Online-Journals.org (International Association of Online Engineering)
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Online Teaching Effect Evaluation and Analysis Using Combined Weighting Technique
Get PDFAn evaluation index system of online teaching satisfaction was established based on the data of a questionnaire survey. In addition, an evaluation index system of an online teaching effect with four first-level indexes and 14 second-level indexes was constructed from the aspects of pre-class preparation, video production, classroom teaching, and after-class guidance. Then, a combination weighting–Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model was established using the analytic hierarchy process (AHP), Criteria Importance Through Inter-criteria Correlation method, and TOPSIS model. The objective is to evaluate the online teaching effect of 10 engineering technology universities in Henan Province. Results show that the online teaching effect of these universities is generally satisfactory. In addition, video production and classroom teaching are important factors affecting online teaching, which, however, is slightly influenced by pre-class preparation. On this basis, this study proposes to enhance online assessment, improve students’ attention in class, strengthen teacher–student communication, actively perfect teaching resources, and create a good learning environment
Integration of AI and Metaheuristics in Educational Software: A Hybrid Approach to Exercise Generation
Get PDFThis study explores the integration of generative artificial intelligence (AI) with Exercise Generation Algorithm+ (EGAL+), a multi-objective harmony search (HS) metaheuristic-based algorithm capable of composing high-quality exercises. These exercises are characterized by their diversity, consistent difficulty, and comprehensive coverage of the source material, tailored to user preferences. One of the main challenges of using metaheuristics to compile exercises efficiently is the initial creation of a large question bank, which often demands significant time and effort from instructors. To overcome this challenge, the integration of a readily available existing generative AI module is proposed. This module is accessed through its application programming interface, autonomously populating the question bank. This sets the stage for EGAL+ to fine-tune the selection and assembly of specific exams. The resulting program enables educators to create an extensive question bank from any educational material, independent of the subject, and subsequently compose exercises with minimal effort. This approach leverages the synergistic benefits of both generative AI and metaheuristicbased optimization, offering a robust and efficient solution for exercise generation
Where Is the Teacher in Data Analytics in Education? Evaluating the Maturity of Analytics Solutions and Frameworks Supporting Teachers
Get PDFCOVID-19 has changed the mindset of many teachers from traditional education to online education. The increased use of learning management systems is leveraging opportunities for increased use of learner data to draw insights about the learners and the learning environment. However, typically learners are the primary beneficiaries, while teachers are quite invisible in the research of data analytics in education, although both are equally important. Thus, this paper aims to position teachers in the spotlight by differentiating between these current two definitions of learning analytics (LA) and teaching analytics (TA) and evaluating the applicability and maturity of existing analytics solutions to support teachers in making decisions on teaching and learning. A systematic literature review was conducted in relevant scientific fields. The results showed clear evidence to distinguish TA from LA and that there are only a few TA solutions and frameworks that can be applied widely or in reality. Evaluating TA solutions and frameworks needs to be attentively considered. This paper also contributes a comprehensive TA process framework that encapsulates the missing elements in the previous models and adds the recent highlights raised in the fields. The implications for research and practice are also discussed
Empowering Safety-Conscious Women Travelers: Examining the Benefits of Electronic Word of Mouth and Mobile Travel Assistant
Get PDFMale solo travelers tend to be more frequent and mobile compared to female solo travelers. This difference can be attributed to travel constraints and safety issues. Social media connects like-minded people and serves as an inspirational resource for deciding where to go and what to do. Numerous netizen travelers are actively sharing their journeys and experiences on their social media profiles. Exciting dining options, diverse locations, recommendations for restaurants, accommodations, and personal experiences are all shared on social media platforms. Millennials rely on electronic word of mouth (e-WOM) to form perceptions about a destination. Thus, the study aims to gain insights into the experiences of solo female travelers who are active on social media platforms. Sentiment analysis is performed on Twitter data by analyzing the latest and trending tweets, which helps in gaining valuable insights regarding the safety of women travelers. Furthermore, research is being conducted to analyze the positive aspects of the travel experience using the Experience Economy model, which provides opportunities for self-discovery and personal growth
Using Interactive Multimedia to Stimulate Early Childhood Students’ Speaking Skills: A Systematic Review
Get PDFInteractive multimedia is currently a significant topic in terms of learning speaking skills. This study aims to describe the use of interactive multimedia in stimulating early childhood speaking skills based on a literature review that has been conducted. The study method used in this literature study is the PRISMA (preferred reporting items for systematic reviews and meta-analyses) method. Data was obtained from the Scopus and Google Scholar databases using scientific articles from reputable international journals with the Scopus Q1–Q4 index. Article searches using the title and keywords “Interactive Multimedia,” “Multimedia,” “Interactive Multimedia in Early Childhood,” or “Speaking Skills” are limited to the last ten years, starting from 2013–2023. The findings showed that the articles in the source database were 10.982 articles, and the final selected papers left 40 articles for review. The results of the study found that: a) the use of interactive multimedia in early childhood learning is dominated by Android-based interactive multimedia (50%), video (30%), and animation (20%); b) the use of interactive multimedia in stimulating early childhood speaking skills is dominated by android media (45%), video (40%), and animation (15%); c) the challenges faced when using interactive multimedia in early childhood learning are limited infrastructure and resources, and not all schools have adequate facilities for the use of technology-based learning media and a lack of teacher creativity. The contribution of this research can provide insight into the use of interactive multimedia to stimulate early childhood speaking skills effectively and efficiently. Thus, the use of interactive multimedia can be a research target in selecting interactive multimedia that is appropriate and effective for stimulating students’ speaking skills at all levels of education and on different research topics
A Textual Content Analysis Model for Aligning Job Market Demands and University Curricula through Data Mining Techniques
