Your SlideShare is downloading. ×
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Introducing the indicators project
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Introducing the indicators project

1,179

Published on

Presentation introducing the Indicators project (http://indicatorsproject.wordpress.com/) and the associated ASCILITE'09 paper. …

Presentation introducing the Indicators project (http://indicatorsproject.wordpress.com/) and the associated ASCILITE'09 paper.

More presentation resources here http://indicatorsproject.wordpress.com/2009/11/12/introducing-the-indicators-project-identifying-effective-learning/

Published in: Education, Technology, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
1,179
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
11
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide
  • General overview. Give context of the project and work we’re talking about. Most of the talk is showing you some initial results – Feature usage is a comparison of what featuresAre being used in courses. It’s a comparison between 2 different “LMS” used at the same institution at the same time. Participation and grades examines the relationship betweenUse of an LMS and student grades and then how that is impacted by a range of factors such as mode of delivery, participation of staff, staff educational background and inputOf an instructional designer. We close with some discussion of future work. Each of the first three sections of space for you to ask questions
  • Let’s start with context
  • Just about every university thinks that to do e-learning you need an LMS. You can’t get fired for selecting an LMS. Anyone know of a university that doesn’t have at least one LMS and isn’t planning to get one?
  • So, what’s going on within the LMS. There are lots of important reasons why you need to know what is going on. Not the least of which is to inform decisions being made by students, teaching staff, support staff and management. My question for you is how much to people really know about what is going on?
  • General overview. Give context of the project and work we’re talking about. Most of the talk is showing you some initial results – Feature usage is a comparison of what featuresAre being used in courses. It’s a comparison between 2 different “LMS” used at the same institution at the same time. Participation and grades examines the relationship betweenUse of an LMS and student grades and then how that is impacted by a range of factors such as mode of delivery, participation of staff, staff educational background and inputOf an instructional designer. We close with some discussion of future work. Each of the first three sections of space for you to ask questions
  • General overview. Give context of the project and work we’re talking about. Most of the talk is showing you some initial results – Feature usage is a comparison of what featuresAre being used in courses. It’s a comparison between 2 different “LMS” used at the same institution at the same time. Participation and grades examines the relationship betweenUse of an LMS and student grades and then how that is impacted by a range of factors such as mode of delivery, participation of staff, staff educational background and inputOf an instructional designer. We close with some discussion of future work. Each of the first three sections of space for you to ask questions
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • Fresen developed a taxonomy of critical success facotrs for quality e-learning. We thought we might investigate the effect of some of these using the same types of graphs.As for the background image, Dave Snowden suggests that taxonomies have a lot in common with taxidermy, suggesting a connection between both and the production static relationships/categories
  • General overview. Give context of the project and work we’re talking about. Most of the talk is showing you some initial results – Feature usage is a comparison of what featuresAre being used in courses. It’s a comparison between 2 different “LMS” used at the same institution at the same time. Participation and grades examines the relationship betweenUse of an LMS and student grades and then how that is impacted by a range of factors such as mode of delivery, participation of staff, staff educational background and inputOf an instructional designer. We close with some discussion of future work. Each of the first three sections of space for you to ask questions
  • Some quick reflections
  • We’re still taking baby steps, still learning, still wobbling. Need some help.
  • It’s a big task, complex combination of factors, educational, technical, statistical, political, social….
  • There are significant limitations on what this information can tell on it’s own. Needs to be applied intelligently in a contextual and contingent way. Needs combination with other methods.
  • But there’s enough of a hint here to indicate that there are rewards.
