Journal of medical imaging and radiation sciences, Год журнала: 2024, Номер 55(4), С. 101741 - 101741
Опубликована: Авг. 27, 2024
Frontiers in Education, Год журнала: 2022, Номер 7
Опубликована: Март 29, 2022
Efforts have constantly been made to incorporate AI into teaching and learning; however, the successful implementation of new instructional technologies is closely related attitudes teachers who lead lesson. Teachers’ perceptions utilization only investigated by few scholars due an overall lack experience regarding how can be utilized in classroom as well no specific idea what AI-adopted tools would like. This study perceived AI-enhanced scaffolding system developed support students’ scientific writing for STEM education. Results revealed that most positively experienced a source superior scaffolding. On other hand, they also raised possibility several issues caused using such change role played transparency decisions system. These results used foundation which create guidelines future integration with education schools, since it reports teachers’ experiences utilizing various considerations its implementation.
Язык: Английский
Процитировано
143
Health Science Reports, Год журнала: 2023, Номер 6(3)
Опубликована: Март 1, 2023
This systematic review examined healthcare students' attitudes, knowledge, and skill in Artificial Intelligence (AI).On August 3, 2022, studies were retrieved from the PubMed, Embase, Scopus, Web of Science databases. Preferred Reporting Items for Systematic Reviews Meta-Analyses recommendations followed. We included cross-sectional that skills, perceptions AI this review. Using eligibility requirements as a guide, titles abstracts screened. Complete texts then independently reviewed per requirements. To collect data, standardized form was used.Of 38 studies, 29 (76%) students had positive promising attitude towards clinical profession its use he future; however, nine (24%), considered threat to fields negative it. Furthermore, 26 evaluated knowledge about AI. Among these, 18 level student low (50%). On other hand, six high reported, two reported average general (almost 50%). Of four (67%) very so they stated never worked with AI.Evidence shows medicine; most limited skills working Face-to-face instruction, training manuals, detailed instructions are therefore crucial implementing comprehending how technology works raising advantages
Язык: Английский
Процитировано
111
Computers and Education Artificial Intelligence, Год журнала: 2023, Номер 4, С. 100139 - 100139
Опубликована: Янв. 1, 2023
This study investigates university teachers' relationships with emerging technologies by focusing on the uptake of artificial intelligence in higher education practices. We utilise an experimental philosophy approach to i) determine intuitions around universities' responsibilities adopt new technologies, ii) understand conditions under which teachers consider defensible and, hence, would be willing introduce such tools and services into their daily practice iii) specify self-reported knowledge intelligence. An online survey, where participants were sent one three different cases (Case A related first-generation students, Case B, archetypical student, C, students a learning disability), 18 identical questions across all cases. The survey was distributed among 1773 teachers. Based responses 194 teachers, we identify differences responsibility, equity, about Our quantitative data exhibited that respondents ranked degree universities should use systems achieve equitable outcomes. Data revealed no statistically significant associations regard background variables A. However, B C disclosed concerning gender, age, faculty, academic position participants. Moreover, fears scepticism education, concerns fairness lack resources engage teaching
Язык: Английский
Процитировано
84
Journal of Dentistry, Год журнала: 2022, Номер 128, С. 104363 - 104363
Опубликована: Ноя. 21, 2022
Язык: Английский
Процитировано
63
Journal of medical imaging and radiation sciences, Год журнала: 2022, Номер 54(1), С. 104 - 116
Опубликована: Дек. 18, 2022
Artificial Intelligence (AI) technologies have already started impacting clinical practice across various settings worldwide, including the radiography profession. This study is aimed at exploring a world-wide view on AI in relation to knowledge, perceptions, and expectations of professionals.An online survey (hosted Qualtrics) key concepts was open professionals worldwide (August 1st December 31st 2020). The sought both quantitative qualitative data topical issues relating implementation practice. Data obtained analysed using Statistical Package for Social Sciences (SPSS) (v.26) six-phase thematic analysis approach.A total 314 valid responses were with fair geographical distribution. Of respondents, 54.1% (157/290) from North America predominantly practicing radiographers (60.5%, 190/314). Our findings broadly relate different perceived benefits misgivings/shortcomings enhanced workflows optimised workstreams while revolve around de-skilling impact patient-centred care due over-reliance advanced technology following implementation.Artificial intelligence tool but operate optimally it requires human input validation. Radiographers working interface between patient are stakeholders implementation. Lack training transparency tools create mixed response when they discuss their challenges. It also possible that nuanced by regional contexts comes deployment. Irrespective geography, there still lot be done about formalised worldwide. vital step ensure safe effective implementation, adoption, faster integration into healthcare workers radiographers.Advancement should accompanied proportional end-users beyond. There many AI-enabled improvement efficiencies equally will widespread disruption traditional roles care, which can managed well-educated well-informed workforce.
