E-learning Content Research Articles

E-Learning Content Design for Corrective Maintenance of Toshiba BMC 80.5 based on Knowledge Conversion using SECI Method: A Case Study in Aerospace Company

Knowledge is a combination of experience, value, and information that is based on the intuition that allows an organization to evaluate and combine new information. In an organization, knowledge is not only attached to document but also in routine value creating activities, therefore knowledge is an important asset for the organization. X Corp is a company that focused on manufacturing aerospace components. In carrying out the production process, the company is supported by various machines, one of the machines is Toshiba BMC 80.5. The machine is used occasionally and therefore maintenance activity is needed, especially corrective maintenance. Corrective maintenance is done to make a breakdown machine back to work. Corrective maintenance is done by maintenance operator whose retirement year is close. The long term experience of the maintenance operator needs to be captured by the organization and shared across maintenance division. E-learning is one type of media that can support and assist knowledge sharing. This research purpose is to create the e-learning content for best practice of corrective maintenance activity for Toshiba BMC 80.5 by extracting the knowledge and experience from the operator based on knowledge conversion using SECI method. The knowledge source in this research is a maintenance supervisor and a senior maintenance engineer. From the evaluation of the e-learning content, it is known that the average test score of the respondents who use the e-learning increases from 77.5 to 87.5.

The effect of problem-based e-learning content on the learning achievement in basic computer system course (DSK) of the student of informatics engineering education department

This study was aimed at finding out the difference in learning achievement in basic computer system course (DSK) between the students who learned from content e-problem-based learning in experiment class and those who learned from conventional model in control class in learning basic computer system course. This study used quasi-experimental non-equivalent Pretest Post-test Control Group Design. There were three variables involved in this study. Two of them were independent variable and dependent variable. The independent variable was e-problem-based learning and the dependent variable was learning achievement. Another variable which functioned as covariate was students’prior learning achievement. The population consisted of all students of the first semester in Informatics Engineering Education Department. The sample was selected by using simple group random sampling technique. An essay test was used to know the students’basic computer system learning achievement (DSK). The hypothesis was tested by one-way analysis of co-variance (ANACOVA). The results showed that the mean score in the learning achievement of the students who learned from content e-problem-based learning was higher than that of those who learned from using conventional model. Content e-problem-based learning plays the role in improving students’ learning achievement.

A Design and Development of micro-Learning Content in e-Learning System

In the rapidly changing digital era, changes in learning through e-learning are required. Micro-learning contents were analyzed as a method that can replace the e-learning contents in existing regular courses implemented with large amounts of learning and large contents. In the present study, a method for easy and quick production of contents was presented for effective micro-learning services. The results of the study indicated that the micro-learning content development method presented in the present study is valid in terms of the efficiency of content development. The content development method presented in the present study is considered to bring about new changes to the existing e-learning content development methods utilizing flash, HTML5, H5P, etc.

Student Involvement in e-Learning Content(Practical Reports and Survey Reports,The 44th CELES Conference in Yamanashi)

Student Involvement in e-Learning Content(Practical Reports and Survey Reports,The 44th CELES Conference in Yamanashi)

Learning Analytics Through Serious Games: Data Mining Algorithms for Performance Measurement and Improvement Purposes

learning analytics is an emerging discipline focused on the measurement, collection, analysis and reporting of learner interaction data through the E-learning contents. Serious game provides a potential source for relevant educational user data; it can propose an interactive environment for training and offer an effective learning process. This paper presents methods and approaches of educational data mining such as EM and K-Means to discuss the learning analytics through serious games, and then we provide an analysis of the player experience data collected from the educational game “ELISA” used to teach students of biology the immunological technique for determination of ANTI-HIV antibodies. Finally, we propose critically evaluation of our results including the limitations of our study and making suggestions for future research that links learning analytics and serious gaming.

Original source tracing enabled by e-learning contents system based on crowdsourcing

ABSTRACTA crowdsourcing environment, where there is a very large volume of diverse content resulting from the participation of a mass of unspecified individuals, has resulted in significant changes in education. This paper presents an e-learning content system to manage the inclusion of crowdsourced material on the Web within lecture materials. The e-learning content system comprises a scrape system, learning content editor, and tracing system. As Web content may change with the progress of time, teachers (and students) must check whether the Web-based materials previously used in their classes have been updated. Accordingly, we designed scrape metadata specifications for tracing the original source. These metadata include information on copyrights and tracing, rather than basic data regarding the original source, to allow users to determine whether the original source has been updated. An editor was also configured so that the scraped Web content could be immediately incorporated into the teaching materials for enhanced convenience. The change point tracing accuracy test and utility evaluation performed using this system show that the accuracy of the change point tracing was 97.1% and that this system effectively saves time as compared with checking for changes by entering each URL directly.

