages = {1-12}, keywords = {Informal Learning, Network of Practice, social capital, Social Network Analysis, wikipedia}, doi = {http://dx.doi.org/10.1080/10494820.2017.1324495}, url = {http://www.tandfonline.com/eprint/5SACaZ4tCTqPGFB7GnaX/full}, author = {Martin Rehm and Allison Littlejohn and Bart Rienties} } @inbook {9271, title = {Lebenslanges Lernen im Kontext sozialer Medien: Chancen f{\"u}r formelles und informelles Lernen}, booktitle = {Lebenslanges Lernen im sozialstrukturellen Wandel}, year = {2017}, pages = {141{\textendash}170}, publisher = {Springer Fachmedien}, organization = {Springer Fachmedien}, address = {Wiesbaden}, keywords = {Informal Learning, lebenslanges Lernen, Social Network Analysis, soziale Medien}, isbn = {978-3-658-14354-1}, doi = {10.1007/978-3-658-14355-8_8 }, author = {Michael Kerres and Tobias H{\"o}lterhof and Martin Rehm} } @conference {9273, title = {Seeing the Invisible: Editing Wikipedia for the Public Good}, booktitle = {EARLI}, year = {2017}, address = {Tampere, Finland}, keywords = {Network of Practice, Social Network Analysis, wikipedia}, author = {Allison Littlejohn and Nina Hood and Bart Rienties and Martin Rehm} } @conference {9275, title = {To go beyond {\textellipsis} New Frontiers for Analyzing Social Networking Sites for Educational Policy \& Practice}, booktitle = {AERA}, year = {2017}, address = {San Antonio, USA}, keywords = {Informal Learning, social capital, Social Network Analysis}, author = {Martin Rehm and Alan Daly and Frank Cornelissen and Ad Notten} } @article {5811, title = {The Impact of Hierarchical Positions on the Type of Communication within Online Communities of Learning}, journal = {Computers in Human Behavior}, volume = {58}, year = {2016}, pages = {158{\textendash}170}, abstract = {Communities of Learning (CoL) have been suggested to facilitate the learning process among participants of online trainings. Yet, previous studies often detached participants from the social context in which learning took place. The present study addresses this shortcoming by providing empirical evidence from 25 CoL of a global organization, where 249 staff members from different hierarchical positions engaged into collaborative learning via asynchronous discussion forums. We conduct a longitudinal study on the type of communication within these CoL, as well as participants{\textquoteright} network positions, in order to investigate the research question: What is the impact of individual{\textquoteright}s hierarchical positions on the type of communication within CoL? Our results indicate that the higher participants{\textquoteright} hierarchical position, the higher their amount of social and cognitive communication, which in turn was also positively related to their network position within CoL. We also identified a sub-group of Stars that outperformed their colleagues and who were at the center of CoL, irrespective of their hierarchical positions. Consequently, we propose design and facilitation strategies to practitioners and organizers of future CoL that can foster the learning processes and outcomes of all participants. Additionally, we consider future research avenues that could be explored further.}, keywords = {Community of Learning, Content Analysis, Hierarchical Positions, Social Network Analysis, type of communication}, doi = {10.1016/j.chb.2015.12.065}, author = {Martin Rehm and Regina H. Mulder and Wim Gijselaers and Mien Segers} } @inbook {7735, title = {Informelles Lernen in Sozialen Medien {\textendash} Sozial-Mediale M{\"o}glichkeitsr{\"a}ume und die Rolle des sozialen Kapitals. Eine quantitative Vergleichsstudie von Konversationen auf Twitter}, booktitle = {Jahrbuch Medienp{\"a}dagogik 13: Vernetzt und entgrenzt - Gestaltung von Lernumgebungen mit digitalen Medien}, year = {2016}, publisher = {Springer VS}, organization = {Springer VS}, keywords = {Informal Learning, social capital, Social Network Analysis, soziale Medien, soziale Netzwerke, Teacher Education}, isbn = {978-3-658-16431-7}, author = {Martin Rehm}, editor = {Mayrberger, Kerstin and Fromme, Johannes} } @article {7079, title = {The invisible hand of informal (educational) communication!? Social capital considerations on Twitter conversations among teachers}, journal = {UNU-MERIT Working Paper}, volume = {2016}, year = {2016}, keywords = {Informal Learning, social capital, Social Media, Social Network Analysis, Teacher Education}, url = {http://www.merit.unu.edu/publications/wppdf/2016/wp2016-052.pdf}, author = {Martin Rehm and Ad Notten} } @conference {6249, title = {Social Media: Social Opportunity Spaces for Informal Learning among Teachers?