Autonomous Learning Model Research Articles

The Intelligent Platform of Autonomous Learning in Post-Secondary Education

The aim of the study was to develop and test the effectiveness of an autonomous learning intelligent platform in post-secondary education. It was conducted on the basis of 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. The considered intelligent learning platform was developed by programmers by prior agreement with educational institutions under study. The experimental stage was aimed at introducing 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 the introduction of 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 level, 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 for further research on the implementation of self-directed training.

Real-time prediction of spatial raster time series: a context-aware autonomous learning model

Real-time prediction of spatial raster time series, such as those derived from satellite remote sensing imagery, is important for making emergency decisions on various geo-spatial processes/events. However, because of the scalability issue and large training time requirement, the neural network (NN)-based models often fail to perform real-time prediction, in spite of their tremendous potential. In this paper, we propose ContRast, a variant of recurrent NN-based context-aware raster time series prediction model that attempts to resolve these issues by: (1) eliminating the need for offline adjustment of network structure by employing self-evolving autonomous learning of recurrent neural network, (2) saving training time by adopting single-pass parameter learning mechanism, and (3) reducing redundant learning by skipping sub-regional data associated with similar spatio-temporal context and reusing already learned parameters to predict for the same. Experimental evaluations with respect to predicting normalized difference vegetation index (NDVI)-raster derived from MODIS Terra satellite remote sensing imagery show that ContRast is highly effective for real-time prediction of spatial raster time series, and it significantly outperforms the existing models. In addition, the theoretical analyses of model complexity and computational cost further justify our empirical observations.

Practice of Autonomous Learning Mode in the Course of “Web Design and Production”

<p>The autonomous learning model is one of the dominant learning models in the era of “Internet + education”. It is sought after by teachers and students in universities. The learning style of college students is shifting from passive to active learning. And the traditional teaching model in the course of “Web Design and Production” is easy to cause the problems of poor learning enthusiasm of students and low teaching effect. According to the characteristics of the course, this article explores how autonomous learning can stimulate students’ learning motivation and improve the learning effect of this course. It also designs a corresponding autonomous learning instructional model to mobilize students’ learning enthusiasm, and to improve the instructional efficiency of the course.</p>

Autonomous Mobile Learning Model of Cloud Education Based on Intelligent Algorithm of Wireless Network Communication

The rapid development of a new generation of information technology and its widespread application in colleges and universities have promoted profound changes in campus informatization. On the one hand, wireless campus networks as the main infrastructure of digital campuses are gradually popularized in domestic colleges and universities, expanding the campus information network coverage. This article is aimed at studying the addition of intelligent algorithms to wireless network communications to optimize and build autonomous mobile learning for cloud education. In order for children to communicate with teachers face to face, no matter where they are, this article proposes how to reduce the energy loss in wireless communication and find the best intelligent algorithm to realize the cloud education mobile learning platform. Experimental results show that the transmission delay of the wireless communication system of this method is significantly shorter than that of the other two methods, close to 5%, which speeds up the data transmission speed of the wireless communication system. It can be implemented under time‐sensitive conditions and has high practical application value. The wireless network communication system of this method has a low packet loss rate and less wireless network data transmission errors, which is nearly 10% lower than the other two methods, thereby improving the data transmission power of the wireless communication network.

A Multimodality Fusion Deep Neural Network and Safety Test Strategy for Intelligent Vehicles

Multimodality fusion based on deep neural networks (DNN) is a significant method for intelligent vehicles. The special characteristics of DNN lead to the issue of AI safety and safety test. In this paper, we firstly propose a multimodality fusion framework called Integrated Multimodality Fusion Deep Neural Network (IMF-DNN), which can flexibly accomplish both object detection and end-to-end driving policy for prediction of steering angle and speed. Then, we propose a DNN safety test strategy, which systematically analyzes DNN's robustness and generalization ability in large amounts of diverse driving environment conditions. The test in this paper is based on our IMF-DNN model and the strategy can be widely used for other DNNs. Finally, the experiment analysis is performed on KITTI for object detection and the dateset DBNet for end-to-end tasks. The results show the superior accuracy of the proposed IMF-DNN model and the test strategy's potential ability to improve the robustness and generalization of autonomous vehicle deep learning model. Code is available at https://github.com/ennisnie/IMF-DNN.