Use of E-Learning by University Students in Malaysian Higher Educational Institutions: A Case in Universiti Teknologi Malaysia

This paper examines university students’ intention to utilize e-learning. In this paper, we apply and use the theory of a technology acceptance model. We employ the structural equation modeling approach with a SmartPLS software to investigate students’ adoption process. Findings indicate that the content of e-learning and self-efficacy has a positive impact and substantially associated with perceived usefulness and student satisfaction, which impact university students’ intention to utilize e-learning. Although e-learning has gained acceptance in universities around the world, the study of the intention to use e-learning is still largely unexplored in Malaysia. The developed model is employed to explain the university student’s intention to utilize e-learning. The study concludes that university students in Malaysia have positive perceptions toward e-learning and intend to practice it for educational purposes.

Secure E-Learning Using Data Mining Techniques

This document presents an approach to make e-learning process secure with the help of data mining techniques and comparing and managing results retrieved out it. Data Mining is widely used in IT sector but still, it needs to implement on E-Learning side securely. Data mining serve approach to solve difficult problems when a volume of data is too large. Influence of Data Mining on ELearning is increasing and with growth in E-Learning content, it needs to be secure also. The aim of the paper is to show how securely we can manage the data with the help of data mining with E-Learning as there is large size of educational data available and to provide better direction for daily learning activity. There will be limitation and challenges to make it more secure but it should be profitable on the sides, learner and provider.

E-learning readiness from perspectives of medical students: A survey in Nigeria.

Learning in the medical school of the study university is still by the traditional face-to-face approach with minimal e-communication. This paper assesses student's perspectives of E-learning readiness, its predictors and presents a model for assessing them. A descriptive cross-sectional study of medical students. By proportional quota sampling 284 students responded to a semi-structured self-administered questionnaire adapted from literature. Ethical issues were given full consideration. Analysis was with SPSS version 20, using descriptive statistics, ANOVA, Spearman's correlation, and multiple regression. Statistical significance was considered at P < 0.05. Medical students are ready for E-learning (Mlr = 3.8 > Melr = 3.4), beyond reliance on the face-to-face approach (69.7%), expecting effective (51.1%), and quality improvement in their learning (73.1%). Having basic information and communications technology skills (68.9%) (Mict = 3.7 > Melr = 3.4), access to laptops (76.1%), ability to use web browsers confidently (91.8%) (Mwb = 4.3 > Melr = 3.4), with only few able to use asynchronous tools (45.5%), they consider content design important to attract users (75.6%), and agree they need training on E-learning content (71.4%). They however do not believe the university has enough information technology infrastructure (62.4%) (Mi = 2.7 < Melr = 3.4) nor sufficient professionals to train them (M = 2.9). Predictors are attitude, content readiness, technological readiness, and culture readiness. The model however only explains 37.1% of readiness in the population. Medical students in this environment are ready to advance to E-learning. Predicted by their attitude, content, technological and cultural readiness. Further study with qualitative methodology will help in preparing for this evolution in learning.

To Improve the E-learning System using Data Mining Technique with Internet of Thing Exposure

Nowadays, E-learning resources are developed by academician (institution) and industrialist (industry) side. there are many techniques is implemented to expose the E-learning for remote area people who are unable to adapt formal education system. However, current system is still suffering from content visualization, subject wise content classification and evaluation issues. To propose an E-Learning Content Retrieval & Visualization (ECRV) technique and it enhances the nature of materials and conveyance techniques. the method enforce to e-learning service provider for potential utilization of Internet of things (Iot) to gather information, which will be broke down to get data helpful for basic leadership to enhance the online content visualization for rural people and as well institution. The technique offers a proposition of a framework where information gathered from the Iot gadgets, it will be utilized to enable the instructive establishment's management to settle on educated choices. The method enhances strategies and suggestions for better arranging, checking, assessment, cost effectiveness, and along these lines enhancing nature of the learner. Based on experiment evaluation, proposed techniques improves the content visualization accuracy and content retrieval time compare than existing methods.

