Pre-conference workshop
Title
How to use data (analytics) to inform eTeaching and eLearning Goh Poh Sun (GPS), Sergio Hernandez-Marin (SHM), Lim Wee Khee (LWK)
Objectives
To illustrate and demonstrate the utility of off the shelf/free(ly available) data analytics to inform eTeaching and give visibility of eLearning (activities) by our students.
Workshop description
The workshop will be based on actual case studies from an experienced medical educator (GPS), who has been using Google Blogger (with in built data analytics), exclusively (rather than PowerPoint) for clinical teaching, and medical education faculty development over the last 6 years (in undergraduate, postgraduate and CME/CPD settings). Co-facilitators in the workshop (SHM and LWK) will share added insights from a technical-strategic (SHM) and market-engagement (LWK) perspective. Participants will have the opportunity to build their own prototype teaching blog (with use of Google Blogger as an illustrative freely available, and free to use platform), together with seeing how embedding additional online tools into a teaching blog (like Slideshare, SurveyMonkey, and Padlet) can give educators further data and visibility of student engagement, and actual learning within an eLearning process and platform. Participants will be expected to have engaged in one to two hours of pre-reading, and a pre-workshop exercise. Participants should bring a WiFi enabled laptop or tablet computer to the workshop.
Who should attend
Health professions educators (Medical, Nursing and Allied Health), and staff who have an administrative and leadership role in supporting and working with eLearning/Technology enhanced learning teams.
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Reflect on how Bloom's taxonomy, Miller's pyramid and the Kirkpatrick model might apply to learning continuum map from Poh-Sun Goh
Why prepare for class? Do pre-reading before class?
Prior knowledge or pre-existing knowledge informs/is required for reading (comprehension)
see below
Using data to guide (e)teaching and (e)learning from Poh-Sun Goh
https://medicaleducationelearning.blogspot.sg/2017/10/requirements-for-data-informed-personal.html
https://medicaleducationelearning.blogspot.sg/2017/10/requirements-for-data-informed-personal.html
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https://telatcenmed.blogspot.sg/2017/05/technology-enhanced-learning-elearning.html
(faculty development workshop for medical educators, for around 25 participants)
Invited presentation for Medicine Review Course, July 8th, 2017 @ Academia, SGH
(large group presentation for postgraduate clinical audience, for around 400 to 500 participants)
Invited teaching faculty for NUHS NCIS organised Radiation oncology target delineation workshop - 10 August 2017
https://learningneuroradiology.blogspot.sg/2017/11/radiology-resident-tutorial-monday-13.html
(small group postgraduate radiology resident interactive tutorial, for around 15 residents)
https://learningabdominalradiology.blogspot.sg/2017/12/interactive-case-based-tutorial-for-m3.html
and
https://learningabdominalradiology.blogspot.sg/2017/10/interactive-case-based-tutorial-for-m3.html
(small group undergraduate medical school year 3 interactive tutorial, for around 20 students)
https://learningchestradiology.blogspot.sg/2017/09/imaging-of-respiratory-disorders-m2.html
see slide 12 from presentation above (screenshot below)
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Goh, P.S. Learning Analytics in Medical Education. MedEdPublish. 2017 Apr; 6(2), Paper No:5. Epub 2017 Apr 4. https://doi.org/10.15694/mep.2017.000067
"...the real revolution (into measurement and attribution ... of the influence of print and TV advertising on sales ... (where) success was measured (previously) by industry awards rather than any financial results ... the real revolution got underway with the Internet and World Wide Web around the turn of the twenty-first century (with) these technologies involved "addressability", in that firms could know who they were addressing with marketing activities and what behaviours followed. For the first time, companies could extensively measure advertising, promotions and marketing oriented content - whether and how long recipients viewed them and what they did after."
above quote from Forward section by Thomas H. Davenport (see also below)
"We can only meaningfully measure based on theory" - David Williamson Shaffer
"We value what we measure, rather than measure what we value" - Jonathan Martin
above quote from Slide 5 from
"...not everything that can be counted counts, and not everything that counts can be counted"
William Bruce Cameron (1963)
https://quoteinvestigator.com/2010/05/26/everything-counts-einstein/
"Can we tell from your digital profile if you're learning?"William Bruce Cameron (1963)
https://quoteinvestigator.com/2010/05/26/everything-counts-einstein/
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Simon Buckingham Shum
"As learning analytics data provides a snapshot of how engaged students are and how they are performing, this could be considered a useful indication of where excellent teaching is taking place"
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From Bricks to Clicks - The Potential of Data and Analytics in Higher Education, report by the Higher Education Comission, on 26 January 2016.
http://www.policyconnect.org.uk/hec/research/report-bricks-clicks-potential-data-and-analytics-higher-education
The Society for Learning Analytics Research (SoLAR) defines learning analytics as “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs” (Long, Siemens, Conole, & Gašević, 2011).
