ChatGPT has taken the world by storm, setting a record for the fastest app to reach a 100 million users, which it hit in two months. The implications of this tool are far-reaching, universities...

This dataset shows how men and women in the U.S. reported using ChatGPT in a 2025 survey, including whether they followed its advice or chose not to use it.

As of June 2023, it was reported that 10.8 percent of employees of worldwide companies have tried using ChatGPT in the workplace at least once. Those who have put confidential corporate data into the AI-powered tool were 4.7 percent.

A major challenge of our time is reducing disparities in access to and effective use of digital technologies, with recent discussions highlighting the role of AI in exacerbating the digital divide. We examine user characteristics that predict usage of the AI-powered conversational agent ChatGPT. We combine behavioral and survey data in a web tracked sample of N=1376 German citizens to investigate differences in ChatGPT activity (usage, visits, and adoption) during the first 11 months from the launch of the service (November 30, 2022). Guided by a model of technology acceptance (UTAUT-2), we examine the role of socio-demographics commonly associated with the digital divide in ChatGPT activity and explore further socio-political attributes identified via stability selection in Lasso regressions. We confirm that lower age and higher education affect ChatGPT usage, but neither gender nor income do. We find full-time employment and more children to be barriers to ChatGPT activity. Using a variety of social media was positively associated with ChatGPT activity. In terms of political variables, political knowledge and political self-efficacy as well as some political behaviors such as voting, debating political issues online and offline and political action online were all associated with ChatGPT activity, with online political debating and political self-efficacy negatively so. Finally, need for cognition and communication skills such as writing, attending meetings, or giving presentations, were also associated with ChatGPT engagement, though chairing/organizing meetings was negatively associated. Our research informs efforts to address digital disparities and promote digital literacy among underserved populations by presenting implications, recommendations, and discussions on ethical and social issues of our findings.

This dataset presents ChatGPT usage patterns across different age groups, showing the percentage of users who have followed its advice, used it without following advice, or have never used it, based on a 2025 U.S. survey.

The data set records the perceptions of Bangladeshi university students on the influence that AI tools, especially ChatGPT, have on their academic practices, learning experiences, and problem-solving abilities. The varying role of AI in education, which covers common usage statistics, what AI does to our creative abilities, its impact on our learning, and whether it could invade our privacy. This dataset reveals perspective on how AI tools are changing education in the country and offering valuable information for researchers, educators, policymakers, to understand trends, challenges, and opportunities in the adoption of AI in the academic contex.

Methodology Data Collection Method: Online survey using google from Participants: A total of 3,512 students from various Bangladeshi universities participated. Survey Questions:The survey included questions on demographic information, frequency of AI tool usage, perceived benefits, concerns regarding privacy, and impacts on creativity and learning.

Sampling Technique: Random sampling of university students Data Collection Period: June 2024 to December 2024

Privacy Compliance This dataset has been anonymized to remove any personally identifiable information (PII). It adheres to relevant privacy regulations to ensure the confidentiality of participants.

For further inquiries, please contact: Name: Md Jhirul Islam, Daffodil International University Email: jhirul15-4063@diu.edu.bd Phone: 01316317573

The potential of using Chat GPT and AI to revolutionize the way we interact with computers, specifically in the field of medical diagnostics. Chat GPT can make conversations between doctors and patients more natural, while AI can analyze vast amounts of patient data to identify trends and estimate a patient’s health. Patients can use Chat GPT to better understand their medical conditions, and both Chat GPT and AI can be used to automate tasks such as scheduling appointments and processing test results. However, there are limitations to using AI, including data bias, complex results, and analysis errors. To reduce errors, it is important to validate findings using various techniques and ensure that data is accurate and up-to-date. Chat GPT also employs security measures to protect patient data privacy and confidentiality.

In a survey conducted across four Southeast Asian countries in February 2023, almost half of the respondents selected collection of personal data as one of the concerns they had regarding the usage of chatbots like ChatGPT. In contrast, ethical issues related to data privacy and intellectual property were a concern for 42 percent of the respondents.