Automatic collection of user behavior in 360° multimedia

The arrival of 360° video to the everyday life creates the necessity of assessing both the audiovisual production and the playback environment offered to the final user. Leveraging the standard Experience API (xAPI), that considers collecting micro-interactions with e-learning content, we propose a platform to automatically collect the users’ interaction with applications based on interactive 360° multimedia. To validate the platform, we introduce an example of educational activities based on interactive 360° videos and the tools used to first, annotate these videos and convert them into interactive activities; second, to perform said activity and collect the users’ behavior via xAPI statements; and finally, to convert these statements to meaningful information in the form of user metrics and charts, both at individual level and also aggregated by activity, creating the possibility of finding singular and group behavior. This work concludes that the presented platform helps to analyze how users behave with omnidirectional interactive productions, with the aim of validating and improving its usability, ending with the discussion of future work ideas.

Students’ perceptual quality standards for judging knowledge quality: Development and validation of a perceived e-learning knowledge quality scale

This study examines the factors contributing towards eLearning knowledge quality based on students’ perspective and presents a 5-dimensional scale to evaluate knowledge quality (KQ). It is an extension of our previously published research which had proposed a novel conceptual KQ model. In this paper, we attempt to quantify knowledge quality (KQ), as opposed to adapting data quality (DQ) and information quality (IQ) measurement tools. A qualitative-quantitative sequential mixed-method design was used for the instrument validation. Data was collected at two levels, undergraduate and postgraduate respectively. Exploratory and confirmatory factor analysis confirmed the 5 dimensional second-order perceived eLearning KQ model – comprising of 33 sub-dimensions. The scale is inclusive of five key dimensions (Intrinsic KQ, Contextual KQ, Representational KQ, Accessible KQ, and Actionable KQ) as measures of quality of knowledge gained from eLearning content. The proposed dimensions are the benchmarks that provide insight to educators and administrators in developing and enhancing e-learning content.

Intelligent rule-based approach for effective information retrieval and dynamic storage in local repositories

Rules in artificial intelligence are able to provide inference facilities for making effective decisions in information retrieval. In such a scenario, a keyword-based information retrieval systems use the keywords as indexes generated by Web crawlers without considering semantics. Moreover, many Web search engines perform re-ranking based on relevance feedback. However, the relevant documents in e-learning applications must be stored in local repositories and must be updated dynamically based on the level of the users. Therefore, it is necessary to have an information retrieval system which performs relevant information extraction and stores such relevant information dynamically in local e-learning repositories. In order to address these issues, a new information retrieval and local storage system is proposed in this paper by applying rules for making effective decisions in the storage and retrieval algorithms which are newly proposed in this paper. For this purpose, two new algorithms called intelligent rule-based relevant information retrieval algorithm with semantics and a secured information storage using semantic knowledge representation are proposed in this paper for effectively retrieving the e-learning contents from the Web on computer science subject and to store them in local repositories with semantic indexing. The major advantages of the proposed information retrieval system include increase in accuracy, reduction in retrieval time and effective storage in local repositories for further use.

E-learning teaches attendings “how to” objectively assess pediatric urology trainees' surgery skills for orchiopexy

Established methods to train pediatric urology surgery by residency training programs require updating in response to administrative changes such as new, reduced trainee duty hours. Therefore, new objective methods must be developed to teach trainees. We approached this need by creating e-learning to teach attendings objective assessment of trainee skills using the Zwisch scale, an established assessment tool. The aim of this study was to identify whether or not e-learning is an appropriate platform for effective teaching of this assessment tool, by assessing inter-rater correlation of assessments made by the attendings after participation in the e-learning. Pediatric orchiopexy was used as the index case. An e-learning tool was created to teach attending surgeons objective assessment of trainees' surgical skills. First, e-learning content was created which showed the assessment method videotape of resident surgery done in the operating room. Next, attendings were enrolled to e-learn this method. Finally, the ability of enrollees to assess resident surgery skill performance was tested. Namely, test video was made showing a trainee performing inguinal orchiopexy. All enrollees viewed the same online videos. Assessments of surgical skills (Zwisch scale) were entered into an online survey. Data were analyzed by intercorrelation coefficient kappa analysis (strong correlation was ICC≥0.7). A total of 11 attendings were enrolled. All accessed the online learning and then made assessments of surgical skills trainees showed on videotapes. The e-learning comprised three modules: 1. "Core concepts," in which users learned the assessment tool methods; 2. "Learn to assess," in which users learned how to assess by watching video clips, explaining the assessment method; and 3. "Test," in which users tested their skill at making assessments by watching video clips and then actively inputting their ratings of surgical and global skills as viewed in the video clips (Figure). A total of 89 surgical skill ratings were performed with 56 (65%) exact matches between raters and 89 (100%) matched within one rank. Interclass correlation coefficient (ANOVA) showed statistically significant correlation. (r=0.725, 95% CI 0.571-0.837, F=3.976, p≤0.00001). Kappa analysis of inter-rater reliability showed strong consensus between attendings for average measures with ICC=0.71, 95% CI 0.46-0.95 (p=0.03). We launched e-learning to teach pediatric urology attendings "how to" assess trainee surgical skills objectively (Zwisch scale). After e-learning, there was strong inter-rater correlation in assessments made. We plan to extend such e-learning to pediatric urology surgical training programs.

