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comparability of the group of regular participants as similar to the formal online learning student groups opens up opportunities for transferring “best practice” and innovating teaching techniques within MOOCs. For example, we observe the importance of forum facilitators and highly active students in the development of the network. Prior research suggests that students in such social positions carry a higher sense of belonging than their less well-connected peers (Dawson, 2008). Our analysis indicates that highly active students and facilitators develop numerous ties of higher frequency. These individuals could potentially take on more of an instructional role by scaling feedback approaches and instilling a sense of belonging, in a manner that is reflective of a teacher in a more formal and bounded groups. However, such activities and roles can also lead to student dominance. In order to avoid such an event, as well as any potential for inadvertently exploiting volunteer efforts, an instructor may consider a rotation of community assistantship, thereby delegating the dedicated role to a number of active students. The present study raises questions related to the types of methodologies and approaches that are effective for researching social learning at scale. To better comprehend the complexities of social learning in MOOCs, researchers’ need to apply appropriate and diverse theoretical lenses to alternate units of analysis – from an entire cohort to individual actors. Networked learning (NL) may provide a sound theoretical framework for describing the various overlapping relationships that co-exist in the complex social organizations that manifest in educational settings (Jones, 2004a, 2004b; Jones, Ferreday, & Hodgson, 2008). Analysing a social entity from the NL perspective does not bias or privilege the strong relationships that imply closeness and unity of purpose within a group of actors (Jones, 2004a, 2004b; Jones & Esnault, 2004). Prior research has well demonstrated the benefits of using NL as an interdisciplinary framework for the analysis of learning due to its capacity to address “multiple scales of groups at multiple granularities of analysis, with multiple methods and theoretical foundations” (Suthers, Hoppe, De Laat, & Shum, 2012). Integral to this work has been the development of methodologies to investigate NL. For instance, de Laat et al. (2007) have outlined the potential of social network analysis (SNA) to inquire about the nature of NL, while Jones (2004b) suggested that network analysis of the links and relationships in NL environments needs to be supplemented with a qualitative analysis of their nature. Consequently, there exist a number of methodological frameworks that utilize social network analysis and complementary methods and diverse techniques to contextualize it (De Laat, Lally, Lipponen, & Simons, 2007; Suthers, 2015). In conclusion, it appears that analysing social interactions in MOOCs from NL perspective and through NL methodologies could further enrich our understanding of learning at scale. Such an approach would allow for the capture of social learning ties of differing strength, as well as defining their role and meaning through the qualitative analysis of such tie types, strength, as well as the socio-cultural dimensions underpinning the network structure and formation. Acknowledgements The authors would like to thank TU Delft Online Learning, in particular Thieme Hennis and Pieter de Vries, for the assistance with obtaining the data, and Srecko Joksimovic for the preparation of the data for this analysis. References Altbach, P. G., Reisberg, L., & Rumbley, L. E. (2009). Trends in global higher education: Tracking an academic revolution. UNESCO Pub.; Sense. Retrieved from http://atepie.cep.edu.rs/public/Altbach,_Reisberg,_Rumbley_Tracking_an_Academic_Revolut ion,_UNESCO_2009.pdf Budhathoki, N. R., & Haythornthwaite, C. (2012). Motivation for Open Collaboration: Crowd and Community Models and the Case of OpenStreetMap. American Behavioral Scientist, 57(5), 548– 575. Bulfin, S., Pangrazio, L., & Selwyn, N. (2014). Making “MOOCs”: The construction of a new digital higher education within news media discourse. The International Review of Research in Open and Distributed Learning, 15(5). Retrieved from http://www.irrodl.org.ezlibproxy.unisa.edu.au/index.php/irrodl/article/view/1856 Carrington, P. J., Scott, J., & Wasserman, S. (2005). Models and methods in social network analysis (Vol. 28). Cambridge university press. 232 FP:220
Coffrin, C., Corrin, L., de Barba, P., & Kennedy, G. (2014). Visualizing patterns of student engagement and performance in MOOCs. Proceedings of the Fourth International Conference on Learning Analytics And Knowledge - LAK ’14, 83–92. Csardi, G., & Nepusz, T. (2006). The igraph software package for complex network research. InterJournal, Complex Systems 1695. Retrieved from http://igraph.org Darabi, A., Liang, X., Suryavanshi, R., & Yurekli, H. (2013). Effectiveness of Online Discussion Strategies: A Meta-Analysis. American Journal of Distance Education, 27(4), 228–241. Dawson, S. (2008). A Study of the Relationship between Student Social Networks and Sense of Community. Educational Technology & Society, 11(3), 224–238. Dawson, S., Joksimović, S., Kovanović, V., Gašević, D., & Siemens, G. (2015). Recognising learner autonomy: Lessons and reflections from a joint x/c MOOC. Presented at the The Higher Education Research and Development Society of Australasia, Melbourne, Australia. Retrieved from https://asnevents.s3.amazonaws.com/Abstrakt-FullPaper/22639- Dawson_22639_version03.pdf De Laat, M., Lally, V., Lipponen, L., & Simons, R.-J. (2007). Investigating patterns of interaction in networked learning and computer-supported collaborative learning: A role for Social Network Analysis. International Journal of Computer-Supported Collaborative Learning, 2(1), 87–103. Eynon, R. (2014). Conceptualising interaction and learning in MOOCs. MOOC Research Initiative Report Ferguson, R., & Clow, D. (2015). Examining Engagement: Analysing Learner Subpopulations in Massive Open Online Courses (MOOCs). In Proceedings of the Fifth International Conference on Learning Analytics And Knowledge (pp. 51–58). Poughkeepsie, New York: ACM. Ferschke, O., Howley, I., Tomar, G., Yang, D., Liu, Y., & Rosé, C. P. (2015). Fostering Discussion across Communication Media in Massive Open Online Courses. In Proceedings of Computer Supported Collaborative Learning. Retrieved from http://www.isls.org/cscl2015/papers/MC-0404- FullPaper-Rose.pdf Gasevic, D., Kovanovic, V., Joksimovic, S., & Siemens, G. (2014). Where is research on massive open online courses headed? A data analysis of the MOOC Research Initiative. The International Review of Research in Open and Distributed Learning, 15(5). Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/1954 Gillani, N. (2013). Learner Communications in Massively Open Online Courses. Master's Thesis. Retrieved from http://iamsoalive.com/doc/dissertation_learner_communications.pdf Gillani, N., Yasseri, T., Eynon, R., & Hjorth, I. (2014). Structural limitations of learning in a crowd: communication vulnerability and information diffusion in MOOCs. Scientific Reports, 4. Retrieved from http://www.nature.com/articles/doi:10.1038%2Fsrep06447 Haythornthwaite, C. (2009). Crowds and Communities : Light and Heavyweight Models of Peer Production. Big Island, Hawaii, Hawaii International Conference on System Sciences. Hollands, F., & Tirthali, D. (2014). MOOCs : Expectations and Reality. Retrieved from http://www.academicpartnerships.com/sites/default/files/MOOCs_Expectations_and_Reality.p df Huang, J., Dasgupta, A., Ghosh, A., Manning, J., & Sanders, M. (2014). Superposter behavior in MOOC forums. In Proceedings of the first ACM conference on Learning@ scale conference (pp. 117–126). ACM. Jiang, S., Fitzhugh, S. M., & Warschauer, M. (2014). Social Positioning and Performance in MOOCs. In Proceedings of the Workshops held at Educational Data Mining 2014, co-located with 7th International Conference on Educational Data Mining (EDM 2014) (Vol. 1183, p. 14). London, United Kingdom. Jones, C. (2004a). Networks and learning: communities, practices and the metaphor of networks. Research in Learning Technology, 12(1). Retrieved from http://journals.coaction.net/index.php/rlt/article/view/11227 Jones, C. (2004b). The conditions of learning in networks. In Kaleidoscope CSCL SIG First Symposium, October 7th-9th 2004 (p. 13–pages). Retrieved from https://telearn.archivesouvertes.fr/hal-00190649/ Jones, C., & Esnault, L. (2004). The metaphor of networks in learning: Communities, collaboration and practice. In Networked Learning 2004 Conference (p. 8). file://localhost/Retrieved from https/::telearn.archives-ouvertes.fr:hal-00190280: Jones, C., Ferreday, D., & Hodgson, V. (2008). Networked learning a relational approach: weak and strong ties. Journal of Computer Assisted Learning, 24(2), 90–102. 233 FP:221
