Artificial intelligence chatbots can be used to conduct research effectively and efficiently in the fifth industrial revolution. Artificial intelligence chatbots are software applications that utilize artificial intelligence technologies to assist researchers in various aspects of the research process. These chatbots are specifically designed to understand researchers’ inquiries, provide relevant information, and perform tasks related to data collection, analysis, literature review, collaboration, and more. The purpose of this study is to investigate the use of artificial intelligence chatbots for conducting research in the fifth industrial revolution. This qualitative study adopts content analysis as its research methodology, which is grounded in literature review incorporating insights from the researchers’ experiences with utilizing artificial intelligence. The findings reveal that researchers can use artificial intelligence chatbots to produce quality research. Researchers are exposed to various types of artificial intelligence chatbots that can be used to conduct research. Examples are information chatbots, question and answer chatbots, survey chatbots, conversational agents, peer review chatbots, personalised learning chatbots and language translation chatbots. Artificial intelligence chatbots can be used to perform functions such as literature review, data collection, writing assistance and peer review assistance. However, artificial intelligence chatbots can be biased, lack data privacy and security, limited in creativity and critical thinking. Researchers must be transparent and take in consideration issues of informed content and data privacy and security when using artificial intelligence chatbots. The study recommends a framework on artificial intelligence chatbots researchers can use to conduct research in the fifth industrial revolution.
The activities and characteristics of heritage, cultural, and creative tourism are notably distinct despite the fact that they are frequently confused and misunderstood. Moreover, these types of tourism have been significantly affected by the COVID-19 pandemic. This review article aims to explore the characteristics of three types of tourism, both pre- and post-pandemic, and seeks to propose sustainable solutions with new opportunities for the tourism industry. The article adopts a PRISMA flow diagram and VOSviewer to perform a systematic literature review, ultimately selecting 179 articles from the Scopus, ScienceDirect, and Google Scholar databases and grouping them into five clusters: 1) heritage, cultural, and creative tourism; 2) co-creation; 3) creative city; 4) sustainability; and 5) technology and innovation. Consequently, this review article proposes a final framework presenting five related clusters suggesting sustainable solutions for creative tourism. It may aid the tourism industries in their transition to creative tourism, which is more sustainable and broadly focused while ensuring safety and enhancing income for local communities in the post-pandemic period.
This study conducts a systematic review to explore the applications of Artificial Intelligence (AI) in mobile learning to support indigenous communities in Malaysia. It also examines the AI techniques used more broadly in education. The main objectives of this research are to investigate the role of Artificial Intelligence (AI) in support the mobile learning and education and provide a taxonomy that shows the stages of process that used in this research and presents the main AI applications that used in mobile learning and education. To identify relevant studies, four reputable databases—ScienceDirect, Web of Science, IEEE Xplore, and Scopus—were systematically searched using predetermined inclusion/exclusion criteria. This screening process resulted in 50 studies which were further classified into groups: AI Technologies (19 studies), Machine Learning (11), Deep Learning (8), Chatbots/ChatGPT/WeChat (4), and Other (8). The results were analyzed taxonomically to provide a structured framework for understanding the diverse applications of AI in mobile learning and education. This review summarizes current research and organizes it into a taxonomy that reveals trends and techniques in using AI to support mobile learning, particularly for indigenous groups in Malaysia.
The architecture and engineering industry employs resource-efficient sustainable building design (SBDC) to reduce greenhouse gas emissions and mitigate environmental damage. This study examines the understanding and practice of SBDC among Chinese architecture students. A survey of 555 undergraduates from China’s architecture universities was conducted. Two independent and seven dependent variables were analyzed to evaluate the impact of academic stages and practical experiences on students’ awareness. The findings reveal that over 70% of respondents consider SBDC important in architecture. More than half have taken courses with over 30% SBDC content. However, 45.85% of respondents only have a basic understanding of SBDC. This result underscores the significance of educational disparities, this insufficiency is likely due to inadequate coverage and representation of SBDC in the curriculum. Our study highlights the necessity of enhancing SBDC-related education within the current curriculum framework to ensure all students receive a systematic and comprehensive knowledge of sustainable building design.