Autonomous Learning Mode based on a Four-Element Teaching Design for Visual Communication Course

With the development and improvement of information transfer efficiency in this era, visual communication has people's life and communication. However, the thinking in the traditional visual communication course is fixed, and students' learning enthusiasm is weak. Hence, this study proposes an autonomous learning mode by using a four-element teaching design. First, we propose relevant knowledge and ability, learning task, supporting program, and special practice as four elements related to education program. Second, we integrate them into the autonomous learning model to help students achieve learning transfer. Third, we use the new K-means algorithm to collect students' autonomous learning behavior data in the online course of visual communication and divide the data into three levels (high, medium, and low levels) for analysis. Finally, we design autonomous learning teaching cases for visual communication by using the proposed four-element teaching design and analyze the teaching effect. Our results show that the proposed learning mode enables a long learning video watching time for students, which in turn produces a high percentage of completed tasks. This result verifies that the application of the autonomous learning mode based on four-element teaching design can improve students' autonomous learning ability. Therefore, this mode is worth promoting.

Research and Practice of Autonomous Learning and Evaluation Mode Based on Mobile Client

This article focuses on the exploration and construction of a mobile online autonomous learning and evalua-tion model, and on the cultivation and guidance of students’ autonomous learning methods and abilities, to complete the construction and optimization of formative evaluation. The basic teaching of computer application in the freshman year is the experimental object and content, and the experimental and control groups with strict variables are built to carry out a comparative analysis, discussion, and in-depth exploration through experimental research on how to build a mo-bile and autonomous learning and evaluation model with perfect content and structure, to promote better online teaching of various majors in the school and improve autonomous learning and evaluation models.

Research on the Autonomous Learning Mode in the Environment of Computer Network Technology

Autonomous learning is an important part of basic education for all. At the same time, with the continuous development of computer network technology, it provides a new model for autonomous learning to some extent and improves the efficiency of learning. This paper mainly studies the needs of residents’ autonomous learning under the computer network technology environment and how to combine computer technology for efficient autonomous learning. Through the analysis of this paper, for the students to create a good learning atmosphere, provide reliable learning guidance, and how to implement the “happy learning”, “learn well”, “learned” as the guiding goal of the educational training model to provide reference.

A Study of College English Autonomous Learning Model based on Computer and Network

Taking the non-English majors as the research object, the traditional college English teaching mode is combined with computer, network, multimedia and other advanced technologies to form a new teaching mode, that is, relying on the computer network platform, building English network course resources, developing an objective and feasible multiple evaluation system, so as to realize the purpose of students’ autonomous learning. The experiment shows that the new teaching mode, which is composed of classroom teaching and online autonomous learning, is effective.

Research on the Elderly Education Model Based on Autonomous Learning Groups under the Regular Situation of COVID-19 Epidemic Prevention and Control

In the face of the sudden outbreak of COVID-19 epidemic, offline learning for elderly education across the country was forced to stop. The school running units of elderly education have to transfer teaching from offline to online, and start to explore the online education model for the elderly. In this context, the autonomous learning model has gradually attracted attention. This paper discusses the educational needs of the elderly, the development trend of elderly education in the world and the characteristics of autonomous learning groups for the elderly. It also analyzes the difficulties faced by the elderly education under the regular situation of COVID-19 epidemic prevention and control and finally proposes the development path of the elderly education based on the autonomous learning groups.