  • General overview. Give context of the project and work we’re talking about. Most of the talk is showing you some initial results – Feature usage is a comparison of what featuresAre being used in courses. It’s a comparison between 2 different “LMS” used at the same institution at the same time. Participation and grades examines the relationship betweenUse of an LMS and student grades and then how that is impacted by a range of factors such as mode of delivery, participation of staff, staff educational background and inputOf an instructional designer. We close with some discussion of future work. Each of the first three sections of space for you to ask questions
  • Transcript

    • 1. The Indicators ProjectIdentifying effective learning: adoption, activity, grades and external factors
      Colin BeerDavid JonesKen Clark
      http://tr.im/FvRQ
    • 2. Overview
      Context
      Feature usage
      Participation, grades and other factors
      Future work and Reflections
      http://www.flickr.com/photos/atbaker/1577665185/
    • 3. Overview
      Context
      Feature usage
      Participation, grades and other factors
      Future work and Reflections
      http://www.flickr.com/photos/atbaker/1577665185/
    • 4. The data that we, educators gatherand utilize is all but garbage.
      (Wiley, 2009)
      http://www.flickr.com/photos/dnorman/251646154/
    • 5. almost every university is
      planning to make use of an LMS
      (Salmon, 2005)
      They are becoming ubiquitous at universities around the world
      (Coates et al, 2005)
      http://www.flickr.com/photos/riverap1/3875718119/
    • 6. Are sites ready for start of term?
      Are students using the site?
      Are thereproblems?
      How?
      Is it worth it?
      With what impact?
      What makes “good” LMS use?
      If I do “x” what happens?
      http://www.flickr.com/photos/dsifry/2452527887/
    • 7. What’s going on within your LMS/course site?
      a) Asking staff and/or students
      b) Manual checking of LMS
      c) LMS reporting facilities
      d) Data mining + other analytics
      e) Opinion/self-reporting
      f) Other
      g) None
      http://www.flickr.com/photos/80417459@N00/2471314610/
    • 8. Mostly ad hoc
      Mostly LMS reporting
      Some surveys
      Peer review?
      One manual check
      (Gonch, 2007)
      http://www.flickr.com/photos/80417459@N00/2471314610/
    • 9. Mostly ad hoc
      Mostly LMS reporting
      No widespread view
      Some surveys
      One manual check
      (Gonch, 2007)
      http://www.flickr.com/photos/80417459@N00/2471314610/
    • 10. Limited views
      Mostly ad hoc
      Mostly LMS reporting
      No widespread view
      Only what is in the LMS
      Some surveys
      One manual check
      (Gonch, 2007)
      http://www.flickr.com/photos/80417459@N00/2471314610/
    • 11. Limited views
      Mostly ad hoc
      Mostly LMS reporting
      No widespread view
      Only what is in the LMS
      Some surveys
      Human recollection
      One manual check
      (Gonch, 2007)
      http://www.flickr.com/photos/80417459@N00/2471314610/
    • 12. Limited views
      Mostly ad hoc
      Mostly LMS reporting
      No widespread view
      Only what is in the LMS
      Some surveys
      Human recollection
      Time-consuming & error prone
      One manual check
      (Gonch, 2007)
      http://www.flickr.com/photos/80417459@N00/2471314610/
    • 13. Limited views
      Mostly ad hoc
      Mostly LMS reporting
      No widespread view
      Only what is in the LMS
      Some surveys
      Human recollection
      No lognitudinal examination
      Time-consuming & error prone
      One manual check
      (Gonch, 2007)
      http://www.flickr.com/photos/80417459@N00/2471314610/
    • 14. Limited views
      Mostly ad hoc
      Mostly LMS reporting
      No widespread view
      Only what is in the LMS
      Some surveys
      Human recollection
      No lognitudinal examination
      No cross LMS comparison
      Time-consuming & error prone
      One manual check
      (Gonch, 2007)
      http://www.flickr.com/photos/80417459@N00/2471314610/
    • 15. Limited views
      Mostly ad hoc
      Mostly LMS reporting
      No widespread view
      Only what is in the LMS
      Some surveys
      Human recollection
      No lognitudinal examination
      No cross LMS comparison
      No cross institutional comparison
      Time-consuming & error prone
