The Intelligent Platform of Autonomous Learning in Post-Secondary Education
Samusenkov V. Klyushin V. Prasolov V. Sokolovskiy K.
2021International Association of Online Engineering
International Journal of Interactive Mobile Technologies
2021#15Issue 1049 - 65 pp.
The study aimed to develop and test an autonomous learning intelligent platforms effectiveness in post-secondary education. It was conducted based on the Institute of Dentistry named after E.V. Borovsky in I.M. Sechenov First Moscow State Medical University (Moscow, Russia) and Humanitarian and technical academy (Kokshetau, Kazakhstan). This research involved 59 teachers and 390 students, who comprised the total sample of 449 respondents. The experiment consisted of three stages – introductory, experimental, and final. The introductory stage included the distribution of enrolled students into the experimental and control groups. Besides, at the introductory stage, the development of questionnaires directed at identifying students and teachers readiness to implement autonomous learning was performed. Apart from this, the involved educators were required to fill the learning platform with predetermined training content. Programmers developed the considered intelligent learning platform by prior agreement with educational institutions under study. The experimental stage aimed to introduce the designed model of autonomous learning based on the created intelligent platform. The final stage implied surveying of all study participants according to the developed questionnaires. After introducing the created autonomous learning model, it was revealed that 51.5% of enrolled teachers were ready for self-directed education at a high level, 20.4% – at a satisfactory level, 18.4% – at a moderate, and 9.7% – at a low level. Among the students of Sechenov University, 21% of respondents had a high level of readiness for autonomous learning based on intelligent platforms, 27% of students had a sufficient level, 35% – moderate, and 17% – low. Among the Humanitarian and technical academy students, 29% had a high readiness for autonomous learning, 30% were ready at a sufficient level, 25% at a moderate, and 16% at a low level. This study provided an opportunity to use the developed questionnaires and the model of autonomous learning in post-secondary education to research the implementation of self-directed training further.
autonomous learning , intelligent platforms , mobile learning , Post-secondary education
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I.M. Sechenov Moscow State Medical University, Moscow, Russian Federation
S.M. Nikolskii Institute of Mathematics, RUDN, Moscow, Russian Federation
Financial University under the Government of the Russian Federation, Moscow, Russian Federation
Humanitarian and Technical Academy, Kokshetau, Kazakhstan
I.M. Sechenov Moscow State Medical University
S.M. Nikolskii Institute of Mathematics
Financial University under the Government of the Russian Federation
Humanitarian and Technical Academy
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