• Educational Technology International
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• v.22 no.2
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• pp.255-283
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• 2021

In the early 2020, COVID-19 changed the traditional way of teaching and learning. This paper aimed to explore the impact of college students' perception of course quality on their online learning satisfaction. A total of 4,812 valid samples were extracted, and the difference analysis and hierarchical regression analysis were used to make an empirical analysis of college students' online learning satisfaction. The research results were as follows. Firstly, there was no difference in online learning satisfaction among students by gender and grade. Secondly, learning assessment, course materials, course activities and learner interaction, and course production had a significant positive impact on online learning satisfaction. Course overview and course objectives had an insignificant correlation with online learning satisfaction. Thirdly, the total effect of online learning satisfaction was as follows. Course production had the greatest effect, followed by course activities and student-student interactions, followed by course materials. It was the learning evaluation that showed the least effect. This study can provide empirical reference for college teachers on how to continuously improve online teaching and increase students' satisfaction with online learning.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.125-139
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• 2021

To explore college students' course satisfaction over the course of the semester during which a full-scale digital transformation was in progress due to COVID-19 pandemic, this study analyzed student survey data from a university located in the metropolitan area. To minimize the respondents' burden to answer long list of detailed questions in repetition, the study utilized a pulse survey method and students were asked to answer a brief and regular set of online questions 5 times throughout the semester. The number of survey respondents ranged from 1,640 to 4,116, with an average of more than 3,700. The main results and implications of this study are summarized as follows. First, the survey data indicated that the overall student satisfaction with online courses was above average (3.46/5). Vast majority of students have chosen pre-recorded, contents-based course over real-time, video-based course as their preferred course delivery method and this tendency remained the same throughout the semester. Second, the results of keyword network analysis of open-ended questions indicated that technical issues, increased workload (e.g., course assignments and course attendance) were main causes of online course dissatisfaction. And students suggested an unified online course platform and more interactive course design to further improve online courses in the future.

• Journal of Information Technology Services
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• v.21 no.3
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• pp.73-87
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• 2022

As the COVID-19 pandemic continues to prolong, non face-to-face, online classes has become the new normal in education. To examine the effect of course types and course delivery modes on student course satisfaction, the study analyzed survey data collected from 2,743 students enrolled in a 4-year university located in a metropolitan area. Basic Frequency analysis as well as keyword network analysis were used to analyze student survey data. The main results and implications of the study are as follows. First, the survey results indicated that students preferred asynchronous classes over synchronous online classes. This tendency was consistent regardless of student grades and majors as well as the course type. However, students majoring in more practice-oriented disciplines tend to prefer synchronous online classes and blended classes, and this tendency gets stronger with courses in major. Second, the keyword network analysis results further indicated that interactivity may play an important role in both synchronous and asynchronous online course satisfaction.

• Educational Technology International
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• v.24 no.2
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• pp.203-236
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• 2023

The purpose of this study is to explore the structural relationship between COVID-19-induced sub-dimensions of Online Self-Regulated Learning (OSRL) and satisfaction in online courses conducted in the 'post-COVID-19 era,' as well as to investigate the moderating effects of situational variables such as 'course planning,' 'device type,' and 'course repetition.' To achieve this, the study constructs a measurement model with sub-dimensions of Environment Structuring, Learning Strategy, Help Seeking, and Self-Evaluation as components of OSRL. Participants in this study were selected from university students who enrolled in online courses offered by the Department of Education at University A in the metropolitan area. The research findings reveal several key insights. First, among the sub-dimensions of Online Self-Regulated Learning, Environment Structuring, Learning Strategy, and Self-Evaluation significantly influence satisfaction with online courses. Second, students' satisfaction with online courses significantly influences their intention to continue participating in such courses. Third, 'course planning' during online course hours and 'course repetition' play a moderating role in the relationship between sub-dimensions of Online Self-Regulated Learning and satisfaction. Based on the discussion of these research results, this study concludes by suggesting some future implications and challenges of online courses.

• Journal of Engineering Education Research
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• v.25 no.2
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• pp.13-21
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• 2022

In many existing studies, the analyses on the application and effect of the project-based learning model (PBL), a student-centered teaching and learning strategy, have been emphasized and carried out in various majors and courses. This case study analyzes the effects of applying a project-based learning model to the engineering accounting course for engineering students in 2021 in the context of the COVID-19 pandemic, compared with the offline course in 2019 and the simple online course in 2020. Project team consisting of 2-3 students carried out online collaborative learning activities for solving open-ended problems through the 5-step PBL procedure including presenting the final result. Except for this online PBL application in 2021, textbooks, lecture contents, assignments, and tests were implemented the same for each semester for three years. Through lecture evaluation and survey by students, the online PBL application semester showed higher effects in inducing student-centered learning, lecture satisfaction, and student competency improvement compared to the non-applying semesters, further, it was evaluated that the online PBL application to the course and evaluation method were more appropriate than other semesters. It is expected that the online PBL method and operation procedure applied in this study can be utilized as a best practice for the design and operation of various online courses for student-centered collaborative learning activities and educational effects.

