Features of Using Mobile Applications to Identify Plants and Google

Lens During the Learning Process

Zhanna I. Bilyk

1 a

, Yevhenii B. Shapovalov

1 b

, Viktor B. Shapovalov

1 c

, Pavlo D. Antonenko

2 d

Sergey O. Zhadan

3 e

, Daniil Lytovchenko

4 f

and Anna P. Megalinska

5 g

The National Center “Junior Academy of Sciences of Ukraine”, 38-44 Degtyarivska Str., Kyiv, 04119, Ukraine

College of Education, University of Florida, PO Box 117042, Gainesville, FL 32611-7044, U.S.A.

Individual Entrepreneur “Dyba”, Kiev, 03035, Ukraine

Taras Shevchenko National University of Kyiv, 60 Volodymyrska Str, Kyiv, 01033, Ukraine

National Pedagogical Dragomanov University, 9 Pyrohova Str., Kyiv, 01601, Ukraine

ﬂ

Keywords:

Mobile Application, STEM, Augmented Reality, Plant Identiﬁcation, Google Lens.

Abstract:

Students’ motivation by providing personalized studies and using IT during classes is relevant in STEM.

However, there is a lack of research devoted to justifying these approaches. The research aims to justify

the choice of AR-plant recognition application, choosing to provide personalized experience during both the

educational process at school and extracurricular activities. All apps have been analyzed and characterized by

all interaction processes of the app with the user. In addition, the social environments of the apps and their

usage during extracurricular activities are described. The didactics of the usage of AR-recognition apps in

biology classes have been described. To provide usability analysis, a survey of experts on digital didactics

was conducted to evaluate such criteria as installation simplicity, level of friendliness of the interface, and

accuracy of picture processing. To evaluate the rationality of usage, apps were analyzed on the accuracy

of plants recognition of the “Dneprovskiy district in Kyiv” list. It is proven that Google Lens is the most

recommended app to use for these purposes. Considering the analysis results, Seek or Flora Incognita are

both valid alternative options. However, these apps were characterized by lower accuracy. The use of mobile

applications to identify plants is especially relevant for distance learning.

1 INTRODUCTION

The implementation of a mobile phone as a mod-

ern instrument into educational process has proven to

achieve impressive results. Mobile phone usage dur-

ing classes provides visualization of educational ma-

terial, thus involving students in research and increas-

ing their motivation for learning (Mart

ın-Guti

errez

et al., 2015; Kinateder et al., 2014). Compared to

computer approaches, mobile phone applications are

characterized by the most promising advantages, in-

https://orcid.org/0000-0002-2092-5241

https://orcid.org/0000-0003-3732-9486

https://orcid.org/0000-0001-6315-649X

https://orcid.org/0000-0001-8565-123X

https://orcid.org/0000-0002-7493-2180

https://orcid.org/0000-0002-1328-7077

https://orcid.org/0000-0001-8662-8584

cluding portability and the possibility to use both

internal and external sensors (not commonly used).

The modern educational directions include person-

alization and the research process, which may be

achieved through the use of mobile phones (Marienko

et al., 2020). However, it was proved that a gen-

eral didactic approach led to a signiﬁcant effect rather

than using the device (mobile phone) for some sep-

arate aspects of education (Amelina et al., 2022).

STEM/STEAM/STREAM technologies appear to be

the most promising and relevant for the use of mobile

apps.

1.1 Types of Software That Can Be

Used During Education

All software that can be used during the learning pro-

cess in the application of STEM can be divided into

688

Bilyk, Z., Shapovalov, Y., Shapovalov, V., Antonenko, P., Zhadan, S., Lytovchenko, D. and Megalinska, A.

Features of Using Mobile Applications to Identify Plants and Google Lens During the Learning Process.

DOI: 10.5220/0012067000003431

In Proceedings of the 2nd Myroslav I. Zhaldak Symposium on Advances in Educational Technology (AET 2021), pages 688-705

ISBN: 978-989-758-662-0

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

desktop applications, mobile applications, and web-

oriented technologies. The most perspective of infor-

mation and communication technology (ITC) in edu-

cation are augmented reality (Mart

ın-Guti

errez et al.,

2015; Marienko et al., 2020; Modlo et al., 2019a;

Agustina et al., 2019; Nechypurenko et al., 2019,

2023; Kramarenko et al., 2019; Oleksiuk and Olek-

siuk, 2022; Rashevska et al., 2020), virtual reality (Ki-

nateder et al., 2014; Potkonjak et al., 2016; Joiner,

2018; Lee and Wong, 2014; Sala, 2014; Hussein and

atterdal, 2015; Zantua, 2017; Antonietti et al., 2001;

Park, 2014), providing digital environments of educa-

tion, including computer modelling (Sarabando et al.,

2014; Sahin, 2006; Sifuna et al., 2016; Khine, 2018;

Clark and Ernst, 2008), providing of ontological edu-

cational networks (Tarasenko et al., 2021; Shapovalov

et al., 2021; Stryzhak et al., 2019), mobile-based ed-

ucation (Modlo et al., 2019b,a; Nechypurenko et al.,

2023), modelling environments (Dziabenko and Bud-

nyk, 2019; de Jong et al., 2014; de Jong, 2019; Kapici

et al., 2019), providing of education visualization by

including YouTube videos (Chorna et al., 2019), 3D

modelling, and printing, smart physiological tools

(Shapovalov et al., 2022) etc. A comparison of the

most used software in the education process is pre-

sented in table 1.