Get PDFAddressing the growing disparity between job market demands and the availability of skilled workers, particularly in the technology sector, is a critical challenge in numerous countries. This study introduces a model that assesses the alignment between job market requirements and university curricula, primarily through textual content analysis. Initially, this research illustrates the operational framework of the model through graphical representation. Subsequently, the proposed techniques vital to the functionality of this model are delineated. Specifically, the integration of data mining techniques is employed for the automated extraction of relevant information from both labor market demands and university curricula. An integral aspect of this study involves outlining the methodology for creating the dataset. This phase is essential as it lays the groundwork for further stages, notably the implementation of code to generate comprehensive results. The findings of this study reveal significant insights into the alignment between job market demands and university curricula. Through textual content analysis and data mining techniques, patterns and discrepancies between the two domains are identified, shedding light on areas for improvement in educational provision. Conclusions drawn from this research underscore the importance of bridging the gap between workforce requirements and educational provisions. By leveraging data-driven approaches, educators and policymakers can make informed decisions to enhance curriculum development and better prepare students for the demands of the job market. The impact of this research extends to both academia and industry, offering actionable insights for curriculum alignment and workforce readiness initiatives. Ultimately, this model contributes to the advancement of educational practices and the enhancement of workforce productivity in response to evolving industry needs
Prospective Science Student Teachers’ Online Learning Environment Experiences: Measurement Based on the Net Promoter Score
Get PDFPersonalization is used in online learning to help students achieve SDG 4.C and Education 4.0 indicators. Not many studies have revealed prospective science student teachers’ online learning experiences. A good experience will provide positive and constructive self-knowledge for prospective science student teachers in designing 21st-century digital learning. This study aimed to inquire into prospective science student teachers’ views on online learning using the Net Promoter Score survey. This study involved 29 prospective science student teachers at one of the public universities in Indonesia. This study revealed that online learning provides freedom to express opinions and ideas freely, helps evaluate learning outcomes, online educational resources help understand the contents, and online simulations help understand concepts. The negative experiences in the online learning environment include the lack of interaction with lecturers, online learning has not yet built creative, innovative, and critical thinking skills and has not supported competency development. There is a significant difference between positive and negative online learning experiences, demonstrating how experiences can impact future teacher conception. Based on our findings, recommendations were provided to assist university lecturers in creating and designing an online learning environment to develop the professional competencies of prospective science student teachers
The Dynamics of Community Engagement in Distance Education: A Sociological Analysis Based on Online Learning Platforms
Get PDFThe rapid advancement of information technology has redefined distance education as a fundamental component of modern education systems. The extensive deployment of online learning platforms has further propelled this transformation, catalyzing innovation in educational methodologies while simultaneously presenting novel challenges and demands in the realm of community engagement. In the sphere of online learning, considerable research has been conducted on the efficacy of these platforms. However, studies specifically dedicated to the effective cultivation and maintenance of community engagement through these platforms are notably scarce. Recognized as pivotal for educational outcomes, student satisfaction, and enduring academic success, community engagement within the context of distance education warrants comprehensive exploration. This study delves into this exploration by developing a dynamic model of interaction and a coupled network evolutionary game model that incorporates the nuances of social group dynamics. Initiating with a critical review of existing literature on community engagement in distance learning, the study identifies prevalent limitations. These limitations include an over-reliance on qualitative data, the absence of dynamic analyses, and an oversight of the intricacies of group interactions. To bridge these gaps, we propose a data-driven interaction dynamics model tailored for online learning platforms. Additionally, we suggest a network evolutionary game model that considers the interplay among social groups. These models collectively deepen our understanding of the evolution of community engagement over time and elucidate how both individual and collective behaviors influence the communal health of online learning environments
Interactive Digital Platforms and Artificial Intelligence Applications to Develop Technological Innovation Skills among Saudi University Students
Get PDFIn this paper, we investigate the efficacy of an edX-based learning technology and learning environment augmented with artificial intelligence (AI) applications in fostering technological innovation skills among university students. A quasi-experimental design was employed, involving two groups of bachelor’s degree students (n = 57) from the College of Education at King Khalid University. The experimental group (n = 28) utilized the edX platform with integrated AI features, while the control group (n = 29) employed the traditional Blackboard platform. Both groups participated in the “Using Computers in Education” course. A pre-post assessment of technological innovation skills was conducted, and the data were analyzed using an independent sample t-test. Results revealed a statistically significant difference in skill development between the groups, favoring the edX platform with AI integration. These findings suggest that using blended learning environments may have the potential to enhance students’ technological innovation capabilities
Learning Management System in Education via Mobile App: Trends and Patterns in Mobile Learning
Get PDFThe mobile revolution has influenced students’ preferences for various educational platforms in the new digital era, especially regarding young learners’ utilization of mobile devices such as smartphones, iPads, and other gadgets for mobile learning (m-learning). Because of this, universities that implement learning management systems (LMS) through standard web-based platforms should explore the potential for integrating mobile devices and technologies into m-learning platforms. Through the utilization of this technology, LMS can facilitate continuous user interaction and enhance user awareness of any revisions made to the material. To reach the majority of LMS users, mobile applications must be developed for all major mobile platforms. By utilizing the Web View API, this research combined native mobile and web technologies to develop the mobile application. This strategy was adopted in anticipation of the requirement to create and maintain the application across multiple mobile platforms. It was anticipated that this approach would reduce the time needed for creation, maintain a consistent interface, and enable the use of platform-specific features. It also makes sense to provide mobile device access to some of the LMS virtual classroom’s functions. The K-means algorithm is used for analyzing course material and learning. Nevertheless, achieving this goal might not be an easy process. To enable this form of connection between the LMS and the m-learning applications, this chapter assesses the challenges involved in achieving that goal and presents various common interchange designs and related research and development efforts