• Educational Technology International
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• v.18 no.2
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• pp.193-213
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• 2017

This study aimed to explore online learning profiles of in-service teachers in South Korea, focusing on video lecture and discussion activities. A total of 269 teachers took an online professional development course for 14 days, using an online learning platform from which web log data were collected. The data showed the frequency of participation and the initial participation time, which was closely related to procrastinating behaviors. A cluster analysis revealed three online learning profiles of in-service teachers: procrastinating (n=42), passive interaction (n=136), and active learning (n=91) clusters. The active learning cluster showed high-level participation in both video lecture and discussion activities from the beginning of the online course, whereas the procrastinating cluster was seldom engaged in learning activities for the first half of the learning period. The passive interaction cluster was actively engaged in watching video lectures from the beginning of the online course but passively participated in discussion activities. As a result, the active learning cluster outperformed the passive interaction cluster in learning achievements. The findings were discussed in regard to how to improve online learning environments through considering online learning profiles of in-service teachers.

• Educational Technology International
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• v.16 no.2
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• pp.85-110
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• 2015

This study investigated whether college students' self-efficacy, learning strategy utilization, academic burnout, and school support predict course satisfaction and learning persistence. To this end, self-efficacy, learning strategy utilization, academic burnout, and school support were used as prediction variables; and course satisfaction and learning persistence, as criterion variables. The subjects were 178 students who registered for online and mobile "Culture and Art History" courses at K online university. They participated in an online survey. Multiple regression analysis revealed that self-efficacy and learning strategy utilization positively predicted course satisfaction and learning persistence, academic burnout negatively predicted them, and school support predicted neither. Accordingly, we suggest that raising self-efficacy and learning strategy utilization, and reducing academic burnout in the learning environment will improve the course satisfaction and learning persistence of online learners.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.57-66
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• 2021

The purpose of this study was to verify whether the Interactive Cinematherapy Course developed based on discussion is still effective for emotional intelligence and empathic ability, even in a college lecture environment where courses are given online due to COVID-19. The subjects were enrolled in the Interactive Cinematherapy Course and experienced either an online (N=139) or offline (N=212) course before and after COVID-19. To the offline course, students were given structural questions and conducted discussions, whereas the online course students were given feedback via e-mail to substitute discussion. The results were as follows. Compared to the offline courses, students in both online/offline courses commonly showed an increase in "Other's emotion appraisal", "Cognitive Empathy", "Perspective taking", "Fantasy", and "Emphatic Concern". The online course students showed an increase in the "Use of emotion", while offline course students showed an increase in "Self emotion appraisal". This shows that online and offline courses do not have a significant difference in effects. In qualitative research, the lecturer's communication ability and concern helped enhance the effectiveness of the Interactive Cinematherapy Course given online. This implies that communication between the lecturer and students and role of the lecturer are more important than the online environment.

• The Journal of Korean Association of Computer Education
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• v.19 no.3
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• pp.55-66
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• 2016

This study explored the rating tendency of online university learners in their course evaluations and its effects on the course evaluation results. Data including the subjects' demographic information, learning activities, rating tendency, and course evaluation results were collected from 1,098 learners in an online university in the spring semester of 2015. There were three main findings. First, the subjects showed distinctive rating tendencies in participation rates for course evaluation and rating consistency. The participation rates went from one extreme (0%) to the other (100%), and the rating consistency among the test items was highly related to that among the courses as a whole. Second, the subjects showed different tendencies in terms of course evaluation period, rating consistency, and course evaluation results according to demographic information and learning activities. Third, course evaluation results were independently affected by demographic information, learning activities, and rating consistency. The study was meaningful in that it explored learners' rating tendencies concretely and suggested that such tendencies should be considered in analyzing course evaluation results.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.360-374
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• 2024

A personalized course recommendation algorithm based on deep learning in an online education cloud platform is proposed to address the challenges associated with effective information extraction and insufficient feature extraction. First, the user potential preferences are obtained through the course summary, course review information, user course history, and other data. Second, by embedding, the word vector is turned into a low-dimensional and dense real-valued vector, which is then fed into the compressed interaction network-deep neural network model. Finally, considering that learners and different interactive courses play different roles in the final recommendation and prediction results, an attention mechanism is introduced. The accuracy, recall rate, and F1 value of the proposed method are 0.851, 0.856, and 0.853, respectively, when the length of the recommendation list K is 35. Consequently, the proposed strategy outperforms the comparison model in terms of recommending customized course resources.