Factors Influencing College Students Research Articles

Examining factors influencing university students’ adoption of generative artificial intelligence: a cross-country study

ABSTRACT The introduction of Generative Artificial Intelligence (GenAI) has transformed the way university students learn. To understand the factors that affect the adoption of GenAI among university students, we proposed a comprehensive research model based on the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2), along with personal factors customized for GenAI. We conducted a cross-sectional survey to collect data from university students in Malaysia and China through an online questionnaire, yielding a total of 500 valid responses. The data were analyzed using the Partial Least Squares method to assess the influence of various factors on GenAI adoption. Our findings reveal notable differences in the factors affecting GenAI adoption between the two countries, with the Malaysian group showing a more diverse range of influencing factors compared to the Chinese group. This study highlights the importance of considering country-specific differences when devising strategies for the adoption of GenAI. By integrating UTAUT2 with personal factors and conducting a cross-country comparative analysis, this study offers significant insights into how factors influencing GenAI adoption vary between countries. These insights can be valuable for university stakeholders.

The internal relationship of college students’ physical exercise behavior and related factors based on ecological model

Background: The persistence of college students’ physical exercise behavior has an important impact on their physical health level and their positive psychological effects. The health behavior ecology model is more comprehensive and progressive than other exercise psychology theories in explaining the effect of physical activity intervention on long-term maintenance. Based on this, In this study, using the socio-ecological model theory as the entry point, applying five different levels of influencing factors in the theoretical model to the field of adolescent physical exercise behavior, The aim is to seek the internal connection between the ecological factors that promote college students’ physical exercise behavior through the investigation, so as to provide corresponding intervention strategies for promoting the healthy development of their physical fitness. So as to promote the formation of college students’ physical exercise habits. Methods: In 2023, 1015 college students were surveyed by questionnaire and measurement scale, followed by descriptive statistical analysis of college students’ current physical exercise behavior, and factor analysis of ecological factors affecting college students’ physical exercise. Results: From the behavior characteristics of college students’ physical exercise, different gender of college students in physical exercise, weekly exercise, exercise time is very significant difference (P < 0.001), the boys in sports participation higher than girls 15.2%, choose occasionally exercise boy’s ratio 10% higher than girls, girls do not participate in exercise more than boys. In terms of exercise time, a few boys choose to do physical exercise on weekends; the proportion of boys in more than 60 min of physical exercise is 7 percentage points higher than girls. In the time of extracurricular exercise, support of parents and physical exercise (P < 0.05), there was no significant difference between male and female students in the aspects of intensity of each exercise, participation in sports competition and reasons for not exercise (P > 0.05). The principal component analysis of the influencing factors of college students’ physical exercise behavior was conducted from the individual, family, school, community, and policy levels. The KOM value was 0.984, which met the judgment criteria of factor analysis. Through principal component analysis of the above five levels, according to the requirements of factors greater than 1, the individual level, family level, school level and policy level respectively two factors, corresponding cumulative contribution rate is 56.545%, 595.350%, 64.870% and 85.700% respectively, community level three factors, corresponding to the cumulative contribution rate of 76.450%. Conclusion: The advantage of the health behavior ecology model is that the comprehensive intervention strategies based on multi-level, multi-level effects greatly expand people’s understanding of the intervention. This model is applied to the field of physical health promotion of college students, to study human exercise behavior through the joint action of physiological, psychological and environmental factors, so as to more comprehensively reveal the various factors of exercise behavior, as well as the mutual relationship and influence between them. The results of this study indicate that: among the ecological factors that affect the physical exercise behavior of college students, the individual factors of college students are a necessary condition for physical exercise, while family, school and community factors affect the direction of the change and development of college students’ physical exercise behavior. Policy factors are a powerful driving force for college students’ physical exercise behavior. Only by considering the relationship between the relevant factors can we better understand the characteristics of college students’ physical exercise development, put forward the corresponding intervention strategies, and promote the formation of college students’ physical exercise habits through effective ways.