Development of a visual e-learning system for supporting the semantic organization and utilization of open learning content

In an open e-learning content management environment, relation metadata is of benefit to improve semantic organization and reusability of learning content. Although the suggested relations defined in the SCORM and the extended relations proposed in the past studies can describe semantic relationships, there are some new requirements of semantic organization and utilization of open learning content. Based on existing models, this paper presents an extended relation metadata model for open knowledge communities. In order to help users to author and utilize the semantic relation, the visual authoring system named web-based visual authoring system for relation metadata (WVAS-RM) in the Learning Cell Knowledge Community is designed and implemented to assist the construction and utilization of semantic relations of Learning Cells. The paper presents an empirical evaluation of the teachers’ and learners’ acceptance and satisfaction of the proposed system using the adapted Technology Acceptance Model and System Usability Scale. The semi-structured interviews are also carried out with participants including teachers and students. It is concluded that students and teachers feel confident and satisfied with the system.

Behavioral Tracking in E-Learning by Using Learning Styles Approach

Currently, e-learning is becoming an option as it can save the cost of education, time, and more flexible in its implementation. The main problem that arises is how to create e-learning content that is interesting and really fit the needs of the users. One way that can be done to optimize the content of e-learning is to analyze the user behavior. This study aims to analyze user (student) behavior in KALAM UMP, based on logs report (activity history), which is often called as behavioral tracking. First, the learning style of the students is determined based on Honey and Mumford Learning Styles Model by using Learning Styles Questionnaire. The analysis is done using SPSS 16.0 for Windows. The results shows that student with Reflector and Theorist learning styles access e-learning materials the most. From Spearman Correlation analysis, the relationship between learning styles and students’ behavior in e-learning is found to be very weak (r&lt;sub&gt;s&lt;/sub&gt;=.276, p=.000), but statistically significant (p&amp;lt;0.05). In other words, students’ learning styles and behavior in e-learning have significant impacts on the improvement or degradation of students’ performance. Therefore, from the results of this study, an adaptive KALAM e-learning system which can suits the learning styles of UMP students is proposed. In adaptive e-learning system, students can access learning materials that match the students' learning needs and preferences.

An Experimental Study on Impact of Visuals in e-Learning Content of Art and Media

An Experimental Study on Impact of Visuals in e-Learning Content of Art and Media

Applying the Technology Acceptance Model to Analyze the Saudi University Students' Attitudes and Intentions toward Using E-learning in their Courses

This study aimed to analyze students' behavioral intentions to use e-learning in the kingdom of Saudi Arabia, and to examine the effectiveness of the technology acceptance model as a theoretical basis for understanding these behaviors. The researchers used analytical descriptive approach to identify the perceptions of a sample of (324) students in the Saudi government and private universities in the e-learning system. The researchers developed a questionnaire consisting of (29) items which covered nine main themes.The results of the field study showed the validity of the technology acceptance model as the theoretical background that would help in understanding and clarifying behavioral intentions of the students toward e-learning. The results showed that the behavioral intentions were affected by students' attitudes, personal standards and system accessibility, while they were not directly affected by perceived ease of use and expected benefits of the system. Also, the results showed that students' attitudes were affected by all variables, including expected benefits of the system, personal standards, system accessibility, ease of use and system effectiveness. The study recommended establishing of a center for teaching and learning within the university to present e-learning system and provide written instructions on that system and be responsible for the development of e-learning strategy. Also, the study recommended increasing self-efficacy for students in e-learning system, and providing more Courses in this system. It was also recommended that the department of e-learning system should help students to confirm or increase their positive perceptions toward e-learning system through developing more user-friendly and user-oriented e-learning content.&#x0D; Keywords: E-Learning, Technology acceptance model, Students' attitudes, Behavioral intentions, Saudi universities.

