July 2007 Volume 10 Number 3 - Educational Technology & Society

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A., Ueno M. & Kashihara A. (Eds.), Proceedings of the 7 th IEEE International Conference on Advanced learning Technologies, Los Alamitos, CA: IEEE Computer Society, 551-555. Knight, C., Gašević, D., & Richards, G. (2006). An Ontology-Based Framework for Bridging Learning Design and Learning Content. Educational Technology & Society, 9(1), 23-37. Koper, R., & Olivier, B. (2004). Representing the Learning Design of Units of Learning. Educational Technology & Society, 7(3), 97-111. Koper, R. (2001). Modeling units of study from a pedagogical perspective - The pedagogical metamodel behind EML, Retrieved June 7, 2007, from, http://dspace.ou.nl/bitstream/1820/36/1/Pedagogical+metamodel+behind+ EMLv2.pdf. Li, J. Z., Gašević, D., Nesbit, J. C., & Richards, G. (2005). Ontology Mappings Enable Interoperation of Knowledge Domain Taxonomies, Retrieved June 7, 2007, from, http://www.lornet.org/Portals/7/presentation_i2lor_05/ papers/i2lor05-07.pdf. Li, J. Z. (2006). Mapping Local Ontologies: Authentic Semantics for Learning Object Evaluation, M.Sc. Thesis, School of Interactive Arts and Technology, Simon Fraser University, Canada. Maamar, Z., Benslimane, D., & Narendra, N. C. (2006). What can context do for web services? Communications of the ACM, 49(12), 98–103. McCalla, G. (2004). The Ecological Approach to the Design of E-Learning Environments: Purpose-based Capture and Use of Information about Learners. Journal of Interactive Media in Education, 2004(7), Retrieved June 7, 2007, from, http://www-jime.open.ac.uk/2004/7. Miles, A., & Brickley D. (2005). SKOS Core Guide, Retrieved June 7, 2007, from, http://www.w3.org/2004/02/skos/core/guide/2005-02-15.html. Preuveneers, D., den Bergh, J. V., Wagelaar, D., Georges, A., Rigole, P., Clerckx, T., Berbers, Y., Coninx, K., Jonckers, V., & Bosschere, K. D. (2004). Towards an extensible context ontology for Ambient Intelligence. Lecture Notes in Computer Science, 3295, 148-159. Ranganathan, A., McGrath, R. E., Campbell, R. H., & Mickunas, D. M. (2003). Ontologies in a Pervasive Computing Environment. In Giunchiglia, F., Gomez-Perez, A., Stuckenschmidt, H., Pease, A., Sure, Y. & Willmott, S. (Eds.), Proceeding of the 1 st International Workshop on Ontologies and Distributed Systems, Retrieved June 7, 2007, from, http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS//Vol-71/. Seaborne, A. (2004). RDQL - A Query Language for RDF, W3C Member Submission, Retrieved June 7, 2007, from, http://www.w3.org/Submission/RDQL. Recker, M. M., & Wiley, D. (2001). A Non-authoritative Educational Metadata Ontology for Filtering and Recommending Learning Objects. Interactive Learning Environments, 9(3), 255-271. Recker, M., Walker, A., & Willey, D. (2001). Collaboratively filtering learning objects. In D. A. Wiley (Ed.), The Instructional Use of Learning Objects, Retrieved June 7, 2007, from, http://reusability.org/read/chapters/recker.doc. Strang, T., Linnhoff-Popien, C., & Frank, K. (2003). CoOL: A Context Ontology Language to enable Contextual Interoperability. Lecture Notes in Computer Science, 2893, 236–247. 59
Dron, J. (2007). Designing the Undesignable: Social Software and Control. Educational Technology & Society, 10 (3), 60-71. Designing the Undesignable: Social Software and Control Jon Dron University of Brighton, UK // Jon.dron@brighton.ac.uk ABSTRACT Social software, such as blogs, wikis, tagging systems and collaborative filters, treats the group as a first-class object within the system. Drawing from theories of transactional distance and control, this paper proposes a model of e-learning that extends traditional concepts of learner-teacher-content interactions to include these emergent properties of the group. It suggests that this feature of social software can facilitate an approach to elearning that is qualitatively different from and capable of significantly augmenting traditional methods, with especial benefits for lifelong learners and those outside institutional boundaries. The paper goes on to explore some of the dangers and issues that need to be addressed in order for this new model to fulfill its promise, and to suggest a framework of principles to be used by designers of educationally-oriented social software. Keywords Social software, Transactional distance, Control, Web 2.0, Self-organization Introduction This is a paper about the potential of social software in education. Social software treats the group as a first class object within the system (Allen, 2004). It is becoming embedded in all aspects of our online lives, from the recommendations of Amazon to the photo sharing of Flickr to the ordering of search results in Google. Social software such as blogs, wikis, link sharing systems, collaborative filters and other tools employing tagging, social recommendation and social navigation are increasingly a part of the fabric of an e-learning environment. In this paper I argue that they have characteristics that strongly distinguish them from earlier software for e-learning, providing particularly notable benefits to informal and lifelong learners. I describe a theoretical foundation which explains the potential benefits of social software in the context of transactional distance and control, extending earlier frameworks for e-learning to account for the emergent control of the group. Drawing on this foundation, I offer a set of ten principles to be employed by designers of social software environments for e-learning. Transactional control Michael Moore’s theory of transactional distance suggests that the relative amount of dialogue and structure is what determines ‘distance’ in learning, rather than physical separation between learner and teacher (Moore, 1986). It is implied by the theory and independently confirmed by Saba and Shearer, that the two are inversely interdependent (Saba & Shearer, 1994). The greater the structure, the lesser the dialogue, and vice versa. To this mix, Moore adds a third dimension of autonomy. Fully autonomous learners need neither dialogue nor structure to learn. Like dialogue and structure, autonomy is seldom absolute. Others have refined this concept, noting that there is a big difference between autonomy