This document discusses the technical benefits and privacy risks of using HTML5 APIs for multimodal learning analytics on mobile devices. It describes how APIs that provide access to device sensors and information could provide insights about learning processes but also raise privacy issues if personal data is not properly anonymized and consent is not obtained. The document advocates for balancing these benefits and risks through practices like informed consent, voluntary and anonymous data collection, and ensuring data is only used to benefit students.

1. A MULTIMODAL LEARNING ANALYTICS VIEW OF HTML5 APIs:
TECHNICAL BENEFITS AND PRIVACY RISKS
Pablo Garaizar & Mariluz Guenaga
DeustoTech Learning
University of Deusto
TEEM'2014, Salamanca, Spain

2. Mobile devices allow
learners to...

3. learn outside the school, virtually everywhere (mLearning)

4. communicate and share learning experiences (PLEs)

5. explore and enhance the real world (AR, sensors)

6. provide insights about their learning processes effortlessly (LA)

7. mLearning +
Learning Analytics =
researchers dream!

9. Geolocation & Orientation
Is the learner at school/home? Is she commuting? Where does the learning process take place?
Is the context suitable for learning?

10. Microphone & Camera
Is the learner in a noisy context? Is she looking at the mobile device?

11. Battery & Network Information
Does the lack of battery / cost of the network access disrupt the learning scenario? How?

12. Local Storage
What did the learner do when she was offline? Did it affect learning processes?

13. Drafts: ambient light, temperature, humidity,
atmospheric pressure, etc.
Insights about the context of learning processes

14. mLearning +
Learning Analytics =
users nightmare!

15. LA privacy issues are not only about user-id anonymization
The relation between id's and users could be reconstructed via EDM

16. Students are not mere sources of data
Who takes advantage from your LA study? If the answer is not your students, you are using them.

17. Goal: mutual trust
Customizing content, preventing failure, enhancing learning

18. mLearning +
Learning Analytics =
a difficult balance

19. Informed consent
Voluntary and anonymous participation. Your data will be analyzed as a whole.

20. Fine-grained data-collection via HTML5
Unique id's, event handlers, remote storage via AJAX

21. Thank you

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