=Paper=
{{Paper
|id=Vol-2740/20200173
|storemode=property
|title=Applied Aspects of Instrumental Digital Didactics: M-learning with the Use of Smartphone Sensors
|pdfUrl=https://ceur-ws.org/Vol-2740/20200173.pdf
|volume=Vol-2740
|authors=Iryna Slipukhina,Ihor Chernetckiy,Nataliia Kurylenko,Sergii Mieniailov,Serhii Podlasov
|dblpUrl=https://dblp.org/rec/conf/icteri/SlipukhinaCKMP20
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==Applied Aspects of Instrumental Digital Didactics: M-learning with the Use of Smartphone Sensors==
https://ceur-ws.org/Vol-2740/20200173.pdf
Applied Aspects of Instrumental Digital Didactics:
M-learning with the Use of Smartphone Sensors
Іryna Slipukhina1[0000-0002-9253-8021], Ihor Chernetckiy2[0000-0001-9771-7830],
Nataliia Kurylenko3[0000-0002-1083-3247], Sergii Mieniailov4[0000-0002-4871-311X],
Serhii Podlasov5[0000-0002-3947-4401]
1,2
National Center «Junior Academy of Sciences of Ukraine», Degtyarivska Street 38/44,
04119 Kyiv, Ukraine
3
Kherson State University, University Street 27, 73000 Kherson, Ukraine
4
National Aviation University, Cosmonaut Komarov Avenue 1, 03058 Kyiv, Ukraine
5
National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute», Victory
Avenue 37, 03056 Kyiv, Ukraine
slipukhina2015@gmail.com, manlabkiev@gmail.com,
kurylenko.n.v1976@gmail.com, msm56msm@gmail.com,
s.podlasov@kpi.ua
Abstract. According to the concept of the new Ukrainian school, the educa-
tional process is undergoing intense changes. This is partly due to the active
implementation of a variety of information and communication technologies
and mobile equipment. The article discusses the methods of use of mobile ap-
plications for physics study. Foreign and Ukrainian experience of using infor-
mation-technological and technical capabilities of mobile devices for educa-
tional purposes is analyzed. The classification of mobile applications is pro-
posed; methodological advantages and disadvantages of their use in the educa-
tional process are defined. Mobile applications are an important part of the digi-
tal didactics tools. Features of innovative teaching methods based on the use of
the measuring, computing, and modeling functions of the sensitive elements of
gadgets are revealed. It has been shown that the use of sensors in the teaching
of physics is a kind of instrumental digital didactics. Besides, an example of ap-
plication the Physics Toolbox Suite to perform research on the topic Mechanics
is described in the article.
Keywords: M-learning, Smartphone, Mobile Application, Physics, Instrumen-
tal Digital Didactics.
1 Introduction
Today, the most popular gadget owned by about 93% of students is a smartphone [1],
which, in particular, creates conditions for access to educational programs, scientific
materials, and mobile applications (MA) for field experiments. The proliferation of
BYOD IT policies in the field of education [2, 3, 4] has led to an exponential increase
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
in the number of pedagogical investigations about the use of various gadgets for
teaching. Models of study with the use of smartphones, which have the common name
m-learning, have acquired extraordinary development over the last 5 years. Therefore,
on request for each of the keywords (m-learning, smartphone, mobile device) on the
Research Gate platform you can get about 100 articles, the earliest of which are writ-
ten, apparently, in 2014. However, much less scientific articles and messages can be
found in the context of using smartphone sensors to collect and analyze data during
educational studies in the field of natural sciences.
Special attention in the new standards of general secondary education is paid to the
importance of developing the abilities to process experimental data using digital tools.
The information-digital competence is admitted in the section «Natural education» of
the new standard. The competence includes the ability to use digital resources to ob-
tain new knowledge, search and process information of natural content, transform it
using modern digital technologies and gadgets from one form to another. It is consid-
ered as know-how potential for modern industry.
An important role in research about using a smartphone is played by specialized
mobile applications (MA), which over the years have changed from digital sensors
«Datchiker» [5] to open platforms such as «Phyphox» [6], which process and analyze
experimental data.
