Comparing Google Lens Recognition Accuracy with Other Plant
Recognition Apps
Zhanna I. Bilyk
1 a
, Yevhenii B. Shapovalov
1 b
, Viktor B. Shapovalov
1 c
, Anna P. Megalinska
2 d
Sergey O. Zhadan
3 e
, Fabian Andruszkiewicz
4 f
, Agnieszka Dołha
4 g
Pavlo D. Antonenko
5 h
National Center “Junior Academy of Sciences of Ukraine”, 38-44 Degtyarivska Str., Kyiv, 04119, Ukraine
National Dragomanov Pedagogical University, 9 Pyrohova Str., Kyiv, 01601, Ukraine
Individual Entrepreneur “Dyba”, Kiev, 03035, Ukraine
Uniwersytet Opolski, 11a Kopernika pl., Opole, 45-040, Poland
College of Education, University of Florida, PO Box 117042, Gainesville, FL 32611-7044, USA
Mobile Application, STEM-Classes, Augmented Reality, Plant Identification, Google Lens.
Motivation students by providing personalized researches and using IT during classes is relevant in the frame
of STEM approach of education. However, there is a lack of researches devoted to the justification of these
approaches. The aim of the research is justifying of the choosing of AR-plant recognition application choosing
to provide personalized during both, educational process at school and extracurricular activities. All apps
were analyzed and characterized by all processes of interaction of the app with the user. In addition, social
environments of the apps and their usage during extracurricular activities described. The didactics of usage of
AR-recognition apps on biology classes have been described. To provide usability analysis, a survey of experts
on digital education on installation simplicity, level of friendliness of the interface, and correctness of picture
processing was conducted. To evaluate the rationality of usage, apps were analyzed on the accuracy of plants
recognition of the “Dneprovskiy district of Kiev” list. It is proven that Google Lens is most recommended to
use. Taking to account results of the analysis, as alternative Seek or Flora Incognita; however, these apps were
characterized by lower accuracy.
To date, the introduction of a mobile phone into the
educational process is a modern instrument, which
provides achieving better results. The usage of a mo-
bile phone during classes provides visualization of
educational material, involving students in research,
which increases students’ motivation for learning
errez et al., 2015; Kinateder et al., 2014).
Mobile phone applications compared to computer ap-
proaches are characterized by the most promising ad-
vantages including mobility of usage, possibility to
use both internal and external sensors (not commonly
used). The modern educational directions include
personalization and research process which may be
achieved by using mobile phones (Marienko et al.,
2020). However, it was proved that not certain el-
ements of education but a general didactic approach
led to significant effect (Shapovalov et al., 2020b).
The main concept during which the mobile approach
relevant to use is STEM/STEAM/STREAM technol-
ogy. Those methods include using of both, research
(scientific) and engineering methods. To improve the
efficiency of them, use of computer software or mo-
bile applications can be used.
The role of information technology in the learning
process is widely described (Kinateder et al., 2014;
Park, 2011; Clark and Ernst, 2008; Shapovalov et al.,
Bilyk, Z., Shapovalov, Y., Shapovalov, V., Megalinska, A., Zhadan, S., Andruszkiewicz, F., Dołha
Sródka, A. and Antonenko, P.
Comparing Google Lens Recognition Accuracy with Other Plant Recognition Apps.
DOI: 10.5220/0010928000003364
In Proceedings of the 1st Symposium on Advances in Educational Technology (AET 2020) - Volume 2, pages 20-33
ISBN: 978-989-758-558-6
2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
2019; Dziabenko and Budnyk, 2019; Kapici et al.,
2019; Devi and Rav, 2018).