The Integration of MALL to Enhance Students Speaking Skill: An Autonomous Learning Model

Mobile-Assisted Language Learning (MALL) is a new approach for students to learn language through the use of mobile technology. Learning a language should not only happen in a class setting activity but also happen outside the class in which the students take charge of their learning. Hence, it requires students' autonomy in learning the language. Students are now able to carry out their learning without depending on the teachers, which then leads to a sustainable and independent learning process. Quizlet, a web application, is introduced in this paper as an alternative solution to improve students’ speaking skill through an autonomous language learning activity. This paper used an action research method combined with a questionnaire to analyze the implementation of Quizlet in an autonomous class setting at STMIK AKAKOM Yogyakarta. The practical, usability, and sustainability aspects become the focus of this research. The data gathered from the action research shows that an autonomous learning activity still requires teachers to be the facilitator, and the questionnaire shows positive feedback from the students regarding the usability and sustainability of their language learning using the application.

Research on business English autonomous learning based on artificial intelligence and improved BP network model

Due to various factors, the learning process of business English is mostly autonomous learning. However, the traditional autonomous learning model is difficult to effectively improve the learning effect of business English. In order to improve the business English learning model, based on artificial intelligence and improved BP network model, this paper builds a business intelligence autonomous learning system with certain intelligence. Moreover, this paper designs functional modules for the characteristics of business English learners, and combines the self-learning needs to facilitate the processing of structural functions, so that students can complete the operation independently. The system sets up multiple functional modules, conducts guided recommendation learning according to the characteristics of the self-learning process, and combines the feedback system to correct the shortcomings in students’ autonomous learning. Through this system, teachers can perform a variety of operations offline and eliminate restrictions on location and teaching time. In addition, in order to verify the performance of the model, the experimental study was conducted by setting up a control group and an experimental group. The research results show that the model constructed in this paper has good performance.

Formative Assessment for Autonomous Learning Through Argumentation; A Proposal Within the Use of the Online Dialogue Design System

There has been a concern to help students learn how to argue in order to become better learners. Different argumentation models have been used as a teaching strategy. In 2009, Makino designed the Dialogue Design System (DDS) which is based on Toulmin’s argumentation model (2003). Through the iterative use of a didactic resource called “idea cards”, the active participation of the student is stimulated as well as the development of critical analysis and the construction of reasonable and well-founded arguments are also enhanced. DDS has also been avowed as an adequate strategy to strengthen, not only argumentative skills, but also skills related to autonomous learning. This work is part of a doctoral research project that considers the design and development of an online tool based on the DDS model. For the specific case of the assessment of written argumentative and autonomy skills, a descriptive and analytical study will be conducted. For this purpose, two assessment tools are proposed: one based on Deane and Song’s learning progression model (2012) and the second developed under the influence of Tassinari’s dynamic model for autonomous learning (2010). The following paper presents the foundations and design of the Self-Assessment of Progress in Argumentative Autonomy instrument (SAPAA).

Learner autonomy versus guided reflection: How different methodologies affect intercultural development in online intercultural exchange

AbstractThis paper presents the results of a study exploring the intercultural development of first-year Japanese university students engaged in online intercultural exchange (OIE) using two variations: one implementing guided reflection, and the other relying on the learner autonomy model. Intercultural development was quantitatively measured using the Intercultural Sensitivity Scale (Chen & Starosta, 2000) and qualitatively investigated through participants’ written reflections. Results of the OIE using guided reflection showed significant gains in respect for the target culture, whereas the OIE that followed the autonomous learning model yielded significant gains in self-efficacy in relation to intercultural contact. Qualitative analysis of student reflections confirmed these findings and provided insight into the processes involved in achieving these results.

Online English Vocabularies Autonomous Learning Model Based on EM Algorithm

Under the background of the rapid spread of the Internet, a variety of English vocabularies learning models have emerged in mobile Internet terminals. On the one hand, its development inherits the traditional English learning theory. On the other hand, it also reveals its own uniqueness. The acquisition of human information is time-sensitive and the generalization of information is full of the horizons of language learners. The problem is how to effectively reduce negative impacts and improve learning efficiency. The EM algorithm can effectively filter English vocabularies and generate a mean value from a mixture of k different normal distributions, which makes English vocabulary online learning more efficient.

