What drives economics students to use generative artificial intelligence?

  • 30 Views
  • 2 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

The increasing integration of Artificial Intelligence (AI) into education requires studying the motives for its use among students. This study aims to identify the key motivations for economics students to use AI and compare these motivations by grade level and gender. The study examines satisfaction with the use of AI and analyzes the number of AI tools used.

An anonymous empirical study was conducted among 264 students from the Faculty of Economics at Taras Shevchenko National University of Kyiv, Ukraine. Data analysis included descriptive statistical methods, non-parametric statistical methods, and exploratory factor analysis.

The study found that students’ main motivations for using AI are the automation of routine tasks (34.2%) and the need to save time (21.5%), while 18.7% use AI to compensate for lack of experience. Among Bachelor’s students, motivations such as automating routine tasks and saving time increased from 53% to 58% over the course of their studies, while lack of experience decreased from 22% to 15%. In contrast, Master’s students showed a decrease in routine automation (from 36% to 28%) but an increase in the need to compensate for lack of experience (from 15% to 28%) and to save time (from 18% to 25%). In terms of gender, men are more likely to use AI for learning and personal development, while women are slightly more likely to use AI for work. More than 38% of respondents say they need to use at least 2 AIs to achieve their goals.

Acknowledgment
This publication is based upon work from 24-PKVV-UM-002, ‘Strengthening the Resilience of Universities: Czech-Ukrainian Partnership for Digital Education, Research Cooperation, and Diversity Management,’ supported by the Czech Development Agency and the Ministry of Foreign Affairs under the initiative ‘Capacity Building of Public Universities in Ukraine 2024.’

view full abstract hide full abstract
    • Figure 1. Quantity of AI tools used for different motivations
    • Figure 2. Motivation to use AI among Bachelor and Master students
    • Figure 3. Boxplot for AI usage by area
    • Figure 4. Box-plot of AI usage areas by gender
    • Figure 5. Factor loadings: Factor 1 vs Factor 2
    • Figure 6. Factor loadings: Factor 1 vs Factor 2 by gender
    • Table 1. Sociodemographic profile of the sample (n = 264)
    • Table 2. Students’ motivation in using AI, %
    • Table 3. Students’ average satisfaction with AI usage based on the number of AI tools (Heatmap)
    • Table 4. Descriptive statistics for AI usage by area
    • Table 5. Mean and median for AI usage by area across gender
    • Table 6. Factor analysis results
    • Table 7. Factor loadings
    • Table 8. Factor loadings by gender
    • Conceptualization
      Mariia Balytska, Martina Rašticová, Nataliia Versal, Nataliia Prykaziuk, Nataliia Tkalenko
    • Data curation
      Mariia Balytska, Ihor Honchar, Nataliia Prykaziuk, Nataliia Tkalenko
    • Methodology
      Mariia Balytska, Martina Rašticová, Nataliia Versal, Ihor Honchar, Nataliia Prykaziuk
    • Supervision
      Mariia Balytska, Nataliia Versal
    • Writing – original draft
      Mariia Balytska, Martina Rašticová, Nataliia Versal, Ihor Honchar, Nataliia Prykaziuk, Nataliia Tkalenko
    • Writing – review & editing
      Mariia Balytska, Nataliia Versal, Nataliia Prykaziuk, Nataliia Tkalenko
    • Project administration
      Martina Rašticová, Nataliia Tkalenko
    • Formal Analysis
      Ihor Honchar
    • Validation
      Ihor Honchar
    • Visualization
      Ihor Honchar
    • Software
      Nataliia Prykaziuk
Related Articles

  • Adoption of Mobile Banking and Perceived Risk in GCC

    Kavita ChavaliORCID , Ajith KumarORCID doi: http://dx.doi.org/10.21511/bbs.13(1).2018.07
    Banks and Bank Systems Volume 13, 2018         Issue #1         pp. 72-79 Views: 2445 Downloads: 566 TO CITE АНОТАЦІЯ

    The study deals with the adoption of mobile banking services by respondents in UAE and the perception of risk factors by them. A model was developed on the Customer Adoption Process of mobile banking. The model is validated based on the data collected using the questionnaire from a sample of 90 respondents in UAE. Factor analysis is used to evaluate and analyze the responses. Belief in technology and the value it creates are the major driving force for respondents to adopt mobile banking. Respondents perceive that mobile banking helps in proper financial planning due to continuous monitoring the transactions and time saving. Lack of privacy in the mobile banking transactions and not all banks offering mobile banking services in UAE are the major challenges perceived by the respondents for non-adoption of mobile banking. Respondents identify time risk, financial risk and performance risk as the most predominant risk factors compared to other risks in the adoption process.

  • The mediating role of emotional intelligence in the employees performance

    Arief Tukiman HendrawijayaORCID , Tatang Ary GumantiORCID , Sasongko , Zarah PuspitaningtyasORCID doi: http://dx.doi.org/10.21511/ppm.16(1).2018.14
    Problems and Perspectives in Management Volume 16, 2018         Issue #1         pp. 145-154 Views: 2022 Downloads: 749 TO CITE АНОТАЦІЯ

    This study investigates the mediating effect of emotional intelligence on the relationship between motivation, compensation, satisfaction, work climate and employees’ performance. The sample consists of 96 field officials who were the government employees specializing in coping with the eradication of Dengue Hemorrhagic Fever (DHF) in the district of Jember, Indonesia. Results using path analysis reveal that all examined variables positively and significantly affect employees’ performance. The study finds that emotional intelligence mediates the relationship of work motivation, compensation, work satisfaction, and work climate with employees’ performance.

  • Challenges of improving effectiveness and efficiency of the higher educational system in developing countries

    Saheer Al-JaghoubORCID , Ahmad Samed Al-AdwanORCID Researcher ID, Hussein Al-YaseenORCID Researcher ID, Anas Al-SoudORCID , Ahmad AreiqatORCID doi: http://dx.doi.org/10.21511/ppm.17(1).2019.03
    Problems and Perspectives in Management Volume 17, 2019         Issue #1         pp. 19-31 Views: 1853 Downloads: 462 TO CITE АНОТАЦІЯ

    Due to the country’s lack of natural resources and its dependence on human resources, Jordanian universities have started to implement quality assurance system aiming to improve effectiveness and efficiency of the higher educational system. This paper presents the results of a research that aims to identify the main issues and challenges facing these universities in implementing quality assurance system. Data for this research were collected using a survey mailed to all public and private universities to investigate the main issues affecting the implementation of quality assurance system in Jordanian universities. The results of this research showed that the most important challenges faced by Jordanian universities are: human and lack of awareness, resistance to change and cultural among others. The research findings hoped to be useful for both universities and policy makers in the government in order to realize the full benefits of implementing quality assurance system. Hence, this and other research on implementing quality assurance in higher educational institutions might be of assistance.

Download Preview
Close
Knowledge and Performance Management
Knowledge and Performance Management