Students’ Attitudes Towards Using ChatGPT as a Learning Tool: The Case of the University of Jordan

International Journal of Interactive Mobile Technologies (iJIM), Год журнала: 2023, Номер 17(18), С. 99 - 117

Опубликована: Сен. 20, 2023

This research aims to examine students’ attitudes toward using ChatGPT as a learning tool quantitative approach with descriptive study design. For data collection, researchers have developed attitude measures that utilize the ABC model, which encompasses three components of (affective, cognitive, and behavioral). The was conducted among random sample 623 undergraduates who enrolled at University Jordan, consisting 476 females 147 males. results statistics indicate there is high level positive utilizing tool. Furthermore, findings confirm moderate affective behavioral cognitive undergraduate students. A proportion respondents (73.2%) agreed on potential ability facilitate process. In comparison, 20.7% participants raised apprehensions regarding precision produced by ChatGPT, while an equivalent percentage (20.7%) reported feeling uncomfortable platform; conversely, 14.6% those surveyed acknowledged experiencing anxiety when unable access ChatGPT’s services. this encourage decision-makers educators Jordan incorporate into curricula instructional practices, considering student concerns risk misuse.

Язык: Английский

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The use of ChatGPT in teaching and learning: a systematic review through SWOT analysis approach

Frontiers in Education, Год журнала: 2024, Номер 9

Опубликована: Фев. 9, 2024

Introduction The integration of ChatGPT, an advanced AI-powered chatbot, into educational settings, has caused mixed reactions among educators. Therefore, we conducted a systematic review to explore the strengths and weaknesses using ChatGPT discuss opportunities threats in teaching learning. Methods Following PRISMA flowchart guidelines, 51 articles were selected 819 studies collected from Scopus, ERIC Google Scholar databases period 2022-2023. Results synthesis data extracted included revealed 32 topics including 13 strengths, 10 weaknesses, 5 4 We used Biggs’s Presage-Process-Product (3P) model learning categorize three components 3P model. Discussion In Presage stage, analyzed how interacts with student characteristics contexts ensure that technology adapts effectively diverse needs backgrounds. Process impacted activities determine its ability provide personalized, adaptive, effective instructional support. Finally, Product evaluated contributed outcomes. By carefully considering application each stage learning, educators can make informed decisions, leveraging addressing optimize processes.

Язык: Английский

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Ethics Education for Healthcare Professionals in the Era of ChatGPT and Other Large Language Models: Do We Still Need It?

The American Journal of Bioethics, Год журнала: 2023, Номер 23(10), С. 17 - 27

Опубликована: Июль 24, 2023

In this paper, we contend with whether still need traditional ethics education as part of healthcare professional training given the abilities chatGPT (generative pre-trained transformer) and other large language models (LLM). We reflect on common programmatic goals to assess current strengths limitations LLMs in helping build competencies among future clinicians. Through an actual case analysis, highlight areas which are conducive bioethics goals. also comment where such technologies remain imperfect substitute for human-led teaching learning. Finally, conclude that relative warrant its consideration a learning tool ways account flexibility technology evolves.

Язык: Английский

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A Critical Review of ChatGPT as a Potential Substitute for Diabetes Educators

Cureus, Год журнала: 2023, Номер unknown

Опубликована: Май 1, 2023

This review article explores the potential of ChatGPT as a substitute for diabetes educators. Diabetes is prevalent chronic disease that requires ongoing education and support patients to effectively manage their condition. However, there shortage educators, traditional methods have limitations in addressing patients' individual needs. an artificial intelligence technology offers personalized interactive approach support. In this review, we provide overview technology, discuss challenges facing evidence supporting use education, examine ethical considerations related its use. We also recommendations further research development integration into clinical practice. has improve access with diabetes, but needed better understand effectiveness limitations. It important ensure developed integrated equitable manner maximize benefits minimize risks.

Язык: Английский

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Revolutionizing generative pre-traineds: Insights and challenges in deploying ChatGPT and generative chatbots for FAQs

Expert Systems with Applications, Год журнала: 2024, Номер 246, С. 123224 - 123224

Опубликована: Янв. 19, 2024

Язык: Английский

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A Systematic Review of the Limitations and Associated Opportunities of ChatGPT

International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 16

Опубликована: Май 8, 2024

This systematic review explores the limitations and opportunities associated with ChatGPT's application across various fields. Following a rigorous screening process of 485 studies identified through searches in Scopus, Web Science, ERIC, IEEE Xplore databases, 33 high-quality empirical were selected for analysis. The identifies five key limitations: accuracy reliability concerns, critical thinking problem-solving, multifaceted impacts on learning development, technical constraints related to input output, ethical, legal, privacy concerns. However, also highlights exciting opportunities: educational support skill workflow enhancement, information retrieval, natural language interaction assistance, content creation ideation. While this provides valuable insights, it some gaps. Limited transparency regarding specific ChatGPT versions used hinders generalizability. Additionally, extent which these findings can be transferred more advanced models like ChatGPT-4 remains unclear. By acknowledging both opportunities, offers foundation researchers, developers, practitioners consider when exploring potential responsible similar evolving AI tools.

