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What’s going on withengagement in onlineinitial teacher education?
Who?
Why?
What?
How?
Early insights?
9 teacher educators
Prof. Peter AlbionAssoc Prof Robyn HendersonDr Lindy AbawiDr Stewart RiddleDr Petrea RedmondDr Jenny DonovanDr Alice BrownMs Amanda HeffernanDr David Jones
USQ QILT ResultsCritiques of initial teacher educationResearch outputsImprove L&T
https://www.education.gov.au/upholding-quality-quality-indicators-learning-and-teaching
http://www.qilt.edu.au
~20%
online/distance learning programs… have not yet been able to provide high
levels of interpersonal interaction between lecturers and students, and students and their peers
All providers are exploring additional
opportunities for…interaction
seen by many as critical to quality teacher preparation.
http://www.nswteachers.nsw.edu.au/DownloadDocument.ashx?DocumentID=1240
pp. 5-6
in traditional learning settings, instructors
can easily gain insight into the way students work and learn. In LMS..it is more difficult for teachers to understand how the students behave and
learn in the system (Graf & Liu, 2009), and compared to other systems that structure interactions, these environments
provide data on the interaction at a very low level. ..it is necessary to search for empirical methods to better observe patterns in the
online environment(Cerezo et al, 2016, p. 43)
What’s going on withengagement in onlineinitial teacher education?
Who?
Why?
What?
How?
Early insights?
Click/gradeTime/grade
“Rossi” data sets
Network & paths
Content & sentiment
analysis
Learning design
Course specific
Develop analytics
What is revealed?What questions?
Student engagement?
What is needed?
Analytics?
Show participants
Click/gradeTime/grade
“Rossi” data sets
Network & paths
Content & sentiment
analysis
Learning design
Course specific
perceived usefulness was the most influential factor on instructors’ intention
and their actual use of the systems
(Motaghian et al, 2013, p. 158)
..currently available research tools do not yet answermany questions of teachers…..causes for these shortcomings are insufficient involvement of teachersin the design and development of indicators..(Dyckhoff et al., 2013, p.
227)
Click/gradeTime/grade
“Rossi” data sets
Network & paths
Content & sentiment
analysis
Learning design
Course specific
a more widespread problem in
the field of learning analytics: that it is being led by data and not pedagogy
(Ellis, 2013, p. 663)
The risk is that research and development focuses on
the data which is simplest to log computationally, perpetuating the dominant pedagogies and learning outcomes from an industrial era
(Buckingham-Shum, 2012, p. 8)
Click/gradeTime/grade
“Rossi” data sets
Network & paths
Content & sentiment
analysis
Learning design
Course specific
..data warehouse development is dominated bycentral IT departments that have little experiencewith decision support.A common theme…is the rediscovery of fundamentalDSS principles like evolutionary development.development processes are not implemented in a linear or even in a parallel fashion, but in continuous action cycles that involve significant user participation. (Arnot & Pervan,
2005)
Click/gradeTime/grade
“Rossi” data sets
Network & paths
Content & sentiment
analysis
Learning design
Course specific
..the challenge posed by learning analytics
is interpreting the resulting data against pedagogical intent and the local context to evaluate the success or otherwise
(Lockyer et al., 2013, p. 1440)
Technology use within individual courses also needs to be accounted for prior to making generalizations at a disciplinary level. (Gašević et al., 2015, p.
82)
fundamental premise…teachers’ pedagogical intent…drives the framing of the analytics that are presented (Corrin et al., 2015, p.
57)
What’s going on withengagement in onlineinitial teacher education?
Who?
Why?
What?
How?
Early insights?
Misc USQ data sources
Kludged into something useful
Converted into analyticson a web server
Viewed by participants
Reflection shared on blog etc.
Outputs generated
What’s going on withengagement in onlineinitial teacher education?
Who?
Why?
What?
How?
Early insights?
Interesting differencesNeCTAR is goodUSQ has work to do
HD A B C F0
500
1000
1500
2000
2500
3000
Clicks/student by grade
# of staff clicks in course site
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
% staff forum posts containing links
Kludged into something useful
USQ has work to do
Silos
Limited infrastructure
Individual system owners
Inconsistent data
Lack clarity around privacy/policy
Arnott, D., & Pervan, G. (2005). A critical analysis of decision support systems research. Journal of Information Technology, 20(2), 67–87. doi:10.1057/palgrave.jit.2000035
Buckingham Shum, S. (2012). Learning Analytics. Moscow. Retrieved from http://iite.unesco.org/pics/publications/en/files/3214711.pdf
Cerezo, R., Sánchez-Santillán, M., Paule-Ruiz, M. P., & Núñez, J. C. (2016). Students´ LMS interaction patterns and their relationship with achievement: A case study in higher education. Computers & Education, 96, 42–54. doi:10.1016/j.compedu.2016.02.006
Corrin, L., Kennedy, G., Barba, P. De, Williams, D., Lockyer, L., Dawson, S., & Copeland, S. (2015). Loop : A learning analytics tool to provide teachers with useful data visualisations. In T. Reiners, B. von Konsky, D. Gibson, V. Chang, L. Irving, & K. Clarke (Eds.), Globally connected,
digitally enabled. Proceedings ascilite 2015 (pp. 57–61). Perth, Western Australia.
Dyckhoff, a. L., Lukarov, V., Muslim, A., Chatti, M. a., & Schroeder, U. (2013). Supporting action research with learning analytics. In Proceedings of the Third International Conference on Learning Analytics and Knowledge - LAK ’13 (pp. 220–229). New York, New York, USA: ACM Press. doi:10.1145/2460296.2460340
Ellis, C. (2013). Broadening the scope and increasing the usefulness of learning analytics: The case for assessment analytics. British Journal of Educational Technology, 44(4), 662–664. doi:10.1111/bjet.12028
References
Gašević, D., Dawson, S., Rogers, T., & Gasevic, D. (2015). Learning analytics should not promote one size fits all: The effects of instructional conditions in predicating learning success. The Internet and Higher Education, 28, 68–84. doi:doi:10.1016/j.iheduc.2015.10.002
Lockyer, L., Heathcote, E., & Dawson, S. (2013). Informing Pedagogical Action: Aligning Learning Analytics With Learning Design. American Behavioral Scientist, 57(10), 1439–1459. doi:10.1177/0002764213479367
Motaghian, H., Hassanzadeh, A., & Moghadam, D. K. (2013). Factors affecting university instructors’
adoption of web-based learning systems: Case study of Iran. Computers & Education, 61, 158–167. doi:10.1016/j.compedu.2012.09.016
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