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and varied domains of student behaviour can be analysed in a holistic manner. These behavioural domains range from a student’s engagement with university systems, attitude towards the quality of the pedagogy received, academic engagement and performance and a number of external factors. . The SOM approach has been shown to successfully identify multiple profiles of student attrition, creating new more nuanced risk profiles by separating behaviours originally thought to belong to a single profile as well as creating whole new classes of profiles SOM is not inherently a predictive technique in contrast with logistic models analysis and binary classifiers; but is effective for understanding the characteristics of a total population, identifying complex atypical clusters of behaviour and supplying other modelling approaches (e.g. linear regression, machine learning predictive techniques) with cohorts that have a high coherence among factors suitable further investigation. We have shown that SOM has potential to be combined with statistical and predictive analyses to form a complementary set of techniques for understanding the factors of retention and attrition for the purpose of developing new highly targeted interventions, actions and policy. Future research is planned to test the impact of the definition of attrition to see if the historic at-risk status based on the 2 semesters missing (we waited three semesters to analyse the data) is truly atrisk and whether the factors can lead to predictive estimations before students leave. References Batagelj, V. (1988). Generalized Ward and Related Clustering Problems Ward clustering problem. In Classification and Related Methods of Data Analysis (pp. 67–74). Crosling, G., Heagney, M., & Thomas, L. (2009). Improving student retention in higher education Improving Teaching and Learning. Australian Universities Review, 51(2), 9–18. De Freitas, S., Gibson, D., Du Plessis, C., Halloran, P., Williams, E., Ambrose, M., … Arnab, S. (2014). Foundations of dynamic learning analytics: Using university student data to increase retention. British Journal of Educational Technology. doi:10.1111/bjet.12212 Gibson, D., & de Freitas, S. (2015). Exploratory Analysis in Learning Analytics. Technology, Knowledge and Learning, (March), 1–15. doi:10.1007/s10758-015-9249-5 Gibson, D., & Jakl, P. (2013). Data challenges of leveraging a simulation to assess learning. West Lake Village, CA. Retrieved from http://www.curveshift.com/images/Gibson_Jakl_data_challenges.pdf Gibson, D., & Webb, M. E. (2015). Data science in educational assessment. Education and Information Technologies, June. doi:10.1007/s10639-015-9411-7 Jensen, U. (2011). Factors influencing student retention in higher education. Research & Evaluation. Retrieved from http://www.ksbe.edu/spi/pdfs/retention_brief.pdf Kohonen, T. (1990). The self-organizing map. Proceedings of the IEEE, 78. doi:10.1109/5.58325 Murtagh, F., & Legendre, P. (2011). Ward’s Hierarchical Clustering Method: Clustering Criterion and Agglomerative Algorithm. arXiv Preprint arXiv:1111.6285, (June), 20. Retrieved from http://arxiv.org/abs/1111.6285 Olsen, P. (2007). Staying the course : Retention and attrition in Australian universities Findings. Sydney. Retrieved from http://www.spre.com.au/download/AUIDFRetentionResultsFindings.pdf Shum, S. B. (2011). Learning Analytics. Yan, X., & Su, X. G. (2010). Stratified Wilson and Newcombe Confidence Intervals for Multiple Binomial Proportions. Statistics in Biopharmaceutical Research. doi:10.1198/sbr.2009.0049 Gibson, D.C., Ambrose, M., & Gardner, M. (2015). Self-organising maps and student retention: Understanding multi-faceted drivers. In T. Reiners, B.R. von Konsky, D. Gibson, V. Chang, L. Irving, & K. Clarke (Eds.), Globally connected, digitally enabled. Proceedings ascilite 2015 in Perth (pp. FP:100Error! Bookmark not defined.- FP:108). Note: All published papers are refereed, having undergone a double-blind peer-review process. The author(s) assign a Creative Commons by attribution licence enabling others to distribute, remix, tweak, and build upon their work, even commercially, as long as credit is given to the author(s) for the original creation. 120 FP:108
New applications, new global audiences: Educators repurposing and reusing 3D virtual and immersive learning resources Sue Gregory School of Education University of New England Judy O’Connell School of Information Studies Charles Sturt University Des Butler Faculty of Law Queensland University of Technology Marcus McDonald School of Health Sciences RMIT University Tom Kerr Faculty of Business & Economics Macquarie University Stefan Schutt Centre for Cultural Diversity & Wellbeing Victoria University Lisa Jacka School of Education Southern Cross University Deborah Corder School of Languages and Social Science Auckland University of Technology Merle Hearns School of Foundation Studies Manukau Institute of Technology Suku Sukunesan Business Systems and Design Swinburne University of Technology Brent Gregory UNE Business School University of New England Scott Grant School of Languages, Literatures, Cultures and Linguistic, Monash University Yvonne Masters School of Education University of New England Sasha Nikolic Engineering & Information Sciences University of Wollongong Sarah de Freitas Learning and Teaching Murdoch University Jenny Sim Medical Radiations University of Auckland Jo Doyle Australian Digital Futures Institute University of Southern Queensland Torsten Reiners Curtin Business School Curtin University Robert Cox Faculty of Education, Science, Technology, and Mathematics University of Canberra Kim Flintoff Curtin Teaching and Learning Curtin University Denise Wood Learning and Teaching Services Central Queensland University Mathew Hillier Institute for Teaching and Learning Innovation The University of Queensland Frederick Stokes- Thompson Learning & Teaching Unit University of South Australia David Ellis School of Education Southern Cross University Helen Farley Australian Digital Futures Institute University of Southern Queensland Belma Gaukrodger Flexible Learning Nelson Marlborough Institute of Technology Phil Blyth Faculty of Medicine University of Otago Dale Linegar Oztron Jay Jay Jegathesan School of Physics The University of Western Australia Leah Irving Curtin Teaching and Learning Curtin University There continues to be strong interest among established, experienced academic users of 3D virtual environments for their sustained educational use. Consistent with global trends, they plan to further develop and optimise existing applications, reuse skills and experiences gained to develop new applications, and to share and reuse existing virtual resources. This is against a background of varied support from institutions, colleagues, students, funding bodies and also changing understanding and awareness of virtual environments and virtual reality by the general community as a result of consumer developments such as the popularity of multi-user online role playing amongst both children and adults, and the acquisition of technologies by companies with deeply entrenched technologies. At the same time, the ongoing development and availability of 121 FP:109
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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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Page 71 and 72: Table 2: Summary of questionnaire r
Page 73 and 74: the material (E) my colleagues (S)
