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2. The AI Divide: Equitable Applications of AI in Higher Education to Advance the Completion Agenda. A Position Paper on AI, Access, and Digital Tools as Levers for Equity in Higher Education.
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Complete College America (CCA)
- Abstract
In this position paper, the authors lay out the imperative for equitable artificial intelligence (AI), highlighting the essential role of access-oriented institutions and calling on technology companies (both large and small), foundations, and local, state, and federal regulators to consult with the newly convened Complete College America Council on Equitable AI in Higher Education. Their belief is that equitable AI spans far beyond the risk of mis-trained data. How schools adopt or reject these tools, the priorities of AI vendors, access to resources that enable the use of these tools, and the systemic integration of historically underrepresented and underserved voices will shape whether technology amplifies privilege or fosters inclusivity. A three-fold framework is presented for understanding Equity in AI, considering not just the quality and unbiased nature of the data used to train generative AI machines but also who has access to conversations around policy and product, as well as which institutions have access to the resources and safety nets that enable innovation and experimentation in the field of AI. A disruptive new advisory council is proposed, the Complete College America Council on Equitable AI in Higher Education, composed of representatives from historically excluded institutions and, by extension, students. The authors urge policymakers, technologists, and funders to proactively consult the Council and disrupt systemic inequities by integrating AI into higher education rather than continue to perpetuate them. [This paper was created in partnership with T3 Advisory.]
- Published
- 2023
3. Has your paper been used to train an AI model? Almost certainly.
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Gibney E
- Subjects
- Copyright economics, Copyright legislation & jurisprudence, Datasets as Topic economics, Datasets as Topic legislation & jurisprudence, Machine Learning economics, Research Personnel economics, Artificial Intelligence economics, Research Report
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- 2024
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4. Exploring the potential of artificial intelligence to enhance the writing of english academic papers by non-native english-speaking medical students - the educational application of ChatGPT.
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Li J, Zong H, Wu E, Wu R, Peng Z, Zhao J, Yang L, Xie H, and Shen B
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- Humans, China, Education, Medical, Undergraduate, Male, Female, Language, Writing, Students, Medical, Artificial Intelligence
- Abstract
Background: Academic paper writing holds significant importance in the education of medical students, and poses a clear challenge for those whose first language is not English. This study aims to investigate the effectiveness of employing large language models, particularly ChatGPT, in improving the English academic writing skills of these students., Methods: A cohort of 25 third-year medical students from China was recruited. The study consisted of two stages. Firstly, the students were asked to write a mini paper. Secondly, the students were asked to revise the mini paper using ChatGPT within two weeks. The evaluation of the mini papers focused on three key dimensions, including structure, logic, and language. The evaluation method incorporated both manual scoring and AI scoring utilizing the ChatGPT-3.5 and ChatGPT-4 models. Additionally, we employed a questionnaire to gather feedback on students' experience in using ChatGPT., Results: After implementing ChatGPT for writing assistance, there was a notable increase in manual scoring by 4.23 points. Similarly, AI scoring based on the ChatGPT-3.5 model showed an increase of 4.82 points, while the ChatGPT-4 model showed an increase of 3.84 points. These results highlight the potential of large language models in supporting academic writing. Statistical analysis revealed no significant difference between manual scoring and ChatGPT-4 scoring, indicating the potential of ChatGPT-4 to assist teachers in the grading process. Feedback from the questionnaire indicated a generally positive response from students, with 92% acknowledging an improvement in the quality of their writing, 84% noting advancements in their language skills, and 76% recognizing the contribution of ChatGPT in supporting academic research., Conclusion: The study highlighted the efficacy of large language models like ChatGPT in augmenting the English academic writing proficiency of non-native speakers in medical education. Furthermore, it illustrated the potential of these models to make a contribution to the educational evaluation process, particularly in environments where English is not the primary language., (© 2024. The Author(s).)
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- 2024
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5. Working Paper: How Are Faculty Reacting to ChatGPT?
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Dukewich, Kriste and Larsen, Carmen
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Generative AI platforms like ChatGPT have exploded into our cultural awareness this year. Across post-secondary institutions, it was immediately apparent that faculty were eager to explore and discuss what this potentially disruptive technology might mean for them, their courses and their students. We wanted to create an opportunity for that discussion and to get a truer sense of initial faculty reactions than what sensational media headlines were offering. This working paper outlines the results of a facilitated online forum, open to faculty and staff from two institutions in the Lower Mainland of British Columbia in January 2023. Our session invited participants to test ChatGPT, reflecting on its strengths and limitations, and then talk through the potential impacts on instructors, our students, and post-secondary education in general of different approaches: ignore it, fight it, and embrace it. Analysis of participant contributions to polls, group discussions and a highly active chat space provide a snapshot of how faculty and staff were feeling and what they were doing in response to ChatGPT and other generative AI platforms. While the data seems to indicate a relatively optimistic take at this early point in the AI revolution, excerpts from discussions and debates do indicate a range of emotions and reactions--a range that will likely only continue to widen with the continuing release of ever more capable AI.
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- 2023
6. The 100 most influential papers in medical artificial intelligence; a bibliometric analysis.
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Zahoor F, Abdullah M, Tahir MW, and Islam A
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- Humans, Periodicals as Topic statistics & numerical data, Artificial Intelligence, Bibliometrics, Clinical Medicine
- Abstract
Objective: To assess the current trends in the field of artificial intelligence in medicine by analysing 100 most cited original articles relevant to the field., Methods: The bibliometric analysis was conducted in September 2022, and comprised literature search on Scopus database for original articles only. Google and Medical Subject Headings databases were used as resources to extract key words. In order to cover a broad range of articles, original studies comprising human as well as non-human subjects, studies without abstract and studies in languages other than English were part of the inclusion criteria. There was no specific time period applied to the search and no specific selection was done regarding the journals in the database. The screening was done using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to extract the top 100 most cited articles in the field of artificial intelligence usage in medicine. Data was analysed using SPSS 23., Results: Of the 11,571 studies identified, 100(0.86%) were analysed in detail. The studies were published between 1986 and 2021, with a median of 43 citations (IQR 53) per article. The journal 'Artificial Intelligence in Medicine' accounted for the highest number 9(9%)) of articles, and the United States was the country of origin for most of the articles 36(36%)., Conclusion: The trends, development and shortcomings in field of artificial intelligence usage in medicine need to be understood to conduct an effective research in areas that still need attention, and to guide the authorities to direct their funding accordingly.