Язык: Английский

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A systematic literature review of empirical research on ChatGPT in education

Discover Education, Год журнала: 2024, Номер 3(1)

Опубликована: Май 26, 2024

Abstract Over the last four decades, studies have investigated incorporation of Artificial Intelligence (AI) into education. A recent prominent AI-powered technology that has impacted education sector is ChatGPT. This article provides a systematic review 14 empirical incorporating ChatGPT various educational settings, published in 2022 and before 10th April 2023—the date conducting search process. It carefully followed essential steps outlined Preferred Reporting Items for Systematic Reviews Meta-Analyses (PRISMA 2020) guidelines, as well Okoli’s (Okoli Commun Assoc Inf Syst, 2015) rigorous transparent review. In this review, we aimed to explore how students teachers utilized primary findings those studies. By employing Creswell’s (Creswell Educational research: planning, conducting, evaluating quantitative qualitative research [Ebook], Pearson Education, London, coding techniques data extraction interpretation, sought gain insight their initial attempts at approach also enabled us extract insights considerations can facilitate its effective responsible use future contexts. The results show learners virtual intelligent assistant, where it offered instant feedback, on-demand answers, explanations complex topics. Additionally, used enhance writing language skills by generating ideas, composing essays, summarizing, translating, paraphrasing texts, or checking grammar. Moreover, turned an aiding tool directed personalized learning assisting understanding concepts homework, providing structured plans, clarifying assignments tasks. However, specific (n = 3, 21.4%) overuse may negatively impact innovative capacities collaborative competencies among learners. Educators, on other hand, create lesson generate quizzes, provide additional resources, which helped them productivity efficiency promote different teaching methodologies. Despite these benefits, majority reviewed recommend importance training, support, clear guidelines both educators mitigate drawbacks. includes developing critical evaluation assess accuracy relevance information provided ChatGPT, strategies integrating human interaction collaboration activities involve AI tools. Furthermore, they ongoing proactive dialogue with policymakers, stakeholders, practitioners refine environments. could serve insightful resource who seek integrate stimulate further field.

Язык: Английский

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A Preliminary Checklist (METRICS) to Standardize the Design and Reporting of Studies on Generative Artificial Intelligence–Based Models in Health Care Education and Practice: Development Study Involving a Literature Review

Interactive Journal of Medical Research, Год журнала: 2024, Номер 13, С. e54704 - e54704

Опубликована: Янв. 26, 2024

Background Adherence to evidence-based practice is indispensable in health care. Recently, the utility of generative artificial intelligence (AI) models care has been evaluated extensively. However, lack consensus guidelines on design and reporting findings these studies poses a challenge for interpretation synthesis evidence. Objective This study aimed develop preliminary checklist standardize AI-based education practice. Methods A literature review was conducted Scopus, PubMed, Google Scholar. Published records with “ChatGPT,” “Bing,” or “Bard” title were retrieved. Careful examination methodologies employed included identify common pertinent themes possible gaps reporting. panel discussion held establish unified thorough AI The finalized used evaluate by 2 independent raters. Cohen κ as method interrater reliability. Results final data set that formed basis theme identification analysis comprised total 34 records. 9 collectively referred METRICS (Model, Evaluation, Timing, Range/Randomization, Individual factors, Count, Specificity prompts language). Their details are follows: (1) Model its exact settings; (2) Evaluation approach generated content; (3) Timing testing model; (4) Transparency source; (5) Range tested topics; (6) Randomization selecting queries; (7) factors queries reliability; (8) Count executed test (9) language used. overall mean score 3.0 (SD 0.58). acceptable, range 0.558 0.962 (P<.001 items). With classification per item, highest average recorded “Model” followed “Specificity” while lowest scores “Randomization” item (classified suboptimal) “Individual factors” satisfactory). Conclusions can facilitate guiding researchers toward best practices results. highlight need standardized algorithms care, considering variability observed proposed could be helpful base universally accepted which swiftly evolving research topic.

Язык: Английский

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Students' Perception of ChatGPT Usage in Education

International Journal of Advanced Computer Science and Applications, Год журнала: 2024, Номер 15(1)

Опубликована: Янв. 1, 2024

This research article delves into the impact of ChatGPT on education, focusing perceptions and usage patterns among high school university students. The begins by introducing ChatGPT, emphasizing its rapid user adoption widespread interest. It explores application in various fields, including healthcare, agriculture, education. A comprehensive survey involving 102 students, both university, is detailed, covering aspects like familiarity with reasons for usage, self-assessment effectiveness, attitudes toward informing teachers about use. findings reveal varied perspectives benefits challenges incorporating learning process. concludes need careful consideration integration AI technologies highlighting risks uncritical reliance such tools advocating a balanced approach to foster students' critical thinking intellectual growth.

Язык: Английский

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Comparing the Performance of Popular Large Language Models on the National Board of Medical Examiners Sample Questions

Cureus, Год журнала: 2024, Номер unknown

Опубликована: Март 11, 2024

Introduction: Large language models (LLMs) have transformed various domains in medicine, aiding complex tasks and clinical decision-making, with OpenAI's GPT-4, GPT-3.5, Google's Bard, Anthropic's Claude among the most widely used. While GPT-4 has demonstrated superior performance some studies, comprehensive comparisons these remain limited. Recognizing significance of National Board Medical Examiners (NBME) exams assessing knowledge medical students, this study aims to compare accuracy popular LLMs on NBME subject exam sample questions. Methods: The questions used were multiple-choice obtained from official website are publicly available. Questions pediatrics, obstetrics gynecology, neurology, ambulatory care, family psychiatry, surgery query each LLM. responses Claude, Bard collected October 2023. response by LLM was compared answer provided checked for accuracy. Statistical analysis performed using one-way variance (ANOVA). Results: A total 163 queried scored 163/163 (100%), GPT-3.5 134/163 (82.2%), 123/163 (75.5%), 138/163 (84.7%). statistically that 17.8%, 15.3%, 24.5%, respectively. not significantly different. outperformed specific subjects, including care medicine. Across all LLMs, had highest average score (18.25/20), while medicine lowest (3.75/5). Conclusion: GPT-4's underscores its potential education practice. exhibit promise, discernment their application is crucial, considering occasional inaccuracies. As technological advancements continue, regular reassessments refinements imperative maintain reliability relevance

Язык: Английский

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