Online-Journals.org (International Association of Online Engineering)
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Evaluating Future Trends of Digital Storytelling in Higher Education: A Bibliometric Analysis
Get PDFDigital storytelling has proven to be a pedagogy that can enhance learners’ motivation and multiple competencies. However, there is a lack of conceptual research on digital storytelling in higher education. This study aims to assess the trends of digital storytelling in higher education through bibliometric analysis. The PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) procedure was used to extract data from the Scopus and Web of Science databases. A thorough review was conducted to classify and rank the relevant literature on digital storytelling in higher education. The result shows that research on digital storytelling in higher education is increasing annually, but there are significant regional and disciplinary gaps at the higher education level. The main findings of this study are helpful for practitioners and researchers to understand better the current state of research on digital storytelling in higher education and to provide directions for future research
Probing Scaffolding Self-Regulated Learning Responses, Resources Contribution and Target Achievements of University Students in Statistics Course
Get PDFScaffolding self-regulated learning is an emerging research agenda in higher education. However, scaffolding self-regulated learning in a relatively complex subject such as statistics is still understudied. The present study addresses this matter by observing university students’ engagement in scaffolding self-regulated learning in a statistics course focusing on their scaffolding responses, resources contribution and target achievements. It was an exploratory case study with the participation of 26 private university students who are enrolled in the fifth semester as their third-year studies. The results indicate that university students are aware of statistics learning goals but overtargeting achievements, as they were less likely to achieve their decided targets. Students prefer to write a self-reflection than take notes. The different duration of watching videos and reading modules does not vary in quiz performance. The current findings add a novel understanding that self-regulated statistics learning requires advanced scaffolds to promote higher outcomes because of its characteristics as a complex and abstract subject
Digital and Mobile Applications for Autism Inclusion
Get PDFThe purpose of this research analysis is to identify the contribution of online applications to the integration of autistic individuals in typical educational contexts. The difficulties faced by both autistic people and teachers are analyzed. These difficulties are calls to improve the technology that has been introduced into the daily life of children and adults with autism. As people are becoming familiar with technology by a very young age, inexpensive applications can be used through devices such as mobiles/tablets. These applications have the power to strengthen areas in which autistic individuals fall behind. The research articles we have studied present data over the last decade, and their results are applicable to a large portion of the autistic population. Data highlighted in current analysis may be useful for improving web applications targeting autistic individuals and their families
The Impact of Gadget Usage on the Social and Linguistic Development of Primary School Students
Get PDFThe objective of this research is to describe the impact of gadget usage on the social and linguistic development of primary school students. The study used the mixed-methods sequential explanatory design. In determining the subject of the research—namely, 251 children consisting of second graders and fifth graders in Jakarta, Indonesia—we used purposive sampling. Purposive sampling was also used to determine the research location—namely, two public primary schools and two private primary schools in Central and South Jakarta. As for the data collection, questionnaires, interviews, and observations were employed, resulting in quantitative data presented statistically in tables and charts. The regression analysis performed to figure out the social development of the primary school students in Jakarta resulted in a score of 0.000, suggesting that the students possess social capabilities and skills displayed when they are among their peers—namely, understanding the emotional conditions of their friends, accepting themselves, and maintaining friendship. The students are also capable of comprehending the thought, feeling, and behavior of their friends, thus enabling them to develop well-being skills. A regression analysis score of 0.001 suggests that gadget usage at home and at school influence the linguistic development of the primary school students. Our qualitative analysis corroborates the regression score by suggesting that gadget usage improves the growth and development of the social and linguistic behavior of the primary school students. In light of the impacts of gadget usage on the social and linguistic development of the primary school students, it is highly recommended that both the school and the parents put in place a code of ethics and educational guidance regarding gadget usage to mitigate the negative impacts of gadgets on students
A Learning Health-Care System for Improving Renal Health Services in Peru Using Data Analytics
Get PDFThe health sector around the world faces the continuous challenge of improving the services provided to patients. Therefore, digital transformation in health services plays a key role in integrating new technologies such as artificial intelligence. However, the health system in Peru has not yet taken the big step towards digitising its services, currently ranking 71st according to the World Health Organisation (WHO). This article proposes a learning health system for the management and monitoring of private health services in Peru based on the three key components of intelligent health care: (1) a health data platform (HDP); (2) intelligent technologies (IT); and (3) an intelligent health care suite (HIS). The solution consists of four layers: (1) data source, (2) data warehousing, (3) data analytics, and (4) visualization. In layer 1, all data sources are selected to create a database. The proposed learning health system is built, and the data storage is executed through the extract, transform and load (ETL) process in layer 2. In layer 3, the Kaggle dataset and the decision tree (DT) and random forest (RF) algorithms are used to predict the diagnosis of disease, resulting in the RF algorithm having the best performance. Finally, in layer 4, the intelligent health-care suite dashboards and interfaces are designed. The proposed system was applied in a clinic focused on preventing chronic kidney disease. A total of 100 patients and six kidney health experts participated. The results proved that the diagnosis of chronic kidney disease by the learning health system had a low error rate in positive diagnoses (err = 1.12%). Additionally, it was demonstrated that experts were “satisfied” with the dashboards and interfaces of the intelligent health-care suite as well as the quality of the learning health system
Project-Based Learning: Authentic Engineering Assessment Supported by Model Design