텍스트마이닝을 통한 최고경영자 대상 이러닝 콘텐츠 트렌드 분석

본 연구는 텍스트마이닝 기법 중 토픽 분석을 활용하여 관련 업계 국내 1위 S社의 최고경영자 대상 온라인 교육 콘텐츠 강의 중심으로 원문 스크립트를 분석했다. 지난 5년간(2011~2015)년 서비스된 총 4,824개 콘텐츠를 바탕으로 핵심 키워드를 추출한 다음 주제별 22가지 토픽으로 분류한 후 동향 분석을 수행했다. 이를 통해 최근 콘텐츠 비중이 급증하고 있는 토픽 주제를 확인할 수 있었다. 다음으로 토픽 분석을 통해 분류한 토픽 및 카테고리를 바탕으로 회원 평가 요인을 적용해 카테고리 및 각 토픽별 지적 관심도를 체계화 할 수 있었다. 경영․경제 분야에서는 마케팅전략, 인사/조직, 커뮤니케이션 분야 등이 높은 관심도와 만족도를 나타냈다. 인문 분야에서는 철학, 전쟁사, 역사(서양) 라이프스타일에서는 마음건강 분야가 관심도와 만족도 둘 다 높은 것으로 나타났다. 이와 함께 교육용 콘텐츠가 시대 변화에 민감하게 반응할지라도 회원의 관심과 만족도 제고에는 실패할 수 있다는 사실을 확인할 수 있었다. 최근 콘텐츠 비중은 급증했지만 평균 이하의 만족도를 기록한 IT기술 토픽이 대표적 사례라 할 수 있다. 이를 통해 최고경영자 대상 콘텐츠 제작 시 단순히 기술적 측면의 정보전달에서 끝나는 것이 아닌 기술 적용을 통한 가치혁신에 대한 깊이 있는 시사점을 도출하거나 풍부한 영상 자료를 바탕으로 다양한 볼거리를 제공하는 등 양적인 측면과 함께 질적인 측면을 고려해야 한다는 교훈을 얻을 수 있었다. 본 연구는 포털 사이트 혹은 SNS 자료가 아닌 국내 가장 영향력 있는 이러닝 기업 데이터를 토대로 분석을 진행했기에 보다 심도 있고 실용적인 결과를 도출했다. 또한 이러닝 관련 연구 분야에서 지금까지는 드물었지만 기술의 발달로 점점 연구 조사 방법론으로 기대가 높아진 텍스트마이닝 방법에 대하여 그 적용 가능성을 성공적으로 탐색해 보았다. 기존에는 콘텐츠 운영 현황 분석 시 콘텐츠 프로그램명에 입각, 표면적인 방식으로 분류할 수밖에 없는 한계가 존재했다면 텍스트마이닝 방법론을 활용하면 비정형 데이터 콘텐츠 스크립트를 바탕으로 분석하여 내용을 바탕으로 한 보다 심도 있는 콘텐츠 분류 및 주제 분류를 이끌어 낼 수 있다. 이를 바탕으로 연도에 따른 주제별 콘텐츠 서비스 현황을 도식화한다면 현재 부족한 분야와 필요한 분야에 대한 보다 심도 있는 고찰이 가능하다. 본 연구는 다양한 텍스트마이닝 기법 중에서 이러닝의 상황에서 효과적으로 연구하기 위한 새로운 방법론을 제시했으며 향후 최고경영자 교육 관련 분야별 지적 관심도에 대한 분석에 도움이 될 것으로 기대된다.

Simulation and Gamification in E-Learning Technical Courses

AbstractThe paper is based on the experience gained in creating eLearning courses to keep the student’s interest high, to encourage them to study additional materials in order to achieve the level of complexity proposed by the discipline objectives. The combination of specific gaming-techniques with simulation elements has been combined into designing the e-learning content. The degree of motivation and the interest in the discipline were appreciated by comparing the results obtained by students attending a blending-learning to those students who did the didactic activities in the traditional way. At present, there is a decrease in students’ interest in technical subjects. On one hand, the complexity of these disciplines is high, and moreover, in order for the students to achieve the didactic objectives of the discipline, they must make a sustained effort and combine the individual study with the explanations in the classroom.