1.1 Types of Software Which Can Be
Used during Education
All software that can be used during the learning pro-
cess in the application of STEM technology can be di-
vided into desktop applications, mobile applications,
and web-oriented technologies. The most perspective
of information and communication technology (ITC)
to use is augmented reality (Mart
errez et al.,
2015; Kinateder et al., 2014; Marienko et al., 2020;
Shapovalov et al., 2018; Agustina et al., 2019), vir-
tual reality (Kinateder et al., 2014; Potkonjak et al.,
2016; Joiner, 2018; Lee and Wong, 2014; Sala, 2014;
Hussein and N
atterdal, 2015; Zantua, 2017; Antoni-
etti et al., 2001; Park, 2011), providing of digital envi-
ronments of education, including computer modeling
(Sarabando et al., 2014; Sahin, 2006; Sifuna, 2016;
Khine, 2018; Clark and Ernst, 2008), providing of
centralized educational networks (Shapovalov et al.,
2019; Stryzhak et al., 2019), mobile-based education
(Modlo et al., 2019), modeling environments (Dzi-
abenko and Budnyk, 2019; Jong et al., 2014; de Jong,
2019; Kapici et al., 2019) providing of education visu-
alization by including YouTube videos (Chorna et al.,
2019), 3D modeling and printing, etc. Comparison
of the most used in the education process software is
presented in table 1.
So, using of mobile phone apps during educa-
tional process is characterized by arrays of advan-
tages such as multi-capabilities, interaction with stu-
dents in their research and visualization on the edu-
cational process. Detailly, mobile apps can be classi-
fied as measuring apps, analyzing apps, image recog-
nition and classification apps, course platforms, VR
and AR-based apps. Based on functions of apps, they
can be deviated into the following categories:
training (course) platforms;
measuring apps;
measuring apps;
video analysis apps;
applications that analyze images and classify
augmented and virtual reality (AR and VR) apps.
Comparison of different mobile apps categories is
shown in table 2.
Apps-identifiers characterized by high potential
to especially in biology classes due possibility to
provide personalized researches. Today, there is a
range of mobile applications that identify wildlife.
Such apps are insects- (for example, Insect iden-
tifier Photo), animals- (Dog Scanner), mushrooms
(Fungus) and plants-identificatory (Flora Incognita,
PlantSnap, Picture This). Some apps provide identifi-
cation of few type nature (both, plants and animals),
for example Seek. In our opinion, most promising are
applications that provide analyzing of the static ob-
jects of the nature (plants and mushrooms). It is due to
lower requirements to the camera. So, they don’t re-
quire high-expensive smartphones and it can be used
widely during the educational process, almost in all
1.2 The Problem of Plants Identification
There are about 27,000 species of flora in Ukraine.
Such biodiversity requires detailed description and
study. Also, natural conditions are constantly chang-
ing, and this causes changes in the species composi-
tion of biocenosis. Both aspects indicate that there is
a problem with plant identification. One of the basic
principles of pedagogy is the principle of a nature ex-
periment. For a modern child, a mobile phone with
Internet access is its natural environment. So, train-
ing should be carried out in an environment, where
the mobile phone should become a full-fledged learn-
ing tool.
Some apps can be installed on the student’s mobile
phone for free to determine the species of plants, their
morphology, the range of distribution, and more.
There are about 10 applications that can be used to
identify the plants. Most common of them are LeafS-
nap, Seek, PlantNet, Flora Incognita, PlantSnap, Pic-
ture This, Florist-X (in Russian), What is a flower
(in Russian), Manager of houseplants (in Russian).
These applications can be divided into three gro plant
identifiers that can analyze photos (Google Lens, for
example, PlanNet, Flora Incognita, PlantSnap, Pic-
ture This. ups, such as:
plant identifiers that can analyze photos (Google
Lens, for example, PlanNet, Flora Incognita,
PlantSnap, Picture This.
plant classification provides the possibility to
identify plants manually. The plant’s classifica-
tory commonly contains pictures and information
about plant kind. But the quality of analysis, in
this case, will depend on the user’s knowledge
and skills which may be hard for both teachers
and students. Their use in biology lessons within
the STEM approach has considerable potential
because it allows to lean the plant morphology.
However, its efficiency depends on the knowledge
of user which may be lacked in case of pupils (for
example, Florist-X and What is a flower).