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- 2024
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7. Is Artificial Intelligence Really the next Big Thing in Learning and Teaching in Higher Education? A Conceptual Paper
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O'Dea, Xianghan and O'Dea, Mike
- Abstract
Artificial Intelligence in higher education (AIED) is becoming a more important research area with increasing developments and application of AI within the wider society. However, as yet AI based tools have not been widely adopted in higher education. As a result there is a lack of sound evidence available on the pedagogical impact of AI for learning and teaching. This conceptual paper thus seeks to bridge the gap and addresses the following question: is artificial intelligence really the new big thing that will revolutionise learning and teaching in higher education? Adopting the technological pedagogical content knowledge (TPACK) framework and the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical foundations, we argue that Artificial Intelligence (AI) technologies, at least in their current state of development, do not afford any real new advances for pedagogy in higher education. This is mainly because there does not seem to be valid evidence as to how the use of AI technologies and applications has helped students improve learning, and/or helped tutors make effective pedagogical changes. In addition, the pedagogical affordances of AI have not yet been clearly defined. The challenges that the higher education sector is currently experiencing relating to AI adoption are discussed at three hierarchical levels, namely national, institutional and personal levels. The paper ends with recommendations with regard to accelerating AI use in universities. This includes developing dedicated AI adoption strategies at the institutional level, updating the existing technology infrastructure and upskilling academic tutors for AI.
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- 2023
8. Evaluating Machine Learning for Projecting Completion Rates for VET Programs. Technical Paper
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National Centre for Vocational Education Research (NCVER) (Australia), Hall, Michelle, Lees, Melinda, Serich, Cameron, and Hunt, Richard
- Abstract
This paper summarises exploratory analysis undertaken to evaluate the effectiveness of using machine learning approaches to calculate projected completion rates for vocational education and training (VET) programs, and compares this with the current approach used at the National Centre for Vocational Education Research (NCVER) -- Markov chains methodology. While the Markov chains methodology currently used by NCVER has demonstrated that it is reliable, with predictions aligning well with the actual rates of completion for historical estimates, it has not been reviewed for some time and it does have some limitations. The evaluation of machine learning techniques for predicting VET program completion rates was undertaken to overcome some of these limitations and with a view to improving our current predictions. This report includes: (1) an overview of the methodologies: Markov chains and two machine learning algorithms that were applied to predict completion rates for VET programs (XGBoost and CatBoost); (2) a comparison of the accuracy of the predictions generated by both methodologies; and (3) an evaluation of the relative strengths and limitations of both methodologies.
- Published
- 2023
9. Automated Paper Screening for Clinical Reviews Using Large Language Models: Data Analysis Study.
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Guo E, Gupta M, Deng J, Park YJ, Paget M, and Naugler C
- Subjects
- Humans, Consensus, Data Analysis, Problem Solving, Natural Language Processing, Workflow, Biomedical Research, Systematic Reviews as Topic, Artificial Intelligence
- Abstract
Background: The systematic review of clinical research papers is a labor-intensive and time-consuming process that often involves the screening of thousands of titles and abstracts. The accuracy and efficiency of this process are critical for the quality of the review and subsequent health care decisions. Traditional methods rely heavily on human reviewers, often requiring a significant investment of time and resources., Objective: This study aims to assess the performance of the OpenAI generative pretrained transformer (GPT) and GPT-4 application programming interfaces (APIs) in accurately and efficiently identifying relevant titles and abstracts from real-world clinical review data sets and comparing their performance against ground truth labeling by 2 independent human reviewers., Methods: We introduce a novel workflow using the Chat GPT and GPT-4 APIs for screening titles and abstracts in clinical reviews. A Python script was created to make calls to the API with the screening criteria in natural language and a corpus of title and abstract data sets filtered by a minimum of 2 human reviewers. We compared the performance of our model against human-reviewed papers across 6 review papers, screening over 24,000 titles and abstracts., Results: Our results show an accuracy of 0.91, a macro F
1 -score of 0.60, a sensitivity of excluded papers of 0.91, and a sensitivity of included papers of 0.76. The interrater variability between 2 independent human screeners was κ=0.46, and the prevalence and bias-adjusted κ between our proposed methods and the consensus-based human decisions was κ=0.96. On a randomly selected subset of papers, the GPT models demonstrated the ability to provide reasoning for their decisions and corrected their initial decisions upon being asked to explain their reasoning for incorrect classifications., Conclusions: Large language models have the potential to streamline the clinical review process, save valuable time and effort for researchers, and contribute to the overall quality of clinical reviews. By prioritizing the workflow and acting as an aid rather than a replacement for researchers and reviewers, models such as GPT-4 can enhance efficiency and lead to more accurate and reliable conclusions in medical research., (©Eddie Guo, Mehul Gupta, Jiawen Deng, Ye-Jean Park, Michael Paget, Christopher Naugler. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 12.01.2024.)- Published
- 2024
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10. Annual Proceedings of Selected Research and Development Papers and Selected Papers on the Practice of Educational Communications and Technology Presented Online and On-Site during the Annual Convention of the Association for Educational Communications and Technology (45th, Las Vegas, Nevada, 2022). Volumes 1 and 2
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Association for Educational Communications and Technology (AECT), Michael Simonson, and Deborah Seepersaud
- Abstract
For the forty-fifth time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented online and onsite during the annual AECT Convention. The Proceedings of AECT's Convention are published in two volumes. Volume #1 contains papers dealing primarily with research and development topics. Papers dealing with the practice of instructional technology including instruction and training issues are contained in Volume #2. This year, both volumes are included in one document.
- Published
- 2022
11. The Skills Imperative 2035: What Does the Literature Tell Us about Essential Skills Most Needed for Work? Working Paper 1
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National Foundation for Educational Research (NFER) (United Kingdom), Taylor, Amanda, Nelson, Julie, O'Donnell, Sharon, Davies, Elizabeth, and Hillary, Jude
- Abstract
Calls are intensifying for workforce reskilling and a re-engineering of education and training to meet the demands of the future. Current policy in England focuses on technical, digital and green economy skills, underpinned by strong literacy and numeracy and a knowledge-rich school curriculum. National Foundation for Educational Research's Nuffield-funded research study, "The Skills Imperative 2035: Essential skills for tomorrow's workforce" investigates: (1) which essential employment skills will be most needed in 2035; (2) what will their likely supply be and where will the gaps be; (3) which occupations and workers are most at risk of not having these skills; (4) which skills will affected workers need to develop to transition into new employment opportunities; and (5) the role of educators and employers in helping to prepare young people and workers for the future labour market. This first report, a review drawing on a wide-ranging and growing evidence base, sets the scene for the wider research study by bringing together what the literature suggests about: (1) what the world of work will look like in 2035; and (2) which essential employment skills will be in demand and how what should be done to prepare.
