BỘ GIÁO DỤC VÀ ĐÀO TẠO TRƯỜNG ĐẠI HỌC KINH TÉ TP. HÒ CHÍ MINH BÁO CÁO TÓNG KÉT ĐÈ TÀI NGHIÊN cứu KHOA HỌC THAM GIA XÉT GIẢI THƯỞNG “NHÀ NGHIÊN cúu TRẺ ƯEH” NĂM 2024 < FACTORS INFLUENCING TRUST AND INTENTION TO USE CHATGPT AMONG STUDENTS IN HO CHI MINH CITY > Thuộc nhóm chuyên ngành : 1 TP. HỒ Chí Minh, tháng 1/2024 1 Abstract Chat GPT, an artificial intelligence model, has attracted significant attention in the field of education. In fact, the belief and intention to use Chat GPT by students in Ho Chi Minh City have become an interesting research topic for student learning.
We chose the research topic "Factors influencing trust and intention to use Chat GPT among students in Ho Chi Minh City." With a sample of over 200 survey responses, using the SPSS data analysis tool, the study has illuminated the trust and intention to use Chat GPT among students in Ho Chi Minh City, providing empirical value to the research community on the relationship between determining factors in using Chat GPT. The results show that Chat GPT has emerged as an important educational tool, benefiting both students and educators. It is hoped that this research will contribute practical values to readers. In addition, we will propose suggestions and directions for the growing trend of accessing services and AI technology in recent years.
In addition to the abbreviated index, table and chart index, reference document index, and appendices, the research paper: "Factors influencing trust and intention to use Chat GPT among students in Ho Chi Minh City" consists of 5 chapters as follows: Chapter 1: Introduction Chapter 2: Theoretical overview and experimental studies Chapter 3: Research method design Chapter 4: Research results Chapter 5: Conclusion and recommendations 2 Table of contents. 2 List of Tables.3 List of Figures.3 Research Subjects, Objects, and Scope.4 Contribution of the study. 9 CHAPTER 2: LITERATURE REVIEW.1 Theoretical Foundation of Research.1 Technology Acceptance Model (TAM) theory.2 Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB) .3 Unified Theory of Acceptance and Use of Technology (UTAUT).2 Development of Hypotheses.3 Proposed Research Model. 20 CHAPTER 3: RESEARCH METHODS.2 Data Collection Method.3 Data Processing Methods.1 Evaluation of Measurement Reliability through Cronbach’s Alpha Test.2 Exploratory Factor Analysis (EFA).3 Pearson Correlation Analysis.4 Multivariate Regression Analysis.5 Independent Sample T-test.29 CHAPTER 4: RESEARCH RESULTS.3 Results of testing the validity of the scale with exploratory factor analysis - EFA.1 Factor Analysis Results for Independent Variable Scales.2 EFA for dependent variables.
Name the factors and summarize the results of EFA analysis:.4 Analyze correlations between variables.5 Check the assumptions of the multivariate regression model.3 Check the suitability of the model.4 Testing the significance of the regression function. Test the partial impact of the independent variable on the dependent variable 58 4.6 Conclusion about research hypotheses. 66 CHAPTER 5: CONCLUSION AND RECOMMENDATIONS.2 Limitations and Future Directions. 71 2 List of Tables Table Table Title Page Number 24 3.1 Scale for "Perceived Utility" 25 3.2 Scale for "Ease of Usability" 25 3.3 Scale for "Risk Awareness" 26 3.4 Scale for "Subjective Norms" 26 3.5 Scale for "Trust" 27 3.6 Scale for "Intention to Use" 31 4.1 Survey Sample Statistics 32 4.2 Descriptive Statistics for Observational Variables 36 4.3 Results of evaluating the reliability of the scale "Perceived Utility" 37 4.4 Results of evaluating the reliability of the scale "Ease of Usability" 38 4.5 Results of evaluating the reliability of the scale "Risk Awareness" 3 39 4.6 Results of evaluating the reliability of the scale "Subjective Norms" 40 4.7 Results of evaluating the reliability of the scale "Trust" 41 4.8 Results of evaluating the reliability of the scale ^Intention to Use” 43 4.9 Results of KMO and Bartlett tests of independent variables (1) 43 4.10 Result of EFA 1 44 4.11 Results of KMO and Bartlett tests of dependent variables 46 4.12 Results of EFA of dependent variable 48 4.13 Summary of factors after EFA analysis 50 4.14 Summary of factor analysis results 51 4.15 Pearson correlation results with dependent variable Intention to use (IU) 52 4.16 Pearson correlation results with dependent variable Trust (T) 56 4.17 Results of testing the suitability of the regression model (1) 58 4.18 Results of testing the suitability of the regression model (2) 4 59 4.19 Results of testing the significance of the regression function (1) 60 4.20 Results of testing the significance of the regression function (2) 61 4.21 Results of testing the partial impact of the independent variable 63 4.22 Results of testing the partial impact of the independent variable on the dependent variable of the regression model (2) 67 4.23 Summary of results of research hypotheses 69 4.24 Independent T test results 70 4.25 Independent T test results 5 List of Figures Figure Figure Title Page Number 12 2.1 Technology Acceptance Model 13 2.2 Theory of Reasoned Action 14 2.3 Theory of Planned Behavior (TPB) 15 2.4 Unified Theory of Acceptance and Use of Technology (UTAUT) 21 2.5 Proposed Research Model 22 3.1 Research Process Flowchart 54 4.4 Diagram of results of the research hypothesis 6 CHAPTER 1: INTRODUCTION 1.1 Research Motivation Nowadays, artificial intelligence has developed and brought innovations in many areas of life.
