{"title":"控制智能辅导系统音频信息个性化播放的三阶段分层逻辑模型","authors":"A. N. Varnavsky","doi":"10.1109/TLT.2024.3439470","DOIUrl":null,"url":null,"abstract":"The most critical parameter of audio and video information output is the playback speed, which affects many viewing or listening metrics, including when learning using tutoring systems. However, the availability of quantitative models for personalized playback speed control considering the learner's personal traits is still an open question. The work aims to develop a model to control the personalized playback speed of audio information for beginners and experienced learners for intelligent tutoring systems. Analysis of the data from the experimental study using traditional machine learning methods did not allow us to classify the preferred playback rate with accuracy higher than 60%. Therefore, we developed the three-level hierarchical logistic model that predicts the preferred playback speed of audio material on the scale from “very low speed” to “high speed” for beginners and experienced learners with 80% accuracy. The model uses a combination of cognitive and psychomotor traits of individual learners and aims to maximize audio listening convenience and satisfaction. We explained the influence of the learners' selected personal traits on the preferred speed of audio playback. We calculated the convenience of listening to the audio materials without and with the model. By using the model, the convenience of listening to audio materials increased by an average of 13% at a low speech speed and 37% at a high speech speed. The model extends the control theory of multimedia information in e-learning systems by describing the influence of selected psychophysiological traits of learners on the preferred playback speed of audio materials.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"2005-2019"},"PeriodicalIF":2.9000,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Three-Stage Hierarchical Logistic Model Controlling Personalized Playback of Audio Information for Intelligent Tutoring Systems\",\"authors\":\"A. N. Varnavsky\",\"doi\":\"10.1109/TLT.2024.3439470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The most critical parameter of audio and video information output is the playback speed, which affects many viewing or listening metrics, including when learning using tutoring systems. However, the availability of quantitative models for personalized playback speed control considering the learner's personal traits is still an open question. The work aims to develop a model to control the personalized playback speed of audio information for beginners and experienced learners for intelligent tutoring systems. Analysis of the data from the experimental study using traditional machine learning methods did not allow us to classify the preferred playback rate with accuracy higher than 60%. Therefore, we developed the three-level hierarchical logistic model that predicts the preferred playback speed of audio material on the scale from “very low speed” to “high speed” for beginners and experienced learners with 80% accuracy. The model uses a combination of cognitive and psychomotor traits of individual learners and aims to maximize audio listening convenience and satisfaction. We explained the influence of the learners' selected personal traits on the preferred speed of audio playback. We calculated the convenience of listening to the audio materials without and with the model. By using the model, the convenience of listening to audio materials increased by an average of 13% at a low speech speed and 37% at a high speech speed. The model extends the control theory of multimedia information in e-learning systems by describing the influence of selected psychophysiological traits of learners on the preferred playback speed of audio materials.\",\"PeriodicalId\":49191,\"journal\":{\"name\":\"IEEE Transactions on Learning Technologies\",\"volume\":\"17 \",\"pages\":\"2005-2019\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Learning Technologies\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10623797/\",\"RegionNum\":3,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Learning Technologies","FirstCategoryId":"95","ListUrlMain":"https://ieeexplore.ieee.org/document/10623797/","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
The Three-Stage Hierarchical Logistic Model Controlling Personalized Playback of Audio Information for Intelligent Tutoring Systems
The most critical parameter of audio and video information output is the playback speed, which affects many viewing or listening metrics, including when learning using tutoring systems. However, the availability of quantitative models for personalized playback speed control considering the learner's personal traits is still an open question. The work aims to develop a model to control the personalized playback speed of audio information for beginners and experienced learners for intelligent tutoring systems. Analysis of the data from the experimental study using traditional machine learning methods did not allow us to classify the preferred playback rate with accuracy higher than 60%. Therefore, we developed the three-level hierarchical logistic model that predicts the preferred playback speed of audio material on the scale from “very low speed” to “high speed” for beginners and experienced learners with 80% accuracy. The model uses a combination of cognitive and psychomotor traits of individual learners and aims to maximize audio listening convenience and satisfaction. We explained the influence of the learners' selected personal traits on the preferred speed of audio playback. We calculated the convenience of listening to the audio materials without and with the model. By using the model, the convenience of listening to audio materials increased by an average of 13% at a low speech speed and 37% at a high speech speed. The model extends the control theory of multimedia information in e-learning systems by describing the influence of selected psychophysiological traits of learners on the preferred playback speed of audio materials.
期刊介绍:
The IEEE Transactions on Learning Technologies covers all advances in learning technologies and their applications, including but not limited to the following topics: innovative online learning systems; intelligent tutors; educational games; simulation systems for education and training; collaborative learning tools; learning with mobile devices; wearable devices and interfaces for learning; personalized and adaptive learning systems; tools for formative and summative assessment; tools for learning analytics and educational data mining; ontologies for learning systems; standards and web services that support learning; authoring tools for learning materials; computer support for peer tutoring; learning via computer-mediated inquiry, field, and lab work; social learning techniques; social networks and infrastructures for learning and knowledge sharing; and creation and management of learning objects.