Using mobile phone apps during the educational

process is characterized by advantages such as multi-

capabilities, interaction with students in their re-

search, and visualization of the educational process.

Mobile apps can be classiﬁed as measuring apps,

analyzing apps, image recognition, and classiﬁca-

tion apps, course platforms, and VR/AR-based apps.

Based on the functions of apps, they can be divided

into the following categories:

• training (course) platforms;

• measuring apps;

• video analysis apps;

• applications that analyze images and classify

them;

• augmented and virtual reality (AR and VR) apps.

A comparison of different mobile apps categories

is shown in table 2.

Apps-identiﬁers are characterized by the high po-

tential, especially in biology classes, due to their ca-

pability to provide personalized studies. Nowadays,

there is an entire range of mobile applications for

identifying wildlife. Such apps may help identify

insects (for example, Insect identiﬁer Photo), ani-

mals (Dog Scanner), mushrooms (Fungus) and plants

(Flora Incognita, PlantSnap, Picture This). In addi-

tion, some apps (such as Seek) provide identiﬁca-

tion of a few types of nature (both plants and ani-

mals). Nonetheless, in our opinion, the most promis-

ing applications provide analysis of the static objects

of nature (plants and mushrooms). It is dependent on

lower requirements for image quality, meaning that

one does not require a high-end expensive smartphone

to use the app effectively. Therefore, Inclusion of

most students in most schools is not guaranteed.

1.2 The Problem of Plants Identiﬁcation

There are about 27,000 species of ﬂora in Ukraine.

Such biodiversity requires detailed description and

study. Natural conditions are constantly changing,

causing changes in the species composition of bio-

cenosis. Both aspects indicate a problem with plant

identiﬁcation. One of the basic principles of peda-

gogy is the principle of a natural experiment. For a

modern child, a mobile phone with Internet access

is a natural environment. So, training should be car-

ried out within the environment where a mobile phone

should become a full-ﬂedged learning tool.

Some apps can be installed on a student’s mobile

phone free of charge while still allowing to determine

the species of plants, their morphology, the range of

distribution, and more.

There are about ten applications that can be used

to identify 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

groups:

1) plant identiﬁers that can analyze photos (for ex-

ample, Google Lens, PlanNet, Flora Incognita,

PlantSnap, Picture This);

2) plant identiﬁers with the function of classiﬁca-

tion allow to identify plants manually. The plant’s

classiﬁcatory commonly contains pictures and in-

formation about plant species. However, the qual-

ity of analysis, in this case, will depend on the

user’s knowledge and skills, which may cause dif-

ﬁculties for both teachers and students. Their use

in biology lessons within the STEM approach has

considerable potential because it allows them to

learn plant morphology. However, its efﬁciency

depends on the user’s knowledge, which may be

lacking in the case of pupils (for example, Florist-

X and What is a ﬂower);

3) plants-care apps that remind to water a plant or

change the soil, characterized by a lower potential

Features of Using Mobile Applications to Identify Plants and Google Lens During the Learning Process

689

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 appli-

cation ﬁle

From ofﬁcial stores or installa-

tion ﬁles

General re-

quirements

Compatible Internet

browser for all features

support

A compatible version of Android,

iOS or another mobile operating

system

A compatible version of Win-

dows / macOS /Linux or another

desktop operating system

Facilities Modelling, calculation,

visualization, video pre-

senting

Modelling, calculation, visualiza-

tion, video presenting, AR, measur-

ing with both internal and external

sensors, photo analysis, AR, VR

Modelling, calculation, visual-

ization, video presenting, using

additional external sensors

Main ad-

vantages

Cross-platforming, no in-

stallation required, low

device space usage

Huge possibilities, portability Stability and variation of appli-

cations

Main dis-

advantages

Limited opportunities,

may not start correctly de-

pending on the platform,

lack of individualization

Needs technical updates, which

may be expensive (a new phone

purchase may be required each two

or three years)

Lack of individualization, the

lesser effect of increasing moti-

vation during STEM-education

Table 2: Comparison of different mobile apps categories.

Type of application Description Examples

Education platforms These platforms allow the teacher to

create instructional content, communi-

cate with students, give them assign-

ments and check them out automatically

Google Classroom, Prometheus,

Coursera, Microsoft Ofﬁce 365 for

Education

Measuring applications These sensors and their software are al-

ready 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, an-

gles, perimeters, areas, and calculate

with this data.