Artificial Intelligence (AI) has made significant progress in healthcare, medicine, military, computer science, communication, industry, and other fields. AĨ refers to "robots, computers, and other machines capable of reasoning and problem-solving like humans" (McPherson, 2018). AI technologies use sophisticated algorithms or guidelines to solve very complex tasks (Hulick, 2016). And the Chat Generative Pre-training Transformer (Chat GPT) technology is a typical example of artificial intelligence, representing a state-of-the-art natural language processing (NLP) system developed by OpenAI.
It is designed to create human-like conversations by understanding the context of the conversation and generating appropriate responses. Chat GPT is based on a deep learning model called GPT-3, trained on a large dataset of conversations (Deng and Lin, 2022). It can understand the context of a conversation and generate relevant answers. It can also generate responses in multiple languages.
The impressive aspect of Chat GPT is its ability to understand and use context. This AI tool is trained using user feedback to improve performance. This platform uses natural language processing (NLP) and machine learning (ML) algorithms to understand user input and generate meaningful feedback. It collects user feedback in the form of rankings, comments, and suggestions.
This feedback is then used to train ML algorithms, allowing the chatbot to better understand user input and provide more accurate feedback. Additionally, Chat GPT can conduct conversations naturally, making users feel like they are communicating with a person rather than a machine. On February 1, 2023 (Reuters) - Chat GPT, estimated to have reached 100 million active users in January, just two months after its launch, making it the fastest-growing consumer application in history, according to a study by UBS. On average, about 13 million visitors used Chat GPT every day in January, more than double the December figure (According to a report from SimilarWeb in the United States).
This demonstrates the rapid popularity of Chat GPT, contributing to significant interest in AI technology in particular and artificial intelligence in general, encouraging deeper research and exploration of its applications and potential. Therefore, we decided to explore the topic 7 "Factors influencing trust and intention to use Chat GPT by students in Ho Chi Minh City". Understanding the trust and intention to use Chat GPT by students in Ho Chi Minh City can provide insights into the application of AI technology in local education. It can offer a clear and diverse perspective on the views, perceptions, and impact of AI technology on learning and life, contributing to the development of higher education in Ho Chi Minh City and across the country.
Thus, it provides recommendations and measures to meet the needs and desires of students in using AI technology, helping determine the best methods to leverage the potential of Chat GPT.1 General Objective This research aims to shed light on the current situation regarding trust and intention to use Chat GPT among students in Ho Chi Minh City. Building on researched theoretical foundations, this study not only clarifies the relationship between trust and the intention to use Chat GPT but also contributes experimental research value for other researchers. It adds knowledge and documentation about the current relationship between determining factors, trust, and the intention to use Chat GPT.2 Specific Objectives This research will address specific objectives as follows: - Systematize the relevant theory related to the usage intention of Chat GPT among students in Ho Chi Minh City. - Examine and evaluate the relationship between factors influencing trust and the intention to use Chat GPT among students in Ho Chi Minh City.
- Provide an overview of the current situation regarding trust and the intention to use the Chat GPT application among students. This will give readers a foundational platform to assess and improve the application of artificial intelligence technology in various fields.3 Research Subjects, Objects, and Scope 1.1 Research Subjects - The inherent relationship between factors influencing trust and the intention to use Chat GPT among students in Ho Chi Minh City.2 Survey Objects - Individuals are students from various universities and colleges across Ho Chi Minh City.3 Research Scope - Timeframe: This research is conducted from July 10, 2023, to July 20, 2023. - Spatial scope: The study is carried out at several universities and colleges in Ho Chi Minh City.4 Contribution of the Study 1.1 Research Contribution - The results of this study can contribute to related research on artificial intelligence and consumer behavior. The findings may provide useful information for other researchers in analyzing, expanding, or constructing other theoretical models related to trust and the intention to use artificial intelligence.
- The application of theories and models applied for research, exploration, and utilization of knowledge related to the topic is clarified. - Clarifying the relationship between the factors mentioned in the model and verifying the mutual impact between variables provides scientific and practical basis for proposing suggestions.2 Practical Contribution On a practical level, this research will contribute valuable insights into the development and application of artificial intelligence technology, particularly Chat GPT, and AI in 9 general. It responds to the need for experimental research in this hot topic, attracting various perspectives from managers, scientists, faculty, and students in Vietnam. For educators, it provides insights into students' needs for using Chat GPT, enabling the cultivation and practical application of Chat GPT as a tool in education.
For universities, it may generate more advanced educational solutions, utilizing artificial intelligence to enhance the effectiveness of student learning and research, thereby ensuring the quality of education is improved. Additionally, through this information, universities can shape the development direction and application of artificial intelligence technology in various industries and services. 10 CHAPTER 2: LITERATURE REVIEW 2.1 Theoretical Foundation of Research Studies on factors influencing trust and intention to use Chat GPT are grounded in important research theories such as the Technology Acceptance Model (TAM), the Theory of Reasoned Action (TRA), the Theory of Planned Behavior (TPB), and the Unified Theory of Acceptance and Use of Technology (UTAUT).1 Technology Acceptance Model (TAM) theory The Technology Acceptance Model, proposed by Fred D. Davis et al.
in 1989, is a theoretical model of technology usage behavior. This model explains how users evaluate and adopt new technologies. According to TAM, technology acceptance is determined by two main factors: • Perceived Usefulness: Measured by users' assessments of the utility that the technology brings to them in completing tasks, enhancing productivity, and providing value. From this definition, it can be concluded that perceived usefulness is the belief of an individual when making a decision.
• Perceived Ease of Usablity: Measured by users' assessments of the ease of using the technology, the absence of significant risks in its use, and the minimal time required to learn to use it (Fred D. Davis et al. Both of these factors influence users' decisions to adopt technology.