Comparing Google Lens Recognition Accuracy with Other Plant Recognition Apps
Table 1: Comparison of the most used in the education process software.
Type Web-oriented Mobile applications Desktop applications
Installation Not required From official stores or using
application file
From official stores or installation
General re-
Compatible Internet browser
for all features support
Compatible version of An-
droid, iOS or another mobile
operating system
Compatible version of Win-
dows/macOS/Linux or another
desktop operating system
Facilities Modeling, calculation, visu-
alization, video presenting
Modeling, calculation, visual-
ization, video presenting, AR,
measuring using both internal
and external sensors, photo
analysis, AR, VR
Modeling, calculation, visualiza-
tion, video presenting, using ad-
ditional external sensors
Cross-platforming, no in-
stallation required, low de-
vice space usage
Huge possibilities, mobility
of usage
Stability and variation of applica-
Main disad-
Limited opportunities, may
not start correctly depending
on the platform, lack of indi-
Needs technical updates
which may be expensive
(in two-three years may be
required to buy new phone)
Lack of individualization, the
lesser effect of increasing motiva-
tion during STEM-education
Table 2: Comparison of the most used in the education process software.
Type of application Description Examples
Education platforms These platforms allow the teacher to create
instructional content, communicate with stu-
dents, give them assignments and check them
out automatically
Google Classroom, Prometheus,
Coursera, Microsoft Office 365
for Education
Measuring applications These sensors and their software are already
built into mobile phones
Measure, AR-ruler, Smart Mea-
sure, Lux-meter, Accelerometer,
Magnet Field Meter
Image analysis apps It allows you to measure distances, angles,
perimeters, areas, and calculate with this data.
Image recognizing and
it’s classification appli-
cations that analyze im-
ages and classify them
These mobile applications allow you to iden-
tify species of plants and animals using photos
Identification, Mushroom, Iden-
tify, Shazam, Dog Scanner, Iden-
VR and AR-based apps Allow virtual travel, get a spatial image of the
training material.
Minecraft Earth, IKEA Place,
Ideofit, Lego Hidden Side
plants-care apps that remind water of the plant or
change the soil, which characterized by the lower
potential compared to other types of application
(for example Manager of houseplants).
Taking into account all advantages of plant iden-
tifiers, they were used as an object of the research. It
was proven that Google Lens provides high efficiency
in plant type and species identification (Shapovalov
et al., 2020a). Google lens can provide analysis of
real-life objects in AR and provide additional infor-
mation using neural network algorithms. A few arti-
cles have devoted to Google Lens that proves its ac-
tuality to use (du Plessis, 2015; Syawaldi et al., 2019;
Devi and Rav, 2018). However, some apps-identifiers
may be more specialized and may provide better effi-
ciency of the identification.
Despite the great specialization of other applica-
tions, hypothesize the research is that Google Lens
is the best plant analyzer due to larger database, bet-
ter algorithmic of analyzing and teaching of AI using
Google crowdsource app (500 000+ installation).
Therefore, the purpose of this article is to analyze
existing applications, that can be used in teaching bi-
ology both in the classroom and in the field.
To provide an analysis of the usability of applications
related to plant identification, a survey of experts on
AET 2020 - Symposium on Advances in Educational Technology
digital didactics was provided. The main criteria were
installation simplicity, level of friendliness of the in-
terface, correctness of picture processing. Each crite-
rion was evaluated from 0 to 5 (as higher than better).
Those applications which were characterized by aver-
age evaluation more than 4 were used to further anal-
ysis on quality of identification due taken to account
fact usage of the application during the educational
process, where it will be used by students and teach-
ers, both potentially with not the highest level of ICT
Analysis of quality of identification was provided
by a simplified method compared to our previous re-
search due aim of this paper to obtain a general state
on application plant identification accuracy. To pro-
vide it, 350 images from the list of plants of the “Dne-
provskiy district of Kiev” were taken to provide anal-
ysis. The key from the “Dneprovskiy district of Kiev”
plant classification was used as control. To analyze
the data, tables with names of the plant as lines and as
names of app in columns has created. For each suc-
cessful identification at the intersections “1” has put
and for each unsuccessful “0” has put (see an exam-
ple in table 3).
