Improvement of Students’ Autonomous Learning Behavior by Optimizing Foreign Language Blended Learning Mode

Given the significance of cultivating students’ autonomous learning ability, there is a need to develop an instructional model that can improve students’ awareness and behavior of autonomous learning, as well as to explore the effectiveness and optimization of this model effectively. Taking college English course as a case study, this paper constructs a blended learning mode based on SPOC, which combines advantages of online and offline teaching. 15 types of nonredundant sets resulting from 500 questionnaires has been explored, and the optimal factor combinations have been found out from 15 types with the technology of data mining to optimize the mode constructed previously. Optimized blended learning mode, emphasizing the optimal factors more, has been applied to College English curriculum design and teaching practice in China. Surveys of students’ achievement and autonomous learning behavior have been conducted after experiment. The results of the research indicate that the optimized blended learning mode will stimulate foreign language learners’ learning motivation, cultivate their autonomous learning ability, so as to construct and improve their autonomous learning behavior further.

Identifying Students’ Problems on Critical Thinking as a Way to Foster Higher Order Thinking Skills

Students in the old days were not taught to think for themselves in a logical, systematic, and coherent way. They simply regurgitated lectures and text materials back to the teachers. Integrating the traditional method of teaching with the critical thinking model would be the better alternative for teachers to prepare students to solve problems in the future. The samples of this study are the whole graduated students from English Department Students at University of PGRI Yogyakarta, starting from 2018-2021. It is descriptive qualitative research, focusing on the assessment matrix in the assessment of thesis examination by giving in-depth highlight on trends. From the data analyses, it is inferred that gender would give less impact to the successfulness of developing Critical Thinking. On the other hand, the autonomous learning would never give the same good results from one condition to another. It is revealed from the finding that learning with peers impacts better than the autonomous learning and learning with teachers.

Immersive virtual-reality computer-assembly serious game to enhance autonomous learning

Immersive virtual reality (VR) environments create a very strong sense of presence and immersion. Nowadays, especially when student isolation and online autonomous learning is required, such sensations can provide higher satisfaction and learning rates than conventional teaching. However, up until the present, learning outcomes with VR tools have yet to prove their advantageous aspects over conventional teaching. The project presents a VR serious game for teaching concepts associated with computer hardware assembly. These concepts are often included in any undergraduate’s introduction to Computer Science. The learning outcomes are evaluated using a pre-test of previous knowledge, a satisfaction/usability test, and a post-test on knowledge acquisition, structured with questions on different knowledge areas. The results of the VR serious game are compared with another two learning methodologies adapted to online learning: (1) an online conventional lecture; and (2) playing the same serious game on a desktop PC. An extensive sample of students (n = 77) was formed for this purpose. The results showed the strong potential of VR serious games to improve student well-being during spells of confinement, due to higher learning satisfaction. Besides, ease of usability and the use of in-game tutorials are directly related with game-user satisfaction and performance. The main novelty of this research is related to academic performance. Although a very limited effect was noted for learning theoretical knowledge with the VR application in comparison with the other methodologies, this effect was significantly improved through visual knowledge, understanding and making connections between different concepts. It can therefore be concluded that the proposed VR serious game has the potential to increase student learning and therefore student satisfaction, by imparting a deeper understanding of the subject matter to students.

A Study on the Efficiency and Countermeasures of Network-Based Autonomous Learning Platform for Vocational College English Learners

This paper investigates the efficiency of 289 vocational college English learners using the network-based autonomous learning platform in Guangdong province in China. The results show that learners have a positive attitude toward the network-based extracurricular English autonomous learning, and learners with different English foundation have different requirements for extracurricular online autonomous learning. This paper puts forward some countermeasures on how to make full use of the network-based extracurricular English autonomous learning.