- Published
- 2022
12. Faculty Members' Use of Artificial Intelligence to Grade Student Papers: A Case of Implications
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Kumar, Rahul
- Abstract
This paper presents the case of an adjunct university professor to illustrate the dilemma of using artificial intelligence (AI) technology to grade student papers. The hypothetical case discusses the benefits of using a commercial AI service to grade student papers--including discretion, convenience, pedagogical merits of consistent feedback for students, and advances made in the field that yield high-quality work--all of which are achieved quickly. Arguments against using AI to grade student papers involve cost, privacy, legality, and ethics. The paper discusses career implications for faculty members in both situations and concludes with implications for researchers within the discourse on academic integrity.
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- 2023
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13. AI beats human sleuth at finding problematic images in research papers.
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Oza A
- Subjects
- Humans, Artificial Intelligence standards, Pattern Recognition, Automated standards, Research Report standards, Photography standards
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- 2023
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14. Assessing the performance of ChatGPT to solve biochemistry question papers of university examination.
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Mahat RK, Jantikar AM, Rathore V, and Panda S
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- Humans, Universities, Artificial Intelligence, Biochemistry education, Academic Performance
- Published
- 2023
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15. Not Lost in Translation: The Implications of Machine Translation Technologies for Language Professionals and for Broader Society. OECD Social, Employment and Migration Working Papers. No. 291
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Organisation for Economic Cooperation and Development (OECD) (France), Borgonovi, Francesca, Hervé, Justine, and Seitz, Helke
- Abstract
The paper discusses the implications of recent advances in artificial intelligence for knowledge workers, focusing on possible complementarities and substitution between machine translation tools and language professionals. The emergence of machine translation tools could enhance social welfare through enhanced opportunities for inter-language communication but also create new threats because of persisting low levels of accuracy and quality in the translation output. The paper uses data on online job vacancies to map the evolution of the demand for language professionals between 2015 and 2019 in 10 countries and illustrates the set of skills that are considered important by employers seeking to hire language professionals through job vacancies posted on line.
- Published
- 2023
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16. Distinguishing ChatGPT(-3.5, -4)-generated and human-written papers through Japanese stylometric analysis.
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Zaitsu W and Jin M
- Subjects
- Humans, Random Forest, Artificial Intelligence, Writing
- Abstract
In the first half of 2023, text-generative artificial intelligence (AI), including ChatGPT from OpenAI, has attracted considerable attention worldwide. In this study, first, we compared Japanese stylometric features of texts generated by ChatGPT, equipped with GPT-3.5 and GPT-4, and those written by humans. In this work, we performed multi-dimensional scaling (MDS) to confirm the distributions of 216 texts of three classes (72 academic papers written by 36 single authors, 72 texts generated by GPT-3.5, and 72 texts generated by GPT-4 on the basis of the titles of the aforementioned papers) focusing on the following stylometric features: (1) bigrams of parts-of-speech, (2) bigram of postpositional particle words, (3) positioning of commas, and (4) rate of function words. MDS revealed distinct distributions at each stylometric feature of GPT (3.5 and 4) and human. Although GPT-4 is more powerful than GPT-3.5 because it has more parameters, both GPT (3.5 and 4) distributions are overlapping. These results indicate that although the number of parameters may increase in the future, GPT-generated texts may not be close to that written by humans in terms of stylometric features. Second, we verified the classification performance of random forest (RF) classifier for two classes (GPT and human) focusing on Japanese stylometric features. This study revealed the high performance of RF in each stylometric feature: The RF classifier focusing on the rate of function words achieved 98.1% accuracy. Furthermore the RF classifier focusing on all stylometric features reached 100% in terms of all performance indexes (accuracy, recall, precision, and F1 score). This study concluded that at this stage we human discriminate ChatGPT from human limited to Japanese language., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Zaitsu, Jin. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2023
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17. AI intensifies fight against 'paper mills' that churn out fake research.
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Liverpool L
- Subjects
- Deception, Artificial Intelligence, Predatory Journals as Topic, Scientific Misconduct legislation & jurisprudence, Scientific Misconduct statistics & numerical data, Scientific Misconduct trends
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- 2023
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18. Annual Proceedings of Selected Research and Development Papers Presented Online and On-Site during the Annual Convention of the Association for Educational Communications and Technology (44th, Chicago, Illinois, 2021). Volume 1
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Association for Educational Communications and Technology (AECT), Simonson, Michael, and Seepersaud, Deborah
- Abstract
For the forty-fourth time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented online and onsite during the annual AECT Convention. Volume 1 contains papers dealing primarily with research and development topics. Papers dealing with the practice of instructional technology including instruction and training issues are contained in Volume 2. [For volume 2, see ED617429.]
- Published
- 2021
19. 2020 Policy Paper on Public Responsibility, Financing and Governance of Higher Education
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European Students' Union (ESU) (Belgium)
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This Policy Paper aims at analysing the most important aspects of Public Responsibility, Financing and Governance of Higher Educations while seeking to formulate a students perspective on the state of play within the European Higher Education Area (EHEA). In doing so it touches upon the very foundation of how and in which socio-political environment educational systems and higher education institutions work nowadays. The European Students' Union (ESU) believes that open access to all levels of education is the cornerstone of a socially, culturally and democratically inclusive society, and a prerequisite for individual and societal development and well-being. ESU sees higher education as a human right, which is guaranteed in the Universal Declaration of Human Rights and the International Covenant on Economic, Social and Cultural Rights. How education is seen in society, how it is funded and how it is governed are tightly interlinked areas. This policy paper focuses on: (1) Public responsibility of higher education (fundamental values; institutional autonomy and academic freedom; academic integrity; intellectual property; education for sustainable development; human rights and democratic citizenship education; digitalization, artificial intelligence, learning analytics and privacy; commodification; partnerships between higher education institutions and industry; internships; and internationalisation and international trade); (2) Financing of higher education (financing of higher education; the funding gap; optimisation of funding of higher education institutions; performance based funding; and education free of tuition fees); and (3) Governance of higher education (students participation; working conditions of academic staff; committees and ombudsmans and leadership, intersectionality and training). [For the 2016 version, see ED587168.]
