O. Pursky, A. Selivanova, I. Buchatska, T. Dubovyk, Tatiana Tomashevska, Petro Palchuk
{"title":"在线学习条件下教育动机的Agent建模","authors":"O. Pursky, A. Selivanova, I. Buchatska, T. Dubovyk, Tatiana Tomashevska, Petro Palchuk","doi":"10.1109/PICST57299.2022.10238575","DOIUrl":null,"url":null,"abstract":"This article is devoted to agent modeling the features of student learning motivation in online learning conditions. Maintaining motivation plays a special role during the introduction of distance learning in connection with the coronavirus epidemic. To analyze the features of motivation in different learning conditions agent model of the student motivation has been used. The effectiveness of the model was tested in both offline and online learning. The results of modeling showed that the influence of the main motivational components in the conditions of offline learning varies from primary school to higher education. The youngest students are best motivated to learn in a situation where the inner desire to learn something new is constantly supported by external stimulation. In primary school, the motivating influence of teachers and parents gradually decreases, but both the negative and positive influence of an important environment (friends, reference adults) increases. Adolescents have clearly defined learning goals. The impact of online learning on this category of students is quite controversial. The study has found mixed trends - both an increase in motivation for learning and a sharp decrease. The first group is quietly moving to online learning, making extensive use of the Internet. The second either completely lose motivation to learn or shows unstable motivation, which either sharply decreases, then just as sharply increases. Agent modeling technologies allows tracking the conditions under which stimulation will be change student learning motivation.","PeriodicalId":330544,"journal":{"name":"2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Agent Modeling of Educational Motivation in Online Learning Conditions\",\"authors\":\"O. Pursky, A. Selivanova, I. Buchatska, T. Dubovyk, Tatiana Tomashevska, Petro Palchuk\",\"doi\":\"10.1109/PICST57299.2022.10238575\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article is devoted to agent modeling the features of student learning motivation in online learning conditions. Maintaining motivation plays a special role during the introduction of distance learning in connection with the coronavirus epidemic. To analyze the features of motivation in different learning conditions agent model of the student motivation has been used. The effectiveness of the model was tested in both offline and online learning. The results of modeling showed that the influence of the main motivational components in the conditions of offline learning varies from primary school to higher education. The youngest students are best motivated to learn in a situation where the inner desire to learn something new is constantly supported by external stimulation. In primary school, the motivating influence of teachers and parents gradually decreases, but both the negative and positive influence of an important environment (friends, reference adults) increases. Adolescents have clearly defined learning goals. The impact of online learning on this category of students is quite controversial. The study has found mixed trends - both an increase in motivation for learning and a sharp decrease. The first group is quietly moving to online learning, making extensive use of the Internet. The second either completely lose motivation to learn or shows unstable motivation, which either sharply decreases, then just as sharply increases. Agent modeling technologies allows tracking the conditions under which stimulation will be change student learning motivation.\",\"PeriodicalId\":330544,\"journal\":{\"name\":\"2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PICST57299.2022.10238575\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PICST57299.2022.10238575","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Agent Modeling of Educational Motivation in Online Learning Conditions
This article is devoted to agent modeling the features of student learning motivation in online learning conditions. Maintaining motivation plays a special role during the introduction of distance learning in connection with the coronavirus epidemic. To analyze the features of motivation in different learning conditions agent model of the student motivation has been used. The effectiveness of the model was tested in both offline and online learning. The results of modeling showed that the influence of the main motivational components in the conditions of offline learning varies from primary school to higher education. The youngest students are best motivated to learn in a situation where the inner desire to learn something new is constantly supported by external stimulation. In primary school, the motivating influence of teachers and parents gradually decreases, but both the negative and positive influence of an important environment (friends, reference adults) increases. Adolescents have clearly defined learning goals. The impact of online learning on this category of students is quite controversial. The study has found mixed trends - both an increase in motivation for learning and a sharp decrease. The first group is quietly moving to online learning, making extensive use of the Internet. The second either completely lose motivation to learn or shows unstable motivation, which either sharply decreases, then just as sharply increases. Agent modeling technologies allows tracking the conditions under which stimulation will be change student learning motivation.