Long, P. D., Siemens, G., Conole, G., & Gašević, D. (Eds.). (2011). Proceedings of the 1st International Conference on Learning Analytics and Knowledge (LAK’11). New York, NY, USA: ACM.
"Assessment is most effective when it reflects an understanding of learning as multidimensional, integrated, and revealed in performance over time. The adoption of learning analytics too must be informed not only by what can be measured but also by what cannot. There will be limits in what learning analytics can do. In this vein, Siemens and Long have appropriately acknowledged that learning "is messy" and have warned that with learning analytics, "we must guard against drawing conclusions about learning processes based on questionable assumptions that misapply simple models to a complex challenge."5 The message here is important: not every aspect of learning can be captured by the powerful tool that analytics promises to be. Sometimes learning is ineffable! Therefore, multiple methods for assessing learning should be employed, including assessments that function as learning opportunities to support students' deep integration of knowledge, their personal development, and (hopefully!) their transformation over time."
and
"Assessment is most likely to lead to improvement when it is part of a larger set of conditions that promote change. As this principle states, assessment alone changes very little; likewise, learning analytics cannot act alone in radically disrupting and transforming education. Assessment (when done well) is about the authentic and deep understanding and improvement of teaching and learning. Analytics is about using the power of information technology to see patterns of success (or failure) in learning. Combining the two might actually produce the seeds of transformation—a powerful inquiry into what supports authentic, deep, transformative learning for students."
above quotes from
https://er.educause.edu/articles/2012/7/learning-analytics-the-new-black
'...Digital “footprints” (or trace data) about user interactions with technology have been recorded since the very introduction of the Internet and web-based software systems ... ...Over time, the value of such digital traces has been recognized as a promising source of data about student learning ...'
above quote from
Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59 (1), 64–71. https://doi.org/10.1007/s11528-014-0822-x
"...The amount of activity and time online for the group of most successful students was mostly below the class average. These learners were interpreted as highly effective with good prior knowledge and strong study skills. The findings of the Kovanović et al. were corroborated in several studies reported by Lust at al. (Lust, Elen, & Clarebout, 2013; Lust, Vandewaetere, Ceulemans, Elen, & Clarebout, 2011).
"Analytics-based tools designed to construct feedback for students, among other key points, are more effective when they adopt a task-specific language and provide guidance while prompting dialogue between students and instructors (Boud & Molloy, 2013; O’Donovan, Rust, & Price, 2016).
Studies making use of learning analytics methods, by examining trace data to extract learning
strategies followed by students, reveal that students have a high tendency to exhibit performance-oriented behaviors – i.e., focusing on summative assessments deemed to contribute to grades (Lust et al., 2013; Pardo, Jovanović, Dawson, Gašević, & Mirriahi, 2016).
Studies making use of learning analytics methods, by examining trace data to extract learning
strategies followed by students, reveal that students have a high tendency to exhibit performance-oriented behaviors – i.e., focusing on summative assessments deemed to contribute to grades (Lust et al., 2013; Pardo, Jovanović, Dawson, Gašević, & Mirriahi, 2016).
________
and
Explore the Google Analytics blog and Google Analytics YouTube Channel
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Goh, P.S. Learning Analytics in Medical Education. MedEdPublish. 2017 Apr; 6(2), Paper No:5. Epub 2017 Apr 4 https://doi.org/10.15694/mep.2017.000067
Main conference symposium
Title
Using data (analytics) to inform eTeaching and eLearning Goh Poh Sun (GPS), Sergio Hernandez-Marin (SHM), Lim Wee Khee (LWK)
Brief description of session
The central thesis of this symposium will be to demonstrate and illustrate how data (analytics) can inform an educational practitioner (in their educational practice), and anchor scholarly teaching and educational scholarship.
The three panelists bring (to the audience) long standing practical frontline and academic experience in their roles as a clinical teacher and in medical education faculty development (GPS), in data analytics and strategic thinking (SHM), and in the real world application of social media analytics in business (LWK).
This interactive symposium and panel discussion (with the audience) will be anchored by a purpose built dedicated presentation online blog (for approximately 30 minutes to one hour of pre-session online review BEFORE the session), each symposium presenter giving a (maximum) 10 minute short overview presentation, followed by ONE HOUR of interactive live discussion (during the session) with the audience (who should bring a WiFi enabled mobile phone, Tablet or Laptop to the session to engage with the panelists - both synchronously and asynchronously, the day before, during, and day after the symposium).
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Learning analytics in Med Ed (updated) from Poh-Sun Goh
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Goh, P.S. Learning Analytics in Medical Education. MedEdPublish. 2017 Apr; 6(2), Paper No:5. Epub 2017 Apr 4. https://doi.org/10.15694/mep.2017.000067
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