- Published
- 2020
20. Annual Proceedings of Selected Papers on the Practice of Educational Communications and Technology Presented at the Annual Convention of the Association for Educational Communications and Technology (43rd, Online, 2020). Volume 2
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Association for Educational Communications and Technology (AECT), Simonson, Michael, and Seepersaud, Deborah
- Abstract
For the forty-third time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented online during the annual AECT Convention. Volume 2 contains 15 papers dealing the practice of instructional technology including instruction and training issues. Papers dealing primarily with research and development are contained in Volume 1. [For Volume 1, see ED617421.]
- Published
- 2020
21. How paediatric drug development and use could benefit from OMICs: A c4c expert group white paper.
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Neumann E, Schreeck F, Herberg J, Jacqz Aigrain E, Maitland-van der Zee AH, Pérez-Martínez A, Hawcutt DB, Schaeffeler E, Rane A, de Wildt SN, and Schwab M
- Subjects
- Humans, Child, Biological Specimen Banks, Prospective Studies, Metabolomics methods, Biomarkers, Drug Development, Artificial Intelligence, Pediatrics
- Abstract
The safety and efficacy of pharmacotherapy in children, particularly preterms, neonates and infants, is limited by a paucity of good-quality data from prospective clinical drug trials. A specific challenge is the establishment of valid biomarkers. OMICs technologies may support these efforts by complementary information about targeted and nontargeted molecules through systematic characterization and quantitation of biological samples. OMICs technologies comprise at least genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiomics in addition to the patient's phenotype. OMICs technologies are in part hypothesis-generating, allowing an in depth understanding of disease pathophysiology and pharmacological mechanisms. Application of OMICs technologies in paediatrics faces major challenges before routine adoption. First, developmental processes need to be considered, including a subdivision into specific age groups as developmental changes clearly impact OMICs data. Second, compared to the adult population, the number of patients is limited as are the type and amount of necessary biomaterial, especially in neonates and preterms. Thus, advanced trial designs and biostatistical methods, noninvasive biomarkers, innovative biobanking concepts including data and samples from healthy children, as well as analytical approaches (eg liquid biopsies) should be addressed to overcome these obstacles. The ultimate goal is to link OMICs technologies with innovative analysis tools, such as artificial intelligence at an early stage. The use of OMICs data based on a feasible approach will contribute to the identification complex phenotypes and subpopulations of patients to improve the development of medicines for children with potential economic advantages., (© 2022 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)
- Published
- 2022
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22. Artificial Intelligence & Higher Education: Towards Customized Teaching and Learning, and Skills for an AI World of Work. Research & Occasional Paper Series: CSHE.6.2020
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University of California, Berkeley. Center for Studies in Higher Education and Taneri, Grace Ufuk
- Abstract
We are living in an era of artificial intelligence (AI). There is wide discussion about and experimentation with the impact of AI on education/higher education. In this paper, we give a discussion of how AI is evolving, explore the ways AI is changing education/higher education, give a concise account of the skills universities need to teach their students to prepare them for an AI world of work, and talk succinctly about the changing nature of jobs and the workforce.
- Published
- 2020
23. The Challenges of Regulating Artificial Intelligence in Healthcare Comment on "Clinical Decision Support and New Regulatory Frameworks for Medical Devices: Are We Ready for It? - A Viewpoint Paper".
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McKee M and Wouters OJ
- Subjects
- Humans, Delivery of Health Care, Health Facilities, Technology, Artificial Intelligence, Decision Support Systems, Clinical
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Regulation of health technologies must be rigorous, instilling trust among both healthcare providers and patients. This is especially important for the control and supervision of the growing use of artificial intelligence in healthcare. In this commentary on the accompanying piece by Van Laere and colleagues, we set out the scope for applying artificial intelligence in the healthcare sector and outline five key challenges that regulators face in dealing with these modern-day technologies. Addressing these challenges will not be easy. While artificial intelligence applications in healthcare have already made rapid progress and benefitted patients, these applications clearly hold even more potential for future developments. Yet it is vital that the regulatory environment keep up with this fast-evolving space of healthcare in order to anticipate and, to the extent possible, prevent the risks that may arise., (© 2023 The Author(s); Published by Kerman University of Medical Sciences This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.)
- Published
- 2023
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24. ChatGPT listed as author on research papers: many scientists disapprove.
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Stokel-Walker C
- Subjects
- Authorship, Publishing legislation & jurisprudence, Publishing trends, Artificial Intelligence legislation & jurisprudence, Artificial Intelligence trends, Research Report standards, Research Report trends
- Published
- 2023
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25. Should Colleges Invest in Machine Learning? Comparing the Predictive Powers of Early Momentum Metrics and Machine Learning for Community College Credential Completion. CCRC Working Paper No. 118
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Columbia University, Community College Research Center and Yanagiura, Takeshi
- Abstract
Among community college leaders and others interested in reforms to improve student success, there is growing interest in adopting machine learning (ML) techniques to predict credential completion. However, ML algorithms are often complex and are not readily accessible to practitioners for whom a simpler set of near-term measures may serve as sufficient predictors. This study compares the out-of-sample predictive power of early momentum metrics (EMMs)--13 near-term success measures suggested by the literature--with that of metrics from ML-based models that employ approximately 500 predictors for community college credential completion. Using transcript data from approximately 50,000 students at more than 30 community colleges in two states, I find that the EMMs that were modeled by logistic regression accurately predict completion for approximately 80% of students. This classification performance is comparable to that of the ML-based models. The EMMs even outperform the ML-based models in probability estimation. These findings suggest that EMMs are useful predictors for credential completion and that the marginal gain from using an ML-based model over EMMs is small for credential completion prediction when additional predictors do not have strong rationales to be included in an ML-based model, no matter how large the number of those predictors may be.
- Published
- 2020
26. Responsible Operations: Data Science, Machine Learning, and AI in Libraries. OCLC Research Position Paper
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OCLC Research and Padilla, Thomas
- Abstract
Responsible Operations is intended to help chart library community engagement with data science, machine learning, and artificial intelligence (AI) and was developed in partnership with an advisory group and a landscape group comprised of more than 70 librarians and professionals from universities, libraries, museums, archives, and other organizations. This research agenda presents an interdependent set of technical, organizational, and social challenges to be addressed en route to library operationalization of data science, machine learning, and AI. Challenges are organized across seven areas of investigation: (1) Committing to Responsible Operations; (2) Description and Discovery; (3) Shared Methods and Data; (4) Machine-Actionable Collections; (5) Workforce Development; (6) Data Science Services; (7) Sustaining Interprofessional and Interdisciplinary Collaboration. Organizations can use Responsible Operations to make a case for addressing challenges, and the recommendations provide an excellent starting place for discussion and action.