}, booktitle = {AERA 2016}, year = {2016}, month = {04/2016}, publisher = {American Educational Research Association}, organization = {American Educational Research Association}, address = {Washington D.C.}, keywords = {Bibliometric Analysis, informal education, social capital, Social Media, Social Network Analysis, Teacher Education}, url = {http://www.aera.net/EventsMeetings/AnnualMeeting/2016AnnualMeeting/tabid/15862/}, author = {Martin Rehm} } @conference {6154, title = {Soziale Medien als sozial-mediale M{\"o}glichkeitsr{\"a}ume f{\"u}r informelles Lernen unter Lehrkr{\"a}ften}, booktitle = {DGfE Kongress: R{\"a}ume f{\"u}r Bildung. R{\"a}ume der Bildung}, year = {2016}, month = {03/2016}, publisher = {Deutschen Gesellschaft f{\"u}r Erziehungswissenschaft (DGfE)}, organization = {Deutschen Gesellschaft f{\"u}r Erziehungswissenschaft (DGfE)}, address = {Kassel, Germany}, abstract = {Informelles Lernen nimmt eine immer wichtigere Rolle im Rahmen der beruflichen Weiterbildung von Lehrkr{\"a}ften aller Ausbildungsg{\"a}nge ein (Eraut, 2004). Erworbenes Wissen und berufsspezifische F{\"a}higkeiten alleine reichen als Voraussetzung f{\"u}r eine Besch{\"a}ftigung nicht mehr aus, um f{\"u}r die Implementation neuer Lehr-/Lernans{\"a}tze und die Sicherung der Qualit{\"a}t Ihrer Veranstaltungen garantieren zu k{\"o}nnen (Finsterwald, Wagner, Schober, L{\"u}ftenegger, \& Spiel, 2013). Stattdessen m{\"u}ssen Lehrkr{\"a}fte ihre Kenntnisse und F{\"a}higkeiten kontinuierlich aktualisieren und ausbauen (Chalmers \& Keown, 2006). In diesem Kontext wird informelles Lernen in der beruflichen Weiterbildung von Lehrpersonen immer h{\"a}ufiger als relevante und zielf{\"u}hrende Option genannt (Conlon, 2004). Hierbei handelt es sich um l{\"a}ngerfristig angelegte Prozesse, die sich zu gro{\ss}en Teilen in den allt{\"a}glichen Arbeitsumfeldern von Lehrkr{\"a}ften abspielen (Butler \& Schnellert, 2012). Es wird angenommen, dass soziale Medien diese Prozesse f{\"o}rdern k{\"o}nnen, indem sie Individuen die M{\"o}glichkeit bieten mit anderen zu diskutieren und Ihr eigenes Handeln kritisch zu reflektieren (Hopkins, 2000). Sie stellen sozial-mediale M{\"o}glichkeitsr{\"a}ume als Meta-Kontext dar, in dem sich Bildungspotentiale ergeben und aus denen im komplexen Zusammenspiel verschiedener Faktoren (Lern-)Prozesse entstehen k{\"o}nnen (Marotzki \& J{\"o}rissen, 2008; Spanhel, 2010). In diesem Rahmen spielt das Konzept des sozialen Kapitals eine immer prominentere Rolle, um den Nutzen und die M{\"o}glichkeiten von sozialen Medien f{\"u}r (informelles) Lernen zu eruieren und hervorzuheben (vgl. Bourdieu, 1986; Ellison, Vitak, Gray, \& Lampe, 2014; Tsai \& Ghoshal, 1998). Insgesamt besteht allerdings noch eine erhebliche Ungewissheit {\"u}ber die spezifische Rolle und Funktion von sozialem Kapital f{\"u}r informelles Lernen im Rahmen der beruflichen Weiterbildung von Lehrkr{\"a}ften. Aus der Analyse fr{\"u}herer Forschung ergeben sich vier Defizite. 1) Eine bildungswissenschaftliche und mediendidaktische Perspektive ist im Themen-Diskurs selten; 2) es gibt nur wenige Befunde aus der beruflichen Weiterbildung; 3) longitudinale Studien wurden nur vereinzelt durchgef{\"u}hrt und 4) die Weiterbildung von Lehrpersonen ist kaum Gegenstand der Forschung zu sozialen Medien. Dieser Beitrag geht auf diese Defizite ein und befasst sich mit den folgenden drei Forschungsfragen: 1) Wie kann soziales Kapital in sozialen Medien f{\"u}r Lehrpersonen beschrieben werden? 2) Wird in sozialen Medien bei Lehrpersonen informelles Lernen initiiert? 