ImageMeter

Image recognizing and it’s clas-

siﬁcation applications that ana-

lyze images and classify them

These mobile applications allow you to

identify species of plants and animals

using photos

Identiﬁcation, Mushroom, Iden-

tify, Shazam, Dog Scanner, Iden-

tify

VR and AR-based apps Allow virtual travel, get a spatial image

of the training material.

Minecraft Earth, IKEA Place, Ide-

oﬁt, Lego Hidden Side

than other application types (for example, Man-

ager of houseplants).

Considering all advantages of plant identiﬁers,

they were used as an object of the research. It was

proven that Google Lens provides high efﬁciency in

plant type and species identiﬁcation (Bilyk et al.,

2022). Furthermore, Google Lens can analyze real-

life objects in AR and provide additional informa-

tion using neural network algorithms. A few articles

have been devoted to Google Lens that prove its rel-

evancy and usability (du Plessis, 2015; Bilyk et al.,

2020; Devi and Gaurav, 2018). However, some apps-

identiﬁers may be more specialized and may provide

better identiﬁcation efﬁciency.

Despite the greater specialization of other ap-

plications, the research hypothesis is that Google

Lens is the best plant analyzer because it may use a

more extensive database, better algorithms or anal-

ysis and teaching AI using the Google crowdsource

app (500 000+ installation).

Therefore, this article aims to analyze existing ap-

plications that can be used in teaching biology both in

the classroom and in the ﬁeld.

1.3 New Features in Google Lens

Interest in learning Google Lens capabilities usage for

the learning process is growing. This is due to the de-

velopment of both the technology itself and the ped-

agogical and psychological aspects of its application.

For example, Google Lens can be installed on a desk-

top computer via Chrome. In this version, Google

AET 2021 - Myroslav I. Zhaldak Symposium on Advances in Educational Technology

690

Lens allows you to not only search for similar images,

but also to perform operations with text on images.

Google Lens announces the emergence of a

new search algorithm Multitasking Uniﬁed Model

(MUM). At the presentation, they demonstrated how

it works by searching for “Socks with this pattern”.

As a result – a list of stores selling socks with a simi-

lar pattern was shown. There is another way to use it

for other purposes, for example looking up how to ﬁx

a speed shifter on a bicycle. Simply by pointing the

lens on the object and asking “How to ﬁx it”, MUM

would show a video with the necessary timecode.

At a ﬁrst glance, the above example with the sock

pattern resembles a successful marketing move, but it

also involves the moment of ﬁnding information and

clarifying its proper use. For example, bicycle repair

is a classic STEM project. There is a problem state-

ment and its practical solution by way of the engineer-

ing method.

An interesting aspect of Google Lens use is fa-

cial recognition of employees working for large enter-

prises. The developers of Google Lens are also work-

ing hard to implement the translation feature. Pho-

tographing text in one language provides automatic

translation into another. Such technology would be

especially relevant for teaching deaf and dumb stu-

dents.

Yue’s work has shown that the use of Google Lens

signiﬁcantly expands the vocabulary among English

for lower primary pupils (Sergeeva et al., 2021) ex-

amined the possibility of utilizing Google Lens in

teaching foreign language. These studies reported

that Google Lens can be applied in foreign language

classes as it contributed to the optimization of the edu-

cational process by ﬁlling it with information, involv-

ing students, and successfully inﬂuencing the process

of development.

Psychological and pedagogical aspects of the

Google Lens application are currently being actively

studied. The study results (Nguyen, 2021) showed

that performance expectancy, utilitarian value, and so-

cial inﬂuence had a statistically signiﬁcant and posi-

tive impact on behavioral intention, but the perceived

risk had a statistically signiﬁcant and negative effect

on behavioral intention.

Nowadays, some aspects of Google Lens use in

marketing, in learning foreign languages with stu-

dents of all ages, and in biology lessons are explored.

However, the effectiveness of Google Lens in recog-

nizing living objects requires further study and com-

parison with other mobile applications.

2 ANALYSIS METHODS

To analyze the plant identiﬁcation apps’ usability, a

survey of experts on digital didactics was provided.

The main criteria were installation simplicity, level of

friendliness of the interface, and accuracy of picture

processing. Each criterion was evaluated from 0 to 5

(the higher the better). Those applications which were

characterized by an average evaluation grade of more

than four were used to further analyze quality of iden-

tiﬁcation taking into account the condition that the ap-

plication may be used by both students and teachers

with a low level of ICT competence.

Analysis of quality of identiﬁcation was provided

by a simpliﬁed method compared to our previous re-

search (Sala, 2014) due to the aim of this paper to

obtain a general state on application plant identiﬁ-

cation accuracy. 350 images from the list of plants

of the catalog “Dneprovskiy district of Kyiv” were

taken to analyse the identiﬁcation accuracy. The key

from the “Dneprovskiy district of Kyiv” plant classi-

ﬁcation was used as a control. The vast majority of

photographs of plants on this list contain distinct veg-

etative organs (shoots with stems, leaves, buds) and

generative organs (ﬂowers or fruits). The presence

of the latter is necessary to accurately determine the

species.