      One manual check
      (Gonch, 2007)
      http://www.flickr.com/photos/80417459@N00/2471314610/
    • 16. “LMS”
      Pre-2010
      Webfuse – 1997-2009
      WebCT – 1999-2003/4
      Blackboard – 2004-2009
      2010-
      Moodle
      http://www.flickr.com/photos/80417459@N00/2471314610/
    • 17. We have lots of data
      Examining it might reveal interesting patterns
      Useful for L&T practice, management and research
      http://www.flickr.com/photos/anders-vindegg/3408838186/
    • 18. Enabling comparisons of LMS usageacross institutions, platforms and time
      http://indicatorsproject.wordpress.com
    • 19. http://www.flickr.com/photos/david_jones/36379215/
    • 20. Research
      T&L Practice
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      LMS Independent Data
      Institution A
      Institution B
      Institution C
      LMS 1
      LMS 2
      LMS
      LMS
      http://www.flickr.com/photos/atbaker/1577665185/
    • 21. Research
      T&L Practice
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      LMS Independent Data
      Enabling
      Institution A
      Institution B
      Institution C
      LMS 1
      LMS 2
      LMS
      LMS
      http://www.flickr.com/photos/atbaker/1577665185/
    • 22. Research
      T&L Practice
      What
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      LMS Independent Data
      Enabling
      Institution A
      Institution B
      Institution C
      LMS 1
      LMS 2
      LMS
      LMS
      http://www.flickr.com/photos/atbaker/1577665185/
    • 23. Why
      Research
      T&L Practice
      What
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      LMS Independent Data
      Enabling
      Institution A
      Institution B
      Institution C
      LMS 1
      LMS 2
      LMS
      LMS
      http://www.flickr.com/photos/atbaker/1577665185/
    • 24. Why
      Research
      T&L Practice
      How
      What
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      LMS Independent Data
      Enabling
      Institution A
      Institution B
      Institution C
      LMS 1
      LMS 2
      LMS
      LMS
      http://www.flickr.com/photos/atbaker/1577665185/
    • 25. Overview
      Context
      Feature usage
      Participation, grades and other factors
      Future work
      http://www.flickr.com/photos/atbaker/1577665185/
    • 26. There are more similarities than differences among LMS
      (Black et al, 2007)
      http://www.flickr.com/photos/chokingsun/3495110670/
    • 27. Level 1: Most used
      Level 2: Moderately used
      Level 3: Rarely used
      More than 50% of courses
      More than 20% of courses
      (much) less than 20% of courses
      CreatingClassInteractions
      EvaluatingStudents
      TransmittingContent
      ComputerBasedInstruction
      Evaluatingcourse and instructors
      Move to features in unexplored categories, until each category is considered for different learning needs
      (Malikowski et al, 2007)
      http://www.flickr.com/photos/chokingsun/3495110670/
    • 37. CQU
      Bb
      Wf
      What we did
      LMS logs
      http://www.flickr.com/photos/chokingsun/3495110670/
    • 38. LMS Independent Data
      CQU
      Bb
      Wf
      LMS logs
      What we did
      http://www.flickr.com/photos/chokingsun/3495110670/
    • 39. Feature usage
      LMS Independent Data
      (Malikowski et al, 2007)
      CQU
      Bb
      Wf
      LMS logs
      What we did
      http://www.flickr.com/photos/chokingsun/3495110670/
    • 40. Malikowskitop & bottomrange
      http://www.flickr.com/photos/chokingsun/3495110670/
    • 41. Blackboard
      http://www.flickr.com/photos/chokingsun/3495110670/
    • 42. Webfuse
      http://www.flickr.com/photos/chokingsun/3495110670/
    • 43. http://www.flickr.com/photos/chokingsun/3495110670/
    • 44. http://www.flickr.com/photos/chokingsun/3495110670/
    • 45. http://www.flickr.com/photos/chokingsun/3495110670/
    • 46. http://www.flickr.com/photos/wadem/2730257498/
    • 47. The particular trajectory of emergence is not wholly determined either by the intentions of the human actors or by the material properties of technology, but rather by the interplay of the two
      (Jones, 1999)
      http://www.flickr.com/photos/wadem/2730257498/
    • 48. Why?
      Future Work
      How
      Will Moodle be different?
      What about other institutions?
      Are Malikowski ranges out of date?
      When is a feature adopted?