Some time ago recording applications had only the function of exporting spread-
sheet data. On the other hand, practice has shown that experimental data analysis is
time-consuming and requires the use of data processing tools (eg Excel, MathLab,
MicroCal Origin, etc.). Furthermore, in students' minds, there is no stable logical
connection between the essence of a physics phenomenon and its mathematical de-
scription.
2 Analysis of Related Research
The use of mobile technologies as a means of teaching physics has been the subject of
research by foreign and Ukrainian scientists. In particular, the importance and influ-
ence of information resources for the modern educational process were investigated
by V. Bykov [7], M. Kyslova et al. [8], I. Salnik [9]; theoretical aspects of mobile
learning were considered in collective methodological recommendations [10] and an
article of N. Rashevskaya [11]; possibilities of mobile technologies using in the edu-
cational process were investigated by A. Babich [12], Y. Modlo et al. [13], J. Kuhn
and P. Vogt [14], V. Sipiy [15], G. Skrypka [16], S. Tereshchuk [17]. They are devot-
ed to the problem of peculiarities of the use of mobile technologies during the study
of the natural and mathematical disciplines. O. Slobodyanyk [1] exploring m-learning
as a pedagogical tool reveals the main advantages (mobility, accessibility, compact-
ness, speed, modernity, personalization of learning, instant feedback, effective use of
time, continuity of the learning process, qualitatively new level of control of the learn-
ing process) and certain risks that may reduce the effectiveness of mobile devices
usage in school practice.
On the other hand, as noted in [1], m-learning technology as part of digital didac-
tics alongside with refining students' motivation to study the subject, shifting the fo-
cus to the learning process interactivity can take out research from the laboratory, turn
the gadget into a means of cognition of the laws of nature.
The use of the BYOD approach as a tool of control of students' knowledge has
been proposed in [18]; it also is possible on the basis of the «Lab4Physics» app for
carrying out frontal physics laboratory works [19].
It should be noted that the research of foreign scientists is more focused on certain
applied aspects of m-learning. J. Traxler [20] demonstrates the ability of mobile de-
vices to extend the range of time frames of information perception. Application of
MA in university education and training of future specialists was investigated by
D. Parsons [21], N. Keskin, and A. Kuzu [22], M. Alqahtani, and H. Mohammad [23]
M. Bice et al. [23]. The problems of implementation and use of mobile devices in the
teaching of physics were investigated by A. Kaps and F. Stallmach [25].
Pierratos and Polatoglou examines the use of «Phyphox» MA to study uniform mo-
tion using an optical stopwatch based on the action of a smartphone photosensor.
There is also attention to the convenience of using smartphones during lectures by
means of projections of the teacher smartphone screen [26].
An original training method for measuring the kinetic friction coefficient using an
accelerometer and inclinometer of a smartphone and MA «Physics Toolbox Sensor
Suite» [27] was proposed by A. Çoban and M. Erol [28].
Interesting experiments focused on overcoming the problems of studying the rela-
tionship between force action and body acceleration using the MA «Physics Toolbox
Sensor Suite» are suggested by the authors [29].
The overall study of the development of MA for processing data from smartphone
sensors (more than 30) as well as some examples of techniques for using the most
popular ones («Physics Toolbox Sensor Suite» and «Phyphox») are presented in [30].
However, a detailed analysis of scientific and pedagogical sources shows that it is
very relevant now to research and systematize the methods of using MA as a practical
tool for educational research conducting during physics study.
3 The Purpose of the Article
In the context of the study of the natural sciences (especially physics), it is important
to create such methods that combine a full-scale (real) experiment with digital analy-
sis and interpretation of the obtained data. For a long time, pedagogical innovations in
this context were focused on the use of digital measuring systems for laboratory pur-
poses. Nowadays, serious instrumental competition has created by smartphones that
contain sets of sensors and related software; they are suitable for full-sized education-
al research, in particular, for distance learning. This aspect, in our opinion, is a key
argument that m-learning in 2020 takes a firm position as an educational technology
on the Plateau of Productivity Trends on eLearning Hype Curve [31]. Therefore, the
aim of the investigation was to analyze the existing types of MA used in the teaching
of physics as well as to demonstrate the technology of determining the priority of MA
suitable for creating effective educational research using field experiments.