To analyze the data, tables with names of the plant

as lines and as names of the app in columns have been

created. Each successful identiﬁcation was evaluated

as 1 and unsuccessful as 0 (see an example in table 3).

Table 3: Example of the table of apps analyzing.

The name of the plant

Flora Incognita

PlantNet

Seek

LeafSnap

Picture This

Prunus armeniaca (Apricot) 0 0 0 0 1

Jasione montana 0 1 1 1 1

Ageratum houstonianum 0 1 0 1 1

Chaenomeles japonica 0 0 0 0 0

Amaranthus 1 0 1 1 0

Ambrosia artemisiifolia 0 1 0 1 1

Amorpha fruticosa 0 0 1 1 0

Anemone sylvestris 1 1 1 1 0

Anemonoides ranunculoides 1 0 0 0 1

Anisanthus tectorum 0 0 1 0 0

Finally, all obtained results, including general us-

ability evaluation (survey) and results on identiﬁca-

tion quality, were compared with results on Google

Lens to summarize information.

Features of Using Mobile Applications to Identify Plants and Google Lens During the Learning Process

691

3 RESULTS

3.1 Analysis of the Interaction with

Apps

General characteristics of the apps. The apps’

databases are signiﬁcantly differing. For example,

the lowest number of plants in the database is in

Flora Incognita (4800 species), and the highest is in

PlantSnap (585,000 species).

In addition, the app’s databases differ in the

presence of species based on geographical loca-

tions. For example, Flora Incognita’s database is

very limited geographically and contains only Ger-

man ﬂora; Conversely, PlantNet’s data is geographi-

cally vast and contains ﬂora of Western Europe, USA,

Canada, Central America, Caribbean islands, Ama-

zon, French Polynesia, including, medicinal plants,

invasive plants, weeds.

the login procedure is signiﬁcant because it is related

to the safety of students’ personal data. On the other

hand, login possibility is vital to save achievements,

progress, and communications which motivates the

student.

Only LeafSnap does not use the additional ac-

count at all (it automatically connected to the Google

account). However, almost all apps request their

own account. For example, Seek requests Inatural-

ist account (to connect with Inaturalist social net-

work). Apps such as FloraIncognita start with the ac-

count creation page; PictureThis starts from the page

with subscription plans, which may be a disadvan-

tage when used by students. The login process into

Flora Incognita, PlantNet, PlantSnap, Seek, Picture-

This, and PictureThis’s is accompanied by aggressive

advertising illustrated in ﬁgure 1.

The feature of detailed video instructions is avail-

able via e-mail only in the PlantSnap app (English au-

dio and Russian subtitles available). Other apps pro-

vide instructions within themselves. PlantNet does

not feature any instructions whatsoever. Instructions

of PictureThis are very simple. LeafSnap’s help sec-

tion is not displayed with the ﬁrst launch conﬁned to a

speciﬁc tab. Instructions presentation in Flora Incog-

nita (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); studying the vegetative parts of

the plant (leaves, stem). In addition, generative or-

gans (ﬂower or fruit) analysis is helpful to determine

a speciﬁc species name. Flora incognita and LeafS-

nap request the addition of different parts of the given

plant’s pictures. The mechanism of processing can

differ. For example, Flora incognita processes photos

of different parts of the plant; PlantNet provides pho-

tography and then choice of the plant part (analysis of

only one photo)

Geographic location is signiﬁcant to identify

many species. For example, Picea omorika and Picea

abies are very similar species, but Picea omorika is

only found in Western Siberia and Eastern Bosnia

and Herzegovina. Seek, Flora Incognita, LeafSnap,

PlantNet request geolocation access during the ﬁrst

launch. If the algorithm for determining the plant in

the application includes the deﬁnition of life form,

photographing the vegetative and generative organs,

and the geographical location of the object, such al-

gorithm has been evaluated as entirely correct. If the

application of the plant is based on the analysis of one

image in a single click, the algorithm has been evalu-

ated as simple. The interface of different apps’ photo

and data input is presented in ﬁgure 3.

apps are free, but PlantSnap limits the quantity

of identiﬁcations by 25 plants per day per account.

The mobile application PictureThis has the biggest

amount of advertising. This mobile application also

allows you to identify only 5 plants per day for free.

Therefore, the use of PictureThis during the learning

process is quite limited. The programs can request a

single photo of the plant or photos of different parts of

plants (PlantNet). In addition, LeafSnap provides au-

tomatic detection of the part of the plant presented in

the photo. In general, all programs allow both making

a real-life photo or uploading the photo made before.

Identiﬁcation results. All apps (except PlantNet

and Seek) provide information on the determined

plant. All data on the plant is very structured in

all apps and displayed, for example, in the manner:

“Genus: Fucus”.

FloraIncognita, PlantNet, PlantSnap provide inter-

action with other sources. Both public sources such

as Wikipedia and more specialized sources, such as

Plants for a Future, are used for interaction. The most

interactive app among them is Plant net. It provides

links to Catalogue of Life, Plants for a Future, and

Wikipedia Flora Incognita. When used with the Rus-

sian interface, it provides the additional link to the

site https://www.plantarium.ru (ﬁgure 4). Compar-

ison results of mobile applications that can analyze

plant photos are presented in table 4.