This dataset presents ChatGPT usage patterns across U.S. Census regions, based on a 2025 nationwide survey. It tracks how often users followed, partially used, or never used ChatGPT by state region.

IntroductionIn recent years, numerous AI tools have been employed to equip learners with diverse technical skills such as coding, data analysis, and other competencies related to computational sciences. However, the desired outcomes have not been consistently achieved. This study aims to analyze the perspectives of students and professionals from non-computational fields on the use of generative AI tools, augmented with visualization support, to tackle data analytics projects. The focus is on promoting the development of coding skills and fostering a deep understanding of the solutions generated. Consequently, our research seeks to introduce innovative approaches for incorporating visualization and generative AI tools into educational practices.MethodsThis article examines how learners perform and their perspectives when using traditional tools vs. LLM-based tools to acquire data analytics skills. To explore this, we conducted a case study with a cohort of 59 participants among students and professionals without computational thinking skills. These participants developed a data analytics project in the context of a Data Analytics short session. Our case study focused on examining the participants' performance using traditional programming tools, ChatGPT, and LIDA with GPT as an advanced generative AI tool.ResultsThe results shown the transformative potential of approaches based on integrating advanced generative AI tools like GPT with specialized frameworks such as LIDA. The higher levels of participant preference indicate the superiority of these approaches over traditional development methods. Additionally, our findings suggest that the learning curves for the different approaches vary significantly. Since learners encountered technical difficulties in developing the project and interpreting the results. Our findings suggest that the integration of LIDA with GPT can significantly enhance the learning of advanced skills, especially those related to data analytics. We aim to establish this study as a foundation for the methodical adoption of generative AI tools in educational settings, paving the way for more effective and comprehensive training in these critical areas.DiscussionIt is important to highlight that when using general-purpose generative AI tools such as ChatGPT, users must be aware of the data analytics process and take responsibility for filtering out potential errors or incompleteness in the requirements of a data analytics project. These deficiencies can be mitigated by using more advanced tools specialized in supporting data analytics tasks, such as LIDA with GPT. However, users still need advanced programming knowledge to properly configure this connection via API. There is a significant opportunity for generative AI tools to improve their performance, providing accurate, complete, and convincing results for data analytics projects, thereby increasing user confidence in adopting these technologies. We hope this work underscores the opportunities and needs for integrating advanced LLMs into educational practices, particularly in developing computational thinking skills.