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ascilite2015 Australasian Society f
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To type or handwrite: student's exp
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Concise papers Learning maps: A des
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The three pillars to building staff
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Posters Metacognitive Development i
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Discussion Papers Decisions and des
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The Conceived, the Perceived and th
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concentration of evaluations being
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“I just felt like we skimmed over
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Figure 3: Student Infographic Proto
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Learning design for science teacher
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existing teaching practice with tec
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the module, 7% said they had heard,
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Calculus 1, 2014 (undergraduat e, 5
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ambitions towards educational techn
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Tensions and turning points: explor
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Virtual Learning Environment Teachi
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• Virtual Learning Environment
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newsroom role-playing scenario requ
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Lisa’s fourth turning point event
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vertically in that the lecturer may
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Navigate Me: maximising student pot
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improve academic outcomes, rather t
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Figure 4: Part of an action plan Fr
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Most common issues One useful produ
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communication/assessment and assist
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Designing an authentic professional
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for designing authentic learning en
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Bannan (2010) proposes a simpler fo
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An overview of CMALT requirements W
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students. From the roof, the overal
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Bruns, A. (2007, March 21-23). Beyo
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Investigating the effectiveness of
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labile, and diachronic interaction,
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learning. It was thought that this
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Table 2: Summary of questionnaire r
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the material (E) my colleagues (S)
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co-construction of knowledge by sup
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Community volunteers in collaborati
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Induction and persistence How are v
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Figure 1: Contributions made in gen
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such acts as mentorship: One is the
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established a record of high qualit
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the OERu project or similar open de
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A ‘participant first’ approach
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five ways in which learning resourc
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Participant Perspective Consider yo
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key focus was on designing tasks th
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Management System, the primary tool
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Jordan, K. (2015). MOOC completion
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new pedagogical methods to engage t
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een perceived to be boring, with lo
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accounting concepts to others. Post
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the one model provided by the resea
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workplace. A further graduate attri
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Moy, J. (1999). The Impact of gener
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provider to understand the dependen
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• In the first semester of their
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Age at Course Start 22.98 4.3 >99.9
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3 1 Figure 4. Attrition Rate: (Top)
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New applications, new global audien
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The modality of game-based learning
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3% 2% 2% 2% 2% 2% Education Other H
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Machinima is being utilised to supp
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a lack of support from many institu
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2015). There are new hardware and s
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Gregory, S., Gregory, B., Wood, D.,
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studies have found that university
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Importantly, TEL is a broad term an
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needs, etc.). Educators create digi
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could take the form of authorities
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To type or handwrite: student's exp
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Phase 1 Institution wide online sur
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There were just over 200 students (
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exam questions for computerisation,
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students on these two issues by cou
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from http://educationtechnologysolu