3) Entsteht f{\"u}r Lehrpersonen in sozialen Medien soziales Kapital? Um diese Forschungsfragen bearbeiten zu k{\"o}nnen werden anhand von sozialen Netzwerkanalysen die (inhaltlichen) Strukturen der sozial-mediale M{\"o}glichkeitsr{\"a}ume und die Beziehungen der Teilnehmer erfasst. Bibliometrische Analysen dienen dazu den Inhalt informellen Lernens zu bewerten und zu kategorisieren. }, keywords = {Bibliometric Analysis, Informal Learning, social capital, Social Media, Social Network Analysis, teacher development, Twitter}, url = {http://dgfe2016.de/}, author = {Martin Rehm} } @article {6799, title = {Twitter as an Informal Learning Space for Teachers!? The Role of Social Capital in Twitter Conversations among Teachers}, journal = {Teaching and Teacher Education}, year = {2016}, chapter = {http://www.journals.elsevier.com/teaching-and-teacher-education}, abstract = {Twitter can contribute to the continuous professional development of teachers by initiating and fostering informal learning. Social capital theory can aid to analyse the underlying communication processes and outcomes. Yet, previous research has largely neglected teachers and the role of social capital on Twitter. The present study addresses this shortcoming by analysing a hashtag conversation among German speaking teachers. Using social network analysis, we are able to show the relevance of the structural dimension of social capital in Twitter conversations among teachers.}, keywords = {Informal Learning, social capital, Social Media, Social Network Analysis, teacher professional development}, doi = {10.1016/j.tate.2016.08.015}, url = {http://authors.elsevier.com/a/1TeSi,GtqvcGHp}, author = {Martin Rehm and Ad Notten} } @conference {4111, title = {The Creation and Distribution of Social Capital in Twitter Conversations among Teachers {\textendash} A Longitudinal Ego-Network Approach}, booktitle = {XXXV. Sunbelt Social Networks Conference }, year = {2015}, month = {06/2015}, address = {Brighton, UK}, abstract = {Social networking sites (SNS) provide a ready-made environment to acquire and share new information, while collaborating in social networks of diverse groups of people. This study focuses on the creation and distribution of social capital within SNS, such as Twitter. Social capital has been repeatedly proposed as a valuable theoretical concept to analyze SNS. Moreover, previous research has greatly contributed to our understanding of how individuals communicate via Twitter. Yet, past studies remained inconclusive about the precise role of social capital in SNS. Additionally, little is known about whether and how teachers use SNS (e.g. Twitte) to share and collect information. The present study addresses these shortcomings by providing empirical evidence from two hashtag conversations, namely $\#$edchat and $\#$edchatde. Both aim at teachers and cover the latest trends and developments in the field of (new) media in teaching and learning processes. We collected longitudinal ego-network data from 22.05. {\textendash} 06.11.2014, yielding more than 144,000 Tweets from about 52,000 Twitter users. Building upon the work of Tsai and Goshal (1998), who acknowledged social network analysis as a valuable tool to assess (aspects of) of social capital, we determined egos{\textquoteright} betweenness and closeness centrality measures. Moreover, we also determined their hub and authority scores (Kleinberg, Kumar, Raghavan, Rajagopalan, \& Tomkins, 1999), as well as brokerage roles (De Nooy, Mrvar, \& Batagelj, 2011). Finally, we also assessed the existence and relevance of structural holes (e.g. Burt, 2009) in the emerging network structures of the hashtag conversations. The results show that there are overarching similarities among the Twitter conversations on how social capital is created and distributed. However, we also revealed decisive differences with respect to brokerage roles, as well as hub and authority scores. Based on these findings we will formulate recommendations for future studies, as well as discuss preliminary implications for practitioners.}, keywords = {ego-network, Longitudinal Analysis, social capital, Social Network Analysis}, author = {Martin Rehm and Michael Kerres} } @proceedings {4235, title = {EduTags {\textendash} How do Teachers share Resources using a Collaborative Tagging System?}, year = {2015}, address = {Limassol, Cyprus}, keywords = {collaborative tagging system, edutags, Social Network Analysis, two-mode network}, author = {Martin Rehm and Tobias H{\"o}lterhof and Michael Kerres} } @proceedings {4167, title = {Sharing Resources to Improve (Teaching) Practice {\textendash} Do Collaborative Tagging System contribute a Network of Practice among Teachers?