Table 3: Example of the table of apps analyzing.
The name of the plant
Prunus armeniaca (Apricot) 0 0
Jasione montana 0 1
Ageratum houstonianum 0 1
Chaenomeles japonica 0 0
Amaranthus 1 0
Ambrosia artemisiifolia 0 1
Amorpha fruticosa 0 0
Anemo 1 1
Anemonoides ranunculoides 1 0
Anisanthus tectorum 0 0
Finally, all obtained results, including both, gen-
eral usability evaluation (survey) and results on iden-
tification quality were compared with results on
Google Lens to summarize information and achieve
a general and final state in this field.
3.1 Analysis of the Interaction with
General characteristics of the apps. The apps
databases are significantly differing. The lowest num-
ber of plants in database is included in Flora Incog-
nita (4800 species) and the highest is included in
PlantSnap (585,000 species).
In additions, the apps databases differ by pres-
ence of species based on geographical locations.
For example, Flora Incognita’s database is very lim-
ited geographically and contains only German flora;
Opposite, PlantNet’s data is geographically very
wide and contains flora of Western Europe, USA,
Canada, Central America, Caribbean islands, Ama-
zon, French Polynesia, including, medicinal plants,
invasive plants, weeds.
Login procedure and instruction. For educa-
tion, the login procedure is very important due its
related to the safety of student’s personal data. On
the other hand, login possibility is important to save
achievements, progress, and communications which
motivates student.
Only LeafSnap doesn’t use the additional account
et al (it automatically connected to Google account).
Almost all apps request their own account. Seek re-
quests Inaturalist account (to connect with social net-
work Inaturalist). Apps such as FloraIncognita starts
from account creation page; PictureThis starts from
payment page which may be a disadvantage for using
by pupils. Login process of Flora Incognita, Plant-
Net, PlantSnap, Seek, Picture-This, and PictureThis’s
aggressive advertising is presented in figure 1.
The detailed video instructions are sent to the e-
mail only using PlantSnap app (English voice and
Russian subtitles). Other apps provide instructions in
app. PlantNet does not have Instructions et al. In-
structions of PictureThis’s are very simple. LeafS-
nap’s help is not displayed at the first start; it is lo-
cated in a specific tab. Instructions in Flora Incognita
(a), PlantSnap (b), PictureThis (c) LeafSnap (d) and
Seek (e, f) apps is presented in figure 2.
Data and photo input process. According to
botanical science, the algorithm for determining a
plant includes: establishing the life form of the plant
(tree, bush, grass); then studying the vegetative parts
of the plant (leaves, stem). In addition, generative or-
gans (flower or fruit) analysis is useful to determine a
specific species name. Flora incognita and LeafSnap
are provide addition of different part of the plant’s pic-
tures. The mechanism of processing can differ. For
example, Flora incognita process photos of different
parts of the plant; PlantNet are provides photography
and then choosing of the plant part (analyzing only
one photo).
Geographic location is very important to identify
many species. Picea omorika and Picea abies are very
similar species, but Picea omorika only in Western
Siberia and Eastern Bosnia and Herzegovina. Seek,
Comparing Google Lens Recognition Accuracy with Other Plant Recognition Apps
(a) (b) (c)
(d) (e) (f) (g)
Figure 1: Login process of Flora Incognita (a), PlantNet (b), PlantSnap (c), Seek (d), Picture-This (e), and PictureThis’s
aggressive advertise (f, g).
Flora Incognita, LeafSnap, PlantNet requests geolo-
cation access during the first start. If the algorithm
for determining the plant in the application includes
the definition of life form, photographing the vegeta-
tive and generative organs, as well as the geographical
location of the object, the algorithm has evaluated as
completely correct. If the application of the plant is
based on the analysis of one image in a single click,
the algorithm has evaluated as simple. The interface
of different apps photo and data input is presented in
figure 3.
