DEVELOPMENT AND EVALUATION OF AN INNOVATIVE
for the datalogger itself and software license of around €100 each or €400 for a site license plus up to a few hundred euros for a specific sensor) but are also installed with their own proprietary software that restricts the teachers’ and students’ full or creative utilization of the systems. Therefore, we have initiated a design-based research (Feng & Hannafin, 2005) project to develop an innovative mobile datalogger for learning science and environmental studies within and outside the classroom environment and applied it in two undergraduate courses for conducting field-based learning (Scanlon, Jones & Waycott, 2005;
Eshach, 2007). Two new Android-based apps have been specifically developed for those field trips.
Evaluation has also been carried out and the findings will be discussed in the subsequent sections.
2. Design of the new system
In essence, we followed the well-known Design-Based Research (DBR) framework (Anderson
& Shattuck, 2012) for the present development of the mobile logger system because DBR is “a systematic but flexible methodology aimed to improve educational practices through iterative analysis, design, development, and implementation, based on collaboration among researchers and practitioners in real-world settings” (Feng and Hannafin, 2005). When DBR is applied in education, it is particularly useful for exploring the possibilities of novel learning and teaching environments. In our present case, development and deployment of the innovative mobile logger can help to link research and development with educational practice (Design-Based Research Collective, 2003). In order to carry out the four key steps of DBR, to wit design, enactment, analysis, and redesign, we iterated two cycles of the DBR processes by implementation of the new technology in two different courses in addition to many rounds of pilot testing, trials, debugging and refinement.
Figure 1. (a) The layout and structure newly developed mobile logger (without the key pad on the lower part of the plastic case) and (b) its instructions for using different sensors to take one-shot or continuous measurement
(a) Layout and structure (b) Instructions:
After powering on the mobile logger for 10s, press any button in the keypad:
1 = temp & humidity
2 = air pressure, altitude and temp 3 = light intensity
4 = IR flame level 5 = gas level
6 = compass direction and magnetic field 7 = IR object and surrounding temp 8 = search logger direction
9 = inclination angles of the logger (static) or 3D acceleration (moving)
* = Help
# = Re-activate the sleeping LCD panel
= continuous measurement mode
= one-shot measurement mode
For the development of the low-cost mobile logger, we adopted the Arduino open-source microcontroller platform (see http://arduino.cc/) by using the Arduino Mega 2560 board plus a sensor shield for connecting to a number of built-in or external sensors (including temperature, humidity, air pressure, light intensity, IR temperature, magnetic field, acceleration, various types of gas and flame sensors etc.). While the board has an USB port for providing 5V power supply and uploading program, the inclusion of a 9V rechargeable battery facilitates field-based learning activities. All the hardware components and internal sensors are enclosed in a transparent plastic case of dimensions: 18 cm x 9 cm x 5 cm with a total weight of 290 grams. Its total cost is only around €20. There are eight ports for connecting to different external sensors. Because of the open-source nature of the Arduino platform, driver libraries for sensors are freely available in the public domain and they have been modified and adapted by the first author to develop the logger’s operating system for controlling the hardware. The logger can receive commands from a key pad mounted on top of the case, remotely from control devices such as IR control pad and Android-based smart phones and tablets, as well as from a computer or tablet
via its USB port. The layout and essential structure of our new mobile logger is depicted in Figure 1 together with a list of commands for using different sensors to take measurement of various physical quantities. The output is directly shown on its built-in LCD display or via Bluetooth to a nearby smart phone or tablet using a new Android-based app, called SESLogger, developed by the first author specifically for the mobile logger (see Figure 2). The most important feature of the app is that it enables instantaneous sharing of the collected data via email, WhatsApp or Google Drive. This allows collaborative learning among students located in different sites during a field trip. The driver library for each type of sensor has been tested to work properly under different situations before it was incorporated into the datalogging program. The entire mobile logger system and its related apps have been tested, debugged and refined/redesigned for many times over several weeks prior to the actual field trip activities. Eight sets of the system have been constructed and demonstrated to several external parties including professionals in the technology field during a training professional development workshop to collect feedback on its applications.
Figure 2.A screen dump of the Android-based app called SES Logger and its setup procedures for connecting to the mobile logger via Bluetooth
Procedures:
1.In the Settings of an Android device, power on its Bluetooth
2.Pair the Bluetooth with your mobile logger (note its address) and input the password: 1234
3.Launch the App called SESLogger3a.
4.Click the “Connect Logger” button and select the right Bluetooth of your logger.
5. Press any button in the IR keypad to send sensor readings to your Android device.
6.If it is in the Continuous mode (i.e. key already pressed), you need to press the OK button to send the current reading to the App.
3. Implementation in field trips
The abovementioned mobile logger was employed in the 3-hour field trip of two different undergraduate courses called A and B in environmental studies (Figure 3). The field trip activity for course A aims to find the most suitable sites for installation of solar panel in a university campus. A total of 22 students participated in course A and they were divided into eight groups, each having a mobile logger connected with a temperature and humidity sensor, a light intensity sensor, an acceleration sensor and an IR temperature sensor plus a tablet computer and a wind speed meter. For course B, the learning objective was to study the urban heat island effect by getting the surface temperature profile in a new town called Tin Shui Wai district, which is located in the north-west part of Hong Kong. The class consisted of 26 students who were divided into seven groups; each having a new mobile logger connected with the abovementioned sensors (without the accelerometer). Location information (including latitude and longitude) was given in another specifically-developed Android app called UHI which used the GPS sensor of the tablet to direct the students to the exact measuring sites. Because those sites were several kilometres apart from each another, synchronous measurements of temperature data were made possible by the mobile logger so that students could share and analyze data via the tablet computer.