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Predictors of students’ perceived
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Lim, Morris, and Yoon (2006) sugges
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The questionnaire was pilot tested
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** p < .001 - a This parameter was
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Among the four exogenous variables,
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influence on perceived course outco
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5(3), 255-269. Marks, R. B., Sibley
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and continuously evaluate the deliv
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supporting teachers in the transiti
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etween other VET schools and the co
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sharing of the tasks, and their pee
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learning. Digital education has led
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McLoughlin, C. (2013). Teacher prof
Page 181 and 182: advancing learning analytics (Dawso
Page 183 and 184: contact students. Additionally, we
Page 185 and 186: Figure 4: Screenshot of part of the
Page 187 and 188: Change The IRAC framework allowed u
Page 189 and 190: Mazza, R., Bettoni, M., Faré, M.,
Page 191 and 192: misconceptions (e.g. Lehman, D'Mell
Page 193 and 194: understanding of the material on th
Page 195 and 196: 6 5 4 3 2 1 0 Excited Interested Co
Page 197 and 198: Results The participants in the sim
Page 199 and 200: The two studies presented here were
Page 201 and 202: The author(s) assign a Creative Com
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Page 205 and 206: within the context of their assessm
Page 207 and 208: perceptions of the use of technolog
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Page 211 and 212: Figure 1: Sample of technology mapp
Page 213 and 214: Conclusion In contrast with other s
Page 215 and 216: Yorke, M. (2003). Formative assessm
Page 217 and 218: Erickson, Greer, & Gutwin, 2011), e
Page 219 and 220: higher than the Australian universi
Page 221 and 222: educators must be careful to offer
Page 223 and 224: Miles, C.A. (2015). Strong and incr
Page 225 and 226: in formal online education. To do s
Page 227 and 228: week analysis for the 8-week 3 cour
Page 229 and 230: First Quartile 1 1 Median 1 1 Mean
Page 231: participation. Similar to Gilliani
Page 235 and 236: Designing for relatedness: learning
Page 237 and 238: inquiry. This collaborative yarning
Page 239 and 240: online in the LMS until connections
Page 241 and 242: each other in educational environme
Page 243 and 244: Figure 2: Evaluation of Components
Page 245 and 246: Conclusion The experience of Aborig
Page 247 and 248: Torche, F., & Valenzuela, E. (2011)
Page 249 and 250: types of content and new models of
Page 251 and 252: ased on real journalism content 10
Page 253 and 254: efficiently access the key literatu
Page 255 and 256: systems. These initiatives are valu
Page 257 and 258: Ren, X. (2013). Beyond open access:
Page 259 and 260: within a constructivist framework (
Page 261 and 262: library, learning centers and couns
Page 263 and 264: testing occurs beyond that? What is
Page 265 and 266: Interdisciplinary opportunities and
Page 267 and 268: interdisciplinary project that aime
Page 269 and 270: J F M A M J J A S O N D 2014 Academ
Page 271 and 272: also vital. Achieving the correct b
Page 273 and 274: odies. Moreover, attracting enough
Page 275 and 276: Paving the way for institution wide
Page 277 and 278: Activity (Workshop) Description and
Page 279 and 280: Keyboard The physical keyboard is a
Page 281 and 282: • Annotating diagrams • Ability
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Conclusion This project demonstrate
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MyCourseMap: an interactive visual
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Figure 1: MyCourseMap visual overvi
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The tool has particular applicabili
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11. Media gallery 10. Graduate attr
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Barriers or challenges. actually go
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Figure 8: The unit information page
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Standing on the shoulders of others
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designer employed by La Trobe Unive
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student interaction are essential c
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Figure 2: Weekly learning design se
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The current [template] speaks clear
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Weaver, D, Robbie, D, Kokonis, S &
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Background Learning analytics The r
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and conducted workshops as the proj
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• Communication (email, Facebook,
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180 Daily Weekly Fortnightly Monthl
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Relevance and comprehensiveness of
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Further Information More informatio
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Virtual worlds have great potential
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conceptual understanding, and (3) m
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Figure 5: Map and Hints of the VW E
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All quiz questions are saved in a X
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Gütl, C. (2011). The Support of Vi
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Remote Access Laboratories for Prep
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een derived from the STEBI-B (Enoch
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15 Students’ achievement in techn
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RALfie offers both hands-on and onl
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and non-user groups and efforts hav
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Maxwell, A. D., Orwin, L., Kist, A.
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To evaluate the feasibility of usin
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their observed behaviour. Towards t
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study and help them adapt to a new
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main student concern, there are add
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Information delivered through the a
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Learning maps: A design-based appro
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4 Integrative • Mixed research me
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Dede, C. (2004). If design-based re
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LAK demonstrates a great deal of co
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Experiences from early reusability
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The future of practice-based resear
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1.1. Consider factoring in control
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3. Consider the research questions
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Features of an online English langu
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Figure 2: Embedded Matbury’s MP3
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References Ayres, P., & Sweller, J.