- Published
- 2019
27. Could AI help you to write your next paper?
- Author
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Hutson M
- Subjects
- Research Personnel, Artificial Intelligence, Authorship, Writing, Research Report
- Published
- 2022
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28. Annual Proceedings of Selected Research and Development Papers Presented at the Annual Convention of the Association for Educational Communications and Technology (42nd, Las Vegas, Nevada, 2019). Volume 1
- Author
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Association for Educational Communications and Technology, Simonson, Michael, and Seepersaud, Deborah
- Abstract
For the forty-second time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented at the annual AECT Convention in Las Vegas, Nevada. The Proceedings of AECT's Convention are published in two volumes. Volume 1 contains 37 papers dealing primarily with research and development topics. Papers dealing with the practice of instructional technology including instruction and training issues are contained in Volume 2. [For Volume 2, see ED609417.]
- Published
- 2019
29. Annual Proceedings of Selected Papers on the Practice of Educational Communications and Technology Presented at the Annual Convention of the Association for Educational Communications and Technology (42nd, Las Vegas, Nevada, 2019). Volume 2
- Author
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Association for Educational Communications and Technology, Simonson, Michael, and Seepersaud, Deborah
- Abstract
For the forty-second time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented at the annual AECT Convention in Las Vegas, Nevada. The Proceedings of AECT's Convention are published in two volumes. Volume 1 contains papers dealing primarily with research and development topics. Twenty-three papers dealing with the practice of instructional technology including instruction and training issues are contained in Volume 2. [For Volume 1, see ED609416.]
- Published
- 2019
30. Text as Data Methods for Education Research. CEPA Working Paper No. 19-04
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Stanford Center for Education Policy Analysis (CEPA), Fesler, Lily, Dee, Thomas, Baker, Rachel, and Evans, Brent
- Abstract
Recent advances in computational linguistics and the social sciences have created new opportunities for the education research community to analyze relevant large-scale text data. However, the take-up of these advances in education research is still nascent. In this paper, we review the recent automated text methods relevant to educational processes and determinants. We discuss both lexical-based and supervised methods, which expand the scale of text that researchers can analyze, as well as unsupervised methods, which allow researchers to discover new themes in their data. To illustrate these methods, we analyze the text interactions from a field experiment in the discussion forums of online classes. Our application shows that respondents provide less assistance and discuss slightly different topics with the randomized female posters, but respond with similar levels of positive and negative sentiment. These results demonstrate that combining qualitative coding with machine learning techniques can provide for a rich understanding of text-based interactions.
- Published
- 2019
31. Proceedings of International Conference on Social and Education Sciences (IConSES) (Las Vegas, Nevada, October 19-22, 2023). Volume 1
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International Society for Technology, Education and Science (ISTES) Organization, Mack Shelley, Valarie Akerson, Mevlut Unal, Mack Shelley, Valarie Akerson, Mevlut Unal, and International Society for Technology, Education and Science (ISTES) Organization
- Abstract
"Proceedings of International Conference on Social and Education Sciences" includes full papers presented at the International Conference on Social and Education Sciences (IConSES), which took place on October 19-22, 2023, in Las Vegas, Nevada. The aim of the conference is to offer opportunities to share ideas, discuss theoretical and practical issues, and to connect with the leaders in the fields of education and social sciences. The IConSES invites submissions that address the theory, research, or applications in all disciplines of education and social sciences. The IConSES is organized for: faculty members in all disciplines of education and social sciences, graduate students, K-12 administrators, teachers, principals, and all interested in education and social sciences. [Individual papers are indexed in ERIC.]
- Published
- 2023
32. Using ChatGPT To Write Scientific Papers In Indonesia: A Systematic Review
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Suntoro Suntoro, Ida Zulaeha, Hari Bakti Mardikantoro, and Tommi Yuniawan
- Subjects
ChatGPT ,writing scientific papers ,artificial intelligence ,systematic review ,Social Sciences - Abstract
Background: The utilization of ChatGPT in writing scientific papers has sparked both pros and cons in Indonesia. Some studies reveal its great potential, while others highlight the negative impacts resulting from the use of ChatGPT. Objective: This research aims to analyze the area, impact, and trends in the use of ChatGPT in writing scientific papers in Indonesia through a systematic review. Methodology: Researchers use PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) to conduct the analysis. The sample consists of 19 selected studies collected from the Google Scholar and Scopus databases. Data analysis uses quantitative and qualitative descriptive methods. Result: The research results show that the areas in which ChatGPT is used in writing scientific papers include topic selection, reference search, data analysis, scientific grammar, and translation. The use of ChatGPT in writing scientific papers faces some serious challenges, especially those related to ethics and academic integrity, such as increasing rates of plagiarism and declining values of honesty and responsibility. Moreover, dependence on artificial intelligence technology has the potential to reduce the development of human intellectual abilities, such as critical thinking, analysis, interpretation, and logic. Until recently, the research trend related to the use of ChatGPT for writing scientific papers is increasing, with the quite low density of research topics; thus, there are opportunities for further research to be carried out. Conclusion: The utilization of ChatGPT in academic writing in Indonesia has both positive and negative aspects. Regulation and morality can be crucial keys to realizing a quality academic environment. Unique Contribution: This research contributes to understanding the opportunities and challenges of utilizing ChatGPT in writing scientific papers, as well as providing information regarding areas that have the potential for further research. Key Recommendation: An in-depth understanding of the appropriate regulations for the use of ChatGPT in writing scientific papers is needed to minimize risks while still maximizing its positive potential.
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- 2024
33. A SOAR-Fired Method for Teaching Synthesis Writing. IDEA Paper #74
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IDEA Center, Luo, Linlin, and Kiewra, Kenneth A.
- Abstract
Students often fail to write effective synthesis essays that compare multiple sources across common intersecting categories. Instead, they compose flawed essays that focus primarily on one source and then add a few ideas from other sources (patchwriting); report ideas from all sources in a disjointed fashion (tag-all writing); or draw from one source after another without comparison (separate-representation writing). Effective synthesis writing depends on three strategies: selecting important information from each source, arranging the selected information in a graphic organizer for easy comparison, and connecting information from the various sources in a comparative way. The authors report on an established teaching and learning system called SOAR (Select, Organize, Associate, and Regulate) and its newly investigated impact on synthesis writing in the two studies that they conducted. In the first study, students provided with SOAR supplements (a graphic organizer, association prompts, and a regulation checklist) composed essays that contained more information, better synthesis organization, and more intertextual relationships than did essays from students who were not using SOAR supplements. In the second study, SOAR-trained students composed better organized synthesis essays than students who used their own preferred strategies. Across studies, students found SOAR helpful for synthesis writing and reported that they would be likely to use SOAR for future writing assignments. The authors conclude with an example of how to teach students to use SOAR when they write.