      …….
      http://www.flickr.com/photos/nedrichards/3234490934/
    • 49. Overview
      Context
      Feature usage
      Participation, grades and other factors
      Future work and Reflections
      http://www.flickr.com/photos/atbaker/1577665185/
    • 50. The results indicated a significant difference between low and high performing students in terms of the quantity of online session times attended during the course
      (Dawson et al, 2008)
      Discussion forum activity has been demonstrated to be a sound indicator of future student academic performance.
      (Dawson, 2009; Morris et al, 2005)
      http://www.flickr.com/photos/wolfgangstaudt/2279651479/
    • 51. Feature usage
      LMS Independent Data
      (Malikowski et al, 2007)
      CQU
      Bb
      Wf
      LMS logs
      What we did
      http://www.flickr.com/photos/chokingsun/3495110670/
    • 52. Feature usage
      LMS Independent Data
      (Malikowski et al, 2007)
      Student records
      CQU
      Bb
      Wf
      LMS logs
      What we did
      http://www.flickr.com/photos/chokingsun/3495110670/
    • 53. Feature usage
      Participation, grades,external factors
      LMS Independent Data
      (Malikowski et al, 2007)
      Student records
      CQU
      Bb
      Wf
      LMS logs
      What we did
      http://www.flickr.com/photos/chokingsun/3495110670/
    • 54. Distance education students
      Hits on course site
      Hits on course forum
      http://www.flickr.com/photos/wolfgangstaudt/2279651479/
    • 55. CQ on-campus students
      http://www.flickr.com/photos/wolfgangstaudt/2279651479/
    • 56. AIC students
      http://www.flickr.com/photos/wolfgangstaudt/2279651479/
    • 57. Distance education students
      # of replies
      # of posts
      http://www.flickr.com/photos/wolfgangstaudt/2279651479/
    • 58. CQ on-campus students
      http://www.flickr.com/photos/wolfgangstaudt/2279651479/
    • 59. AIC students
      http://www.flickr.com/photos/wolfgangstaudt/2279651479/
    • 60. The results indicated a significant difference between low and high performing students in terms of the quantity of online session times attended during the course
      (Dawson et al, 2008)
      Discussion forum activity has been demonstrated to be a sound indicator of future student academic performance.
      (Dawson, 2009; Morris et al, 2005)
      http://www.flickr.com/photos/wolfgangstaudt/2279651479/
    • 61. Mixed design ANOVA
      All reported effects are significant
      Significant interaction effectbetween grades and participation
      http://www.flickr.com/photos/wolfgangstaudt/2279651479/
    • 62. http://www.flickr.com/photos/wadem/2730257498/
    • 63. FLEX/DE = no face-to-face
      CQ = Quite a bit emphasis face-to-face
      AIC = emphasis on face-to-face
      Course site designedby CQ-based staff(usually)
      NESB?
      http://www.flickr.com/photos/wadem/2730257498/
    • 64. Taxonomy of critical success factorsfor quality web-supported learning
      (Fresen, 2007)
      Lecturer interaction/facilitation
      Academic background of lecturer/instructional design
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 65. Taxonomy of critical success factorsfor quality web-supported learning
      (Fresen, 2007)
      Lecturer interaction/facilitation
      Academic background of lecturer/instructional design
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 66. Course groups based on staff hits
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 67. High staff participation courses
      Hits
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 68. High staff participation courses
      Replies & posts
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 69. Super low staff participation courses
      Hits
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 70. Super low staff participation courses
      Replies & posts
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 71. Posts comparisons
      High
      Superlow
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 72. The results indicated a significant difference between low and high performing students in terms of the quantity of online session times attended during the course
      (Dawson et al, 2008)
      Discussion forum activity has been demonstrated to be a sound indicator of future student academic performance.
      (Dawson, 2009; Morris et al, 2005)
      http://www.flickr.com/photos/wolfgangstaudt/2279651479/
    • 73. http://www.flickr.com/photos/wadem/2730257498/
    • 74. Examination of super-low
      Future Work
      - Course size
      Forum content
      Networks of interaction
      (Bakharia et al, 2009; Dawson, 2009)
      http://www.flickr.com/photos/nedrichards/3234490934/
    • 75.