4 Results and Discussion
4.1 Classification of MA According to the Didactic Purpose
All mobile devices have software applications that are installed in the device itself or
can be downloaded from the online mobile app stores such as the App Store, Google
Play, Windows Phone Store for free or for money.
The analysis of various sources of technical, technological and pedagogical data
makes it possible to divide all mobile applications into four classes according to the
didactic purpose (Fig. 1).
Fig. 1. Classification of MA according to the didactic purpose
A special feature of these MA-directories is the availability of physics course materi-
al, which is structured into sections and topics. It can help in an easy and accessible
way to understand the essence of physics phenomena.
Applications for knowledge and skills controlling represent a multi-level system of
tasks. They are designed for easy test or survey results processing.
Virtual laboratories are advisable to use for an educational physics experiments,
demonstration of phenomena, structure and properties of real and artificial (technical)
objects, various simulations; the laboratories also have interactive mathematical tools
for experimental data processing.
In our opinion, sensor applications as platforms for obtaining and analytical pro-
cessing of data from smartphone sensors during full-scale (non-virtual) experiments
deserve special attention.
«Physics at school» [32] is Android compliant MA that has 16 physics sections; it
can help to understand the essence of physics phenomena in simple and accessible
form using visual animation clips; it is freely distributed.
«Physics. Formulas» [33] contains reference material, equations for the school
physics course; the material is structured by classes, sections, topics. Although the
MA covers almost the entire physics course, some topics may be missing. This ap-
proach assumes that the student has a basic knowledge of the subject. Thus, it is ad-
visable to use the application rather as a guide when completing homework or stu-
dents' independent work. It is freely distributed.
«Physics» [34] is intended for students with low or intermediate levels of the sub-
ject knowledge. The profile of «Physics» is presented in the form of a short guide
where you can find not only equations and explanations for them but also physics
laws with explanations. In total, the application has five sections each of which has
from four to seven units. Due to its rather brief structure and availability of the mate-
rial, this MA can be used instead of a textbook. The app is also free and available for
devices running Android 4.0.3 and later. Among the drawbacks is a slightly dull inter-
face.
«The Physics virtual lab» [35] has an English language version only. This is a vir-
tual physics lab, where everyone can check the basic laws of physics using touch
control.
Particularly popular among teachers and students is the «Get a class: Smart» MA
[36]. It provides many opportunities for studying physics from 7th to 11th grade. The
program contains a separate section «Preparation for the External independent test-
ing» where for each topic at least 20 multi-level tasks are selected. To make the learn-
ing process more interesting, a character named Smart is in the role of assistant in the
application.
Control and evaluation of students' knowledge and skills is an important part of the
educational process. Usually, the teacher spends a lot of time preparing the tasks and
checking their accomplishment. The Google Forms app [37] allows somebody to
create large-scale surveys of different types of questions. It can be used both for class-
room work and for long-distance surveying. Both options provide students with an-
swers from their own mobile devices. «Kahoot!» [38], «Socrative» [39], and «Plick-
ers» [40] focus on the rapid processing of tests or survey results. This is especially
important when the teacher is using a knowledge-based orientation test.
Note that the types of MA we have described can form a hybrid, integrated digital
platforms. This is especially remarkable on the example of the MA created at Nation-
al Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute». The
Department of Physics has used one of the educational process support systems that
enable students and teachers to work using mobile devices – LMS Moodle (Phys-
ics.zfftt.kpi.ua). The training materials on this platform can be presented in video and
audio formats, in book format similar in structure to print publications, as well as in
the format of lessons scheduled for weeks of work or topics for study. You can also
download and play materials offline. The powerful testing subsystem due to the varie-
ty of test forms not only allows us to accurately evaluate the learning outcomes of
students or pupils but also obtain the consequences of statistical processing of the
results; therefore, it is possible to determine the quality of the proposed tasks. The
quality of learning can also be checked using the resource «Tasks»; it defines the task
for fulfillment, which the student draws in the form of a file and sends it to the teacher
for review. Chat, Forum, Seminar, and others are essential for teamwork skills for-
mation. All these capabilities determine the widespread use of Moodle to support both
traditional and distance learning.