Page 75 and 76: co-construction of knowledge by sup
Page 77 and 78: Community volunteers in collaborati
Page 79 and 80: Induction and persistence How are v
Page 81 and 82: Figure 1: Contributions made in gen
Page 83 and 84: such acts as mentorship: One is the
Page 85 and 86: established a record of high qualit
Page 87 and 88: the OERu project or similar open de
Page 89 and 90: A ‘participant first’ approach
Page 91 and 92: five ways in which learning resourc
Page 93 and 94: Participant Perspective Consider yo
Page 95 and 96: key focus was on designing tasks th
Page 97 and 98: Management System, the primary tool
Page 99 and 100: Jordan, K. (2015). MOOC completion
Page 101 and 102: new pedagogical methods to engage t
Page 103 and 104: een perceived to be boring, with lo
Page 105 and 106: accounting concepts to others. Post
Page 107 and 108: the one model provided by the resea
Page 109 and 110: workplace. A further graduate attri
Page 111 and 112: Moy, J. (1999). The Impact of gener
Page 113 and 114: provider to understand the dependen
Page 115 and 116: • In the first semester of their
Page 117 and 118: Age at Course Start 22.98 4.3 >99.9
Page 119: 3 1 Figure 4. Attrition Rate: (Top)
Page 123 and 124: The modality of game-based learning
Page 125 and 126: 3% 2% 2% 2% 2% 2% Education Other H
Page 127 and 128: Machinima is being utilised to supp
Page 129 and 130: a lack of support from many institu
Page 131 and 132: 2015). There are new hardware and s
Page 133 and 134: Gregory, S., Gregory, B., Wood, D.,
Page 135 and 136: studies have found that university
Page 137 and 138: Importantly, TEL is a broad term an
Page 139 and 140: needs, etc.). Educators create digi
Page 141 and 142: could take the form of authorities
Page 143 and 144: To type or handwrite: student's exp
Page 145 and 146: Phase 1 Institution wide online sur
Page 147 and 148: There were just over 200 students (
Page 149 and 150: exam questions for computerisation,
Page 151 and 152: students on these two issues by cou
Page 153 and 154: from http://educationtechnologysolu
Page 155 and 156: Predictors of students’ perceived
Page 157 and 158: Lim, Morris, and Yoon (2006) sugges
Page 159 and 160: The questionnaire was pilot tested
Page 161 and 162: ** p < .001 - a This parameter was
Page 163 and 164: Among the four exogenous variables,
Page 165 and 166: influence on perceived course outco
Page 167 and 168: 5(3), 255-269. Marks, R. B., Sibley
Page 169 and 170: 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
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advancing learning analytics (Dawso
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contact students. Additionally, we
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Figure 4: Screenshot of part of the
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Change The IRAC framework allowed u
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Mazza, R., Bettoni, M., Faré, M.,
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misconceptions (e.g. Lehman, D'Mell
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understanding of the material on th
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6 5 4 3 2 1 0 Excited Interested Co
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Results The participants in the sim
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The two studies presented here were
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The author(s) assign a Creative Com
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approach which focuses on documenti
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within the context of their assessm
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perceptions of the use of technolog
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frequently than library databases.
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Figure 1: Sample of technology mapp
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Conclusion In contrast with other s
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Yorke, M. (2003). Formative assessm
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Erickson, Greer, & Gutwin, 2011), e
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higher than the Australian universi
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educators must be careful to offer
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Miles, C.A. (2015). Strong and incr
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in formal online education. To do s
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week analysis for the 8-week 3 cour
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First Quartile 1 1 Median 1 1 Mean
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participation. Similar to Gilliani
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Coffrin, C., Corrin, L., de Barba,
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Designing for relatedness: learning
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inquiry. This collaborative yarning
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online in the LMS until connections
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each other in educational environme
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Figure 2: Evaluation of Components
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Conclusion The experience of Aborig
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Torche, F., & Valenzuela, E. (2011)
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types of content and new models of
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ased on real journalism content 10
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efficiently access the key literatu
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systems. These initiatives are valu
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Ren, X. (2013). Beyond open access:
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within a constructivist framework (
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library, learning centers and couns
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testing occurs beyond that? What is
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Interdisciplinary opportunities and
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interdisciplinary project that aime
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J F M A M J J A S O N D 2014 Academ
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also vital. Achieving the correct b
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odies. Moreover, attracting enough
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Paving the way for institution wide
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Activity (Workshop) Description and
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Keyboard The physical keyboard is a
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• 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
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Freitas, 2006; Fröding & Peterson,
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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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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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ascilite 2015 Reviewers Reem Abu As
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Kulari Lokuge Dona Swinburne Univer
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