Introducing the indicators project
Upcoming SlideShare
Loading in...5
×
 

Introducing the indicators project

on

  • 1,655 views

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/

Statistics

Views

Total Views
1,655
Views on SlideShare
1,405
Embed Views
250

Actions

Likes
0
Downloads
10
Comments
0

2 Embeds 250

http://indicatorsproject.wordpress.com 246
http://www.slideshare.net 4

Accessibility

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment
  • 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

Introducing the indicators project Introducing the indicators project Presentation Transcript

  • The Indicators ProjectIdentifying effective learning: adoption, activity, grades and external factors
    Colin BeerDavid JonesKen Clark
    http://tr.im/FvRQ
  • Overview
    Context
    Feature usage
    Participation, grades and other factors
    Future work and Reflections
    http://www.flickr.com/photos/atbaker/1577665185/
  • Overview
    Context
    Feature usage
    Participation, grades and other factors
    Future work and Reflections
    http://www.flickr.com/photos/atbaker/1577665185/
  • The data that we, educators gatherand utilize is all but garbage.
    (Wiley, 2009)
    http://www.flickr.com/photos/dnorman/251646154/
  • 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/
  • 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/
  • 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/
  • Mostly ad hoc
    Mostly LMS reporting
    Some surveys
    Peer review?
    One manual check
    (Gonch, 2007)
    http://www.flickr.com/photos/80417459@N00/2471314610/
  • Mostly ad hoc
    Mostly LMS reporting
    No widespread view
    Some surveys
    One manual check
    (Gonch, 2007)
    http://www.flickr.com/photos/80417459@N00/2471314610/
  • 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/
  • 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/
  • 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/
  • 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/
  • 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/
  • 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/
  • “LMS”
    Pre-2010
    Webfuse – 1997-2009
    WebCT – 1999-2003/4
    Blackboard – 2004-2009
    2010-
    Moodle
    http://www.flickr.com/photos/80417459@N00/2471314610/
  • 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/
  • Enabling comparisons of LMS usageacross institutions, platforms and time
    http://indicatorsproject.wordpress.com
  • http://www.flickr.com/photos/david_jones/36379215/
  • 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/
  • 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/
  • 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/
  • 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/
  • 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/
  • Overview
    Context
    Feature usage
    Participation, grades and other factors
    Future work
    http://www.flickr.com/photos/atbaker/1577665185/
  • There are more similarities than differences among LMS
    (Black et al, 2007)
    http://www.flickr.com/photos/chokingsun/3495110670/
  • 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
    • Chat
    • Discussion forum
    • Email
    • Quizzes
    • Drop box
    • Content/files
    • Announcements
    • Gradebook
    ComputerBasedInstruction
    Evaluatingcourse and instructors
    • Some quizzes
    • Adaptive release
    • Surveys
    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/
  • CQU
    Bb
    Wf
    What we did
    LMS logs
    http://www.flickr.com/photos/chokingsun/3495110670/
  • LMS Independent Data
    CQU
    Bb
    Wf
    LMS logs
    What we did
    http://www.flickr.com/photos/chokingsun/3495110670/
  • Feature usage
    LMS Independent Data
    (Malikowski et al, 2007)
    CQU
    Bb
    Wf
    LMS logs
    What we did
    http://www.flickr.com/photos/chokingsun/3495110670/
  • Malikowskitop & bottomrange
    http://www.flickr.com/photos/chokingsun/3495110670/
  • Blackboard
    http://www.flickr.com/photos/chokingsun/3495110670/
  • Webfuse
    http://www.flickr.com/photos/chokingsun/3495110670/
  • http://www.flickr.com/photos/chokingsun/3495110670/
  • http://www.flickr.com/photos/chokingsun/3495110670/
  • http://www.flickr.com/photos/chokingsun/3495110670/
  • http://www.flickr.com/photos/wadem/2730257498/
  • 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/
  • 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/
  • Overview
    Context
    Feature usage
    Participation, grades and other factors
    Future work and Reflections
    http://www.flickr.com/photos/atbaker/1577665185/
  • 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/
  • Feature usage
    LMS Independent Data
    (Malikowski et al, 2007)
    CQU
    Bb
    Wf
    LMS logs
    What we did
    http://www.flickr.com/photos/chokingsun/3495110670/
  • 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/
  • 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/
  • Distance education students
    Hits on course site
    Hits on course forum
    http://www.flickr.com/photos/wolfgangstaudt/2279651479/
  • CQ on-campus students
    http://www.flickr.com/photos/wolfgangstaudt/2279651479/
  • AIC students
    http://www.flickr.com/photos/wolfgangstaudt/2279651479/
  • Distance education students
    # of replies
    # of posts
    http://www.flickr.com/photos/wolfgangstaudt/2279651479/
  • CQ on-campus students
    http://www.flickr.com/photos/wolfgangstaudt/2279651479/
  • AIC students
    http://www.flickr.com/photos/wolfgangstaudt/2279651479/
  • 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/
  • Mixed design ANOVA
    All reported effects are significant
    Significant interaction effectbetween grades and participation
    http://www.flickr.com/photos/wolfgangstaudt/2279651479/
  • http://www.flickr.com/photos/wadem/2730257498/
  • 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/
  • 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/
  • 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/
  • Course groups based on staff hits
    http://www.flickr.com/photos/orinrobertjohn/3321067724/
  • High staff participation courses
    Hits
    http://www.flickr.com/photos/orinrobertjohn/3321067724/
  • High staff participation courses
    Replies & posts
    http://www.flickr.com/photos/orinrobertjohn/3321067724/
  • Super low staff participation courses
    Hits
    http://www.flickr.com/photos/orinrobertjohn/3321067724/
  • Super low staff participation courses
    Replies & posts
    http://www.flickr.com/photos/orinrobertjohn/3321067724/
  • Posts comparisons
    High
    Superlow
    http://www.flickr.com/photos/orinrobertjohn/3321067724/
  • 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/
  • http://www.flickr.com/photos/wadem/2730257498/
  • 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/
  • 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/
  • 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/
  • None of the above
    http://www.flickr.com/photos/orinrobertjohn/3321067724/
  • Grad cert in L&T
    http://www.flickr.com/photos/orinrobertjohn/3321067724/
  • Teaching awards
    http://www.flickr.com/photos/orinrobertjohn/3321067724/
  • Education discipline
    http://www.flickr.com/photos/orinrobertjohn/3321067724/
  • Instructional design
    http://www.flickr.com/photos/orinrobertjohn/3321067724/
  • Overview
    Context
    Feature usage
    Participation, grades and other factors
    Future work & Reflections
    http://www.flickr.com/photos/atbaker/1577665185/
  • http://www.flickr.com/photos/mikebaird/2985066755/
  • http://www.flickr.com/photos/david_jones/36379215/
  • http://www.flickr.com/photos/dmatos/540688952/
  • http://www.flickr.com/photos/mwichary/2188958154/
  • http://www.flickr.com/photos/sylvar/1138341328/
  • http://www.flickr.com/photos/fncll/145149313/
  • http://www.flickr.com/photos/nedrichards/3234490934/
  • 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/
  • http://www.flickr.com/photos/fncll/145149313/
  • http://indicatorsproject.wordpress.com
    http://tr.im/FvRQ
    http://www.flickr.com/photos/jamuraa/813966437/
  • 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.