The Effectiveness of Cross-Disciplinary Learning Using Augmented Reality Technology

An active introduction to the use of digital technology for reality virtual in online education. The COVID-19 event is one of the main reasons. In this study, AR technology is applied to the development of instructional media was invented to teach them about Thai floral hanging garlands, especially for High-class Thai craftsmanship in online classrooms for university students for cross-disciplinary learning to study online for 9 consecutive weeks. The research results suggest that students' learning objective is to use AR self-learning. The results of the comparison between male and female research participants in terms of their perceptions using the augment reality-based Thai floral hanging garland course for cross-disciplinary learning no significant difference in opinions. Students were highly motivated to learn the Thai floral hanging garlands according to the ARCS model to learn and opinions are consistent. Copyright © 2022, Anka Publishers. All rights reserved.

Improving Dropout Forecasting during the COVID-19 Pandemic through Feature Selection and Multilayer Perceptron Neural Network

Nowadays, online education in universities is mature from the situation of COVID-19 spread. It has greatly changed the learning environment in the classroom and has also resulted in students’ dropout. The purpose of this study is to examine the factors that influence students’ dropout in the department of information technology of Suan Sunandha Rajabhat University. Students enrolled in the subjects in the COVID-19 pandemic situation must study online at their homes and must take online courses. This study investigated 1,650 student records, 19,450 enrollments, 16,200 grades, and 11,780 social media accounts that had access to all online courses. It was examined how to improve the model's performance by combining feature selection with a multilayer perceptron neural network method. The model was compared to student dropout predictions generated by Logistic regression, Decision Tree, Random Forest, Naive Bayes, Support Vector Machine, and Multilayer Perceptron Neural Network, with feature selection (1). The 10-Folds Cross Validation method was used to determine the efficiency of the Gain Ratio, Chi-Square, and Correlation-based Feature Selection models to compare accuracy, precision, sensitivity, F1 score, and classification error rate (e). After adjusting the modeling parameters, the multilayer perceptron neural network method combined with CFS characterization achieved an accuracy of 96.98%. The study’s findings indicate that the feature selection technique can be used to improve the neural network model's efficiency in predicting student dropout during a COVID-19 pandemic. Furthermore, the simulation can improve student dropout forecasting during spread out that persists. © 2022 by the authors.

The Efficiency of Elderly Community Product Using Digital Marketing through Unfolding of Practice during COVID19 Pandemic

The development of the trade sector of elderly community enterprise in Thailand during the COVID-19 pandemic triggers the need to study the processes of formation and evaluation of digital marketing through the unfolding of local practice. This research has developed the Digital Marketing for Elderly Community Enterprises (DMeCE) model to increase online trade capability and customer relationship management for elderly entrepreneurs who do not have sufficient digital skills in Thailand community enterprises. DMeCE model includes social media CRM, storytelling for branding, gamification CRM, augmented reality for branding using the hybrid marker QR code, and Thai ontology Thai chatbot services for both customers and elderly entrepreneurs via the voice command function. The evaluation results based on the classification of the model performance measurement indicated that the developed model could help the elderly entrepreneurs reach the infrastructure, process, customers, and organizational performance. Furthermore, it was found that both the effectiveness and satisfaction of the developed DMeCE model were rated at the highest level. Moreover, it provided an accuracy rate of more than 98%, giving the elderly community enterprises more income-making opportunities. © 2021, Success Culture Press. All rights reserved.

Developing gamification to improve mobile learning in web design course during the COVID-19 pandemic

Thailand is currently facing a widespread third wave of COVID-19 outbreaks in the second quarter of 2021. The government has encouraged social distancing compliance to work from home and study at home policy to mitigate the risks of the pandemic. As a result, educational institutions at all levels must temporarily close their services within the premises. The students need to lean towards the online system independently. Hence, this research aims to develop gamification in the Web Design course to increase the perception and achievement of Information Technology students through mobile learning. The research results showed that the students who registered for the academic year of 2020, the majority’s learning performance improved after adopting the gamification approach via developed mobile application. According to the statistical test (t-Test) results, a significant difference was discovered between pre-test and post-test scores at a significance level (α) of 0.05. The learners also rated the effectiveness of the developed game at the highest level and accepted the developed game with high consensus. In conclusion, the research findings indicate that games can be used as effective instruction media for undergraduate students and online classrooms amidst the situation of the COVID-19 pandemic. © 2021, International Journal of Information and Education Technology. All rights reserved.