Phd defence: Learner Models in Online Personalized Educational Experiences: an infrastructure and...
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Transcript of Phd defence: Learner Models in Online Personalized Educational Experiences: an infrastructure and...
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Presented by L. Mazzola
Faculty of Communication SciencesInstitute for Communication Technologies
University of Lugano, CH
Lugano - 23 May 2014
Learner Models in Online Personalized Educational Experiences: an infrastructure and
some experiments
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Agenda● The context
● The problem
● A solution
● The proposal
● Initial analysis in GRAPPLE
● Some testing in and outside GRAPPLE
● Consideration/Conclusions
● Possible next steps
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The context● Technology Enhanced Learning (TEL)
– ICT applied to education process● Availability of connection● Enhancement in research and science → new knowledge● Support for individual needs● Availability of Learning Management and Intelligent Tutoring System
– Possibility of continuous education● Distance and Blended modalities● Informal learning● On-the-job training
→ additional resources and tools to support educational experiences
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The problem of TEL● PROS:
– Decoupling of time and space– Personal pace– Asynchronous interaction
● CONS:
– Disengagement / Drop Out– Less “social pressure”– Difficulty in self-regulating– Depletion of stimulus to active participation
● Needs of tools to support the learning/teaching process
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A solution, in the literature● Creating a user profile
– Adoption of content and presentation– Positive effect of Disclosure (OLM)– Integration with other sources/external provider (global
and long-run indicators)– Representation aspect (Information Visualization):
● From text/analytic to graphical/summary
● For Supporting purposes:
– Enhance and stimulating self-reflection / awareness– Fostering the tutoring process
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AIMS
(1) Representation aspects:
– How the OLM can be represented fruitfully to learners?– ...and to teacher/tutors?
(2) Adaptive and social visualization of OLM:
– How they can affect the user experience?
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OBJECTIVES
(1) Demonstrate that mixing different and heterogeneous sources can have a meaningful didactic interpretation
(2) Explore approaches and representational models considered effective by learners and tutors/teachers
(3) Measure the perceived effect/impact of the introduction of such a tool
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The proposal: GVIS
Configurations / Semantics
Data Sources
Processing levels
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The proposal : GVIS● PHP code with OO approach
● 3 layers that are specialized in source interfacing, aggregation of data into information, and presentation aspects
● Each layer controlled by one or more XML description of the operation/attribute (didactic semantic)
● AJAX controlled interaction (interactive and responsive)
● Adaptive segments in the XML configuration
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The proposal: GVIS
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UML sequence
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Representation aspect analysisOn mockups, through online questionnaire (learner & teacher)
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Analysis of MockUp● # Users:
– 43 Learners– 32 Instructor (Tutor/Teacher)
● Results:
– Simpler visualizations preferred– More complex on user request (exploration)– Usefulness of filtering capabilities of data presented– Peers comparisons useful, but only at aggregated level– Didactic meaningful aggregation for tutors/teacher
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Widgets for GRAPPLE
Bridge
Bridge
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Subjective Assessment of VisualisationDimensions Learner Teacher/Tutor
Perceived usability/suitability - in terms of:
- suitability for the task XX XX
- self-descriptiveness XX XX
Visualization benefits:
- Meta-cognition XX XX
- Cognitive load XX XX
- Learning effectiveness XX
- Benefits for instructors (personalised/individualised instruction) XX
- Benefits for peers/collaboration XX
- Acceptance XX
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Subjective Assessment of Visualisation: result(+) Suitable for their intended purpose and largely self-descriptive and understandable
(+) Suitable for getting an overview of the current status in the learning process
(+) Generally easy to understand and not unnecessarily complex
(-) Comparison with the class might be problematic and negatively affect self-worth and collaboration, especially for underachievers
● Better a comparison with one self own prior performance
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GVIS and Moodle
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GVIS in Moodle: evaluationQuestion ++ + 0 -Easy understandable X
Not unnecessarily complex X
Help instructor to tailor to individual needs X
Suitable for getting an overview of the current status X
Visualization does not provide irrelevant information X
Visualization can help learners to reflect on their learning X
Usefulness of comparison with other peers for reflection X
Expected impact on learners performances X
Promote awareness and understanding of learning progress X
Help teacher in better understand the learners needs X
Visualization able to leverage mental workload X
Risk of hindering the collaboration amongst peers X
Additional cognitive effort on learner to understand it X
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GVIS and Adapt2: social visualization
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GVIS and Adapt2: social visualization
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GVIS and Adapt2: evaluationMidTerm Final
WITH GVIS
WITHOUT
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GVIS for User navigation history
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GVIS for Domain profile
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Adaption of visualizations● At two levels: aggregation and building (presentation)
<cond> + <op>(v1 AND ((A > 3) OR !(z)))</op> // FIRST LEVEL | <operands> | <val id="v1">CourseX.Concepts.list</val> | <val id="z">CourseX.Student.count</val> | <val id="A">CourseX.ConceptA.mean.knowledge</val> | </operands> + <true>...</true> + <false> | + <op>(h < t)</op> // SECOND LEVEL CONDITION | | <operands> | | <val id="t">CourseX.ConceptA.mean.knowledge</val> | | <val id="h">CourseX.ConceptA.userH.knowledge</val> | | </operands> | + <true>...</true> | + <false>...</false> +</false> </cond>
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Adaption of visualizations: examplesGraphical format & aggregation
Graphical vs. Textual
Relative vs. Absolute scale
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Results
● Found an impact on user behaviors, enhanced by social aspects
● Simpler and immediate presentation correlate with higher (perceived or measured) effects
● Positive social pressure factor for learners, improved by the peers comparison functionality
– Sense of community – Stimulating healthy competition
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Results
● Tutors/teacher: preferred compact, intuitive, and just-in-time information (didactic interpretation)
– Clearer picture– Able to support identifying performances issues
● Possible cognitive overload: needed further studies.
● Sum-up: consider generally useful and enough flexible to be adapted to different needs and context.
● TinCan API recently solved some of these issues...
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Possible Next Steps● A graphical language to specify the pipeline from data
to didactic meaningful information
● An interface/editor for generating the XML configurations of extractor, aggregator and builder from the graphical language
● A library of freely available basic didactic components (common and useful configurations) for reuse
● a set of adaptation templates could simplify the usage of these capabilities by the Instruction Designers
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Possible Next Steps● More filtering and data reordering procedures
through an easy visual interface to facilitate the exploratory navigation of the information
● A more extensive and structured testing of the tool, both to understand
– its full potentialities and threats – to analyse more in depth the impact that a visualisation
(in all its form: adaptive, social and others) can have on different type of education models, from blended courses to completely online ones or from single course to fully online degree.