4.2 Features of Smartphone Sensors
Modern smartphones are powerful and sophisticated devices. Smartphones combine
various subsystems such as communication module (calls and Internet, Bluetooth,
Wi-Fi), navigation system (GPS, QZSS and others), sensor set, I / O device (keyboard
display, speakers).
The electronic elements responsible for the implementation of such functionality
are located on a common physical platform (card). The operating system (OS) inte-
grates at the software level all the components to perform the specific tasks of this
device. The performance of modern processors is largely determined by the number
of cores that also determine the number of simultaneous execution threads. Different
smartphone equipment performs the same task (scaling property). Modern
smartphones use UNIX-similar portable operating systems such as Google Android,
Apple iOS.
The implementation of these systems began with the creation of compact comput-
ers, which at the same time contained sufficient hardware (performance and clock
speed of the processor, amount of RAM). Modern budget, mid-range phones offer the
ability to use, for example, analytical MatLab software.
The performance of modern processors is defined by the architecture used and the
number of information flow streams: 1.8 - 2.8 GHz and up to 12GB RAM.
Important physical elements of the smartphone are the sensitive elements that pro-
vide the measurement process.
In general, sensors of modern mobile phones can be divided into three categories:
─ motion sensors (for example, an accelerometer measures acceleration values simul-
taneously along the X, Y, Z axes, determines the position of the device in space,
setting its angle of inclination relative to the Earth's surface; thanks to the accel-
erometer, the gadget responds to overturning, shaking, or shock; gyroscope re-
sponds to the change of rotation angles around the three axes of coordinates with
the tracking of movement relative to three planes simultaneously that allows to de-
termine the orientation of the device in space);
─ position sensors, such as a magnetometer (measures the magnetic field along the X,
Y, and Z axes as well as the magnetic properties of materials), GPS (used to navi-
gate or locate coordinates), proximity sensor (chip to track how close a smartphone
is located to any object);
─ environmental sensors, such as light sensor and barometer.
It should be noted that methods of study using smartphone sensors can be focused
not only on obtaining experimental data but also on the study of the structure and
physics principles of operation of these high-tech devices themselves.
The principle of accelerometer operation, otherwise called the G-sensor, is based
on the inert properties of the bodies during their motion with acceleration: a load of a
certain mass is fixed between the spring and the damper, which are attached to the
frame. When moving with acceleration the force leads to deformation of the spring.
The extent of deformation determines the device acceleration. The damper dampens
the load vibration. G-sensor for smartphone has an electromechanical chip design.
The most widely accelerometers are used in aircraft navigation devices, car DVRs
and speedometers, industrial vibration control systems, information systems for pro-
tecting hard drives, as well as in various gadgets.
Likewise, the proximity sensor is worth considering; it tracks how close a
smartphone is to an object. Its main function, which was first installed on a Nokia
phone, is to turn off the display when lifting the phone to your ear to prevent acci-
dentally tapping the touch screen with your cheek or ear while talking. Also, it saves
battery power during long-term calls as the display consumes a lot of power. In addi-
tion, the proximity sensor can be used for gesture recognition and the camera focus-
ing.
Detection of the distance most often acts on the principle of radar: the smartphone
emits infrared rays, which in the case of any obstacle reflect on it and the reflected
signal is caught by a special receiver. Note that there are already sensors «Elliptic
Labs» that use ultrasound (imitating bats). This does not require major changes in the
design of the smartphone since the ultrasound is emitted and received by the speaker
and the microphone of the device.
4.3 Smartphone hardware and operating parts research
Note that the smartphone capabilities to measure and analyze physics quantities are
determined by two main factors: the presence of sensing elements - sensors as well as
the type and generation of OS.