An analysis of factors influencing college students’ acceptance of telemedicine

An analysis of factors influencing college students’ acceptance of telemedicine

Advancing open education through open-source software: examining UTAUT 2 factors in adoption and implementation

PurposeThis study aims to examine the factors influencing university students' adoption of open-source software (OSS) within the context of open educational practices (OEP) by applying an extended Unified Theory of Acceptance and Use of Technology (UTAUT 2) model.Design/methodology/approachThe research employs a quantitative approach, gathering data from 156 students at Hong Kong Metropolitan University through an online survey. The survey was designed to test nine hypotheses derived from the UTAUT 2 model, incorporating additional constructs relevant to OSS. Structural equation modelling (SEM) was used to analyse the data and test the relationships between constructs.FindingsThe results indicate that Performance Expectancy (PE), Effort Expectancy (EE), Price Value (PV), Self-Efficacy (SE) and Value Alignment (VA) significantly influence students' Behavioral Intention (BI) to adopt OSS. Conversely, Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM) and Habit (HT) were not significant predictors. The findings suggest that while UTAUT 2 provides a useful framework for understanding OSS adoption, it requires adaptation to fully capture the unique characteristics of OSS in educational settings.Originality/valueThis study contributes to the literature by extending the UTAUT 2 model to the context of OSS adoption in higher education, highlighting the importance of economic factors and user alignment with OSS values. The results offer practical insights for higher education institutions aiming to promote OSS, emphasizing the need for support structures, training, and the promotion of OSS’s economic and collaborative benefits.

Integrating Sustainable Educational Innovations and Spatial Cognition: A Study of Factors Affecting College Students’ Sustainable Learning Behavior in Virtual Simulation Environments

Objective: This study investigated the factors influencing college students’ continuous utilization intention of virtual simulation software (Animation Character Virtual Simulation Software V1.0) in the context of current efforts to promote sustainable educational practices and explored design strategies to enhance this willingness in a sustainable manner. Method: Based on the Expectation Confirmation Model of Information System Continuance (ECM-ISC), this study developed a model to examine the impact of college students’ spatial ability (SA) on their virtual simulation learning behavior. Upon administering a questionnaire to the selected participants (N = 164), the survey data were analyzed for reliability and validity. Subsequently, the relationships among the model’s variables were explored. Result: For college students majoring in Digital Media Art, spatial ability significantly positively affects their sustainable utilization intention of virtual simulation software within 3D virtual scenarios. Meanwhile, it positively impacts perceived ease of use (PEU) and flow experience (FE), which are key factors in promoting the sustainable adoption of such technologies. The introduced spatial ability, perceived ease of use, and flow experience influence the endogeneity of the ECM-ISC. Moreover, gender differences in spatial ability are profound among these students. Conclusion: The primary influencing pathway is spatial ability → flow experience → expectation confirmation → perceived usefulness → continuous utilization intention. Enhancing spatial ability is one effective way to advance virtual simulation software, offering new insights for its design and long-term improvement in alignment with sustainable educational practices.

Factors Influencing University Students’ Continuance Intentions towards Self-Directed Learning Using Artificial Intelligence Tools: Insights from Structural Equation Modeling and Fuzzy-Set Qualitative Comparative Analysis

This study investigates the intricate causal mechanisms of university students’ sustained use of artificial intelligence (AI) tools for self-directed learning (SDL) within the theoretical framework of self-determination theory (SDT). Employing a convenience sampling strategy, 387 university students from China were included in the study. Methodologically, we employed structural equation modeling (SEM) for the measurement and causal analysis, and we employed fuzzy-set qualitative comparative analysis (fsQCA) for the configurational analysis. The research results emphasize several important insights. Perceived usefulness, intrinsic motivation, and satisfaction play important roles in encouraging university students’ continuance intentions. Satisfaction emerges as a pivotal mediator, bridging the connection between perceived usefulness, intrinsic motivation, and continuance intention. The system quality, the information quality, and social interaction have significant positive influences on perceived usefulness. Perceived autonomy and perceived competence display strong correlations with both intrinsic motivation and satisfaction. Moreover, the results from the fsQCA show five configurations, in which the key factors collectively shape students’ continuance intentions through complex interactions through various configurations. The findings reveal diverse configurations by which university students form continuance intentions towards using AI tools for SDL, providing detailed insights into the profound and indirect impacts on forming continuance intention behaviors. This enriches and advances the current theoretical understanding.

Incident factors in the use of ChatGPT and dishonest practices as a system of academic plagiarism: the creation of a PLS-SEM model

The objective of this study was to construct a causal model that explores the factors influencing university students’ behavioral intention to use ChatGPT as a learning resource, and to understand the reasons behind their engagement in dishonest practices when incorporating ChatGPT into their academic work. We gathered data through a survey, with the participation of 368 university students. Our analysis employed a causal model based on the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach. On one hand, we verified the hypotheses regarding factors contributing to the intention to use ChatGPT, such as the quality of information generated by the software, the credibility of this information, and student satisfaction with the responses provided. On the other hand, we found compelling evidence of significant factors affecting the intention to use ChatGPT inappropriately, including the absence of clear regulations on plagiarism and corresponding penalties in universities, the students’ insufficient research and academic skills (such as conducting research or writing in a scholarly manner), the adverse impact of teachers’ workload (excessive tasks or insufficient commitment to assessments), and the general lack of interest and motivation towards academic tasks. Collectively, these factors accounted for 53.20% of the variance in students’ behavioral intention to utilize ChatGPT. These findings affirm the effectiveness of this model in explaining the software’s role in text production and quality, as well as students’ tendencies toward dishonest use.

