A Study of User Interaction with Context Aware Notifications from a Moodle Learning Environment
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This document presents a study on user interaction with context-aware notifications in a Moodle learning environment, focusing on mobile device usage among students. The research aims to determine the effectiveness of context in delivering information based on various parameters such as time and location. Results indicate usage patterns are primarily during formal hours, with a significant number of interactions observed in early afternoons.
A Study of User Interaction with Context Aware Notifications from a Moodle Learning Environment
- 1. School of Computing & Communication Systems Lancaster University, UK A Study of User Interaction with Context Aware Notifications from a Moodle Learning Environment Phil Benachour: p.benachour@lancaster.ac.uk Laura Crane: l.crane@lancaster.ac.uk The 13th IEEE International Conference on Advanced Learning Technologies July 15-18, 2013 Beijing, China
- 2. School of Computing & Communication Systems Lancaster University, UK Motivations of Research Previous Research Dimensions of Context Precedence of Context Rationale of Study Architecture of Applications Deployment Results Conclusions
- 3. School of Computing & Communication Systems Lancaster University, UK The research carried out was based on the following motivations: Investigate student interactions with mobile devices Profile student usage of mobile applications which support their organisation of learning Attempt to answer the question of: “Can we utilize context in pervasive learning environments?” Profile student usage of mobile applications which support their organisation of learning
- 4. School of Computing & Communication Systems Lancaster University, UK
- 5. School of Computing & Communication Systems Lancaster University, UK Investigation of RSS as an appropriate information channel for Mobile Learning Comparison of RSS and Twitter based Web 2.0 systems The delivery of information based upon either a time or location mechanism Can we deliver information from a VLE by more than time or location?
- 6. School of Computing & Communication Systems Lancaster University, UK Dey (2001) “Co nte xt is any info rm atio n that can be use d to characte riz e the situatio n o f an e ntity. An e ntity is a pe rso n, place , o r o bje ct that is co nside re d re le vant to the inte ractio n be twe e n a use r and an applicatio n, including the use r and applicatio ns the m se lve s. ”
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- 13. https://www.alohar.com/developer/learnmore.html • Automatically detect the places (including the name and category) that the user visits. • Minimize battery power consumption while gathering data from the mobile device. • Get notifications when a user arrives at or departs from a place. • Automatically get the number of times a user visits a place, and how much time is spent there per visit. • Automatically understand a user’s mobile motion state (e.g. stationary, walking or driving). School of Computing & Communication Systems Lancaster University, UK
- 14. Time Application Location Application Activity Application
- 16. •3 Groups of participants •5 participants in each group for Time, Location & Activity • Deployed onto 15devices • Full term of 10 weeks (70 days) School of Computing & Communication Systems Lancaster University, UK
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- 20. Results – Weeks of the Term School of Computing & Communication Systems Lancaster University, UK
- 21. Results – Weeks of the Term School of Computing & Communication Systems Lancaster University, UK
- 22. Results – Weeks of the Term School of Computing & Communication Systems Lancaster University, UK
- 23. Results – Weeks of the Term School of Computing & Communication Systems Lancaster University, UK
- 24. Results – Weeks of the Term School of Computing & Communication Systems Lancaster University, UK
- 25. Results – Weeks of the Term School of Computing & Communication Systems Lancaster University, UK
- 26. School of Computing & Communication Systems Lancaster University, UK
- 27. • Patterns of Usage • Mainly contained in formal hours and spaces • Early afternoons show peaks of interactions • Time mobile application held the most amount of interactions • Location and Activity very close in numbers
- 28. • Build useful user profiles and patterns of usage • Ensure wireless access & infrastructure is available in situations where interactions take place • Currently in the second term of academic year long study • The groups have been deployed with a different context application • Awaiting results April to May 2013
- 29. Contact Us for more information Email: p.benachour@lancaster.ac.uk l.crane@lancaster.ac.uk Twitter.com/laura_crane Twitter.com/benachourP School of Computing & Communication Systems Lancaster University, UK