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Gibson, D., Ostashewski, N., Flintoff, K., Grant, S., & Knight, E. (2015). Digital badges in education. Education and Information Technologies, 20(2), 403-410. doi: 10.1007/s10639-013-9291-7 Glover, I., & Latif, F. (2013). Investigating perceptions and potential of open badges in formal higher education. Paper presented at the Proceedings of the World Conference on Educational Multimedia, Hypermedia and Telecommunications 2013. ACCE, Chesapeake, VA. Grant, S. L. (2014). What Counts as Learning: Open Digital Badges for New Opportunities Connected Learning. Irvine, CA: The Digital Media and Learning Research Hub.http://dmlhub.net/wp-content/uploads/files/WhatCountsAsLearning_Grant.pdf [viewed 20 May 2015] Hickey, D., Otto, N., Itow, R., Schenke, K., Tran, C. & Chow, C. (2014). Badges Design Principles Documentation Project: Interim Report January 2014 Update, Center for Research on Learning and Technology Indiana University. Irvine, CA, (verified 9 July 2015) http://dpdproject.info/files/2014/05/DPD-interim-report-v4-january.pdf International Standards Organization. (2004). Portable Network Graphics (PNG): Functional specification. ISO/IEC 15948:2004. [verified 26 May 2013] http://www.iso.org/iso/catalogue_detail.htm?csnumber=29581 Surman, M. (2011). Mozilla Launches Open Badges Project. http://commonspace.wordpress.com/2011/09/15/openbadges-2/ [viewed 26 May 2013] Gibson, D., Coleman, K., & Irving, L. (2015). Badging digital pathways of learning. 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. CP:88-CP:92). 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. 444 CP:92
The Agile Learning Model: Using big data to personalise the acquisition of accounting skills Brent Gregory UNE Business School University of New England Matthew Wysel UNE Business School University of New England Sue Gregory School of Education University of New England Big data mirrors the accounting process to the extent that it deals with how we capture, categorise, summarise and report information so that users can make informed decisions. By modelling this process, we can both demonstrate the future of accounting to our students, and build an agile learning environment that identifies for a student their ‘next crucial action’ in the learning process. Presented in this paper is a pilot study. Keywords: Agile learning, education big data, personalised learning, automated intervention Introduction Effective learning is predicated on feedback, as feedback enables the student to determine the effectiveness of their efforts in achieving the desired goal (Gregory, Uys & Gregory, 2014). This feedback can vary from: personalised to heuristic, continuous to discrete, adaptive to rigid, and is regarded as the key to self-regulated learning environments and the challenge in classical, didactic environments (Butler & Winne, 1995). In more sophisticated and effective learning environments both the student and the teacher actively participate in a mutual process of feeding back and processing information regarding the efficacy of the learning process to one another, with the common goal of refining the process (Cantillon & Wood, 2011). Feedback, therefore, relies on the provision and recording of data, its categorisation and summarisation, and timely reporting to one or more parties within the learning process. Historically, administrative overheads associated with evaluating the numbers of students typically found in school and university classes has enforced highly uniform, and therefore structured, evaluation processes with corresponding rigidity within tuition programs. In this case, institutions’ operational requirements to process sufficient volumes of students drive an increase in curriculum rigidity, a reduction in the number of assessments – and therefore a widening of feedback loops, and consequentially force students to increase their reliance on heuristic techniques to guide them through their learning environment. In order to develop our agile learning system a pilot study was undertaken through the selection of student activities, assessing learning and gathering feedback, we may need to step back from of our existing operational assumptions. This will enable us to adapt to realities such as the inputs to the system, (the students), are not homogeneous. A starting point may be to garner information about the student that does not come from the traditional assessment tasks. As well, we should develop resources that are outside the normal learning resources for a particular unit of study. One of our initial challenges will be to identify the questions that we need to ask. This suite of challenges is precisely where big data is most powerful. The commercial utilisation of big data hinges on the ability to collect large quantities of discrete sample points, assemble them for analysis and assessment and respond to the aggregated information in a timely manner. Typically, the commercial collection of sample points within big data applications involves an attempt to garner high quality information about the true position, activities, or knowledge of the subject, while minimising the impact of external influences associated with the assessment. Moreover, the systems created to capture and respond to the collection of big data are designed to retain sufficient agility to deliver personalised content to individuals based on the statistical correlation of one subjects’ current position to numbers of previous subjects’ next successful actions. Big data provides schools and universities the framework to: leverage data created by large numbers of students in the past; 445 CP:93
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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
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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
Page 393 and 394: But, J. & Shobbrook, R. (2012). Web
Page 395 and 396: potential of social media in educat
Page 397 and 398: Another tweet included a photo of t
Page 399 and 400: Teachers Cloud-based Content Creati
Page 401 and 402: Deviation CBLD? 1. Learning Outcome
Page 403 and 404: McGee, P., & Reis, A. (2012). Blend
Page 405 and 406: The Next Wave of learning Innovatio
Page 407 and 408: than a static system / website / mo
Page 409 and 410: Loop: A learning analytics tool to
Page 411 and 412: Figure 1: The Loop tool dashboard f
Page 413 and 414: efore it is released as an open sou
Page 415 and 416: programmed through freely available
Page 417 and 418: In addition to this experiment, at
Page 419 and 420: An investigation of blended learnin
Page 421 and 422: Results The experiences of learning
Page 423 and 424: Chan, S. (1999). The Chinese learne
Page 425 and 426: ambiguous nature of discussion post
Page 427 and 428: Discussion Linking assessment to on
Page 429 and 430: Digital Futures research and societ
Page 431 and 432: challenges of specifying real-world
Page 433 and 434: Hemsley-Brown, J., & Sharp, C. (200
Page 435 and 436: is taking digital technologies into
Page 437 and 438: The Making the Connection project t
Page 439 and 440: Jeroschewski, A., Levisse, A., Sala
Page 441 and 442: (2014, p.19). New business models f
Page 443: Table 3. Badges on lifelong learnin
Page 447 and 448: Preliminary results Methodology A p
Page 449 and 450: (e.g. students that were directed t
Page 451 and 452: It has been predicted that “by th
Page 453 and 454: including: timely access to teacher
Page 455 and 456: Occupational Medicine Simulation Pr
Page 457 and 458: just being presented with a data sh
Page 459 and 460: Gustafson, P. (2001). Meanings of p
Page 461 and 462: This exploratory research step focu
Page 463 and 464: Week 3 of the course. Figure 2: Acc
Page 465 and 466: A pedagogical end game for exams: a
Page 467 and 468: that a bachelor degree is the new h
Page 469 and 470: However, this vision is not pie-in-
Page 471 and 472: Are Higher Education Institutions P
Page 473 and 474: Method Design In order to reach a l
Page 475 and 476: of LA frameworks and on expected be
Page 477 and 478: Talented, and Learning and Behaviou
Page 479 and 480: I felt prepared to set my own LGs 5
Page 481 and 482: Measuring creativity in collaborati
Page 483 and 484: y Beghetto and Kaufman (2013), who
Page 485 and 486: And how does this creativity become
Page 487 and 488: In short, research in these paradig
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Page 493 and 494: 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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