A Mobile Sensor Activity for Ad-Hoc Groups

The Mind Lab by Unitec | 2016

A Mobile Sensor Activity for Ad-Hoc Groups

mLearn 2016

David Parsons, Herbert Thomas, Milla Inkila

The Mind Lab by Unitec | 2016The Mind Lab by Unitec | A Mobile Sensor Activity for Ad-Hoc Groups| mLearn 2016

Research Context➔ 32 week part time Postgraduate Certificate

programme in Digital and Collaborative Learning➔ Qualified teachers with at least three years of

teaching experience.➔ Courses cover multiple aspects of pedagogy,

leadership and innovation➔ Supports applied practice in the use of digital tools

for teaching and learning➔ BUT limited mobile learning content


★ Survey data gathered from students around their interests in experiencing mobile learning activities

★ Survey was based on mobile device affordances

Parsons, D., Wishart, J. & Thomas, H. (2016). Exploring Mobile Affordances in the Digital Classroom. In I. Arnedillo-Sanchez & P. Isaias (Eds.) Proceedings of 12th International Conference on Mobile Learning (Mobile Learning 2016). IADIS. pp.43-50.

Background to the Study

http://davidparsons.ac.nz/papers/Exploring%20Mobile%20Affordances.pdf


Mobile Affordances★ Portability (Naismith et al, 2004)★ Data gathering (Orr, 2010) ★ Communication (Liang et al. 2005)★ Interaction (Lai et al., 2007)★ Contextual learning (So, Kim & Looi, 2008)★ Outdoor environments (Tan & So, 2015)


Mobile Affordances★ From the results of the survey, we aimed to

develop a collaborative, outdoor, sensor based activity

★ Design focused on outdoor navigation, gathering and sharing of data, communication, interaction with different devices, and learning related to context

★ Learning outcome: being able to use mobile sensors to measure environmental factors


SensorsNew types of sensor are a significant change to mobile device capability3 generic types of sensor:Motion - some types of measurement, control of

software and other devicesEnvironment - e.g. weather, noise pollution, light and

shade, geography (orientation, elevation)Position - guide learners to different locations


Learning Focus★ Position (GPS) and environmental sensors★ Enable our students to explore the availability,

reliability and potential uses of such sensors on their devices

★ Gather a shared pool of environmental data★ Consider how this data might be analysed


Design Context● Outdoor, sensor based activity (user choice)● BYOD (programme practice)● 30 minute ‘station rotation’ (class context)● Limited setup time (easy install and use)● Collaborative group activity (multiple roles)● No cost (teachers could use in their schools)● Multiple sites (no setup time, 6 locations)

○ Hence GPS, not QR codes


Navigation Based AppsA number of tools support mobile

learning experiences in outdoor environments

None provide integrated sensor supportARIS provides a combination of reliable

GPS performance and powerful tools for mobile activities

Main drawback is the mobile app only runs on iOS


ARIS Web-Based Editor


Example Sensor Tool - Sense-itSense-it was developed as part of the nQuire projecthttp://www.nuire-it.org/#/home

http://www.nuire-it.org/#/home

http://www.nuire-it.org/#/home


ARIS Mobile App


Collaborative, Contextual, Outdoor, Gathering and Visualising Data


Sensor Readings Taken★ Light (lx)★ Sound (dB)★ Temperature (oC)★ Pressure (hPa)★ Humidity (%)★ Compass (relative orientation)★ Elevation (meters above sea level)★ Wind speed (kph)

The Mind Lab by Unitec | 2016The Mind Lab by Unitec | 2016

Shared Google Sheet for DataCollaborative data gathering and analysis


Collated DataSensor Readings Units of measurement Measurement

sRange

Light lux (lx) = lumen per square metre 64 589.2 lx to 1977.7 lx

Sound decibel (dB) 75 from 42 dB to 88.4 dB

Temperature degrees Centigrade (oC) 63 15.2 oC to 30 oC.

Atmospheric pressure hectopascal (1 hPa = 100 Pa) 1 millibar

46 982 hPa to 1022 hPa

Humidity percentage (%) 51 from 50% to 80%.

Compass relative orientation 41 -10 to 298 meters above sea level.

Elevation meters above sea level 36 N/A

Wind speed Kilometers per hour (kph) 18 range 0.3 kph to 38.4 kph.


Outcomes● 42 teams participated across six sites● Able to compare across three locations and across

sites● Increased awareness of sensors and potential for

mobile learning activities● Experience of collaborative BYOD approach for

problem solving and data gathering● Uses of smartphones for crowdsourcing data by

pooling resources for shared analysis

Dr David Parsons | The Mind Lab by Unitec | April 2016Kathryn MacCallum & David Parsons | mLearn 2016

Dr David Parsonshttp://davidparsons.ac.nz/[email protected]

Contact Details

http://davidparsons.ac.nz/

mailto:[email protected]

Education

A Mobile Sensor Activity for Ad-Hoc Groups