Data for this study were collected at the University of California – Irvine (UCI) as part of the UCI-MUST (Measuring Undergraduate Success Trajectories) Project, a larger longitudinal measurement project aimed at improving understanding of undergraduate experience, trajectories and outcomes, while supporting campus efforts to improve institutional performance and enhance educational equity (Arum et. al. 2021). The project is focused on student educational experience at a selective large, research-oriented public university on the quarter system with half of its students first-generation and 85 percent Hispanic, Asian, African-American, Pacific Islander or Native American. Since Fall 2019, the project has tracked annually new cohorts of freshmen and juniors with longitudinal surveys administered at the end of every academic quarter. Data from the Winter 2023 end of term assessment, administered in the first week of April, was pooled for four longitudinal study cohorts for this study (i.e., Fall 2019-2022 cohorts). There was an overall response rate of 42.5 percent for the Winter 2023 end of term assessment. This allowed us to consider student responses from freshmen through senior years enrolled in courses throughout the university. Students completed questionnaire items about their knowledge and use of ChatGPT in and out of the classroom during the winter 2023 academic term. In total 1,129 students completed the questionnaire, which asked questions about: knowledge of ChatGPT (“Do you know what ChatGPT is?”); general use (“Have you used ChatGPT before?”); and instructor attitude (“What was the attitude of the instructor for [a specific course students enrolled in] regarding the use of ChatGPT?”). Of those 1,129 students, 191 had missing data for at least one variable of interest and were subsequently dropped from analysis, resulting in a final sample of 938 students. In addition, for this study we merged our survey data with administrative data from campus that encompasses details on student background, including gender, race, first-generation college-going, and international student status. Campus administrative data also provides course-level characteristics, including whether a particular class is a lower- or upper-division course as well as the academic unit on campus offering the course. In addition, we used administrative data on all students enrolled at the university to generate classroom composition measures for every individual course taken by students in our sample – specifically the proportion of underrepresented minority students in the class, the proportion of international students in the class and the proportion of female students in the class. For our student-level analysis [R1], we used binary logistic regressions to examine the association between individual characteristics and (1) individual awareness and (2) individual academic use of ChatGPT utilizing the student-level data of 938 students. Individual characteristics include gender, underrepresented minority student status, international student status, first generation college-going student status, student standing (i.e. lower or upper classmen), cumulative grade point average and field of study. Field of study was based on student major assigned to the broad categories of physical sciences (i.e. physical sciences, engineering, and information and computer science), health sciences (i.e. pharmacy, biological sciences, public health, and nursing), humanities, social sciences (i.e. business, education, and social sciences), the arts, or undeclared. We defined awareness of ChatGPT as an affirmative response to the question “Do you know what ChatGPT is?” Regarding ChatGPT use, we focused on academic use which was defined as an affirmative response of either “Yes, for academic use” or “Yes, for academic and personal use” to the question “Have you used ChatGPT before?” For our course-level analysis [R2], we constructed a measure – course-level instructor encouragement for ChatGPT use – based on student responses to the end of the term survey conducted at the completion of the Winter 2023 term. In the survey, students were asked to indicate the extent to which their instructors encouraged them to use ChatGPT in each of their enrolled courses. The response

Within a year of its launch, ChatGPT has seen a surge in popularity. While many are drawn to its effectiveness and user-friendly interface, ChatGPT also introduces moral concerns, such as the temptation to present generated text as one’s own. This led us to theorize that personality traits such as Machiavellianism and sensation-seeking may be predictive of ChatGPT usage. We launched two online questionnaires with 2,000 respondents each, in September 2023 and March 2024, respectively. In Questionnaire 1, 22% of respondents were students, and 54% were full-time employees; 32% indicated they used ChatGPT at least weekly. Analysis of our ChatGPT Acceptance Scale revealed two factors, Effectiveness and Concerns, which correlated positively and negatively, respectively, with ChatGPT use frequency. A specific aspect of Machiavellianism (manipulation tactics) was found to predict ChatGPT usage. Questionnaire 2 was a replication of Questionnaire 1, with 21% students and 54% full-time employees, of which 43% indicated using ChatGPT weekly. In Questionnaire 2, more extensive personality scales were used. We found a moderate correlation between Machiavellianism and ChatGPT usage (r = .22) and with an opportunistic attitude towards undisclosed use (r = .30), relationships that largely remained intact after controlling for gender, age, education level, and the respondents’ country. We conclude that covert use of ChatGPT is associated with darker personality traits, something that requires further attention.

ChatGPT is used most widely among those between 25 and 34 around the world. The youngest group, those under 24, are the second largest userbase, and together those under 34 account for over 60 percent of ChatGPT users. It is perhaps unsurprising that the younger age brackets use the chatbot more than older as that is the common trend with new technologies. Male users were far more numerous than female users, with males representing over 65 percent of total users in 2023.

This repository contains two datasets used in the study exploring the impact of Generative AI, specifically ChatGPT, on the public sector workforce in the United States. The datasets provide detailed information on the core tasks of public sector occupations and their estimated performance metrics, including potential for automation and augmentation by ChatGPT. These estimations are generated by OpenAI’s GPT-4 model (GPT-4-1106-preview) through OpenAI API.