Get PDFIn this study, we examined the effects of project-based learning (PBL) on student learning outcomes related to the subject of signals and systems in the field of electronic engineering at the Universidade Estadual de Campinas (UNICAMP) in Brazil and at the Pontificia Universidad Javeriana (PUJ) in Colombia. We used two methods to assess the effect of PBL on student outcomes: (1) we used the Signals and Systems Concept Inventory (SSCI) to measure the increase in conceptual understanding of signals and systems among electronic engineering UNICAMP students as a consequence of implementing PBL; and (2) we compared the results on a comprehensive signals and systems final exam of a group of electronic engineering students at PUJ who received PBL to those who did not. Results indicated that (1) UNICAMP students achieved outcomes comparable to those of Buck and Wage’s study: UNICAMP students taught with projects learned more than students in 15 Signal and Systems lecture-based courses in the United States; and (2) PUJ students taught with projects received higher final exam grades than students taught via lectures. Students were able to apply their knowledge of signal processing and systems analysis using MATLAB models. These models provide authentic assessments of engineering students’ knowledge and skills. The findings of this study indicate that PBL is more effective than lectures in enhancing students’ understanding and application of signals and systems concepts
Changing Mathematical Paradigms at the University Level: Feedback from a Flipped Classroom at a Peruvian University
Get PDFThe university-level mathematics teaching adopted by many professors is still a traditional classroom, and many students’ perception of mathematics is that it is a complicated subject. The operationality of the flipped classroom proposal implemented at a university has a potential that can be used to change the perception that university students and teachers have towards the mathematics course, as well as to change the methodology of many teachers on how they teach their courses in the classroom. This research is the result of the implementation of the flipped classroom methodology in the basic mathematics course that is part of the professional careers of the engineering faculty of a Peruvian university. The aim of this study was to analyze the impact of applying the flipped classroom on academic results and attitudes towards mathematics, with an experimental group of 227 students and a control group of 215 students. The academic results were measured at each of the stages indicated in the course syllabus, T1, partial exam, T2 and final exam; attitudes towards mathematics were also assessed at cognitive, procedural and affective levels at the end of the university semester. The Kolmogorov-Smirnov normality test was applied and yielded a value of p = 0.00, indicating that the grades obtained by the students did not follow a normal distribution. With the data obtained, the Mann-Whitney U test was performed, obtaining a p = 0.00 value (α = 0,052 tails). p < α makes us conclude that there are statistically significant differences between the scores of the experimental group compared to the control group. The results show a significant improvement in the academic performance and positive attitudes of students who took the course using the flipped classroom compared to those who did not use this methodology
Selecting the Best K Features for Predicting Student Participation in Generic Competency Development Activities in Higher Education
Get PDFGeneric competency (GC) is an essential but often overlooked aspect of developing students in higher education. While there is much research about using technologies to develop discipline- specific skills for students, the use of technologies in GC development is insufficient. In particular, more research is needed on using technologies to predict student participation in GC development activities (GCDAs). Machine learning (ML) can use student characteristics, known as features, to predict their involvement in GCDAs. However, too many features will slow down the prediction process and reduce the ability to pinpoint the best features for prediction. This study explored an effective way to identify the minimal number of features essential for predicting student participation in GCDAs. The findings help educators develop recommendation systems to help students select the most beneficial GCDA for their holistic development. We collected 98 features from 9570 students from a community college. Then, we applied the Principal Component Analysis and SelectKBest algorithms to reduce the number of features from 98 to 8. Finally, we compared the accuracy of predictions using KNN and ANN based on the all-feature dataset with those based on the reduced-feature dataset. The results showed that the reduced-feature dataset maintained good prediction accuracy and enabled the educator to recommend the GCDAs to students. The findings could drive further research and development in applying machine learning technologies to enhance the recommendations for GCDAs for higher-education students
Intercultural Education and ADHD: Τhe Use of Virtual Reality as a Means of Intervention and Assessment
Get PDFPeople are looking to the digital world for solutions to the challenges they face in their everyday lives, as technology continues to advance rapidly. People with impairments now have equal access to learning opportunities due to technological advancements. ADHD (attention deficit hyperactivity disorder) has become more prevalent among children and teenagers from ethnic minorities in recent years. Due to challenges with cognitive and metacognitive functioning, this condition is associated with various learning and behavioral difficulties. People can only assimilate into the social environment once they have developed these functions. Children can learn alternative techniques to manage their cognitive deficiencies and adapt to various contexts by developing self-awareness, self-regulation, and self-control through internal attention. With the rapid advancement of research, numerous medical and psychological approaches have been developed for the treatment of ADHD, significantly assisting in the management of symptoms. The current study examines different therapeutic strategies aimed at improving the quality of life for children from racial and ethnic minorities who are affected by ADHD. These strategies include video games with virtual reality (VR) environments
Analysis of Synergistic Research on Digital Governance and Green Development under the Two-Carbon Target
Get PDFGreen development and digital governance are closely related under the concept of “two carbons.” In order to achieve the harmonious coexistence of humans and nature, the synergistic development of digital governance and green development is necessary to accomplish the goal of “two carbons.” As the global economic structure undergoes a new round of industrial change and technological revolution, digital governance emerges as a dynamic force in the fields of science, technology, and economic development. It plays a crucial role in promoting green development in China. Therefore, this paper conducts further research on the synergistic development of digital governance and green development with the goal of achieving “two carbons.” It systematically analyzes the relevant literature using the Cite Space big data literature analysis tool. The paper identifies and quantifies the research hotspots and keywords in the field of research through citation pattern and co-word analysis. Additionally, it reveals the knowledge evolution of the discipline by analyzing the time-series data of the citation relationship of the literature. We analyze the accumulation of literature results and changes in research trends to comprehend the developmental history and evolution of knowledge in the discipline. Additionally, we examine the research lineage and hotspots of scholars both domestically and internationally and explore the synergistic relationship between digital governance and green development in achieving the two-carbon goal