There are some spesiﬁc functions available during

identiﬁcation:

• PictureThis can provide an auto diagnosis of

plant’s problems with pests and determination of

their diseases (ﬁgure 5);

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(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 advertising (f, g).

• PlantSnap ﬁnds the plant on amazon and provides

an infographic on solar activity, water usage and

activation temperature.

3.2 Infrastructure and Social

Environment

Some applications have their own approach to provid-

ing complex research of nature. Those features are

useful forincreasing students’ motivation to research

nature. However, it is worth noting that the most de-

veloped environment is in Seek used iNaturalist appli-

cation (developed by California Academy of Science

and National Geographic), which delivers robust sys-

tems of different instruments to students and teachers.

Photo sharing and communications. PlantNet

provides the feed of photos to identify plants shared

by other users of PlanNet. The information in the

feed is divided into classes “identiﬁed”, “unidenti-

ﬁed”, and “All” ﬁlter (displays both identiﬁed and

unidentiﬁed). The items in the feed with an “iden-

tiﬁed” ﬁlter will display already identiﬁed plants by

users, and “unidentiﬁed” ﬁlter will display unidenti-

ﬁed pictures updated by users. The most promising

approach is to use an “unidentiﬁed” feed which may

be helpful in a few cases:

• To help with identifying the plant

• To train own identiﬁcation skills by providing

Features of Using Mobile Applications to Identify Plants and Google Lens During the Learning Process

693

(a) (b) (c)

(d) (e) (f)

Figure 2: Instructions in Flora Incognita (a), PlantSnap (b), PictureThis (c) LeafSnap (d) and Seek (e, f) apps.

identiﬁcation of pictures of others

• To share thoughts in the ﬁeld of botanic, commu-

nicate with other researchers, and provide social

science networking.

Personal journals. The ﬁrst instrument to mo-

tivate a young researcher is providing a personal

journal of observation and identiﬁcation. It is a

widespread feature. For example, Flora Incognita has

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694

(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.

the tab “My observations”; PictureThis has “My gar-

den”; Leaf snap has “My plants”. However, some

apps do not provide an explicitly personal journal. For

example, PlantNet only saves the history of observa-

tions.

Projects and social. Seek provides collaboration

Features of Using Mobile Applications to Identify Plants and Google Lens During the Learning Process

695

(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

(g).

through access to projects. Users can ﬁnd and choose

projects that they would like to join. It is worth not-

ing that the app is ubiquitous and that there are even

projects available in Ukraine. The project selection

and speciﬁc project interfaces are presented in ﬁg-

ure 6a.

Achievements. Seek-identiﬁcation app provides

a signiﬁcantly different approach to increasing stu-

dents’ motivation. It provides achievements for each

plant students may ﬁnd, which motivates them to

delve into new studies from time to time. The effect of

achievement affects the brain as exaltation, and peo-

ple desire it repeatedly. It is used in games to motivate

students to play again and again (Abramovich et al.,

2011; Hart and Albarrac

ın, 2009; Weiner, 1985). In

the case of Seek, some factors will motivate students

to research nature.

The iNaturalist offers to observe plant and animal

species, which a student can ﬁnd nearby. This fea-

ture is activated by the “Exploring All” function and

choosing “My location”. Moreover, based on loca-

tion, students can use Missions which gibes quests for

students to do, for example, to ﬁnd a “Rock Pigeon”.

Hence, students can observe nature nearby to study it

in general terms while the program keeps encouraging

students by illustrating progress through completion

of various missions. The Exploring All and Missions

functions are presented in ﬁgure 6b, c.

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Table 4: Comparison results of mobile applications that can analyze plant photos.

Application

Number of

plants in the

database

Accuracy of the

analyzing process

Links to other information services

Flora Incognita

4800 (only

German)

The analysis algorithm is correct Links to Catalogue of Life, Plants for a

Future and Wikipedia. Flora Incognita,

with a Russian interface, provides links to

the Russian site

PlantNet 21920 The analysis algorithm is entirely

correct

Gives only the name of the plant. Includes

elements of social networks (by sharing

plants student found and subscriptions).

In addition, it contains links to Wikipedia.

PlantSnap 585000 The analysis algorithm is simple. Has its own description. Searches via

Amazon to give purchase options of the

plant in question.

Picture This 10000 The analysis algorithm is simple. Provides very structured information (in-

cluding type, lifespan, height, ﬂower di-

ameter), care aspects, usage of the plant

LeafSnap No data The analysis algorithm is correct.

Evaluation of health state (healthy

and unhealthy) is included into de-

termination process.

Contains links to Wikipedia, Pl@ntUse,

Global Biodiversity Information Facility

Seek No data The analysis algorithm is the sim-

plest. Achievements are given to

users after some successful identi-

ﬁcations

Has no detailed description but proposes

“species nearby in this taxon”

3.3 Analysis of Application

Identiﬁcation Accuracy

PlantNet is the most straightforward app to install.

