the indicators project - ascilite version
Post on 17-Oct-2014
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DESCRIPTION
A reworked version of presentation for ASCILITE'09 paper (http://tr.im/FD7a).TRANSCRIPT
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The Indicators ProjectIdentifying effective learning: adoption, activity, grades and external factors
Colin BeerDavid JonesKen Clark
http://tr.im/FvRQ
Twitter: #eair
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http://www.flickr.com/photos/anders-vindegg/3408838186/
Surprising patterns in CQU LMS data
Apparent benefit in LMS usage analysis that is
Different from established patterns
Due to limitations in current work?
Cross-LMS
Cross-institutional
Longitudinal
Want to play?
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Overview
http://www.flickr.com/photos/atbaker/1577665185/
Context
Level of feature adoption
Link between participation & grades
Reflection and Future work
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Overview
http://www.flickr.com/photos/atbaker/1577665185/
Context
Level of feature adoption
Link between participation & grades
Reflection and Future work
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The data that we, educators gatherand utilize is all but garbage.(Wiley,
2009)
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http://www.flickr.com/photos/mikebaird/2087879492/
(Dawson, 2009; Dawson et al, 2009)
(Bakharia et al, 2009)
(Malikowski, 2008; Malikowski, et al, 2007;Malikowski et al, 2006)
(Campbell et al, 2007)
(Griffiths, 2007)
(Dawson, 2006)
(Black et al, 2008)
(Dawson et al, 2008)
(Heathcoate et al, 2005)
(Hornik et al, 2008)
(Romero et al, 2007)
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LMS reporting toolsOnly what is in the
LMS
Limited views
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Some surveysHuman
recollectionLMS reporting toolsOnly what is in the
LMS
Limited views
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Some surveysHuman
recollection
Manual checksTime-
consuming
Error prone
LMS reporting toolsOnly what is in the
LMS
Limited views
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http://www.flickr.com/photos/mwichary/2188958154/
Some surveysHuman
recollection
Limited longitudinal data
Manual checksTime-
consuming
Error prone
LMS reporting toolsOnly what is in the
LMS
Limited views
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http://www.flickr.com/photos/mwichary/2188958154/
Some surveysHuman
recollection
Limited longitudinal data
Limited cross-LMS comparisons
Manual checksTime-
consuming
Error prone
LMS reporting toolsOnly what is in the
LMS
Limited views
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http://www.flickr.com/photos/mwichary/2188958154/
Some surveysHuman
recollection
Limited longitudinal data
Limited cross-LMS comparisons
Limited cross-institutional comparisons
Manual checksTime-
consuming
Error prone
LMS reporting toolsOnly what is in the
LMS
Limited views
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“LMS” situation
Students
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Webfuse 1997-2009
Pre-2010 “LMS”
WebCT 1999-2004
Blackboard 2004-2009
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Webfuse 1997-2009
Post-2010 “LMS”
Blackboard 2004-2009
Moodle….
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Students - 2009
CQ on-campus
4436
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Students - 2009
CQ on-campus
Distance education
4436
8444
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Students - 2009
CQ on-campus
Distance education
AIC on-campus
4436
8444 796
2
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The data that we, educators gatherand utilize is all but garbage.(Wiley,
2009)
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http://indicatorsproject.wordpress.com
Enabling comparisons of LMS usageacross institutions, platforms and
time
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Overview
http://www.flickr.com/photos/atbaker/1577665185/
Context
Level of feature adoption
Link between participation & grades
Reflection and Future work
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There are more similarities than differences among LMS (Black et al,
2007)
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TransmittingContent
CreatingClass
Interactions
ComputerBased
Instruction
Move to features in unexplored categories, until each category is considered for different learning needs
Level 1: Most used Level 2: Moderately used Level 3: Rarely used
• Content/files• Announcements• Gradebook
More than 50% of courses More than 20% of courses (much) less than 20% of courses
EvaluatingStudents• Quizzes• Drop box
Evaluatingcourse and instructors
• Surveys• Chat• Discussion forum• Email
• Some quizzes• Adaptive release
(Malikowski et al, 2007)
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What we did
CQU
Wf BbLMS logs
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CQU
Wf BbLMS logs
LMS Independent
Data
What we did
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CQU
Wf BbLMS logs
LMS Independent
Data
What we did
(Malikowski et al, 2007)
% of courses adopting “Malikowski features”
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Year Blackboard Webfuse2005 777 3042006 810 2962007 874 2522008 945 2252009 868 174
# course sites per “LMS”
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Malikowskitop & bottomrange
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Blackboard
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Webfuse
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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)
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Future Work
Will Moodle be different?