as a psychological trait, and the varying degrees of autonomy of the learner to choose a path within a given learning context (Brockett & Hiemstra, 1991; Candy, 1991). Moore’s theory has been widely used and verified in a number of contexts (Chen, 2000; Dron, Seidel, & Litten, 2004; Lowe, 2000; Saba & Shearer, 1994; Stein, Wanstreet, Calvin, Overtoom, & Wheaton, 2005), but suffers from a fuzziness and inconsistency that troubles some (Garrison, 2000; Gorsky & Caspi, 2005). I have proposed a different but intimately connected model, a subset of transactional distance that I have called transactional control (Dron, 2006). Transactional control is concerned with choices. In traditional education, whether online or offline, some choices are made by teachers and some by learners. The extent to which those choices are dictated by particular individuals determines their level of transactional control at any moment. Transactional control theory does not aim to replace transactional distance theory as it says nothing significant of the psychological gap between learner and teacher, but it helps to explain some of its dynamics. Structure equates to teacher control, dialogue to negotiated control, and autonomy to learner control. At any point in a learning trajectory, transactional control will vary. It is concerned with the choices that determine a change in trajectory, not those that ISSN 1436-4522 (online) and 1176-3647 (print). © International Forum of Educational Technology & Society (IFETS). The authors and the forum jointly retain the copyright of the articles. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear the full citation on the first page. Copyrights for components of this work owned by others than IFETS must be honoured. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from the editors at kinshuk@ieee.org. 60
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Advertisements Educational Technolo
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Distinguishing between games and si
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“sometimes” is less demanding t
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Figure 2. From generic skill to lea
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The large window on the left presen
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Page 25 and 26: Conclusion The importance given to
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Page 35 and 36: REDEEM is now a senior citizen in t
Page 37 and 38: Chieu, V. M. (2007). An Operational
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Page 41 and 42: COFALE as a learning environment an
Page 43 and 44: COFALE supports a set of predefined
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Page 53 and 54: learning settings. However, such a
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Figure 2: The CAM schema elements (
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• Context: the context element ca
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4.1 Generation of Attention Metadat
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addition, such keywords can be extr
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Action related data, data about sea
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Braun, S., & Schmidt, A. (2006). Do
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El-Bishouty, M. M., Ogata, H., & Ya
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collaboration (Ogata, et al., 1999)
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In case of LOI value is equal or cl
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Also, the learner can click on an e
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System Evaluation An experiment was
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In the fifth phase, 89% of the stud
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Fischer, G., & Konomi, S. (2005). I
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application for specific needs, whi
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(4) Multimedia: The truth is that e
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Program Company Price OS 6 eZediaMX
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Program Text editor Text import for
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Program Sound Formats Image Formats
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Program Image Painting Export Scrip
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Program Effects Needs player 5 Easy
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Program WYSIWYG Design Interactivit
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the grades awarded to the programs
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Grade Image formats Sound formats V
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Figure 3. Adequacy of image formats
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Animating objects, pictures, etc.,
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Educational overview Having taken m
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In summary, the final outcome is th
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Developing the Interactivity Survey
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technique. be treated as a desired
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55. A lecture in which student lear
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specific conclusions that researche
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Discussion and conclusion Although
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Juwah, C. (2003). Using peer assess
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Publish results Set a few goals for
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familiarity with computer terms, ex
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provide a framework for the integra
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tool themselves, and then gauge its
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associated with the effective use o
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portrayed as even more time-consumi