    • 76. Taxonomy of critical success factorsfor quality web-supported learning
      (Fresen, 2007)
      Lecturer interaction/facilitation
      Academic background of lecturer and instructional design
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 77. Course offerings with
      n=167
      Staff with grad certs in L&T
      n=4
      Significant input from instructional designer
      n=196
      Staff who have received teaching awards
      N=362
      Staff teaching education courses
      n=3288
      None of the above
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 78. None of the above
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 79. Grad cert in L&T
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 80. Teaching awards
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 81. Education discipline
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 82. Instructional design
      http://www.flickr.com/photos/orinrobertjohn/3321067724/
    • 83. Overview
      Context
      Feature usage
      Participation, grades and other factors
      Future work & Reflections
      http://www.flickr.com/photos/atbaker/1577665185/
    • 84. http://www.flickr.com/photos/mikebaird/2985066755/
    • 85. http://www.flickr.com/photos/david_jones/36379215/
    • 86. http://www.flickr.com/photos/dmatos/540688952/
    • 87. http://www.flickr.com/photos/mwichary/2188958154/
    • 88. http://www.flickr.com/photos/sylvar/1138341328/
    • 89. http://www.flickr.com/photos/fncll/145149313/
    • 90. http://www.flickr.com/photos/nedrichards/3234490934/
    • 91. Why
      Research
      T&L Practice
      How
      Little bit
      Not much
      What
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      Useful Data/Information
      Little bit
      LMS Independent Data
      Enabling
      Little bit
      Institution A
      Institution B
      Institution C
      LMS 1
      LMS 2
      LMS
      LMS
      http://www.flickr.com/photos/atbaker/1577665185/
    • 92. http://www.flickr.com/photos/fncll/145149313/
    • 93. http://indicatorsproject.wordpress.com
      http://tr.im/FvRQ
      http://www.flickr.com/photos/jamuraa/813966437/
    • 94. Black, E., D. Beck, et al. (2007). "The other side of the LMS: Considering implementation and use in the adoption of an LMS in online and blended learning environments." Tech Trends51(2): 35-39.
      Coates, H., R. James, et al. (2005). "A Critical Examination of the Effects of Learning Management Systems on University Teaching and Learning." Tertiary Education and Management 11(1): 19-36.
      Dawson, S. (2009). "'Seeing' the learning community: An exploration of the development of a resource for monitoring online student networking." British Journal of Educational Technology: in press.
      Dawson, S., E. McWilliam, et al. (2008). Teaching smarter: How mining ICT data can inform and improve learning and teaching practice. Hello! Where are you in the landscape of educational technology? Proceedings ascilite Melbourne 2008. Melbourne: 221-230
      Fresen, J. (2007). "A taxonomy of factors to promote quality web-supported learning." International Journal on E-Learning6(3): 351-362.
      Gonch, B. (2007). An inventory of Term 2 2006 online courses at CQU. Rockhampton, Central Queensland University: 18.
      Jones, M. (1999). Information systems and the double mangle: Steering a course between the scylla of embedded structure and the charybdis of strong symmetry. Information Systems: Current Issues and Future Chalenges. T. Larsen, L. Levine and J. DeGross. Laxenburg, Austria, IFIP: 287-302.
      Malikowski, S., M. Thompson, et al. (2007). "A model for research into course management systems: bridging technology and learning theory." Journal of Educational Computing Research36(2): 149-173.
      Morris, L., C. Finnega, et al. (2005). "Tracking student behavior, persistence, and achievement in online courses." Internet and Higher Education8(3): 221-231.
      Salmon, G. (2005). "Flying not flapping: a strategic framework for e-learning and pedagogical innovation in higher education institutions." ALT-J, Research in Learning Technology13(3): 201-218.
      Wiley, D. (2009). "The LHC and education." Retrieved 29 November, 2009, from http://opencontent.org/blog/archives/1098.

    ×