Factors Influencing Chinese Vocational College Students' Satisfaction with Learning Management Platform

Background and Aim: In the rapidly evolving landscape of education, online learning platforms, such as the Chaoxing Learning Platform, have gained substantial attention. Recognizing the pivotal role of student satisfaction in the effectiveness of these platforms, this study aims to investigate the factors influencing college students' satisfaction specifically within the context of Beihai Vocational College.Materials and Methods: This study employed a purposive sampling method, selecting 150 respondents from Beihai Vocational College who met the research objectives to ensure the representativeness and credibility of the survey results. Quantitative research methods were applied, utilizing measurement tools in various aspects, including system quality, information quality, interaction, perceived usefulness, and student satisfaction. Results of Cronbach’s Alpha of the research instruments show that the alpha coefficient of information quality and interaction is within the range of 0.8 to <0.9， and the alpha coefficient of system quality, perceived usefulness, and student satisfaction is within the range of 0.9. The level of Cronbach’s alpha in the variables is within very good to excellent level. This indicated the acceptable level of internal consistency of the research instrument, which confirmed the reliability of the research instrument. Ultimately, methods such as descriptive statistics and multivariate regression analysis were used to conduct in-depth data analysis, aiming to comprehensively understand the impact of the Chaoxing learning platform on student satisfaction. Results: The results of the study showed that the independent variables system quality (β = 0.1465, P = 0.287), information quality (β = 0.3602, P = 0.016), and perceived usefulness (β = 0.5478, P = 0.005) were significantly positively correlated. In addition, the test also found that interaction (β = -0.0430, P = 0.084) did not have a significant effect on students' satisfaction with the Chaoxing Learning Platform at Beihai Vocational College. Conclusion: The results of the study indicate that most of the students of Beihai Vocational College are satisfied with using the Chaoxing Learning Platform for learning, and students can learn, communicate, and collaborate well through this platform, which provides satisfactory learning results.

The effect of environmental values, beliefs, and norms on social entrepreneurial intentions among Chinese university students

This study explores the factors influencing university students’ social entrepreneurial intentions based on the values-beliefs-norms theory. Data were collected from 769 Chinese university students through online surveys. The hypotheses were tested using partial least squares-structural equation modeling. The results confirmed the positive influence of altruistic and traditional values on normative beliefs. Awareness of the consequences and attribution of responsibility had no significant effect on personal norms among university students, which have been discussed in-depth in relation to the phenomenon of inadequate student socialization due to closed-loop management policies at Chinese universities during the COVID-19 pandemic. Furthermore, the findings verified the positive and significant effects of personal, injunctive, and descriptive social norms on social entrepreneurship intentions. With the aim of promoting social entrepreneurship among university students and broadening the understanding of the phenomenon of social entrepreneurs, this study provides a favorable direction and expands the discussion on the topic. The results will help the government and universities foster more effective prosocial behaviors among university students.

Study on university students’ intention to choose reusable takeaway food containers: evidence from China

Purpose Reusable takeaway food containers (RTFCs) are a newly emerging green packaging choice for the takeaway industry that can effectively reduce campus solid waste but are not yet well accepted. Therefore, this study aims to identify the key factors influencing university students’ intention to choose RTFCs, seeking to enhance RTFC project management practices and contribute to developing a sustainable “green university.” Design/methodology/approach In total, 316 valid respondents from a Chinese university were surveyed for data collection. A multivariate ordered logistic regression model was used to conduct empirical analysis. Findings The results of this study underscore the crucial role of perceived value in the relationship between perceived green attributes and students’ intention to choose RTFCs. The positive impacts of perceived green attributes on intention are direct and indirect, through the lens of perceived value. When the value is substantial, it significantly boosts the student’s intention to choose RTFCs. Conversely, the perception of lower hygienic quality or higher returning time cost dampens this intention, with a more pronounced effect than perceived green attributes. Notably, perceived publicity activities have the most significant impact on student’s intention to choose RTFCs. Originality/value This study contributes to the understanding of promoting RTFCs, a key strategy for reducing plastic waste on campuses. The findings provide actionable recommendations for the project company and the university, offering practical ways to encourage students to use RTFCs and contribute to plastic waste reduction.