Google Lens, LeafSnap and Flora Incognita have also

simple installation procedure. Google Lens, LeafS-

nap, Flora Incognita, Seek have the most straightfor-

ward interface. Google Lens, PlantSnap, PictureThis,

and PlantNet are characterized by the most uncom-

fortable identiﬁcation process, which can be compli-

cated for teachers. Results of detailed analyses on

plant identiﬁcation applications are presented in ﬁg-

ure 7.

In general, Google Lens, LeafSnap, Flora Incog-

nita, PlanNet, and Seek have proven to be the most us-

able after detailed research. However, the total num-

ber of points each application received is presented in

ﬁgure 8.

The most accurate apps are Google Lens, with

92.6% identiﬁcation accuracy. Flora Incognita cor-

rectly identiﬁes 71% of cases; PlantNet – 74%; Seek –

in 76%, LeafSnap – in 76%. The PictureThis percent-

age of correct deﬁnitions was not determined, because

this mobile application allows to identify only three

plants per day for free. For a comparison of the iden-

tiﬁcation plants accuracy by research applications, see

ﬁgure 9.

Our previous work 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 train the neural network, and

they have missed during identiﬁcation of speciﬁc

Ukrainian kinds of plants. Flora Incognita provides

signiﬁcantly different speciﬁc analyses; it may be due

to Flora Incognita using a Russian database (similar

to the Ukrainian region).

In our previous studies, it was shown that the ac-

curacy of plant detection by the mobile application

PlantNet is 55%. However, in the current test, the

percentage of correct identiﬁcation of plants by this

mobile application has increased to 74%. This ten-

dency indicates the ability of this neural network to

learn.

The algorithm for determining plants using Seek

also differs signiﬁcantly. All other applications stud-

ied, except Seek, require a clear real-time photograph

of the plant. Seek works with the user by interactively

managing his activities in terms of image quality.

From the point of view of botanical science, the

possibility to add different parts to the plants and

choose the plant’s type and geolocation access must

Features of Using Mobile Applications to Identify Plants and Google Lens During the Learning Process

697

(a)

(b)

Figure 5: PictureThis’ app features autodiagnosis on pests and diseases function: photo input interface (a) and the result of

the analysis (b).

affect the identiﬁcation process accuracy. However,

considering the results of the experiment, applications

with a simple algorithm deﬁnition (analysis of a sin-

gle image) more accurately identify plants. There-

fore, it seems that internal algorithms of identiﬁca-

tion (due to higher statical characteristics of neural

network) and the fullness of the database are more

important than accuracy of data input or taking user

geolocation into account.

It should be noted that Seek identiﬁes plants

according to the algorithm used by professional

botanists. Firstly, Seek deﬁnes the department, then

the class, family, genus, and, ﬁnally, the species.

Therefore, Google Lens is the most recommended

app for use during classes (Bilyk et al., 2020). It is

thus characterized by the highest general evaluation

with 4.6 points of interface analysis, which is signiﬁ-

cantly higher than marks for other apps.

However, taking into account results of usability

analysis and quality of analysis, it is possible to use

Seek or Flora Incognita for students and teachers who

do not like the Google Lens app for whichever rea-

son. However, PlantNet cannot be recommended to

use due to low accuracy which may result in half of

incorrect analysis results.

3.4 Advantages of Using Mobile Phone

Applications in the Educational

Process

In our opinion, the use of mobile applications that

identify plants during the education process has the

following functions:

1. Function of creating a learning environment.

Even in the works of Montessori (Montessori,

AET 2021 - Myroslav I. Zhaldak Symposium on Advances in Educational Technology

698

(a) (b) (c)

Figure 6: The Exploring All (a), Missions functions (b) and concrete project (c) functions.

1961) (a true classic of pedagogical thought), it

was proven that the environment should develop

the child. To a greater or lesser extent, mobile

applications create such an environment. For ex-

ample, Seek stimulates the child to search for new

plant objects, manages the process of photograph-

ing plants, provides links to additional informa-

tion about the plant, creates its own synopsis for

the child, and motivates the child with “achieve-

ments”.

2. Cognitive function. Only 70 hours are allotted

to study all plants in Ukrainian schools. Such

amount of time is insufﬁcient for such task Mo-

bile applications allow students to learn about the

diversity of the plant world.

3. Training function. Due to the limited number of

teaching hours, a teacher cannot focus enough on

the development of 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, for instance

Flora Incognita, request a deﬁnition of life form.

All these functions contribute to the formation of

this skill.

The use of mobile applications promotes the de-

velopment of students with the following competen-

cies:

1. STEM competence. When using mobile applica-

tions, students gain experience in the study of na-

ture.

2. Environmental competence. Some applications,

such as Seek, explain the rules of behavior in na-

ture.

3. ICT competence. Mobile applications allow stu-

dents to demonstrate the safe use of technology

for learning.

