Online Autonomous Learning Research Articles

Enhancing language learning: EFL teachers’ insights on online autonomous learning activities

Students can improve their skills, broaden their knowledge, and practice their language using online language learning resources. These resources include several activities designed to meet students’ requirements, promote self-learning, and fit their learning preferences. This study investigates EFL teachers’ perceptions of students’ performance in online self-learning activities during laboratory classes. They reflect on how these activities can excite students’ interest, motivate them, and involve them. The research addresses two questions: (a) what teachers think about the importance of e-learning laboratory activities in language learning, and (b) how these activities can promote personalized and active learning. The researchers employed a survey, interviews, field notes, reflections, and class recordings to describe, examine, and interpret the data through narrative analysis. The results show encouraging trends in engagement, motivation, interest, time, independence, and future use. Most students had strong critical thinking skills and enjoyed the self-completion of the assignments. Few learners became demotivated and lost interest owing to the absence of grading, seriousness, or effective surroundings. Additionally, the research shows that compared to traditional face-to-face learning, online learning gives teachers more time and opportunities to update their methods and help students in new ways.

Blended pedagogy for computer programming language

In the face of the challenges posed by the COVID-19 pandemic, the hybrid teaching model has garnered significant attention for its combination of the depth of traditional education with the convenience of distance learning. Focusing on the domain of computer programming language instruction, this study innovatively designs a hybrid teaching strategy aimed at fully exploiting the flexibility of its teaching design and the variety of pedagogical approaches. The strategy integrates face-to-face teaching with online autonomous learning, incorporating project-based teaching methodologies and immediate feedback mechanisms to facilitate active student engagement and deep learning. Through a year-long practice in a C++ programming course, encompassing 68 students, the study empirically validates the effectiveness of the hybrid teaching approach. It not only demonstrates remarkable educational outcomes, enhancing the quality of programming instruction and student satisfaction with their learning experience, but also employs Bayesian analysis to delve into the relationship between learning trajectories and students’ sense of self-efficacy. By focusing on key indicators during the learning process, such as the timeliness and quality of online learning, laboratory work, and project assignments, the study then utilizes Bayesian models to directly assess the impact of these learning behavior metrics on students’ perceived self-efficacy. The findings reveal that students with outstanding academic achievements exhibit higher levels of self-efficacy, confirming that academic performance can reasonably reflect teaching effectiveness and provide a quantifiable basis for assessing individual learning progress. Consequently, this research not only contributes a novel strategy to computer programming education practice but also offers a valuable reference for the application of hybrid teaching models in other disciplines. Furthermore, it promotes in-depth contemplation on post-pandemic innovations in teaching modes and issues of educational equity, laying a solid foundation for constructing a more adaptive and inclusive future education system.

Does checking-in help? Understanding L2 learners’ autonomous check-in behavior in an English-language MOOC through learning analytics

AbstractConcerns over the quality of teaching in massive open online courses devoted to language learning (LMOOCs) have prompted extensive research on learning behavior in such courses. The purpose of this study is to gain a better understanding of autonomous learning check-ins – that is, individuals sharing their own learning records and/or other information about their learning-related experience – a novel behavior that has not been studied in previous LMOOC research. Using learning analytics, we found that just 6.2% (n = 699) of a sample of 11,293 learners autonomously engaged in check-in behavior, and that the content of these learners’ check-ins varied considerably according to their contexts and the language skills they were seeking to acquire. We further found (1) a positive association between check-in behavior and LMOOC completion; (2) that students who chose to check in earned relatively low grades on unit quizzes, especially in their early stage of learning, but outperformed the non-check-in group significantly in final exam scores; and (3) that those who checked in engaged with a significantly wider array of in-LMOOC learning components than those who did not, and thus accessed a wider system of language-learning experiences. Taken together, these results confirm that check-in behavior can aid the process of learning in an LMOOC and further highlight this behavior’s wider potential to aid self-directed autonomous online learning.

Teachers’ motivating styles and students’ agentic engagement in online learning

Facing the growing popularity of autonomous online learning, students require more agentic engagement (AE) to construct a supportive learning environment for themselves. Existing studies based on self-determination theory (SDT) state that teachers’ motivating style can predict students’ engagement, and students’ competence beliefs can moderate the predicting effect. However, few studies have discussed the correlation between teaching motivating styles and AE in middle- and high-school online courses, considering the students’ self-regulated learning (SRL) ability as a moderator. To address this gap, this study examined the effect of autonomy-supportive motivating style (ASMS) and controlling motivating style (CMS) on AE, taking into account students’ SRL ability as a potential moderator. A total of 425 valid questionnaires were collected to evaluate the model. The results revealed that teachers’ ASMS positively predicted students’ AE; CMS positively predicted students’ AE; and SRL ability positively predicted AE. However, SRL ability did not significantly moderate the correlation between teachers’ motivating styles and AE. These findings provide educators with insights into how to improve students’ AE, and suggest that teachers should be involved as much as possible in online teaching interactions, and explore strategies to enhance the effectiveness of students’ AE.