}, year = {2015}, month = {06/2015}, address = {Brighton, UK}, abstract = {Continuous professional development of teachers, fostered by collaborative knowledge sharing, is a pivotal element in providing high quality education. In this context, Networks of Practice (NoP) have been proposed as a beneficial digital environment where such a process can be enhanced. Additionally, collaborative tagging systems (CTS) have gained increasing popularity, allowing individuals to collaboratively contribute to a growing repository of (online) resources that can improve teaching practice. However, CTS systems are seldom dedicated to teachers. Even more so, only limited evidence is available on whether and to what extent teachers actually engage in (online) knowledge sharing activities, as they are largely supposed to be preparing their classes in isolation (Hou, Sung, \& Chang, 2009). The present study addresses this issue by providing empirical evidence on a CTS, which aims at establishing a NoP among (German speaking) primary and secondary school teachers. We collected longitudinal data on individuals{\textquoteright} sharing behavior on the CTS in question. Second, we employed social network analysis (SNA). Building upon the work of scholars like Halpin and colleagues (2007), we considered a {\textquotedblleft}tripartite graph structure within tagging systems{\textquotedblright} (p. 213). Focussing on individuals{\textquoteright} tagging behaviors, we simplified the network into a one-mode projection concerning only users, and a two-mode projection concerning users and tags. In order to analyze the type of resources that have been shared, we ran a Clauset-Newman-Moore cluster analysis to identify subgroups among the users that link via commonly used tags. The underlying data was collected from the 1st of September 2013 until the 31st of August 2014. The statistical software package R was used to collect and analyze the data. Our results indicate that 244 users added at least one resource with a minimum of one tag. This resulted in 3745 shared resources and 3218 unique tags being used. A subset of isolated users (41) used tags that were not used by any of their colleagues. In contrast, more than 50 percent of teachers used at least 16 tags that were commonly used among participants of the CTS. Our cluster analysis revealed 4 clusters, whereby the isolated users were put into one cluster. The shared resources covered the general topic domains of {\textquotedblleft}social media{\textquotedblleft}, {\textquotedblleft}open educational resources{\textquotedblright} and {\textquotedblleft}(multi)media learning resources{\textquotedblright}. These findings provide valuable insights. First, our results suggest that teachers actively engage in the CTS to store and exchange information and resources, thereby contributing to the formation of a NoP among teachers. Second, using SNA allowed us identifying network structures and reveals (thematic) commonalities among users that might have otherwise been overlooked. Overall, future research can build upon these findings by investigating the possibility of creating spill-over activities (e.g. face-to-face workshops, tailored information channels) among sub-groups of alike-minded users. }, keywords = {longitudinal study, semantic network anaylsis, Social Network Analysis, two-mode network}, author = {Tobias H{\"o}lterhof and Martin Rehm} } @proceedings {4237, title = {Tweeting Teachers {\textendash} Does Social Capital play a Role in Twitter Conversations among Teachers?}, year = {2015}, address = {Limassol, Cyprus}, keywords = {semantic network anaylsis, social capital, Social Network Analysis, Teacher Education, two-mode network}, author = {Martin Rehm and Ad Notten and Michael Kerres} } @article {3723, title = {Effects of Hierarchical Levels on Social Network Structures within Communities of Learning}, journal = {Frontline Learning Research}, volume = {Learning through Networks}, year = {2014}, abstract = {Facilitating an interpersonal knowledge transfer among employees constitutes a key building block in setting up organizational training initiatives. With practitioners and researchers looking for innovative training methods, online Communities of Learning (CoL) have been promoted as a promising methodology to foster this kind of transfer. However, past research has only provided limited data from actual organizations and largely neglected