Autonomous Learners: How Competency-Based Curriculum could Accelerate EFL at English Education Department

This paper will explore the implementation of the Competency-Based Curriculum at the Department of English Education, Universitas Muhammadiyah Yogyakarta, in reaching the goal of creating autonomous learners. Autonomous Learner is the ultimate objective in teaching learning processes. It is the beginning of the long-life learning processes. By creating autonomous learners, the process of achieving better graduate quality will be more effective and efficient. To reach the goal of producing autonomous learners, the Department of English Education, Universitas Muhammadiyah Yogyakarta, focuses its curriculum on the graduate abilities in “thinking how to think” and “learning how to learn” through the Competency Based Curriculum.Competency-Based Curriculum (CBC) is the teaching learning planning which bases its objectives on the students’ competences. To achieve the ultimate goal of language learning the Department of English Education, Universitas Muhammadiyah Yogyakarta needs to choose the relatively most effective curriculum and method of teaching for the students. Therefore, the department chooses CBC that applies student centred learning (SCL) to achieve the autonomous learning model. The department also applies constructivism approach which enhance the students curiosity to accelerate the autonomous learning in the student centred learning.

Exploration and Mining Learning Robot of Autonomous Marine Resources Based on Adaptive Neural Network Controller

Abstract To study the autonomous learning model of the learning robot for marine resource exploration, an adaptive neural network controller was applied. The motion characteristics of autonomous learning robots were identified. The mathematical model of the multilayer forward neural network and its improved learning algorithm were studied. The improved Elman regression neural network and the composite input dynamic regression neural network were further discussed. At the same time, the diagonal neural network was analysed from the structure and learning algorithms. The results showed that for the complex environment of the ocean, the structure of the composite input dynamic regression network was simple, and the convergence was fast. In summary, the identification method of underwater robot system based on neural network is effective.

Advanced Dynamic Autonomous Knowledge Learning Method for Distance Learning

Abstract As the manufacturing of vast amount of information transmits at an unprecedented rate, traditional learning is no way to meet the needs of open learning and lifelong learning, how can distance learning be used to help us study become a problem to think about. Distance learning requires improvement of interactivity and initiative to achieve their aptitude. Using a variety of formats data, learners master the initiative in the learning process, it is not easy to lead to deviation from the learning goals phenomenon. To this end, in order to solve this problem, we use the basis of ILTMK theory and distributed interactive technology to introduce the active learning factors and propose a dynamic autonomous knowledge learning model and build its model’s simulation running environment and related mechanism. Through simulation experiment, we can verify the effectiveness of the autonomous learning methods.

A Study on English Listening and Speaking Autonomous Learning Model Based on Micro Course

Based on the micro audio visual English from the perspective of said independent construction and effectiveness of learning mode as the research content, establish the effective operation of micro class give strong the audio-visual English autonomous learning mode, the use of modern information technology, change the single teaching method, mobile learning and ubiquitous learning, online learning and the traditional learning combined optimization of autonomous learning mode, to greatly improve the students' English comprehensive ability, independent learning ability, also have a positive effect on their English learning attitude, teaching practice and cultivate students' autonomous learning ability thinking and provide some suggestions to English listening and speaking.

Research and Analysis on English Cross-Cultural Teaching and Research System from the Perspective of Constructivism and Multiple Intelligences Theory

In recent years, the common concern of foreign language education is self-learning. Autonomous learning model has been greatly noticed by many researchers with the rise of metacognitive strategy research since 1980s. We discuss the relationship between constructivism and autonomous learning in this paper. Through reflection on the traditional teaching concept, and from the constructivist view of learning to reform the teaching system and with the reform of national curriculum in our country, single course system has been unable to meet the current teaching requirements, therefore, the establishment of the three-level curriculum system reallocates the decision-making power and responsibility of the course. Gardner's theory of multiple intelligences gives us some inspiration and guidance. Although multiple intelligence theory is still in the development stage, but it is intelligent diversity, and the development of interpretation is in place. According to the curriculum concept under the guidance of multiple intelligences theory, we propose to design courses based on students' intelligence differences and characteristics. The English cross culture teaching system can draw lessons from the essence of the theory, so that the curriculum development is more scientific.