What do Context Aware alerts from Virtual Learning Environments tell us about user time & location?

Laura CraneSchool of Computing &

Communication Systemsl.crane@lancaster.ac.uk

@laura_crane

Dr.Phil BenachourSchool of Computing &

Communication Systemsp.benachour@lancaster.ac.uk

@phil_benachour

IADIS M-Learning Conference, Lisbon 2013

Outline of Presentation

Motivations of Research Previous Research Dimensions of Context Precedence of Context Rationale of Study Architecture of Applications Deployment Results Conclusions

Motivations of Research

Investigate student interactions with mobile devices

Profile student usage of mobile applications which support their organisation of learning

Can we utilize context in pervasive learning environments

Precedence of contextual dimensions

Disseminating Information to Students

Previous Work

Investigated RSS as an information channel for mobile learning

Compared RSS to Twitter Delivered RSS based upon a time or

location mechanismCan we deliver RSS based alerts

using more than time and location?

Dimensions of Context

Identity

Location

TimeActivity

Relationship to n.

Dimensions of Context

Precedence of Context Dimensions

Prescendence of Context Dimensions

Time

Activity

Relationships to n.

0.25 0.75 1.25 1.75 2.25 2.75 3.25

Time Location Activity Your Identity

Rela-tion-

ships to n.

Mean Re-sponse

2.996727266666

67

2.850189666666

67

2.926665333333

33

2.39890303

1.979968443333

33

Mean Values from Student Responses

Architecture of Applications

API Integration

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).

Screenshots of ApplicationsTime Application Location Application Activity Application

Screenshots of Applications

Deployment of Context Aware Applications

3 Groups of participants5 participants in each group for

Time, Location & Activity Deployed onto 15 devices Full term of 10 weeks (70 days)

Study Results – Time of Day

Results – Day of the Week

17%

17%

9%18%

29%

8% 3%

Percentage of Interactions over Term by Day of the Week

Monday Tuesday Wednesday ThursdayFriday Saturday Sunday

Results – Weeks of the Term

1 2 3 4 5 6 7 8 9 100

5

10

15

20

25

30

35

40

45

50

Number of Interactions per Week of the Term

TimeLocationActivity

Num

ber

of

Inte

racti

ons

Results – Location Based Results

Conclusions & Future Work

Build useful user profiles and patterns of usage

Ensure wireless access 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