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Clarke, B. (2001). Corporate curric
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Neal, E. (1998). Using technology i
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Yearwood, J., & Stranieri, A. (2007
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entertaining (Neuhauser 1993). The
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in being addressed with the sequent
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The GAAM represents reasoning to a
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Other situations have more serious
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Figure 6. NARRATE phase screen afte
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The narration at Step 10 informs th
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very large degree of free-will has
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Rumelhart, D. E. (1975). Notes on a
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The School of Business at Universit
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Authentic assessment and OBOW exams
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iii. The assessment asks the studen
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world problems in relation to the s
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Herrington, J., & Herrington, A. (1
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services required by most clients i
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Wisdom. J. P., White, N., Goldsmith
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Work outside the U.S. has also prom
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of the Telecommunication Act, and t
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Parent-advocate respondents also re
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school administrators may be persua
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of legal requirements for accessibl
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Thus, while we have reason to belie
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underlying structure of the two pri
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still not familiar with its use; in
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Table 3: An Analysis of Different V
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of males. Secondly, as far as age w
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Conclusion This study examined the
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Sandholtz, J. H., Ringstaff, C., &
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The design and validation of a text
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Predetermined goal of a game The pr
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A true, precise and valid model “
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Bain, C., & Newton, C. (2003). Art
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Prensky, M. (2005). Adopt and Adapt
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opportunities based on studying dif
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The game -called Chase the Cheese-
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another token. Other tokens further
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The system is organized in differen
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“to produce a single product or p
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(e.g., cheese) or loses the game (a
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collaboration is not an easy task.
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Collazos, C., Ortega, M., Bravo, C.
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Soller, A., & Lesgold, A. (2000). K
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Is the usual hierarchical organizat
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The final step 7 in the procedure i
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This methodology is summarised in F
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‘IsBasisOf’, ‘HasConstraint
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The presented results are a reflect
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‘HasExample’, and ‘HasFurther
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DCMI (2003). DCMI Metadata Terms, R
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Literature review Astronomy educati
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Systems of type I provide different
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night. To prevent students from get
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Figures 2-5 display screenshots of
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Results of the study reveal the imp
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vertical axis leads to the disappea
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Dede, C., Salzman, M., Loftin, R. B
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Trumper, R. (2000). University stud
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ased on pre-defined adaptation rule
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Therefore, the higher-level items o
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common prefix with the existing pa
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later should be omitted (presented
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5.1 The Average Length of each Sequ
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Recall 6. Discussion 0.8 0.7 0.6 0.
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easily take lessons in a good learn
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Laborda, J. G., & Royo, T. M. (2007
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Chapter 8, Online reference tools,
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Kenyon, D. M., & Malabonga, V. (200
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and concise manner (e.g. Weeding =
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stream are chapters 7 and 8 which f
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