Using case-based learning supported by role-playing situational teaching method in endocrine physiology education.

Embedding clinically relevant learning experience in basic science subjects is desired for the preclinical phase of undergraduate medical education. The present study aimed to modify case-based learning (CBL) with a role-playing situational teaching method and assess the student feedback and learning effect. One hundred seventy-six sophomore students majoring in clinical medicine from Harbin Medical University were randomly divided into two groups: the control group (n = 90), who received traditional hybrid teaching, and the experimental group (n = 86), who received the role-playing situational teaching. Students in the experimental group were given a 1-wk preclass preparation to dramatize a hyperthyroidism scenario through online autonomous learning of thyroid physiology and performed the patient's consultation process in class, followed by a student presentation about key points of lecture content and a question-driven discussion. A posttest and questionnaire survey were conducted after class. The test scores of the two groups had no statistical differences, whereas the rate of excellence (high scores) of the experimental group was significantly higher than that of the control group. Furthermore, the record of online self-directed learning engagements was significantly improved in the experimental group. In the questionnaire, >70% of the students showed positive attitudes toward the role-playing situational teaching method and were willing to participate in other chapters of the physiology course. Such results show that CBL supported by a role-playing situational teaching method encourages active learning and improves the application of basic knowledge of physiology, which can be incorporated in the preclinical curricula to bridge the gap between theory and practice.NEW & NOTEWORTHY Formal application through structured role-play is often overlooked in physiology education. In traditional case-based learning (CBL), clinical cases are the subject and unfocused discussion often occurs. The present study aimed to modify CBL with a role-playing situational teaching method and assess the student feedback and learning effect. The results show that the new teaching model encourages active learning and improves the application of basic knowledge of physiology.

Functional Analysis of English Carriers and Related Resources of Cultural Communication in Internet Media

Abstract In the Internet intelligent teaching platform, students’ demand for English cultural content is increasingly obvious. To help students quickly locate the overall content of resources in online autonomous learning, this study constructs a video annotation model for online teaching. This method classifies text by designing an optimized Bidirectional Encoder Representation from the Transformers model and designs a Text Rank keyword extraction model that integrates external knowledge and semantic feature weights. The extraction of knowledge points contained in audio and video resources can be realized. In the experimental data set, a relatively complete video content summary could be obtained by combining the first three sentences with the last two sentences. The F1 value of the classification model was up to 91.3%. In addition, the BERT-T model proposed in this article had the best effect on the experiment. Compared with the original BERT model, the macro-F1 was 0.8% higher and 0.5% higher than the Ro BERTA model. In the keyword extraction experiment, B-Text Rank was 2.19 and 2.85% higher than the traditional Text Rank in the two datasets. The experiment shows that the BERT-Text Rank network resource annotation model has excellent application performance in English online autonomous teaching and could guide students to learn.

Corpus-driven recommendation algorithm for English online autonomous learning resources

Corpus-driven recommendation algorithm for English online autonomous learning resources

Study on the differences in behaviour characteristics of distance online autonomous learning in different network virtual environments

Study on the differences in behaviour characteristics of distance online autonomous learning in different network virtual environments

A Tutorial-Generating Method for Autonomous Online Learning

A Tutorial-Generating Method for Autonomous Online Learning

Corrections to “A Tutorial-Generating Method for Autonomous Online Learning”

Corrections to “A Tutorial-Generating Method for Autonomous Online Learning”

The Impact of ChatGPT on the Learning Efficacy of Chinese College Students

With the popularization of online autonomous learning and the development of artificial intelligence, more and more students are starting to use ChatGPT to assist learning. Research gaps exist in understanding the intersection of artificial intelligence (AI), ChatGPT, and education. Based on reviewing relevant literature from domestic and foreign scholars, the authors combine quantitative and qualitative research methods to explore the relationship between the usage of ChatGPT and the learning efficacy of Chinese college students. A total of 113 questionnaires were collected, and 100 valid questionnaires were obtained through screening eventually. The empirical results show that: looking up information, doing coursework and assisting with dissertation writing were common functions for college students to use ChatGPT; The impact of ChatGPT on the learning efficacy of domestic college students was relatively positive, but it was not yet significant; The frequency of using ChatGPT among college students of different genders showed significant differences, and the frequency of using ChatGPT among college students of different grades showed significant differences. Through interviews with 3 out of 100 students, the following conclusion was drawn: they generally believed that ChatGPT was more useful in solving difficult problems and could help them achieve success.