A systematic review of factors influencing the childbearing intentions of college students in developed and developing countries

This paper provides in-depth knowledge regarding the fundamental factors influencing college students’ childbearing intentions. We used PubMed, ProQuest Dissertations, Web of Science, EBSCOhost, Scopus, and China National Knowledge Infrastructure to search for relevant articles published between January 1946 and April 2023. Among these, we incorporated 51 studies conducted in 20 countries into a quantitative synthesis. The results indicated that there were differences between developed and developing countries in terms of the factors influencing college students’ childbearing intentions. The primary factors affecting childbearing intentions in developed countries were fertility knowledge, personal pursuits, and partner relationships. However, the influencing factors in developing countries were more complex: Financial pressures and personal pursuits deterred college students from their aspirations to have children, and these challenges delayed their intended reproductive age. Implications of the findings are discussed.

Factors Influencing College Students’ Learning Intention to Online Teaching Videos During the Pandemic in China

Factors Influencing College Students’ Learning Intention to Online Teaching Videos During the Pandemic in China

Discovering students' continuous intentions to use ChatGPT in higher education: a tale of two theories

PurposeThis study investigates the factors affecting university students’ intentions to continuously use ChatGPT by integrating the UTAUT3 (Unified Theory of Acceptance and Use of Technology) and ISS (Information Systems Success) theories.Design/methodology/approachBy using self-reported questionnaires, 388 usable data from university students in Malaysia were analysed using partial least squares structural equation modelling.FindingsThe results indicate that hedonic motivation, habit, and facilitating conditions significantly impact students’ continuous intentions to utilise ChatGPT. Furthermore, system quality, information quality, service quality, and conversational quality significantly influence students’ ChatGPT satisfaction. Crucially, satisfaction is a critical factor in continuous intention to utilise ChatGPT.Originality/valueThis research integrates UTAUT3 and ISS theories to understand factors influencing university students’ satisfaction with continuous intentions to use ChatGPT, filling the gap in previous studies that have focused on these theories separately.

Factors influencing college students' online rumor refuting behavior during major public health crises: the moderating effect of group norms.

This study integrates SOR (Stimuli-Organism-Response) theoretical framework and rational behavior theory within a theoretical framework, incorporating group norms as a moderating factor to investigate the psychological mechanisms influencing Chinese college students' online rumor-refutation behavior amidst public health crises. Using the structural equation modeling research method, data was collected via questionnaires from 1,254 participants in the context of the COVID-19 pandemic. The findings indicate that both online and offline information seeking are positively correlated with college students' attitudes and subjective norms. Moreover, the attitudes and subjective norms of college students are positively correlated with the online rumor refuting behavior. Furthermore, group norms serve to strengthen the connection between college students' attitudes and their engagement in online refuting rumors. These results illuminate the psychological underpinnings driving college students' online rumor-refuting actions, offering practical and policy implications for effectively managing rumor behaviors.

Investigating college students' green food consumption intentions in China: integrating the Theory of Planned Behavior and Norm Activation Theory

IntroductionThe global trend toward consuming green food is on the rise. College students, as the future consumer base, have sparked significant interest in their inclination toward consuming environmentally-friendly foods. This paper integrates the Theory of Planned Behavior with the Norm Activation Theory to investigate the factors influencing college students' propensity to choose green foods, establishing a comprehensive model.MethodsThis study utilized online and paper questionnaires for data collection, distributing them among college students and receiving 350 valid responses. In the data analysis phase, SPSS was employed for statistical data analysis, including descriptive statistics and regression analysis, while AMOS was used for structural equation modeling.Results and discussionThe data analysis results indicate that subjective norms, behavioral attitudes, and individual norms have a significant positive influence on college students' inclination to purchase green food. Purchase intention is indirectly influenced by personal norms and behavioral attitudes through perceptions of consequences. Responsibility attribution indirectly impacts purchase intention of green food through personal norms. Personal norms are indirectly influenced by responsibility attribution through perceptions of consequences.

Understanding University Students’ Acceptance of ChatGPT: Insights from the UTAUT2 Model

ABSTRACT The current study explores the determinants of ChatGPT adoption and utilization among a sample of Norwegian university students. The theoretical perspective of the study is anchored in the Unified Theory of Acceptance and Use of Technology (UTAUT2) and based on a previously tested model. The proposed model integrates six constructs to explain the Behavioral intentions and actual usage patterns of ChatGPT in a higher education context. The study analyzed responses from 104 students attending Universities in West and Central Norway using the partial-least squares approach to structural equation modeling. The data showed that performance expectancy emerged as the construct with the biggest impact on Behavioral intention, followed by Habit. This study contributes to the research on the factors influencing university students’ engagement with generative AI technologies. Furthermore, it contributes to a more comprehensive understanding of how tools like ChatGPT can be integrated effectively in educational contexts in both students learning and instructors teaching.