Why?
What about other institutions?
Are Malikowski ranges out of date?
When is a feature adopted?
How
…….
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Overview
http://www.flickr.com/photos/atbaker/1577665185/
Context
Level of feature adoption
Link between participation & grades
Reflection and Future work
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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)
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What about
Different student types?
Different levels of staff interaction?Different staff academic background?
(Fresen, 2007)
CQU context
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CQU
Wf BbLMS logs
LMS Independent
Data
What we did
(Malikowski et al, 2007)
Feature usage
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CQU
Wf BbLMS logs
LMS Independent
Data
What we did
(Malikowski et al, 2007)
Feature usage
Student records
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CQU
Wf BbLMS logs
LMS Independent
Data
What we did
(Malikowski et al, 2007)
Feature usage
Participation, grades,external factors
Student records
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Participation
Hits
Discussion forum
Entire course siteJust course forum
# replies# posts
http://www.flickr.com/photos/adactio/1259245482/
N = 510,158
Student/courses
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Mixed design ANOVA
All reported effects are significant
Significant interaction effectbetween grades and participation
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Hits on course site
Hits on course forum
Distance education students
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CQ on-campus students
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AIC students
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AIC
CQ
FLEX
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Distance education students
# of replies
# of posts
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CQ on-campus students
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AIC students
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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)
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http://www.flickr.com/photos/jamuraa/813966437/
What about
Different student types?
Different levels of staff interaction?Different staff academic background?
(Fresen, 2007)
CQU context
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Course groups based on staff hits
Group Courses Student-courses
Students/course
Definition
High 678(17%)
156,770 231 x>3000 hits
Medium 980(25%)
143,314 146 3000>x>1000
Low 1474(37%)
102,214 69 1000>x>100
Super low 849(21%)
68,354 80 100>x>0
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Hits
High staff participation courses
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Replies & posts
High staff participation courses
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Hits
Super low staff participation courses
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Replies & posts
Super low staff participation courses
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High
Posts comparisons
Superlow
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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)
![Page 65: The indicators project - ASCILITE version](https://reader033.vdocuments.site/reader033/viewer/2022052819/5441af9eb1af9ff44d8b4760/html5/thumbnails/65.jpg)
http://www.flickr.com/photos/wadem/2730257498/
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Future Work
- Course size
Examination of super-low
Networks of interaction (Bakharia et al, 2009; Dawson,
2009)
Forum content
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What about
Different student types?
Different levels of staff interaction?Different staff academic background?
(Fresen, 2007)
CQU context
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Course offerings with
Staff with grad certs in L&TSignificant input from instructional designerStaff who have received teaching awards
Staff teaching education coursesNone of the above
n=167
n=4
n=196
n=3288
N=362
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None of the above
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Grad cert in L&T
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Teaching awards
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Education discipline
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Instructional design
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Overview
http://www.flickr.com/photos/atbaker/1577665185/
Context
Level of feature adoption
Link between participation & grades
Refleection and Future work
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http://www.flickr.com/photos/mikebaird/2985066755/
Some interesting patterns
Useful idea
Needs more work
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http://www.flickr.com/photos/atbaker/1577665185/
Institution A
LMS 1 LMS 2
Institution B
LMS
Institution C
LMS
LMS Independent
Data
Useful Data/Informat
ion
Useful Data/Informat
ion
Useful Data/Informat
ion
Useful Data/Informat
ion
T&L Practice Research
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http://www.flickr.com/photos/atbaker/1577665185/