In general, all apps are free, but PlantSnap lim-
its identifications by 25 plants per account per day.
The programs can request or a single photo of the
plant or photos of different parts of plants (PlantNet).
LeafSnap provides automatic detection of the part of
the plant presented in the photo. In general, all pro-
grams provide the possibility of both, making a real-
life photo or uploading of photo made before.
Identification results. All apps (except PlantNet
and Seek) provides information on the determined
plant. All data on the plant is very structured in all
apps and displayed for example in style: “Genus: Fu-
FloraIncognita, PlantNet, PlantSnap provide inter-
action with other sources. Both, general sources such
as Wikipedia and very specific sources such as Plants
for a Future are used to interact. The most interactive
is Plant net. It provides links to Catalogue of Life,
Plants for a Future and Wikipedia Flora Incognita,
AET 2020 - Symposium on Advances in Educational Technology
(a) (b) (c)
(d) (e) (f)
Figure 2: Instructions in Flora Incognita (a), PlantSnap (b), PictureThis (c) LeafSnap (d) and Seek (e, f) apps.
and in the case of Russian interface provides the link
with site (figure 4). Comparison
results of mobile applications that can analyze plant
photos are presented in table 4.
There some very specific functions during identi-
PictureThis can provide auto diagnose of plant’s
problem on pests and diseases (figure 5);
PlantSnap finds the plant at amazon and provides
an infographic on solar activity, water usage and
activation temperature.
Comparing Google Lens Recognition Accuracy with Other Plant Recognition Apps
(a) (b) (c)
(d) (e) (f)
Figure 3: The interface of photo and data input of Flora Incognita (a), PlantNet (b) PlantSnap (c) PictureThis (d) LeafSnap
Seek (e) apps.
3.2 Infrastructure and Social
Some applications have their own approach to pro-
vide complex research of nature. Those features are
very useful to increase the motivation of students to
research nature. It’s worth noting that the most de-
veloped environment is in Seek used iNaturalist ap-
plication (developed by California Academy of Sci-
ence and National Geographic). Which delivers to
AET 2020 - Symposium on Advances in Educational Technology
(a) (b) (c) (d)
(e) (f) (g)
Figure 4: Data on identified plant Flora Incognita (a), PlantNet (b), PlantSnap (c, d), PictureThis (e), LeafSnap (f), and Seek
students and teachers’ powerful systems of different
Photo sharing and communications. PlantNet
provides the feed of photos to identify, shared by
other users of PlanNet. The information in the feed
is divided into classes “identified”, “unidentified” and
All”-filter (displays both, identified and unidenti-
fied). The items in feed with an “identified” filter will
display already identified plants by users and “uniden-
tified” will display not-identified pictures updated by
users. The most perspective is using “unidentified”
feed which may be useful in a few cases:
To help with identifying of the plant
To train own identification skills by providing
identification of pictures of others
To share thoughts in the field of botanic, commu-
nicate with other researchers, and to provide so-
cial science networking.
Personal journals. The first instrument to mo-
tivate is personal journals of observation and iden-
tification. This is a very common feature. For ex-
ample, Flora Incognita has tab “My observations”;
PictureThis has “My garden”; Leaf snap has “My
plants”. However, some apps do not provide explic-
itly personal journal. For example, PlantNet saves just
the history of observations.
Projects and social. Seek provides collabora-
tion by providing projects. Users can find and chose
projects they like and join be involved in them. It’s
worth note, that the app is very widespread and there
Comparing Google Lens Recognition Accuracy with Other Plant Recognition Apps
Table 4: Comparison results of mobile applications that can analyze plant photos.
App title Plants amount
in database
Correctness of the analyzing pro-
Links with other information services
4800 (only
The analysis algorithm is correct Links to Catalogue of Life, Plants for a Fu-
ture and Wikipedia. Flora Incognita with
Russian interface provides links to the Rus-
sian site
PlantNet 21920 The analysis algorithm is com-
pletely correct
Only the name of the plant. Includes ele-
ments of social networks (by sharing plants
student found and subscriptions). It con-
tains links to Wikipedia.