- Published
- 2019
34. One Hundred Most-cited Papers on Bacterial Meningitis: A Bibliometric Study.
- Author
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Hakkaraki, Vinayak Parashuram
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BACTERIAL meningitis ,SERIAL publications ,DATABASES ,MEDICAL information storage & retrieval systems ,ARTIFICIAL intelligence ,BRAIN ,CITATION analysis ,DESCRIPTIVE statistics ,PUBLISHING ,BIBLIOMETRICS ,DATA analysis software ,ELECTRONIC publications ,BACTERIAL diseases ,TIME - Abstract
Background: In previous decades, large-scale research has been carried out on bacterial meningitis. In every field, citation analysis is the most significant contribution. The study's objective was to identify and analyze the 100 articles on bacterial meningitis that received the most citations between 2000 and 2023, highlighting the most significant developments in the field. Objective: The objective of this study was to find out what makes a highly influential article by identifying and analyzing the characteristics of the 100 articles in the field of bacterial meningitis that receive the most citations. The goal of this study was to find and examine the 100 articles on bacterial meningitis that received the most citations. Methodology: We identified the top 100 most-cited papers in the field of bacterial meningitis from 55 journals using the Dimensions AI database. The results of each author's analysis of 100 articles were then compared. We gathered fundamental data such as the journal's title, country of publication, and study type. Descriptive counts or percentages were used to compare the various categories. Results: Between the year 2000 and the year 2023, articles were published. The total number of citations ranged from 115 to 1176, with 42 papers receiving more than 200 citations. In 2008, 14 articles were published, followed by 10 in 2000 and 2007. One thousand one hundred and seventy-six times were given to the most-cited paper, whereas 115 times were given to the least-cited article. "Clinical Features and Prognostic Factors in Adults with Bacterial Meningitis," by Diederik van de Beek, et al. (2004) was the article that received the most citations. 1176 people have cited this article. van de Beek Diederik of the Academic Medical Center in The Netherlands is the author who has written the most articles, was mentioned in 14 of the top 100 articles. Papers were primarily published in Pediatrics (n = 9) publication with 1861 citations. The Netherlands came in second with 18 publications, followed by the United States (n = 46). Conclusion: Our study uses bibliometrics and visualization analysis of the most important articles in this field to show the current state of research in the area of bacterial meningitis, provide a history of research trends, and offer a perspective for future bacterial predicts the growth of meningitis. [ABSTRACT FROM AUTHOR]
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- 2024
- Full Text
- View/download PDF
35. Investigating the impact of sewer overflow on the environment: A comprehensive literature review paper.
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Owolabi TA, Mohandes SR, and Zayed T
- Subjects
- Humans, Sewage, Wastewater, Artificial Intelligence, Groundwater
- Abstract
Sewer networks play a pivotal role in our everyday lives by transporting the stormwater and urban sewage away from the urban areas. In this regard, Sewer Overflow (SO) has been considered as a detrimental threat to our environment and health, which results from the wastewater discharge into the environment. In order to grapple with such deleterious phenomenon, numerous studies have been conducted; however, there has not been any review paper that provides the researchers undertaking research in this area with the following inclusive picture: (1) detailed-scientometric analysis of the research undertaken hitherto, (2) the types of methodologies used in the previous studies, (3) the aspects of environment impacted by the SO occurrence, and (4) the gaps existing in the relative literature together with the potential future works to be undertaken. Based on the comprehensive review undertaken, it is observed that simulation and artificial intelligence-based methods have been the most popular approaches. In addition, it has come to the attention that the detrimental impacts associated with the SO are fourfold as follows: air, quality of water, soil, and business and structure. Among these, the majority of the studies' focus have been tilted towards the impact of SO on the quality of ground water. The outcomes of this state-of-the-art review provides the researchers and environmental engineers with inclusive hindsight in dealing with such serious issue, which in turn, this culminates in a significant improvement in our environment as well as humans' well-beings., (Copyright © 2021. Published by Elsevier Ltd.)
- Published
- 2022
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36. 'Words are flowing out like endless rain into a paper cup': ChatGPTand law school assessments
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Hargreaves, Stuart
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- 2023
37. Use of Artificial Intelligence-Based Software as Medical Devices for Chest Radiography: A Position Paper from the Korean Society of Thoracic Radiology.
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Hwang EJ, Goo JM, Yoon SH, Beck KS, Seo JB, Choi BW, Chung MJ, Park CM, Jin KN, and Lee SM
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- Humans, Radiography, Radiography, Thoracic, Republic of Korea, Software, Artificial Intelligence, Radiology
- Abstract
Competing Interests: Eui Jin Hwang received research grants from Lunit Inc., Coreline Soft, and Monitor corporation, outside the present study.
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- 2021
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38. Cardiovascular RNA markers and artificial intelligence may improve COVID-19 outcome: a position paper from the EU-CardioRNA COST Action CA17129.
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Badimon L, Robinson EL, Jusic A, Carpusca I, deWindt LJ, Emanueli C, Ferdinandy P, Gu W, Gyöngyösi M, Hackl M, Karaduzovic-Hadziabdic K, Lustrek M, Martelli F, Nham E, Potočnjak I, Satagopam V, Schneider R, Thum T, and Devaux Y
- Subjects
- Cardiovascular Diseases diagnosis, Cardiovascular Diseases genetics, Cardiovascular System virology, Humans, Quality of Life, SARS-CoV-2 pathogenicity, Artificial Intelligence economics, Biomarkers analysis, COVID-19 diagnosis, RNA genetics
- Abstract
The coronavirus disease 2019 (COVID-19) pandemic has been as unprecedented as unexpected, affecting more than 105 million people worldwide as of 8 February 2020 and causing more than 2.3 million deaths according to the World Health Organization (WHO). Not only affecting the lungs but also provoking acute respiratory distress, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is able to infect multiple cell types including cardiac and vascular cells. Hence a significant proportion of infected patients develop cardiac events, such as arrhythmias and heart failure. Patients with cardiovascular comorbidities are at highest risk of cardiac death. To face the pandemic and limit its burden, health authorities have launched several fast-track calls for research projects aiming to develop rapid strategies to combat the disease, as well as longer-term projects to prepare for the future. Biomarkers have the possibility to aid in clinical decision-making and tailoring healthcare in order to improve patient quality of life. The biomarker potential of circulating RNAs has been recognized in several disease conditions, including cardiovascular disease. RNA biomarkers may be useful in the current COVID-19 situation. The discovery, validation, and marketing of novel biomarkers, including RNA biomarkers, require multi-centre studies by large and interdisciplinary collaborative networks, involving both the academia and the industry. Here, members of the EU-CardioRNA COST Action CA17129 summarize the current knowledge about the strain that COVID-19 places on the cardiovascular system and discuss how RNA biomarkers can aid to limit this burden. They present the benefits and challenges of the discovery of novel RNA biomarkers, the need for networking efforts, and the added value of artificial intelligence to achieve reliable advances., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)
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- 2021
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39. Ethical issues in two parallel trials of personalised criteria for implantation of implantable cardioverter defibrillators for primary prevention: the PROFID project-a position paper.