Construction and Analysis of Intelligent English Teaching Model Assisted by Personalized Virtual Corpus by Big Data Analysis

At present, a new round of scientific and technological revolution and industrial transformation with information technology at its core are accelerating. At present, a new round of scientific and technological revolution and industrial transformation with information technology at its core is accelerating. The challenge of new economy and new industry has put forward new requirements for the training of talents in China. The challenges of new economy and new industry have put forward new requirements for the cultivation of engineering talents in China. Based on corpus, this study constructed a model of intelligent English teaching assisted by virtual corpus. The traditional teaching of college English reading is based on, around, and for texts. Using DDL model, teachers can break the limitation of textbooks. On the basis of analyzing the general idea of the text, they can search out massive real corpus related to the general idea of the text by searching the core words in the text, so as to provide extensive reading resources for students in the maximum range. At the same time, teachers can rely on the corpus to design different types of teaching activities, realize student-centered task-based, inquiry-based, and autonomous learning and cultivate students’ critical thinking ability, practical ability, and cross-cultural communication ability. This model breaks the limitation of “classroom + textbook,” realizes student-centered task-based, exploratory, and autonomous learning, trains interdisciplinary new engineering talents needed by emerging industries and new economy in the future, and promotes the sustainable development of English teaching. Corpus-data-driven college English teaching mode breaks the limitation of “classroom + textbook,” changes the traditional college English teaching mode, and realizes student-centered task-oriented, inquiry-based, and autonomous learning.

Semi-Autonomous Learning Algorithm for Remote Image Object Detection Based on Aggregation Area Instance Refinement

Semi-autonomous learning for object detection has attracted more and more attention in recent years, which usually tends to find only one object instance with the highest score in each image. However, this strategy usually highlights the most representative part of the object instead of the whole object, which may lead to the loss of a lot of important information. To solve this problem, a novel end-to-end aggregate-guided semi-autonomous learning residual network is proposed to perform object detection. Firstly, a progressive modified residual network (MRN) is applied to the backbone network to make the detector more sensitive to the boundary features of the object. Then, an aggregate-based region-merging strategy (ARMS) is designed to select high-quality instances by selecting aggregation areas and merging these regions. The ARMS selects the aggregation areas that are highly related to the object through association coefficient, and then evaluates the aggregation areas through a similarity coefficient and fuses them to obtain high-quality object instance areas. Finally, a regression-locating branch is further developed to refine the location of the object, which can be optimized jointly with regional classification. Extensive experiments demonstrate that the proposed method is superior to state-of-the-art methods.

Analisis Penerapan Project Based Learning Approach dalam Pembelajaran On-Line dimasa Pandemi Covid 19

Project based learning merupakan suatu pendekatan yang menekankan peserta didik sebagai student-centred dalam kegiatan pembelajaran. Penelitian ini merupakan penelitian kualitatif dimana mahasiswa semester 2 menjadi sample penelitian yang dipilih secara purposive. Penelitian ini bertujuan untuk mengetahui persepsi mahasiswa terhadap penerapan pendekatan project based learning serta efek terhadap mahasiswa dalam kelas public speaking yang dilaksanakan secara online. Data dalam penelitan ini dikumpulkan menggunakan wawancara, observasi, dan analisis dokumen. Terdapat 12 mahasiswa yang menjadi partisipan dalam penelitian ini. Hasil dari penelitian menunjukkan bahwa mahasiswa memberikan respon yang positif terhadap penggunaan pendekatan project based learning. Mereka merasa dapat belajar sambil mengerjakan tugas. Penggunaan pendekatan ini membuat mahasiswa menjadi termotivasi dalam mengikuti perkuliahan, kemampuan mereka menjadi lebih baik dalam autonomous learning, menyusun ide atau tugas, bekerjasama dengan teman, menyampaikan ide kepada orang lain atau komunikasi, dan memecahkan masalah. Tetapi ada beberapa kendala yang harus diminimalisir yaitu besarnya biaya penggunaan kuota, jaringan yang tidak stabil, serta mahasiswa yang terkadang bosan karena harus menatap layar HP atau laptop sepanjang pembelajaran.