4. Lifelong learning competence. The use of mobile

applications teaches students to ﬁnd opportunities

for learning and self-development throughout life.

4 DISCUSSION

4.1 The Effect of UI/UX of the Apps on

the Student’s Motivation

The likelihood of students using mobile applications

to identify plants depends on their interest. Accord-

ing to modern theories, there is individual and situa-

tional interest. Individual interest depends on the psy-

chological characteristics of the individual. In con-

trast, situational interest arises in response to the pe-

culiarities of the environment. Situational interest

Features of Using Mobile Applications to Identify Plants and Google Lens During the Learning Process

699

Figure 7: Results of detailed results on plants identiﬁcation applications usability analysis.

Figure 8: Integrated results on the usability of plants identiﬁcation applications.

(SI) is divided into triggered situational interest and

maintained situational interest (Linnenbrink-Garcia

et al., 2010). Triggered-SI occurs quickly, directly,

and on the “catch”. Maintained-SI is a more stable

form of interest in which the student begins to delve

into the details. If maintained-SI deepens, this inter-

est may become individual. According to Schiefele

(Schiefele, 1991), Maintained-SI can be divided into

maintained-SI, feeling component and maintained-SI,

value component. These researchers believe that per-

sonality’s value and sensory component support inter-

est.

Situational interest may depend on the content of

the study material. Quite a small number of students

are interested in plants. However, many students may

be interested in mobile applications. One way to cap-

ture users’s attention is to provide mobile applications

on the social network principle. PlantNet works ac-

cordingly. Users can share unique photos of plants

and discuss the species. In modern pedagogics, social

networks have signiﬁcant didactic potential (Green-

how and Askari, 2017).

Enhancing students’ motivation is an essential ele-

ment, when modern informational tools usage is con-

cerned. Motivation enhancement is signiﬁcantly de-

pendent on many factors. Situational interest plays

a vital role in this context. In the case of mobile

phones, students’ motivation state is affected by both

of them. Other factors affect motivation, such as en-

gagement (Fredricks et al., 2004), well-being (Ren-

shaw and Arslan, 2016; Bates and Boren, 2019; Ren-

shaw, 2015), satisfaction (Ritzhaupt, 2019), positive

AET 2021 - Myroslav I. Zhaldak Symposium on Advances in Educational Technology

700

Figure 9: Comparison of the deﬁnition plants mobile apps accuracy.

and negative factors affect schedule (PANAS) (Ebe-

sutani et al., 2012; Laurent et al., 1999). However,

it seems that situational interest is caused by other

factors; therefore, for analysis’ sake, we will focus

on situational interest. Indeed, some students will be

looking for a tool that will help them satisfy their need

for investigation of nature, and that causes a high level

of maintained-SI when using identiﬁcation mobile ap-

plications. However, triggered-SI will affect students

that are not interested in nature investigation. For this

purpose, the program’s interface and UI/UX are very

important because these are the components forming

the ﬁrst impression.

For example, the use of situational interest, which

was triggered yet not maintained – markedly de-

creased from pre-test to post-test during a digital

mathematics game (Rodr

ıguez-Aﬂecht et al., 2018).

This result may be explained by the program inter-

face, which was neither easy to understand nor en-

joyable to use. Consequently, enhancement of moti-

vation when using such tools during biology classes

becomes impossible with the interface, which con-

tributes neither to the ease of understanding nor en-

joyment of app use.

Due to the above understanding, detailed results

on usability analysis (UI/UX) of plant identiﬁcation

applications are utterly signiﬁcant (ﬁgure 7). The

examples of comparison between different parts of

the programs’ interface are shown in ﬁgures 1-4. As

shown in ﬁgure 7, the programs with the best UI/UX

are Leaf Snap, Flora incognita, and Google lens.

The login process is an important part of UX, es-

pecially in the case of school usage. The experts took

into account the login procedure during the evaluation

of the simplicity and friendliness of the interface (ﬁg-

ure 7). The most straightforward procedures were in

Google Lens and Plant Net because it is possible to

use them without additional login steps. Plant Snap

and Seek also have relatively simple login procedure.

Instructions are helpful, but their effect seems to have

a much lesser inﬂuence on student motivation (ﬁg-

ure 2). However, their absence may have a signiﬁcant

negative effect on students’ motivation.

However, no programs were characterized by the

absence of instructions. The simplicity and friend-

liness of the interface during the process of plant

identiﬁcation seem to deliver reverse accuracy within

such a process. Even with the inaccuracy of in-

putting photos, some programs, such as Google Lens,

nonetheless provide impressive results. Therefore, we

will take into account the simplicity of such process.

Google lens, PlantNet and Seek were also the easiest

due to their one-click-based process. All the above

steps are essential to use the factors to transfer sit-

uational triggered to maintaining interest. In most

cases, obtaining additional data UX/UI will depend

on maintaining situational interest. Consequently, ob-

taining additional data on UX/UI contribution to stu-

dents’ motivation will exhibit a lesser effect.

