tools and methods to enhance information seeking, sensemaking and learning

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Opportunities to facilitate learning on the Internet are widely recognized across subject matters, levels of education and situations ranging from extending one’s hobbies to life-long learning relating to workers’ changing roles in the workplace. However, information available in the Internet, even in formal academic courses, is rarely presented using empirically proven findings from the learning sciences. Often, learners are left “on their own” to figure out which tactics work best for them in seeking and understanding information, and studying to learn it. Given that most learners have weak skills in these areas and in self-regulating learning, this sets a stage for major failures in sensemaking and learning that can have dire societal consequences. On the other hand, there are open issues with the existing (a) tools that are typically designed for a hypothetical but factually non-existent “average” user; and (b) methods that are too often based on self-reports (e.g., questionnaires) that are insufficient to advance research on sensemaking and complex learning processes that involve dynamic feedback loops. This talk (i) discusses results of several studies, in which we have addressed the above challenges, and (ii) outlines promising research topics that spans across the three main research cornerstones – computational, socio-cognitive, and user-centered design.

TRANSCRIPT

Tools and Methods to Enhance Information Seeking,

Sensemaking, and Learning

Dragan Gašević@dgasevic

https://semtech.athabascau.ca

Exciting times

MOOC-mania

http://www.scientificamerican.com/article.cfm?id=massive-open-online-courses-transform-higher-education-and-science

Scientific American, March 13, 2013

Aren’t they great?!

They offer good resources, but…

CHALLENGES

What skills to promote?

How about – critical thinking, creativity, research-intensive learning,

information seeking, sensemaking,self-directed and self-regulated learning,

“We teach what we can measure. If we don't measure what we care about,

it will never be taught.”

Paulo Blikinsein, LAK 2013

Three Generation of Distance Education Pedagogies

Anderson, T. & Dron, J. (2011). Three Generations of Distance Education Pedagogy, International Review of Research in Open and Distance Learning 12(3), 80-97, http://goo.gl/j3mRF

Why does it matter?!

ChallengeInformation seeking skills

Judd, T., & Kennedy, G. (2011). Expediency-based practice? Medical students’ reliance on Google and Wikipedia for biomedical inquiries. British Journal of Educational Technology, 42 (2), 351-360. doi:10.1111/j.1467-8535.2009.01019.x

Why does it matter?!

ChallengeSensemaking paradox

Butcher, K. R., & Sumner, R. (2011). Self-Directed Learning and the Sensemaking Paradox. Human–Computer Interaction, 26(1-2), 123-159. doi:10.1080/07370024.2011.556552

Why does it matter?!

ChallengeMetacognitive skills

Bjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-Regulated Learning: Beliefs, Techniques, and Illusions. Annual Review of Psychology, 64, 417-444. doi:10.1146/annurev-psych-113011-143823

How can we help?

Information seeking, sensemaking, & learning

Complex processes w/ dynamic feedback loops

APPROACH

Evidence-based Discipline

Integration of best research evidence with practitioner expertise and stakeholder values

The goal made up based on

Evidence-based discipline

Information seeking,sensemaking,

learning

Practice

Real world

Research

Evidence-based discipline

Information seeking,sensemaking,

learning

Practice

Real world

Research

Self-reports, laboratory, intrusive,

causality,…

Evidence-based discipline

Information seeking,sensemaking,

learning

Practice

Real world

Research

Self-reports, laboratory, intrusive,

causality,…

Users “on average”, GIGO, ..

GIGO – Garbage In Garbage Out

Intervene/instrument

Evidence-based discipline

Information seeking,sensemaking,

learning

Practice

Real world!

Research

Self-reports, laboratory, intrusive,

causality,…

Users “on average”,GIGO, …

GIGO – Garbage In Garbage Out

Intervene/instrument

Collect/Analyze

Learning Analytics – What?

Measurement, collection, analysis, and reporting of data about

learners and their contexts

Learning Analytics – Why?

Understanding and optimising learning and the environments

in which learning occurs

TOOLS

Data Collection

Importance of context

Tool and format independent Aggregates and integrates

Learning Context Ontology: LOCO

Jovanovic, J., Knight, C., Gasevic, D., Richards, G. (2007). Ontologies for Effective Use of Context in e-Learning Settings. Educational Technology & Society, 10(3), 47-59.

http://intelleo.eu

LOCO-Analyst

OAST and LOCO-Analyst

Ali, L., Hatala, M. Gašević, D., Jovanović, J., (2012). A Qualitative Evaluation of Evolution of a Learning Analytics Tool," Computers & Education, 58(1), 470-489

Learning Environment

LOCO-Analyst

Learning Analytics

Visual analytics requested (77.8%)

Ali, L., Hatala, M. Gašević, D., Jovanović, J. (2012). A Qualitative Evaluation of Evolution of a Learning Analytics Tool. Computers & Education, 58(1) 470-489.