characteristics that constitute a major obstacle to such collaborative processes, namely participants{\textquoteright} hierarchical levels. The current study addresses these shortcomings by providing empirical evidence from 25 CoL of an online training program, provided for 249 staff members of a global organization. Using social network analysis, we are able to show significant differences in participants{\textquoteright} network behaviour and position based on their hierarchical rank. This translates into higher in- and out-degree network ties, as well as centrality scores among participants from higher up the hierarchical ladder. Finally, based on a longitudinal analysis of all indicated network measures, our results indicate that the main trend develops predominately during the first half of the training program. By incorporating these insights into the implementation of future CoL, it is not only possible to anticipate participants{\textquoteright} behaviour. Our findings also allow to draw conclusions about how collaborative activities within CoL should be designed and facilitated, in order to provide employees with a valuable learning experience.}, keywords = {Centrality, Community of Learning, Hierarchical Positions, Longitudinal Analysis, Social Network Analysis}, url = {http://journals.sfu.ca/flr/index.php/journal/article/view/85}, author = {Martin Rehm and Wim Gijselaers and Mien Segers} } @conference {3721, title = {Preparing in Isolation?! Sharing \& Tagging Educational Resources Among Teachers}, booktitle = {Association for Educational Communications and Technology (AECT)}, year = {2014}, address = {Jacksonville, USA}, keywords = {Network of Practice, Social Bookmarking, Social Network Analysis, Teacher Education}, author = {Martin Rehm and Tobias H{\"o}lterhof and Heinen, Richard and Scharnberg, Gianna and Michael Kerres} } @conference {3717, title = {A social network perspective on learning and professional development}, booktitle = {EARLI - SIG 14 (Learning and Professional Development)}, year = {2014}, address = {Oslo, Norway}, keywords = {Network of Practice, Social Network Analysis}, author = {Martin Rehm and Markus Hirschmann and Hans Gruber and Bart Rienties and Simon Beausaert and Dominik Fr{\"o}hlich and Mien Segers and Sara Van Waes and Piet van den Bossche and Nienke Moolenaar and Peter Van Petegem and Anoush Margaryan} } @proceedings {3713, title = {Unified Yet Separated - Empirical Study on the Impact of Hierarchical Positions within Communities of Learning}, year = {2014}, address = {Tampere, Finland}, abstract = {

The arcticle has receiced an Outstanding Paper Award at the EdMedia World Conference on Educational Media and Technology\ 

Communities of Learning (CoL) are suggested to facilitate the co-construction of knowledge among participants of online trainings. Yet, previous studies often detached participants from the social context in which learning took place. The manuscript addresses this shortcoming by providing empirical evidence from 30 CoL of a global organization, where 337 staff members from different hierarchical positions collaboratively enhanced their knowledge via asynchronous discussion forums. The results from four dedicated studies clearly indicate that the higher participants\’ hierarchical position, the higher their amount of social and cognitive messages, and the more central their network position within CoL. However, we also identified a group of \“Stars\” that outperformed their colleagues and who were at the centre of CoL networks, irrespective of their hierarchical positions. Based on these findings, HRD practitioners can better design and facilitate future collaborative learning activities that build upon the strength and weaknesses of all participants.

}, keywords = {Community of Learning, Content Analysis, Hierarchical Position, Social Network Analysis}, author = {Martin Rehm} } @conference {3719, title = {$\#$WhatsTheDifference? Comparing Hashtag Conversation on Twitter among Teachers}, booktitle = {Association for Educational Communications and Technology (AECT)}, year = {2014}, address = {Jacksonville, USA}, keywords = {Network of Practice, Social Network Analysis, Teacher Education, Twitter}, author = {Martin Rehm and Preussler, Annabell and Michael Kerres and Katerina Bohle-Carbonell and Ad Notten} }