The Google Lens analyzing quality: an analysis of the possibility to use in the educational process

Abstract

<jats:p>Biology is a fairly complicated initial subject because it involves knowledge of biodiversity. Google Lens is a unique, mobile software that allows you to recognition species and genus of the plant student looking for. The article devoted to the analysis of the efficiency of the functioning of the Google Lens related to botanical objects. In order to perform the analysis, botanical objects were classified by type of the plant (grass, tree, bush) and by part of the plant (stem, flower, fruit) which is represented on the analyzed photo. It was shown that Google Lens correctly identified plant species in 92.6% cases. This is a quite high result, which allows recommending this program using during the teaching. The greatest accuracy of Google Lens was observed under analyzing trees and plants stems. The worst accuracy was characterized to Google Lens results of fruits and stems of the bushes recognizing. However, the accuracy was still high and Google Lens can help to provide the researches even in those cases. Google Lens wasn’t able to analyze the local endemic Ukrainian flora. It has been shown that the recognition efficiency depends more on the resolution of the photo than on the physical characteristics of the camera through which they are made. In the article shown the possibility of using the Google Lens in the educational process is a simple way to include principles of STEM-education and “New Ukrainian school” in classes.</jats:p>

Critical Factors Influencing Pre-Service Teachers’ Use of the Internet of Things (IoT) in Classrooms

“…More recently, [19] conducted a study to investigate the possibilities of Google Lens as an IoT tool in biology classes in Ukrainian schools. They found that Google Lens had outstanding outcomes and should be used in teaching.…”

Possibilities of Application of Augmented Reality in Different Branches of Education

“…Many AREdu 2019 authors have addressed various aspects of AR technology, in particular: Ihor O. Arkhypov [8], Volodymyr O. Artemchuk [5], Zhanna I. Bilyk [22; 23; 24], Anzhela P. Boiko [6], Stanislav L. Bondarevskyi [13], Oleksandr Yu. Burov [5], Iryna I. Deinega [5], Andrii V. Іatsyshyn [5], Anna V. Іatsyshyn [5], Valeriia O. Kovach [5], Yaroslav M. Krainyk [6], Tetiana H. Kramarenko [7], Ivan V. Kravets [11], Olexander I. Kuchma [8], Yulii G. Kutsan [5], Olga V. Kuzyshyn [11], Olena O. Lavrentieva [8], Victor M. Lutsyshyn [11], Svitlana H. Lytvynova [5], Maiia V. Marienko [20; 25], Oksana M. Markova [13; 16; 28], Anna P. Megalinska [23], Lilia Ya. Midak [11]…”

A repeatable scoring system for assessing Smartphone applications ability to identify herbaceous plants

“…Table 1 lists the apps and provides details on their popularity at the time of download (spring 2021). Plant Net, Leaf Snap and Plant Snap were among the top four suggestions in the Google Store, Google Lens was selected due to its pre-installation on virtually all devices and its link to the widely used Google Search engine [ 18 ]; and Seek and iNaturalist, which both utilise the same database, were created through collaboration of the National Geographic Society and the California Academy of Sciences [ 19 ]. iNaturalist relies on a database and requires users to confirm identifications but can also provide “live” identification and has been used in this manner for this study.…”