Institution A
LMS 1 LMS 2
Institution B
LMS
Institution C
LMS
LMS Independent
Data
Useful Data/Informat
ion
Useful Data/Informat
ion
Useful Data/Informat
ion
Useful Data/Informat
ion
T&L Practice Research
Enabling
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http://www.flickr.com/photos/atbaker/1577665185/
Institution A
LMS 1 LMS 2
Institution B
LMS
Institution C
LMS
LMS Independent
Data
Useful Data/Informat
ion
Useful Data/Informat
ion
Useful Data/Informat
ion
Useful Data/Informat
ion
T&L Practice Research
Enabling
What
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http://www.flickr.com/photos/wolfgangstaudt/2279651479/
Avg course hits
DE under grad students
By age
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http://www.flickr.com/photos/atbaker/1577665185/
Institution A
LMS 1 LMS 2
Institution B
LMS
Institution C
LMS
LMS Independent
Data
Useful Data/Informat
ion
Useful Data/Informat
ion
Useful Data/Informat
ion
Useful Data/Informat
ion
T&L Practice Research
Enabling
What
Why
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http://www.flickr.com/photos/atbaker/1577665185/
Institution A
LMS 1 LMS 2
Institution B
LMS
Institution C
LMS
LMS Independent
Data
Useful Data/Informat
ion
Useful Data/Informat
ion
Useful Data/Informat
ion
Useful Data/Informat
ion
T&L Practice Research
Enabling
What
WhyHow
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http://www.flickr.com/photos/david_jones/36379215/
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http://www.flickr.com/photos/dmatos/540688952/
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http://www.flickr.com/photos/mwichary/2188958154/
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http://www.flickr.com/photos/sylvar/1138341328/
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http://www.flickr.com/photos/fncll/145149313/
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http://www.flickr.com/photos/jamuraa/813966437/
http://tr.im/FvRQ
http://indicatorsproject.wordpress.com
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Bakharia, A., E. Heathcote, et al. (2009). Social networks adapting pedagogical practice: SNAPP. Same places, different spaces. Proceedings ascilite Auckland 2009. Auckland: 49-51.
Black, E. W., K. Dawson, et al. (2008). "Data for free: Using LMS activity logs to measure community in online courses." Internet and Higher Education 11(11): 65-70.
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 Trends 51(2): 35-39.
Campbell, J., P. DeBlois, et al. (2007). "Academic analytics: A new tool for a new era." EDCAUSE Review 42(4): 40-42.
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., L. Macfadyen, et al. (2009). Learning or performance: Predicting drivers of student motivation. Same places, different spaces. Proceedings ascilite Auckland 2009, Auckland.
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
Dawson, S. (2006). "Online forum discussion interactions as an indicator of student community." Australian Journal of Educational Technology 22(4): 495-510.
Fresen, J. (2007). "A taxonomy of factors to promote quality web-supported learning." International Journal on E-Learning 6(3): 351-362.
Griffiths, M. E. (2007). Patterns of user acitivity in the Blackboard course management system across all courses in the 2004-2005 academic year at Brigham Young University. Department of Instructional Psychology and Technology., Brigham Young. Master of Science: 117.
Heathcoate, L. and S. Dawson (2005). "Data Mining for Evaluation, Benchmarking and Reflective Practice in a LMS." E-Learn 2005: World conference on E-Learning in corporate, government, healthcare and higher education.
Hornik, S., C. S. Saunders, et al. (2008). "The Impact of Paradigm Development and Course Level on Performance in Technology-Mediated Learning Environments." Informing Science. The international journal of an emerging transdiscipline 11(11).
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.
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Malikowski, S., M. Thompson, et al. (2007). "A model for research into course management systems: bridging technology and learning theory." Journal of Educational Computing Research 36(2): 149-173.
Malikowski, S., M. Thompson, et al. (2007). "A model for research into course management systems: bridging technology and learning theory." Journal of Educational Computing Research 36(2): 149-173.
Malikowski, S., M. Thompson, et al. (2006). "External factors associated with adopting a CMS in resident college courses." Internet and Higher Education 9(3): 163-174.
Morris, L., C. Finnega, et al. (2005). "Tracking student behavior, persistence, and achievement in online courses." Internet and Higher Education 8(3): 221-231.
Romero, C. b., S. n. Ventura, et al. (2007). "Data mining in course management systems: Moodle case study and tutorial." ScienceDirect Computers and Education (51 (2008)): 368-384.
Salmon, G. (2005). "Flying not flapping: a strategic framework for e-learning and pedagogical innovation in higher education institutions." ALT-J, Research in Learning Technology 13(3): 201-218.
Wiley, D. (2009). "The LHC and education." Retrieved 29 November, 2009, from http://opencontent.org/blog/archives/1098.