The OS version also identifies MA that can be installed on a smartphone. In this
context, we conducted a comparative analysis of the main characteristics of the popu-
lar brands of these gadgets, the results of which are summarized in Table 1.
From the data, we can see that in all modern models there are motion and proximity
sensors, which we will use in the future.
The study also found that some types of smartphones can be equipped by sensors
that can measure acceleration, magnetic field, light level, pressure, and temperature;
however, the OS version does not allow installing MA designed for the older genera-
tion operating system. On the base of these conditions, we considered the most multi-
purpose MA focused on different versions of OS.
To find out the types of OS and available sensors as well as to evaluate the skills of
using the MA as research tools we conducted a survey using Google Forms with the
involvement of teachers and students studying at the National Pedagogical Draho-
manov University, Kherson State University and National Aviation University (total
136 persons). One of the questions was to determine the characteristics of
smartphones using the system menu of gadgets (Fig. 2). It was found that most of the
respondents' smartphones use the Android operating system (Fig. 2a).
Table 1. Сomparative analysis of the main characteristics of popular brands of gadgets
Brand Apple Xiaomi Meizu Samsung Samsung CAT
Redmi
iPhone
Model Note 8 X8 A30s Galaxy S4 S60
11
Pro
Apple MediaTek Snapdragon Exynos Exynos 5 Snapdragon
A13 Helio 710; 10нм 7904; Octa 5410; 617; 28нм
Processor
Bionic; G90T; 14нм 28нм
7нм 12нм
RAM 4 GB 6 GB 6 GB 3/4 GB 2 GB 3 GB
Accelerometer + + + + + +
Gyroscope + + + + + +
Light sensor + + + + + +
Proximity
+ + + + + +
sensor
Compass - + + + + +
Face scanner + + + + - -
Fingerprint
- + + + - -
scanner
Hall sensor - - + + - -
Barometer + - - + + -
Unique sen- Thermal
- - - - Thermometer
sors imager
Note that anybody can check which sensors are on the smartphone with the help of
many free downloadable MA such as Sensors MultiTool, Sensor Kinetics, Datchiker
(for Android) and Sensors (for iOS).
The study found that full-length use of MA sensors is possible with OS not lower
than Android 5. The survey also reveals that users of gadgets with Android OS have
new versions of 5 and above (99%); it creates the best opportunities for using MA
(Fig. 2b).
a b
Fig. 2. Distribution of answers to the questions: OS type (a); Android version (b)
The same survey has shown that the vast majority of respondents were aware of the
presence of sensors (Fig. 3a), (especially popular GPS navigation applications) but
did not use them in their educational activities (Fig. 3b) and are eager to learn more
about these opportunities (Fig. 3c).
a b c
Fig. 3. Sensor usage data
The review and testing of the most promising MA sensors that can be installed and
run on the studied smartphones allowed distinguishing the «Physics Toolbox Sensor
Suite», «Phyphox» and the «Science Journal» (Google). Note that additional selection
criteria were free of charge and cross-platform.
These MA automatically detect the presence of sensitive elements and have the
ability to store and transmit data in a format that uses mathematical tables (for exam-
ple, Excel spreadsheets). Note that the use of each of these applications is determined
by the task. For example, the MA «Physics Toolbox Sensor Suite» records and trans-
mits data to other digital devices but the analytical capabilities of this application are
insufficient.
MA «Phyphox» contains ready-made methodological solutions for practical work
and is an open platform with the possibility to add individual techniques. A teacher
can arrange a new experiment with the appropriate processing and presentation of
measurements. In addition, the app lets share the smartphone screen with another
device, for example, a desktop computer with a video projector, and control the
smartphone through a connected device.
The «Science Journal» (Google) MA cannot always identify sensitive elements but
allows creating a full-length study with comments and illustrations and saving it to
Google Drive.
4.4 Methods of Carrying Out Educational Research Using a Smartphone
Let us consider one of the options for doing the lab «Determination of free fall accel-
eration using a simple pendulum» based on the use of MA «Physics Toolbox Sensor
Suite» and Excel spreadsheets. Such a study can be carried out using two smartphone
sensors – a proximity sensor and an accelerometer. In this case, the task can be ex-
panded comparably with its «classical» variant: calculation of the value of free-fall
acceleration by the average value of the pendulum oscillation period measured with
the proximity sensor and comparison it with the accelerometer data.