PlantSnap 585000 The analysis algorithm is simple. Has own description. Provides searching
on Amazon to buy it.
10000 The analysis algorithm is simple Provides very structured information (in-
cluding type, lifespan, height, flower diam-
eter), care aspects, usage of the plant.
LeafSnap No data The analysis algorithm is correct.
Determining includes evaluation of
health state (healthy and unhealthy).
Contains links to Wikipedia, Pl@ntUse,
Global Biodiversity Information Facility.
Seek No data The analysis algorithm is the sim-
plest. The achieves are given for
users after some successful identifi-
Has no detailed description, but propose
“species nearby in this taxon”.
are even projects in Ukraine. The interfaces of project
selection and concrete project interface are presented
in figure 6a.
Achievements. The Seek-identification app pro-
vides a significantly different approach to increase
students’ motivation. It provides achieves for each
plant students found which motivates students to get
new and new researches from time to time. The ef-
fect of achievement affects the brain as exaltation and
people want it again and again. This is used in games
to motivate students to play again. In the case of Seek,
some factors will motivate students to research nature.
The iNaturalist propose observing of plant and an-
imal kinds student can find nearby. This feature is
activated by the “Exploring All” function and choos-
ing “My location”. Also, based on location students
can use Missions which provides quests for students
to do, for example, to find “Rock Pigeon”. So, stu-
dents can observe nature nearby in general to study
it and the program will stimulate students by com-
pleting the missions. The Exploring All and Missions
functions are presented in figure 6b,c.
3.3 Analysis of Application
Identification Accuracy
PlantNet is the easiest app to install. Also, pretty easy
to install are Google Lens, LeafSnap and Flora Incog-
nita. Apps Google Lens, LeafSnap, Flora Incognita,
Seek to have the simplest interface. Google Lens,
PlantSnap, PictureThis, and PlantNet are character-
ized by the most uncomfortable process of identifica-
tion which can be complicated for teachers. Results of
detailed analyses on plant identification applications
are presented in figure 7.
In general, Google Lens, LeafSnap, Flora Incog-
nita, PlanNet, Seek has evaluated as most usable and
they were detailly researched. However, the total
number of points each of the applications received is
presented in figure 8.
The most accurate apps are Google Lens with
92.6% of correctness of the identification. Flora
Incognita provides correct identification of 71% of
cases; PlantNet – in 55%; Seek – in 76%. In our pre-
vious work, we demonstrated that Google Lens does
not differentiate native species from Ukraine. It seems
that Seek, PlantNet and Google Lens mostly use data
of American and European kinds of plants to training
the neural network and they have missed under identi-
fication of specific Ukrainian’s kinds of plants. Flora
Incognita was characterized by significantly different
specific of analyses; it may be due to Flora Incognita
uses a Russian database (similar to the Ukrainian re-
gion). This may explain a higher percent of identifica-
tion accuracy of Flora Incognita, compared to Plant-
Net. Results on analysis quality of apps which are
identified plants are presented in figure 9.
From the point of view of botanical science, the
AET 2020 - Symposium on Advances in Educational Technology
Figure 5: PictureThis’ plant’s auto diagnose on pests and diseases function: photo input interface (a) and the result of the
analysis (b).
possibility to add different parts the plants and choos-
ing of the plant’s type and geolocation access must af-
fect the identification process correctness. However,
taking to account the results of the experiment, appli-
cations with a simple algorithm definition (analysis
of a single image) more accurately identify plants. It
seems that internal algorithms of identification (due
to higher statistical characteristics of neural network)
and fullness of database is more important than cor-
rectness of data input or taking to account of geoloca-
So, Google Lens is characterized by the highest
quality of analysis which may be due to the better
recognition algorithm and the most trained neural net-
work. However, it still may be relevant to use other
applications in case it will be characterized by sig-
nificantly higher parameters of use. To evaluate this,
a similar survey as used for other plant identification
applications was used for Google Lens. Google Lens
has the most intuitive interface, is the most easily
loaded, and gives the most accurate definition result
and therefore is characterized by the highest general
evaluation with 4.6 points of interface analysis. This
is significantly higher than marks for other apps.