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Willems D, Bak M, Tan H, Lindinger G, Kocar A, Seperhi Shamloo A, Schmidt G, Hindricks G, and Dagres N
- Subjects
- Death, Sudden, Cardiac etiology, Humans, Artificial Intelligence, Clinical Trials as Topic ethics, Death, Sudden, Cardiac prevention & control, Decision Making, Defibrillators, Implantable, Myocardial Infarction complications, Primary Prevention ethics
- Abstract
Aim: To discuss ethical issues related to a complex study (PROFID) involving the development of a new, partly artificial intelligence-based, prediction model to enable personalised decision-making about the implantation of an implantable cardioverter defibrillator (ICD) in postmyocardial infarction patients, and a parallel non-inferiority and superiority trial to test decision-making informed by that model., Method: The position expressed in this paper is based on an analysis of the PROFID trials using concepts from high-profile publications in the ethical literature., Results: We identify ethical issues related to the testing of the model in the treatment setting, and to both the superiority and the non-inferiority trial. We underline the need for ethical-empirical studies about these issues, also among patients, as a parallel to the actual trials. The number of ethics committees involved is an organisational, but also an ethical challenge., Conclusion: The PROFID trials, and probably other studies of similar scale and complexity, raise questions that deserve dedicated parallel ethics and social science research, but do not constitute a generic obstacle. A harmonisation procedure, comparable to the Voluntary Harmonization Procedure (VHP) for medication trials, could be needed for this type of trials., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
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- 2021
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40. The paper chase and the big data arms race.
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Curchoe CL
- Subjects
- Humans, Artificial Intelligence, Data Management, Fertilization in Vitro, Reproductive Medicine
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- 2021
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41. Faculty members’ use of artificial intelligence to grade student papers: a case of implications
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Kumar, Rahul
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- 2023
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42. Publishing artificial intelligence research papers: A tale of three journals.
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Shortliffe EH, Peleg M, Combi C, Chang AC, and Vinci J
- Subjects
- Bibliometrics, Publishing, Artificial Intelligence, Periodicals as Topic
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- 2021
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43. ChatGPT as a Fullstack Web Developer - Early Results
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Abrahamsson, Pekka, Anttila, Tatu, Hakala, Jyri, Ketola, Juulia, Knappe, Anna, Lahtinen, Daniel, Liukko, Väinö, Poranen, Timo, Ritala, Topi-Matti, Setälä, Manu, van der Aalst, Wil, Series Editor, Ram, Sudha, Series Editor, Rosemann, Michael, Series Editor, Szyperski, Clemens, Series Editor, Guizzardi, Giancarlo, Series Editor, Kruchten, Philippe, editor, and Gregory, Peggy, editor
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- 2024
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44. An extended reality platform for inclusion of adults on the autism spectrum: a position paper.
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Westin, Thomas, Rahmani, Rahim, Palosaari-Eladhari, Mirjam, and Romero, Mario
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INCLUSION (Disability rights) ,AUTISM ,ARTIFICIAL intelligence ,ADULTS ,MOBILE apps ,AUTISTIC children - Abstract
Extended reality (XR) enables both new opportunities but also introduces new barriers for inclusion in society. Furthermore, XR is less researched than web, desktop and mobile applications. This position paper presents the concept of an XR platform for inclusion, with the purpose to make people on the autism spectrum and with other disabilities, more independent of help from others in everyday life situations. Based on previous research, our position is that, through current and future XR technologies combined with civic and artificial intelligence, it is possible to create individually personalised support for this purpose, grounded in practice to ensure validation. [ABSTRACT FROM AUTHOR]
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- 2024
- Full Text
- View/download PDF
45. Canadian Association of Radiologists White Paper on De-Identification of Medical Imaging: Part 1, General Principles.
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Parker W, Jaremko JL, Cicero M, Azar M, El-Emam K, Gray BG, Hurrell C, Lavoie-Cardinal F, Desjardins B, Lum A, Sheremeta L, Lee E, Reinhold C, Tang A, and Bromwich R
- Subjects
- Algorithms, Canada, Humans, Machine Learning, Societies, Medical, Artificial Intelligence ethics, Data Anonymization ethics, Diagnostic Imaging ethics, Radiologists ethics
- Abstract
The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboration between different sites or data transfer to a third party, precautions are required to safeguard patient privacy. Safety measures are required to prevent inadvertent access to and transfer of identifiable information. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI Ethical and Legal standing committee with the mandate to guide the medical imaging community in terms of best practices in data management, access to health care data, de-identification, and accountability practices. Part 1 of this article will inform CAR members on principles of de-identification, pseudonymization, encryption, direct and indirect identifiers, k-anonymization, risks of reidentification, implementations, data set release models, and validation of AI algorithms, with a view to developing appropriate standards to safeguard patient information effectively.
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- 2021
- Full Text
- View/download PDF
46. Intelligent checklists improve checklist compliance in the intensive care unit: a prospective before-and-after mixed-method study.