LOCO-Analyst

LOCO-Analyst

LOCO-Analyst

LOCO-Analyst

Student comprehension

Student comprehension

Gašević, D., et al. (2011). An Approach to Folksonomy-based Ontology Maintenance for Learning Environments. IEEE Transactions on Learning Technologies, 4(4), pp. 301-314.

METHODS

Learning Analytics Acceptance Model

Ali, L., Asadi, M., Gašević, D., Jovanović, J., Hatala, M. (2013). Factors Influencing Beliefs for Adoption of a Learning Analytics Tool: An Empirical Study," Computers & Education, 62, 130–148.

Learning Analytics

What to measure?

We don’t need page access counts!

Wilson, T.D. (1999). Models in information behaviour research. Journal of Documentation, 55(3), 249 - 270, doi:10.1108/EUM0000000007145

Cognitive Presence in Online Discussions – Moderator Role

Cognitive presence Non-moderator Moderator t(df)

Control

group

Triggering event 4.29 (4.51) 1.05 (0.23) 4.18(37)*

Exploration 4.92 (4.12) 5.26 (3.43) -0.46(37)

Integration 1.42 (2.07) 2.68 (1.76) -3.05(37)**

Resolution 0.24 (0.49) 0.74 (1.01) -3.15(37)**

Other 0.89 (1.45) 0.89 (1.03) 0.00(37)

Interventi

on grou

p

Triggering event 1.43 (1.98) 1.02 (0.15) 1.35(43)

Exploration 3.64 (2.47) 2.82 (2.09) 1.83(43)

Integration 3.86 (3.00) 3.93 (2.32) -0.15(43)

Resolution 0.43 (0.85) 1.07 (1.50) -2.74(43)***

Other 0.86 (1.36) 0.61 (0.90) 1.21(43)

* p < 0.001; ** p < 0.005; *** p < 0.01

Cognitive Presence in Online Discussions – Association w/ Grades

Cognitive presence TMA1 TMA2 TMA3 TMA4 Final

Control group

Triggering event -.226 .005 -.046 -.050 -.010Exploration -.001 .141 .009 -.037 .048Integration .128 .060 .034 .043 .113Resolution .201 .027 -.023 -.054 .074Other -.028 .078 .113 .106 .154

Intervention group

Triggering event .149 -.077 -.070 .000 .016Exploration .216 .197 .163 .223 .243

Integration .156 .396** .417** .338* .454**

Resolution -.041 .060 .154 .083 .129Other .219 .046 .050 .075 .088

** p < 0.01; * p < 0.05

Analytics for Social Learning Environments

Automated content analysis and role miningOpen learner modeling

Recommendations

Self-regulated (Workplace) Learning

Trace-based Measurement Protocol

Siadaty, M. (2013). Semantic Web-Enabled Interventions to Support Workplace Learning, PhD Thesis, Simon Fraser University.

Siadaty, M. (2013). Semantic Web-Enabled Interventions to Support Workplace Learning, PhD Thesis, Simon Fraser University.

Siadaty, M. (2013). Semantic Web-Enabled Interventions to Support Workplace Learning, PhD Thesis, Simon Fraser University.

Siadaty, M. (2013). Semantic Web-Enabled Interventions to Support Workplace Learning, PhD Thesis, Simon Fraser University.

Siadaty, M. (2013). Semantic Web-Enabled Interventions to Support Workplace Learning, PhD Thesis, Simon Fraser University.

Siadaty, M. (2013). Semantic Web-Enabled Interventions to Support Workplace Learning, PhD Thesis, Simon Fraser University.

Self-regulated (Workplace) Learning

Self-regulated (Workplace) Learning

http://learningworksforkids.com/EF/metacognition.html

Information Interaction

Zhou, M., & Winne, P. H. (2012). Modeling academic achievement by self-reported versus traced goal orientation. Learning and Instruction, 22(6), 413–419. doi:10.1016/j.learninstruc.2012.03.004

Information Interaction

Zhou, M., & Winne, P. H. (2012). Modeling academic achievement by self-reported versus traced goal orientation. Learning and Instruction, 22(6), 413–419. doi:10.1016/j.learninstruc.2012.03.004

Achievement goal orientation (2x2)

Concept and relation filtering

Zouaq, A., Gašević, D., Hatala, M., "Towards Open Ontology Learning and Filtering," Information Systems, Vol. 36, No. 7, 2011, pp. 1064-1081.

Concept and relation filtering

Zouaq, A., Gašević, D., Hatala, M., "Towards Open Ontology Learning and Filtering," Information Systems, Vol. 36, No. 7, 2011, pp. 1064-1081.

FORWARD-LOOKING

Analyzing dynamic processes

http://www.processmining.org

Enough text obsession!

Forward-looking

George Siemens, LAK 2013

CLAS – Collaborative Lecture Annotation System

Multimodal analytics

Forward-looking

http://www.solaresearch.org

SUMMARY

Thank you!

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