To achieve this aim, in addition to the smartphone attached to the stand, we use a
bifilar thread pendulum, ruler, and caliper (Fig. 4). The technological map of the work
consists of three main parts: measurement of physics quantities, data analysis, and
presentation.
Measurement of free-fall acceleration. The support is mounted on a horizontal sur-
face and secures the bifilar suspension for the pendulum. Measure the diameter of the
ball of the pendulum (the ball should have a good reflectivity of light color) then hang
up and, using a ruler, measure the shortest distance from the point of the ball attach-
ment to the horizontal bar of the bifilar suspension. In the MA «Physics Toolbox
Suite», select the «Proximeter» and check the proximity sensor response to moving
obstacles (most smartphones perceive obstacles less than 8 cm).
Fig. 4. Installation for measuring T, s using simple pendulum
Place the smartphone on the stand and adjust its position so that the pendulum ball at
the greatest deviation will trigger the proximeter (the angle of deviation should be
small). Select the Pendulum function and enable data recording. Stop recording after
measuring a time of 10 – 15 oscillations and turn the results in a convenient CSV
format. Next, switch to the g-Force Meter accelerometer tab. Place the phone on a
horizontal surface, read and record the free-fall acceleration along the vertical axis
(Fig. 5).
a b
Fig. 5. Screenshot of the «Physics Toolbox Sensor Suite» app with tools:
«Proximeter» (a), «g-Force Meter» (b)
Experiment Data Analysis. Download the oscillations period (T, ms) data file and
open it in Excel. Using the tools of mathematical tables, get the average period, and
express it in seconds. Calculate the length of the pendulum by measuring the shortest
distance from the point of attachment of the ball to the crossbar of the bifilar and add-
ing the radius of the ball and record it in the tables. Using mathematical tables, the
values of ⁄ obtained by the proximity sensor are calculated; then the ac-
celeration values of free fall ⁄ obtained by the accelerometer are recorded
in the tables (Fig. 6). Compare the values obtained and make a conclusion.
Study Development. To improve the accuracy of the experiment, we can repeat the
measurements of the oscillation period at different lengths that the oscillation period
of the pendulum should be within 0,5 s to 1,5 s.
Fig. 6. The experiment data Table Excel
5 Conclusions
Our analysis of modern MA for physics education showed that they can be divided
into four groups: MA-manuals, MA for control and evaluation of knowledge and
skills, MA-virtual laboratories, and MA sensors. These MA can help to reach a new
level of experiment performance not only through access to virtual, remote experi-
ments but also by providing real measuring tools for educational research.
Analysis of smartphones of different generations and operating systems has shown
that nowadays the smartphone can be actively used as a measuring and analytical tool
for the natural sciences study. A comparative analysis of the hardware and operating
parts of teachers’ and students’ smartphones revealed that today most of them use
smartphones running the latest-generation Android OS and contain a large number of
sensors. However, the questionnaire showed the lack of targeted use of MA sensors
for experiments. Thus, the crucial need for the formation of the following teachers’
skills was identified, namely:
─ be able to investigate sensors of MA and form groups of learners (on the basis of
the analysis of available sensitive elements in their smartphones);
─ be able to explain to students at what stage and how to use effectively the capabili-
ties of MA sensors;
─ be able to combine the possibilities of measuring instruments of the smartphone
with other types of MA (Fig. 1).
It is also important to expand the proposed techniques by studying the structure
and physics principles of sensors.
Obviously, the application of smartphones reinforces the competence of teachers in
using MA to solve education tasks. The method of measuring and processing data
with the use of MA sensors of smartphones is one of the key examples of the effec-
tiveness of m-learning. Such technology significantly changes the education process.
It removes the routine stages, rationalizes, and facilitates the process of data analysis
during educational physics experiment. Evidently, it is the best way to complement
traditional approaches to natural sciences study.
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