- Author
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De Bie AJR, Mestrom E, Compagner W, Nan S, van Genugten L, Dellimore K, Eerden J, van Leeuwen S, van de Pol H, Schuling F, Lu X, Bindels AJGH, Bouwman ARA, and Korsten EHHM
- Subjects
- Attitude to Computers, Benchmarking standards, Guideline Adherence standards, Health Status, Humans, Length of Stay, Patient Safety, Practice Guidelines as Topic standards, Prospective Studies, Quality Improvement standards, Quality Indicators, Health Care standards, Artificial Intelligence, Checklist, Critical Care standards, Decision Support Systems, Clinical, Intensive Care Units standards, Paper, Practice Patterns, Physicians' standards, Teaching Rounds standards
- Abstract
Background: We examined whether a context and process-sensitive 'intelligent' checklist increases compliance with best practice compared with a paper checklist during intensive care ward rounds., Methods: We conducted a single-centre prospective before-and-after mixed-method trial in a 35 bed medical and surgical ICU. Daily ICU ward rounds were observed during two periods of 8 weeks. We compared paper checklists (control) with a dynamic (digital) clinical checklist (DCC, intervention). The primary outcome was compliance with best clinical practice, measured as the percentages of checked items and unchecked critical items. Secondary outcomes included ICU stay and the usability of digital checklists. Data are presented as median (interquartile range)., Results: Clinical characteristics and severity of critical illness were similar during both control and intervention periods of study. A total of 36 clinicians visited 197 patients during 352 ward rounds using the paper checklist, compared with 211 patients during 366 ward rounds using the DCC. Per ICU round, a median of 100% of items (94.4-100.0) were completed by DCC, compared with 75.1% (66.7-86.4) by paper checklist (P=0.03). No critical items remained unchecked by the DCC, compared with 15.4% (8.3-27.3) by the paper checklist (P=0.01). The DCC was associated with reduced ICU stay (1 day [1-3]), compared with the paper checklist (2 days [1-4]; P=0.05). Usability of the DCC was judged by clinicians to require further improvement., Conclusions: A digital checklist improved compliance with best clinical practice, compared with a paper checklist, during ward rounds on a mixed ICU., Clinical Trial Registration: NCT03599856., (Copyright © 2020 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.)
- Published
- 2021
- Full Text
- View/download PDF
47. Canadian Association of Radiologists White Paper on De-identification of Medical Imaging: Part 2, Practical Considerations.
- Author
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Parker W, Jaremko JL, Cicero M, Azar M, El-Emam K, Gray BG, Hurrell C, Lavoie-Cardinal F, Desjardins B, Lum A, Sheremeta L, Lee E, Reinhold C, Tang A, and Bromwich R
- Subjects
- Algorithms, Canada, Humans, Machine Learning, Societies, Medical, Artificial Intelligence ethics, Data Anonymization ethics, Diagnostic Imaging ethics, Radiologists ethics
- Abstract
The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboration between different sites or data transfer to a third party, precautions are required to safeguard patient privacy. Safety measures are required to prevent inadvertent access to and transfer of identifiable information. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI Ethical and Legal standing committee with the mandate to guide the medical imaging community in terms of best practices in data management, access to health care data, de-identification, and accountability practices. Part 2 of this article will inform CAR members on the practical aspects of medical imaging de-identification, strengths and limitations of de-identification approaches, list of de-identification software and tools available, and perspectives on future directions.
- Published
- 2021
- Full Text
- View/download PDF
48. Modern Approaches in Sport Biomechanics: A Review Paper
- Author
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Maryam Mohammad Pour Koli and Ali Fatahi
- Subjects
new approaches ,artificial intelligence ,information technology ,wearable sensors ,biomechanics ,Sports medicine ,RC1200-1245 - Abstract
Objective In recent years, advancements in information technology, such as wireless EMG, high-resolution cameras, programs like OpenSim, innovations in textile sensors, and the emergence of artificial intelligence and smart mobile devices, have provided biomechanists with new tools and approaches. This study aims to investigate emerging trends in sports biomechanics, summarizing and providing practical insights from research conducted between 2015 and 2023. Methods A systematic search of research articles on new biomechanics approaches published between 2015 and 2023 was conducted. Specialized databases were queried, and 47 articles meeting the inclusion criteria were selected for analysis. Results Analysis of the selected studies revealed that the integration of information technology, artificial intelligence, smartphones, software, and wearable medical sensors in sports biomechanics has shown promising results in enhancing performance and reducing injury risks. Conclusion The findings of this study suggest that advancements in sports biomechanics technologies are pushing the boundaries of current research. Continued exploration and application of these technologies will likely shape the future of sports science and performance.
- Published
- 2024
49. Multi-AI competing and winning against humans in iterated Rock-Paper-Scissors game.
- Author
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Wang L, Huang W, Li Y, Evans J, and He S
- Subjects
- Female, Humans, Male, Markov Chains, Algorithms, Artificial Intelligence, Competitive Behavior physiology, Decision Making physiology, Game Theory, Memory physiology
- Abstract
Predicting and modeling human behavior and finding trends within human decision-making processes is a major problem of social science. Rock Paper Scissors (RPS) is the fundamental strategic question in many game theory problems and real-world competitions. Finding the right approach to beat a particular human opponent is challenging. Here we use an AI (artificial intelligence) algorithm based on Markov Models of one fixed memory length (abbreviated as "single AI") to compete against humans in an iterated RPS game. We model and predict human competition behavior by combining many Markov Models with different fixed memory lengths (abbreviated as "multi-AI"), and develop an architecture of multi-AI with changeable parameters to adapt to different competition strategies. We introduce a parameter called "focus length" (a positive number such as 5 or 10) to control the speed and sensitivity for our multi-AI to adapt to the opponent's strategy change. The focus length is the number of previous rounds that the multi-AI should look at when determining which Single-AI has the best performance and should choose to play for the next game. We experimented with 52 different people, each playing 300 rounds continuously against one specific multi-AI model, and demonstrated that our strategy could win against more than 95% of human opponents.
- Published
- 2020
- Full Text
- View/download PDF
50. Selected Papers from 2019 IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (IEEE ECBIOS 2019).
- Author
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Meen TH, Matsumoto Y, and Hsu KS
- Subjects
- Delivery of Health Care, Sustainable Development, Artificial Intelligence, Biomedical Engineering
- Abstract
Recently, healthcare has undergone a sector-wide transformation thanks to advances in computing, networking technologies, big data, and artificial intelligence. Healthcare is not only changing from being reactive and hospital-centered to preventive and personalized, but it is also changing from being disease focused to well-being centered. Healthcare systems, as well as fundamental medicine research, are becoming smarter and enabled in biomedical engineering. This special issue on "Selected Papers from 2019 IEEE Eurasia Conference on Biomedical Engineering, Healthcare, and Sustainability (IEEE ECBIOS 2019)" selected nine excellent papers from 160 papers presented at IEEE ECBIOS 2019 on the topics of environmental health sciences and public health. Our aim is to encourage scientists to publish their experimental and theoretical research to promote scientific predictions and impact assessments of global change and development.
- Published
- 2020
- Full Text
- View/download PDF
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