Furthermore, it is essential to consider that trig-

gered motivation is affected not only by UI/UX,

but also, by involving students in the investigation

process, for instance, by providing the social net-

work effect and communication with other young re-

searchers – a function available in Seek.

The Seek mobile application system is interesting

from the point of view of didactics. The principle of

operation of this application uses gamiﬁcation princi-

ples. Numerous studies have proven the high educa-

tional potential of games. In many cases, the appli-

Features of Using Mobile Applications to Identify Plants and Google Lens During the Learning Process

701

cation of games and simulations for learning provides

an opportunity for learners to apply acquired knowl-

edge and experiment. Some things cannot be applied

in real-world contexts. Games can motivate to learn,

increasing the likelihood that the desired learning out-

comes will be achieved. Learning is deﬁned as the

acquisition of knowledge or skills through experience

or practice, and what better way to learn is there other

than through a game? (Pivec and Kearney, 2007).

The student can register in Seek and get a nick-

name. For each plant identiﬁed, he receives an

achievement and becomes a higher-level user. Dur-

ing computer games, the participant learns to use their

knowledge in a speciﬁc situation without even realiz-

ing it. These steps allows to use knowledge, skills,

and abilities automatically (Facer et al., 2001). The

impact of games on motivation to learn is not unam-

biguous; it all depends on the game itself. Students

whose situational interest trajectories were stable (ei-

ther high or low) presented no changes in individual

interest, yet the individual interest of students whose

situational interest was triggered but not maintained

markedly decreased from pre-test to post-test. Re-

sults suggest that it is vital to use game-based learning

not because games are believed to be “motivating”;

rather, games with proven learning outcomes should

be carefully selected (Rodr

ıguez-Aﬂecht et al., 2018).

When a student uses Seek for a while, he sees that

ﬁrst, the mobile application deﬁnes the class, then the

family, then the species. This knowledge is deeply

remembered.

Therefore, Seek increases the motivation to learn

because, in addition to virtual awards, it offers partic-

ipation in real environmental projects.

4.1.1 Alignment With Relevant K-12 STEM

Education Standards in the United States

and Ukraine

The main document declaring the introduction of

STEM education in Ukraine is the concept of the

implementation of natural and mathematical (STEM)

education (Cabinet of Ministers of Ukraine, 2020).

According to this document, the task of STEM in ed-

ucation is the formation of skills for solving complex

(complex) practical problems, comprehensive devel-

opment of personality by identifying its inclinations

and abilities; mastering the means of cognitive and

practical activities; education of a person who strives

for lifelong learning, the formation of skills of practi-

cal and creative application of acquired knowledge.

In our opinion, the use of mobile applications:

1. allows to solve a practical problem (determining

the type of plant, for example, if it is a parasitic

plant and one needs to get rid of it);

2. comprehensive development of personality is

realized through the acquisition of biological

knowledge, the practice of using mobile applica-

tions, and communication with people who have

similar interests;

3. the concept of lifelong learning is perfectly imple-

mented when using mobile applications because

anyone can use them at any time.

In the United States and many European coun-

tries, the ISTE 2016 standard is one of the most well-

known educational standards. According to this stan-

dard, the modern student must be able to solve spe-

ciﬁc problems, making optimal use of modern tech-

nology. Such technologies include mobile applica-

tions for identifying plants which solve a speciﬁc

problem. ISTE states that students use collaborative

technologies to interact with others, including peers

and experts, to study problematic issues from differ-

ent points of view. This item is signiﬁcantly supported

by mobile applications for identifying plants, which

are created on the principle of social networks. Us-

ing these applications, a student can discuss s photos

of the most interesting plants with others. According

to ISTE 2016, students jointly explore the problems

at both local and global levels and use technology to

develop standard ways to solve these problems. Seek

promotes real projects from researching a few faunas

and ﬂora representatives to solve global problems.

5 CONCLUSION

1. Apps related to plant identiﬁcation can be referred

to as those which can analyze photos, devoted to

manual identiﬁcation, and apps devoted to plant

care monitoring.

2. It has been proven that LeafSnap, Flora Incognita,

PlanNet, and Seek are the most usable plant iden-

tiﬁer apps.

3. Seek and LeafSnap correctly identiﬁed plant

species in 76% of cases, PlantNet correctly did

this in 74% of cases, Flora Incognita correctly

identiﬁed plant species in 71% of cases, which

is signiﬁcantly lesser than the same parameter for

Google Lens (92.6%). Google Lens was charac-

terized by the highest usability mark compared to

PlantNet, Flora Incognita, LeafSnap, and Seek.

4. Based on the above, Google Lens is the most rec-

ommended app for use during biology classes.

However, it is possible to use Seek or Flora Incog-

nita for students and teachers who do not like the

Google Lens app for whichever reason.

AET 2021 - Myroslav I. Zhaldak Symposium on Advances in Educational Technology

702

5. The Seek mobile application can be used as a

learning environment.

6. PlantNet app is characterized by an accuracy of

55% and cannot be recommended for use during

biology classes.

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