MECHANISMS FOR REAL-TIME ASSESSMENT OF STUDENTS’ KNOWLEDGE IN BIOLOGY USING MOBILE APPLICATIONS
Keywords:
mobile applications, real-time assessment, biology education, digital pedagogy, formative assessment, learning analytics, interactive testing, feedbackAbstract
This article analyzes the mechanisms for real-time assessment of students’ knowledge in biology using mobile applications. It explores the pedagogical potential of interactive testing tools, automated assessment systems, and instant feedback in a digital learning environment. The study examines how mobile applications such as Kahoot, Quizizz, and Google Forms influence students’ engagement, knowledge acquisition, and independent thinking. Special attention is given to the role of real-time assessment within formative assessment and its contribution to personalized learning. The findings demonstrate the effectiveness of mobile technologies in improving the assessment process in biology education.
References
1. Толипов Ў. Қ., Усмонбоева М. Педагогик технологиялар ва педагогик маҳорат. – Тошкент: Инновация-Зиё, 2019. – 300 б.
2. Ишмухамедов Р. Ж., Абдуқодиров А. А., Пардаев А. Таълимда инновацион технологиялар. – Тошкент: Фан ва технология, 2014. – 240 б.
3. Рўзиева Д. И. Олий таълим муассасаларида ўқитиш технологиялари. – Тошкент: Фан, 2016. – 200 б.
4. Crompton H., Burke D. The use of mobile learning in higher education: A systematic review // Computers & Education. – 2018. – Vol. 123. – P. 53–64.
5. Bano M., Zowghi D., Kearney M., Schuck S., Aubusson P. Mobile learning for science and mathematics school education: A systematic review // Computers & Education. – 2018. – Vol. 121. – P. 30–58.
6. Black P., Wiliam D. Assessment and classroom learning // Assessment in Education: Principles, Policy & Practice. – 1998. – Vol. 5, No. 1. – P. 7–74.
7. Wiliam D. Embedded formative assessment. – Bloomington: Solution Tree Press, 2011. – 192 p.
8. Siemens G. Learning analytics: The emergence of a discipline // American Behavioral Scientist. – 2013. – Vol. 57, No. 10. – P. 1380–1400.
9. Long P., Siemens G. Penetrating the fog: Analytics in learning and education // EDUCAUSE Review. – 2011. – Vol. 46, No. 5. – P. 31–40.
10. Kolb D. A. Experiential learning: Experience as the source of learning and development. – New Jersey: Prentice Hall, 1984. – 256 p.
11. Tavares R., Vieira R. M., Pedro L. Mobile applications in science education: Design and evaluation // Procedia Computer Science. – 2020. – Vol. 164. – P. 123–130.
12. Jeno L. M., Grytnes J. A., Vandvik V. The effect of a mobile-application tool on biology students’ motivation and learning // Computers & Education. – 2017. – Vol. 107. – P. 1–12.
13. Kukulska-Hulme A., Traxler J. Mobile learning: A handbook for educators and trainers. – London: Routledge, 2005. – 192 p.
14. Ally M. Mobile learning: Transforming the delivery of education and training. – Edmonton: Athabasca University Press, 2009. – 296 p.
15. Hwang G. J., Tsai C. C. Research trends in mobile and ubiquitous learning // British Journal of Educational Technology. – 2011. – Vol. 42, No. 4. – P. E65–E70.