Therefore, Google Lens is the most recommended
app to use. Talking to account, results of usability
analysis, and quality of analysis, for those students
and teachers who do not like Google Lens app, it is
Comparing Google Lens Recognition Accuracy with Other Plant Recognition Apps
(a) (b) (c)
Figure 6: The Exploring All (a), Missions functions (b) and concrete project (c) functions.
possible to use Seek or Flora Incognita, but Plant-
Net can’t be recommended to use due to low accuracy
which may provide up to half of incorrect analyzing
3.4 Advantages of using Mobile Phone
Application in the Educational
In our opinion, the use of mobile applications that
identify plants during the education process has the
following functions:
1. Creating a learning environment. Even in the
works of the classic of pedagogical thought
M. Montessori, it was proved that the environ-
ment should develop the child. Mobile applica-
tions to a greater or lesser extent create such an
environment. For example, Seek stimulates the
child to search for new plant objects, manages the
process of photographing plants, provides links to
additional information about the plant, creates its
own synopsis for the child, rewards the child with
2. Cognitive function. Only 70 hours are allotted to
study all plants in Ukrainian schools. There is
very little time. Mobile applications allow stu-
dents to learn about the diversity of the plant
3. Training function. Due to the limited number of
teaching hours, the teacher cannot focus enough
on the developed practical skills, such as deter-
mining the life form of plants (bush, grass, tree,
vine). Such skills are developed as a result of re-
peated training. Some applications, such as Flora
Incognita, request a definition of life form. And
this contributes to the formation of this skill.
The use of mobile applications promotes the de-
velopment of students with the following competen-
1. Competencies in the field of natural sciences, en-
gineering, and technology (Gil-Quintana et al.,
2020). When using mobile applications, students
gain experience in the study of nature.
2. Environmental competence (Morkun et al., 2018).
Some applications, such as Seek, explain the rules
of behavior in nature.
3. Information and communication competence
(Kuzminska et al., 2019). The use of mobile ap-
plications allows students to demonstrate the safe
use of technology for learning.
4. Lifelong learning competence (van den Broeck
et al., 2020). The use of mobile applications
teaches students to find opportunities for learning
and self-development throughout life.
AET 2020 - Symposium on Advances in Educational Technology
Figure 7: Results of detailed results on plants identification applications usability analysis.
Figure 8: Integrated results on the usability of plants identification applications.
Figure 9: Results on analysis quality of apps which is iden-
tified plants.
Apps related to plant identifications can be referred to
as those which can analyze photos, devoted to manual
identification, and apps devoted to plant care moni-
toring. LeafSnap, Flora Incognita, PlanNet, Seek are
the most usable plant identifiers apps during STEM-
based classes.
It is shown that Google Lens characterized by the
highest mark of usability compare to PlantNet, Flora
Incognita, and Seek. In addition Google Lens has
the highest accuracy of identification rate (92.6%).
Seek and Flora Incognita has significantly lower accu-
racy of identification rate 76% and 71%, respectively.
PlantNet provides correct identification only in 55%
of case which is significantly and can’t be used dur-
ing education at all. Therefore, Google Lens is the
most recommended app to use during biology classes.
Comparing Google Lens Recognition Accuracy with Other Plant Recognition Apps
However, for those students and teachers who do not
like the Google Lens app, it is possible to use Seek or
Flora Incognita.
However, Google Lens provides only identifica-
tion without ecosystem. The Seek mobile application
can be used as a complex learning environment. It in-
cludes communications between naturalists, achieve-
ment system for motivation of the students and other
In general, it is proven that using of AR-based
identification programs characterized by positive ef-
fect on education process and provides development
of the competencies.
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Comparing Google Lens Recognition Accuracy with Other Plant Recognition Apps