A Study on the Preferences and Behaviors of College Students Who Shop Online for Clothes

In today’s society, e-commerce is becoming more and more popular, ushering in a new era of online shopping. As an emerging mode of consumption, online consumption has brought great convenience to college students’ daily life, but also has a serious impact on the consumption concept of college students whose psychological development is not yet mature, among which the negative impact is undeniable and needs to be taught and corrected in time. As a group with distinctive characteristics among many online consumers, college students can grasp the changing ways of the Internet as quickly as possible and skillfully use online channels to shop. Irrational consumption behaviors such as blind following, excessive, comparison, and impulsiveness are common among college students. In the case of insufficient funds from their families, some college students will even choose to borrow online. How to correctly guide college students to establish a rational outlook on consumption is the biggest problem facing the whole society. Based on the questionnaire survey method and the characteristics of college students’ online clothing consumption behavior in Jiangxi Province, this paper analyzes the main influencing factors of college students’ online consumption behavior by stating the sources of living expenses, consumption platforms, clothing types, and purchase mentality, summarizes their consumption psychological characteristics, and puts forward scientific guidance countermeasures and programs for college students to establish a correct online consumption concept from five levels: government, society, universities, families and individuals.

Greening ambitions: exploring factors influencing university students' intentions for sustainable entrepreneurship

Greening ambitions: exploring factors influencing university students' intentions for sustainable entrepreneurship

Factors Influencing University Students’ Behavioral Intention and Use of eLearning in Kathmandu Valley

This study aims to investigate the factors influencing university students’ intention and behavior toward eLearning in Kathmandu Valley, Nepal. The research framework used in this study was the Unified Theory of Acceptance and Usage of Technology (UTAUT). The most common factors associated with UTAUT are social influence, facilitating conditions, habit, performance expectancy, effort expectancy, behavioral intention, and use behavior. Data were collected from 385 university students through a closed-ended questionnaire through social media platforms. The demographic information of respondents was summarized using SPSS version 25 software, while structural equation modeling was performed using SmartPls version 3 to identify the factors that influence behavioral intention and use behavior of eLearning. The data analyses revealed that performance expectancy, effort expectancy, facilitating conditions, social influence, and habit all significantly influence the behavioral intention of eLearning, with facilitating conditions being the most significant factor. Similarly, habit, facilitating conditions, and behavioral intention also significantly influence the use behavior of eLearning, with facilitating conditions as the most significant factor. It suggests that students are more likely to utilize eLearning tools when they have access to various technical devices and receive sufficient support from educational institutions. Therefore, universities should prioritize accessibility, feedback mechanisms, and seamless integration of eLearning into curricula. Peer support, technical assistance, and promotion of the benefits of eLearning are also essential for fostering engagement. By focusing on these aspects, eLearning adoption can be optimized, leading to improved academic performance and learning outcomes among university students in Kathmandu Valley.

Exploring the Key Factors Influencing College Students’ Willingness to Use AI Coding Assistant Tools: An Expanded Technology Acceptance Model

The application of artificial intelligence (AI) in programming assistance has garnered researchers’ attention for its potential to reduce learning costs for users, increase work efficiency, and decrease repetitive coding tasks. However, given the novelty of AI Coding Assistant Tools (AICATs), user acceptance is currently limited, and the factors influencing this phenomenon are unclear. This study proposes an expanded model based on the Technology Acceptance Model (TAM) that incorporates the characteristics of AICAT users to explore the key factors affecting college students’ willingness to use AICATs. Utilizing a survey methodology, 303 Chinese participants completed the questionnaire. Factor analysis and Structural Equation Modeling (SEM) results indicate that users’ dependence worry (DW) about AICATs positively affects perceived risk (PR), which in turn negatively impacts perceived usefulness (PU) and perceived ease of use (PEOU), thus reducing user willingness to use. Dependence concerns also negatively impact perceived trust (PT), while PT positively affects PU and PEOU, thereby enhancing willingness to use. Additionally, a user’s self-efficacy (SE) negatively impacts DW and positively affects PEOU. This study discusses the potential significance of these findings and offers suggestions for AICAT developers to foster and promote widespread use.