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that will provoke a specific kind o
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Preliminary results The study is on
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Using expectation confirmation theo
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Findings and Discussion The data an
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Fawcett, S. L. (2002). Group gaming
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visualization affects learning but
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Demonstrate the ability to construc
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Implementing blended learning at fa
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Exploring approaches taken at other
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But, J. & Shobbrook, R. (2012). Web
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potential of social media in educat
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Another tweet included a photo of t
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Teachers Cloud-based Content Creati
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Deviation CBLD? 1. Learning Outcome
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McGee, P., & Reis, A. (2012). Blend
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The Next Wave of learning Innovatio
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than a static system / website / mo
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Loop: A learning analytics tool to
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Figure 1: The Loop tool dashboard f
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efore it is released as an open sou
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programmed through freely available
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In addition to this experiment, at
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An investigation of blended learnin
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Results The experiences of learning
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Chan, S. (1999). The Chinese learne
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ambiguous nature of discussion post
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Discussion Linking assessment to on
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Digital Futures research and societ
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challenges of specifying real-world
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Hemsley-Brown, J., & Sharp, C. (200
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is taking digital technologies into
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The Making the Connection project t
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Jeroschewski, A., Levisse, A., Sala
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(2014, p.19). New business models f
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Table 3. Badges on lifelong learnin
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The Agile Learning Model: Using big
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Preliminary results Methodology A p
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(e.g. students that were directed t
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It has been predicted that “by th
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including: timely access to teacher
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Occupational Medicine Simulation Pr
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just being presented with a data sh
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Gustafson, P. (2001). Meanings of p
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This exploratory research step focu
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Week 3 of the course. Figure 2: Acc
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A pedagogical end game for exams: a
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that a bachelor degree is the new h
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However, this vision is not pie-in-
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Are Higher Education Institutions P
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Method Design In order to reach a l
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of LA frameworks and on expected be
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Talented, and Learning and Behaviou
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I felt prepared to set my own LGs 5
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Measuring creativity in collaborati
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y Beghetto and Kaufman (2013), who
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And how does this creativity become
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In short, research in these paradig
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esearch is heavily context dependen
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Collaboration between Primary Stude
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Results The analysis of the observa
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even difficult for them to bring to
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A digital what? Creating a playspac
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As of writing, plans are underway t
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Lamond, H. & Rowatt, A.J. (2015). A
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Furthermore, staff PD in digital te
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Figure 1: Expert Review of Peer Rev
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Developing Self-Regulated Learning
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Technological Structure The underly
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analytics-functionality-and-wirefra
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model of professional learning that
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ecognition of their teaching in a t
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Connecting fun and learning- an act
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Figure 1. Engestrom's Activity Syst
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pedagogical and technological barri
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(e.g. Graesser et al., 2005), it ca
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ability to perform well on a test a
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Exploring my university students’
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15.00% 10.00% 5.00% 0.00% created a
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Miller, M. D. (2014). Online Learni
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component, evaluation that connects
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not be enough to encourage its wide
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Benchmarking for technology enhance
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Findings groups to try and streamli
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Author, M. (2014a). Benchmarking fo
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uploaded document with consistent m
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Promoting Critical Thinking in a La
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Table 1: Overview Summary of How In
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and post-exam online surveys were a
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Seow, T.K. & Soong, S.K.A. (2015).
