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Rich Content, Not Content-Rich Alan J. Cann Department of Biology University of Leicester. Evaluation Synthesis Analysis Application Understanding Knowledge Bloom's Taxonomy of Educational Objectives Benjamin Bloom, 1956: e-Learning 5 E-mod - supporting, responding
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Rich Content, Not Content-Rich Alan J. Cann Department of Biology University of Leicester.
Evaluation Synthesis Analysis Application Understanding Knowledge Bloom's Taxonomy of Educational ObjectivesBenjamin Bloom, 1956:
e-Learning 5 E-mod - supporting, responding Tech - providing links outside closed conferences Development Knowledge construction 4 E-mod - facilitating process Tech - conferencing Information exchange 3 E-mod - facilitate tasks; support use of learning materials Tech - searching, personalizing Online socialization 2 E-mod - familiarization; building bridges (cultural, social & learning environment) Tech - sending & receiving messages Access & motivation 1 E-moderating - welcome & encourage Technical - Setting up & accessing Salmon, E-Moderating, Routledge, (2004)
Rich Content • Push technology • Keyword-specific RSS • Dynamically generated content: • PHP • Javascript • HTML
Why Discuss ? • Discussion promotes reflection. • Deep versus superficial learning. • Reflection encourages higher level learning competencies and inclusivity (ownership of learning).
The Model • A model of online assessment for (bioscience) students. • Optimum group size8-15: • Smaller groups than this do not have the critical mass to sustain discussion • Larger groups are difficult to assess / allow anonymity. • Contributions to the discussion boards were explicitly linked to assessment.
What's needed? • Prior to the commencement of any discussions, the entire class engaged in an online E-tivity, an icebreaker to promote group cohesion, in this case, construction of a homepage on the VLE to introduce themselves to other module participants (Salmon, G. (2002) E-tivities: The key to active online learning. Kogan Page). • To accommodate the new form of assessment, the previous in course essay was dropped in favour of three one hour essays written under exam conditions and submitted electronically via the VLE.
Module Hits Outcome 1 • 87,000 hits in 10 week period, an average of 256 per student per week. • 66% of total module hits.
Hits per post Outcome 2 • Average 22 hits to each post - they *are* reading. • Ratio highest for general module forum, lowest for week 10.
Outcome 3 • Evidence of fatigue. • Need to inject new enthusiasm with e-tivities midway through module - eLearning demands novelty for engagement! Total Hits Per Week
Random Statistics • Very popular with students (feedback). • No significant difference in end of module marks. • Gender difference: females contribute significantly more hits, but no significant differences in posts or marks.
Wikis • Online collaborative writing: Motivation? • Discussion group becomes the tool to moderate and firefight contributions. • Assessment scheme records minimal acceptable contribution - online community of practice assesses quality.
Questions • How do you motivate learners to engage the full potential of eLearning? • What's in it for me?
www-micro.msb.le.ac.uk/AJC/talks.html alan.cann@leicester.ac.uk Education costs money - ignorance costs more.