Indonesian EFL Students’ Autonomus Learning Implementation in Online Learning

Although studies on online learning have been widely discussed, most of the studies still focus on the students’ experiences adjusting to online learning. However, few studies have analyzed students’ experiences in online learning regarding autonomous learning implementation. This study aimed at identifying Indonesian EFL students' autonomous learning implementation in online learning. A questionnaire adapted from Khotimah et al. (2019) and Hidayati and Husna (2020) was used as a single instrument to obtain data from EFL students from 22 universities around Indonesia. This study sample was selected using a random sampling technique, and the data was analyzed using a simple percentage statistics formula. The results showed how students learned English online in four areas: listening, reading, speaking, and writing. They also showed how the students felt about online learning on their own. These experiences relate to students’ experiences selecting learning materials and learning activity preferences. These preferences are divided into learning English for academic purposes and learning English for pleasure. However, regarding students’ efforts to foster their autonomous online learning, the students had implemented three categories of autonomous learning, namely the initiating process, monitoring process, and evaluating process in their learning process. Hence, the research results are expected to provide new insights for the readers about implementing online learning, which can support the students to be more autonomous learners.

An online autonomous learning and prediction scheme for machine learning assisted structural optimization

In this paper, an online autonomous learning and prediction (ALP) scheme is proposed for machine learning assisted structural optimization (MLaSO) to reduce total computational time with controlled accuracy of objective function prediction. In MLaSO, information in selected routine iterations is used via online learning to train a Neural Network, which is then used to perform online prediction of information in subsequent other iterations. Although using MLaSO with pre-defined learning and prediction scheme can save total computational time, it is difficult to determine the most suitable learning and prediction scheme prior to solving an optimization problem. The present ALP method enables autonomous activation of online learnings and predictions via maximizing specific computational efficiency while constraining the accuracy of the objective function prediction. Four numerical 2D and 3D examples are presented to demonstrate the computational benefits of integrating ALP with gradient based MLaSO method. The present numerical results demonstrate that: (a) using ALP in MLaSO can save more computational time than using the pre-defined scheme with similar prediction accuracy, and (b) more computational time can be saved by allowing larger tolerance in the accuracy of objective function prediction.

Retracted: Corpus-Driven Resource Recommendation Algorithm for English Online Autonomous Learning.

[This retracts the article DOI: 10.1155/2022/9369258.].

Research and Practice of Precision Evaluation in Blended Learning Context

Precision evaluation plays a vital role in improving students’ blended learning performance. In accordance with the teaching philosophy of Outcome-Based Education (OBE) and education requirements in China, this paper put forward a Three-stage Blended Learning and Evaluation (TsBLE) method to improve students’ learning performance. The TsBLE method assumes that the blended learning process can be divided into three stages: pre-class online autonomous learning, in-class off-line in-depth research and after-class consolidation. Based on this assumption, the TsBLE method emphasizes that precision evaluation in blended learning should be multi-dimensional and fine-grained. Teaching practice was carried out to evaluate the effectiveness of the TsBLE method. The results showed that this method can effectively improve students’ learning performance and help teachers adjust teaching strategies in time.

Study on the differences in behaviour characteristics of distance online autonomous learning in different network virtual environments

Study on the differences in behaviour characteristics of distance online autonomous learning in different network virtual environments

Corpus-driven recommendation algorithm for English online autonomous learning resources

Corpus-driven recommendation algorithm for English online autonomous learning resources

Current Situation Dissection and Ability Cultivation Strategies of Online Autonomous Learning for College Students

Current Situation Dissection and Ability Cultivation Strategies of Online Autonomous Learning for College Students

Research on Influence Factors and Driving Strategies of Online Autonomous Learning

Research on Influence Factors and Driving Strategies of Online Autonomous Learning

English Education Students' Attitude toward Autonomous Learning Amidst the Abundant Online Learning Sources

The development of information and communication technology has provided various learning resources that can be accessed by students anytime and anywhere, including for learning languages. This should provide benefits for improving students’ language skills. This article explored several things related to the use of online learning resources by students majoring in English Education, including three problem statements, namely: (1) what kind of online learning activities did the students do for autonomous learning purposes? ; (2) what kind of improvement did they obtain from autonomous online learning activities? ; (3) what were the challenges they found in using online learning sources for autonomous learning activities? This study utilized quantitative and qualitative data to provide detailed description. Furthermore, the data was analyzed thematically. This study revealed that students tended to use social media, Youtube, and university LMS for their autonomous learning. Their reported that their autonomous learning improved their English skills, especially in listening, speaking and vocabulary mastery. It was influenced by their interest in certain skills and the learning resources they accessed. The challenges associated with online autonomous learning were unstable connections, lack of clear learning goals, and low student motivation. Several implications and recommendations are also discussed in this study.