After each field trip activity, evaluation of the learning effectiveness and implementation problems were also carried out using a self-developed questionnaire instrument, interview, class observation with video recording and photo-taking as well as lecturers’ reflection. Apart from the personal particulars, the questionnaire instrument is composed of four parts, namely (1) ten items on respondents’ prior learning experience with mobile devices, (2) seven items on respondents’ attitudes and views on mobile learning, (3) seven items on the evaluation of respondents’ e-learning experience in the field trip, and (4) four open-ended questions to collect respondents’ opinions and feedback on the problems of using mobile devices for e-learning, reasons for their most interesting activities, ways for improvement and other comments.
Figure 3. Students using the new mobile logger and related app in a tablet computer to conduct field-based learning in (a) the university campus for course A and (b) a new town for course B.
(a) Students using the mobile logger and a tablet computer to take measurement
(b) Seven locations in a new town for comparing urban heat island effect
4. Findings
From the questionnaire survey of two classes of students in the two field trips, 48 questionnaires were collected with a 100% return rate. For this paper, we focus on findings from the respondents’
evaluation of their learning experience in each of the two field trips as reported in Table 1 in which the Cronbach’s reliability α = 0.94 and the seven items were rated by the 5-point Likert scale (with 1=strongly disagree, 2=agree, 3=neutral, 4=agree and 5=strongly agree). The mean score of every item and its standard deviation (SD) were given in Table 1 while the qualitative data collected from the open-ended questions and interview were summarized in Table 2.
Table 1. Combined results of the respondents’ evaluation of their learning experience in the field trip
Item Statement Mean (SD)
1. The e-learning activities as based on mobile devices are interesting and stimulating to me. 3.79(0.68)
2. I can carry out the e-learning activities as expected. 3.75(0.73)
3. The e-learning approach can induce my learning of the course content more effectively than the traditional one.
3.81(0.70)
4. I like or enjoy the e-learning activities. 3.75(0.91)
5. The e-learning approach can enhance my motivation in learning the course. 3.77(0.75) 6. I prefer to have more e-learning activities in other courses. 3.58(0.92) 7. I will apply similar e-learning approach in my future teaching in schools, if appropriate. 3.71(0.65) Table 2. Consolidated results of the open-ended questions in the survey and students’ comments in the interview
Question Aspect Opinions or feedback
Advantages An interesting new trial
Making e-learning more efficient
Better than traditional approach by simply pressing a few buttons
More interactive and the app could check the student’s progress and correct their misconception
Different from conventional lessons by providing hands-on activities
Doing is better than listening to lecture
Learn more than textbook knowledge
Interesting because of locating in outdoor environment
New approach with data recorded by a tablet Reasons for
most interesting activities
Know how to collect data by using different sensors
The mobile logger is reliable and can provide the results instantaneously
Students could collaborate to visit different places
Can share results with students and lecturer
Buttons to press in the logger Problems on
e-learning
Not easy to learn how to take measurement
A wire was loose or the logger was malfunctioning
Not so familiar with the new
equipment, used it with some difficulty
Difficult to read data in the app and the logger was out of order
Route from Google map disappeared
Tablet cannot show data from logger at the beginning
Machines are troublesome Improvement or
solution to problems
Need a map to show the direction
Improve communication methods by providing instantaneous phone call
Need more user-friendly and simpler interface with better quality
5. Discussion and Conclusions
Apart from a high reliability α>0.9, the seven items in Table 1 are in fact highly correlated and an exploratory factor analysis revealed that all of them fell into a single dimension. Apparently, the findings indicated that the two field trips were quite successful as evaluated by the students concerned.
However, a valid conclusion could only be drawn after the students having been exposed to the new pedagogy for an extended period, as changes in education are often slow processes. The issues and problems identified in Table 2 are in fact congruent with the reflection and observation provided by the relevant course lecturers as follows:
Some groups have not successfully shared the data.
Some minor hardware functions, suggesting for the change of remote controller, or setup some precautionary measure.
Not able to look for GPS in the apps.
Time is not enough at the later part of the lesson for a group discussion
A definite advantage of the mobile logger is its ability to save calibration. The temperature and IR temperature sensor after calibration is very accurate which allow valid between-equipment comparison.
As each group of students gets their chance to collect data, it positively promoted students’ interest to the activity.
The mobile logger is fully customizable and the locational and map function is able to guide students, some of which has minimal map reading skills, to independently arrive at various sampling locations.
One group is unable to arrive at the exact sampling point due to inaccurate pathings generated by google map.
Those findings and comments were taken into due consideration for the subsequent refinement, redesign and improvement of the mobile logger and the apps in accordance with the DBR framework. For example, a key pad for direct input was added on top of the logger’s case and the app was re-designed to have simpler setup procedures, to use GPS to show location and more user-friendly interface after its application in the first course. A help menu was also added in both the mobile logger and the apps.
Acknowledgement
Financial support from the Hong Kong Institute of Education is gratefully acknowledged. Thanks are also due to the research assistants, student helpers and students concerned for their help and participation in this project.
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