The researcher tests the QA capability of ChatGPT in the medical field from the following aspects:1. Test their reserve capacity for medical knowledge2. Check their ability to read literature and understand medical literature3. Test their ability of auxiliary diagnosis after reading case data4. Test its error correction ability for case data5. Test its ability to standardize medical terms6. Test their evaluation ability to experts7. Check their ability to evaluate medical institutionsThe conclusion is:ChatGPT has great potential in the application of medical and health care, and may directly replace human beings or even professionals at a certain level in some fields;The researcher preliminarily believe that ChatGPT has basic medical knowledge and the ability of multiple rounds of dialogue, and its ability to understand Chinese is not weak;ChatGPT has the ability to read, understand and correct cases;ChatGPT has the ability of information extraction and terminology standardization, and is quite excellent;ChatGPT has the reasoning ability of medical knowledge;ChatGPT has the ability of continuous learning. After continuous training, its level has improved significantly;ChatGPT does not have the academic evaluation ability of Chinese medical talents, and the results are not ideal;ChatGPT does not have the academic evaluation ability of Chinese medical institutions, and the results are not ideal;ChatGPT is an epoch-making product, which can become a useful assistant for medical diagnosis and treatment, knowledge service, literature reading, review and paper writing.

This dataset shows the types of advice users sought from ChatGPT based on a 2025 U.S. survey, including education, financial, medical, and legal topics.

Large language models present new opportunities for teaching and learning. The response accuracy of these models, however, is believed to depend on the prompt quality which can be a challenge for students. In this study, we aimed to explore how undergraduate students use ChatGPT for problem-solving, what prompting strategies they develop, the link between these strategies and the model’s response accuracy, the existence of individual prompting tendencies, and the impact of gender in this context. Our students used ChatGPT to solve five problems related to embedded systems and provided the solutions and the conversations with this model. We analyzed the conversations thematically to identify prompting strategies and applied different quantitative analyses to establish relationships between these strategies and the response accuracy and other factors. The findings indicate that students predominantly employ three types of prompting strategies: single copy-and-paste prompting (SCP), single reformulated prompting (SRP), and multiple-question prompting (MQP). ChatGPT’s response accuracy using SRP and MQP was significantly higher than using SCP, with effect sizes of -0.94 and -0.69, respectively. The student-by-student analysis revealed some tendencies. For example, 26 percent of the students consistently copied and pasted the questions into ChatGPT without any modification. Students who used MQP showed better performance in the final exam than those who did not use this prompting strategy. As for gender, female students tended to make extensive use of SCP, whereas male students tended to mix SCP and MQP. We conclude that students develop different prompting strategies that lead to different response qualities and learning. More research is needed to deepen our understanding and inform effective educational practices in the AI era.

This dataset reflects how Americans perceive ChatGPT's broader societal impact, based on a 2025 survey that asked whether the AI will help or harm humanity.

Personality research has traditionally relied on questionnaires, which bring with them inherent limitations, such as response style bias. With the emergence of large language models such as ChatGPT, the question arises as to what extent these models can be used in personality research. In this study, ChatGPT (GPT-4) generated 2000 text-based personas. Next, for each persona, ChatGPT completed a short form of the Big Five Inventory (BFI-10), the Brief Sensation Seeking Scale (BSSS), and a Short Dark Triad (SD3). The mean scores on the BFI-10 items were found to correlate strongly with means from previously published research, and principal component analysis revealed a clear five-component structure. Certain relationships between traits, such as a negative correlation between the age of the persona and the BSSS score, were clearly interpretable, while some other correlations diverged from the literature. An additional analysis using four new sets of 2000 personas each, including a set of ‘realistic’ personas and a set of cinematic personas, showed that the correlation matrix among personality constructs was affected by the persona set. It is concluded that evaluating questionnaires and research hypotheses prior to engaging with real individuals holds promise.

In a survey conducted across four Southeast Asian countries in February 2023, 76 percent of the respondents in Singapore selected the collection of personal data as one of the concerns they had regarding the usage of chatbots like ChatGPT. In contrast, this was an issue for 36 percent of respondents in Indonesia.