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family and friends to help them. Di
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Upon completion of the unit, studen
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Blended Learning Adoption Monitorin
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for each stage are listed as Strate
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References Alammary, A., Sheard, J.
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environment), and (3) civic engagem
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Kolb, D. A. (1984). Experiential le
Page 567 and 568:
Freitas, 2006; Fröding & Peterson,
Page 569 and 570:
The research methodologies appropri
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Teräs, H. (2014). Collaborative on
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Upon completion of a learning activ
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Figure 3: Drag and drop application
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Pre-service teachers’ reflections
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like the Renaissance, and the teach
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from http://www.researchgate.net/pu
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concept of summer learning loss. Th
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Figure 2: Relationships between Cou
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Webby, B., Quinn, D., Albrecht, A.,
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The University’s Approach to a Le
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Figure 2: Draft CSU Learning Analyt
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Dreaming of Electric Sheep: CSU’s
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student learning. Furthermore, many
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something that is done by the “da
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SkillBox: a pilot study Rachel Anne
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agree, A=agree, N=neutral, D=disagr
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Whitsed, R.A. & Parker, J. (2015).
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critical theory and feminist studie
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connectedness between individual an
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Description of proposed interventio
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Kaufman & L. Li (Eds.), Routledge i
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Matthews, A., Aggarwal, R., and Lim
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Schau, C., & Mattern, N. (1997). Us
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eight of the nine interviewees in a
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communicate proposals, plans, compa
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Creating concept vignettes as a mod
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Preparing Students for Future Learn
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References Association for the Adva
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The use of rubrics for the assessme
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Developing an online challenge-base
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Let’s Talk Learning Analytics and
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Experiential Learning in Accounting
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The CSU Online Learning model Tim K
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MOOCs as spaces to innovate Alison
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The author(s) assign a Creative Com
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In terms of educational uses, the l
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The framework At the University of
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Enhancing Workplace Learning throug
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Figure 2: GPS for WPL structure Con
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The success of this new support mod
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Acknowledgement Supported by the Di
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Discussion Who owns learning? Educa
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Pawlaczek, Z. & Allan, G. (2015). D
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These divergent student perceptions
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Connecting or constructing academic
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define one academic literacy for al
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Learning, 12(3), 139-160. Retrieved
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Data collection The seven case stud
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share their own experiences in orde
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of Goals-Signals-Metrics as columns
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material, perform self-assessment t
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Many educational technology researc
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non-technical users can participate
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particularly in the early stages. T
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Williams, T., Kaui,T. & Ernst, J. (
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Campbell & Oblinger, 2007; Clow, 20
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Johnson, L., Adams Becker, S., & Ha
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sine qua non of LA, and a recent co
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Lodge, J., & Lewis, M. (2012). Pige
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academic referencing system Sente 6
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Norton, A. (2012). Mapping Australi
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How new teaching methods affect our
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Calderon, O., Ginsberg, A., Ciabocc
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thus enabling libraries to learn ab
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Formulating research questions whic
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as well as examples of each element
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the learning materials are presente
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activity results in a collaborative
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the definition, not the technology.
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in researching and developing teach
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2. Examples of open scholarship net
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#NPF14LMD Learners and Mobile Devic
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Adrienne Moyle Academic Advisor wit
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Easing into mobile learning Angela
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Clinical Logs: Best Practices in th
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Digitally enabled learning through
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Using interactive multimedia for
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References Barbezat, D., & Bush, M.
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The author(s) assign a Creative Com
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ascilite 2015 Reviewers Reem Abu As
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Kulari Lokuge Dona Swinburne Univer
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