Язык: Английский
Процитировано
42
International Journal of Environmental Research and Public Health, Год журнала: 2023, Номер 20(2), С. 1589 - 1589
Опубликована: Янв. 16, 2023
The rise of artificial intelligence (AI) in medicine, and particularly radiology, is becoming increasingly prominent. Its impact will transform the way specialty practiced current future education model. aim this study to analyze perception that undergraduate medical students have about situation AI especially radiology. A survey with 17 items was distributed between 3 January 31 March 2022. Two hundred eighty-one correctly responded questionnaire; 79.3% them claimed they knew what is. However, their objective knowledge low but acceptable. Only 24.9% would choose radiology as a specialty, only 40% one first three options. applications technology were valued positively by most students, who give it an important Support Role, without fear radiologist be replaced (79.7%). majority (95.7%) agreed need implement well-established ethical principles AI, 80% academic training positively. Surveyed basic understanding perceive useful tool
Язык: Английский
Процитировано
30
JMIR Research Protocols, Год журнала: 2023, Номер 12, С. e51873 - e51873
Опубликована: Окт. 20, 2023
The integration of artificial intelligence (AI) into health sciences students' education holds significant importance. rapid advancement AI has opened new horizons in scientific writing and the potential to reshape human-technology interactions. may impact critical thinking, leading unintended consequences that need be addressed. Understanding implications adoption is essential for ensuring its responsible effective use, empowering students navigate AI-driven technologies' evolving field with knowledge skills.This study aims provide details on protocol methods used investigate usability efficacy ChatGPT, a large language model. primary focus assessing role as supplementary learning tool improving processes outcomes among undergraduate students, specific emphasis chronic diseases.This single-blinded, crossover, randomized, controlled trial part broader mixed study, this paper quantitative component overall research. A total 50 will recruited study. alternative hypothesis posits there difference technology between using ChatGPT (group A) those standard web-based tools B) access resources complete assignments. Participants allocated sequence AB or BA 1:1 ratio computer-generated randomization. Both arms include participation assignment intervention, washout period 21 days interventions. outcome measure effectiveness whereas secondary perceptions experiences tool. Outcome data collected up 24 hours after interventions.This understand benefits challenges incorporating an educational tool, particularly context student learning. findings are expected identify areas attention help educators develop deeper understanding AI's field. By exploring differences conventional tools, seeks inform academic settings, education.By compared about settings.ClinicalTrails.gov NCT05963802; https://clinicaltrials.gov/study/NCT05963802.PRR1-10.2196/51873.
Язык: Английский
Процитировано
29
Insights into Imaging, Год журнала: 2023, Номер 14(1)
Опубликована: Фев. 3, 2023
Artificial intelligence (AI)-enabled applications are increasingly being used in providing healthcare services, such as medical imaging support. Sufficient and appropriate education for professionals is required successful AI adoption. Although, currently, there training programmes radiologists, formal radiographers lacking. Therefore, this study aimed to evaluate discuss a postgraduate-level module on developed the UK radiographers.A participatory action research methodology was applied, with participants recruited from first cohort of students enrolled faculty members. Data were collected using online, semi-structured, individual interviews focus group discussions. Textual data processed data-driven thematic analysis.Seven six members participated evaluation. Results can be summarised following four themes: a. participants' professional educational backgrounds influenced their experiences, b. found learning experience meaningful concerning design, organisation, pedagogical approaches, c. some design delivery aspects identified barriers learning, d. suggested how ideal course could look like based experiences.The findings our work show that an assist educators/academics developing similar provisions other radiation sciences professionals. A blended format, combined customisable contextualised content, interprofessional approach recommended future courses.
Язык: Английский
Процитировано
28
Radiography, Год журнала: 2024, Номер 30(2), С. 474 - 482
Опубликована: Янв. 12, 2024
Medical imaging is arguably the most technologically advanced field in healthcare, encompassing a range of technologies which continually evolve as computing power and human knowledge expand. Artificial Intelligence (AI) next frontier medical pioneering. The rapid development implementation AI has potential to revolutionise however, do so, staff must be competent confident its application, hence readiness an important precursor adoption. Research ascertain best way deliver this AI-enabled healthcare training infancy. aim scoping review compare existing studies investigate evaluate efficacy educational interventions for staff.
Язык: Английский
Процитировано
17
Radiography, Год журнала: 2024, Номер 30(2), С. 612 - 621
Опубликована: Фев. 7, 2024
IntroductionDespite the rapid increase of AI-enabled applications deployed in clinical practice, many challenges exist around AI implementation, including clarity governance frameworks, usability validation models, and customisation training for radiographers. This study aimed to explore perceptions diagnostic therapeutic radiographers, with existing theoretical and/or practical knowledge AI, on issues relevance field, such as procurement, about enablers future priorities adoption.MethodsAn online survey was designed distributed UK-based qualified radiographers who work medical imaging radiotherapy have some previous working AI. Participants were recruited through researchers' professional networks social media support from advisory group Society College Radiographers. Survey questions related training/education, data privacy procedures, implementation considerations, adoption. Descriptive statistics employed analyse data, chi-square tests used significant relationships between variables.ResultsIn total, 88 valid responses received. Most (56.6 %) had not received any AI-related training. Also, although approximately 63 % them an evaluation framework assess models' performance before (36.9 still unsure suitable methods. Radiographers requested clearer guidance governance, ample time implement their practice safely, adequate funding, effective leadership, targeted champions. training, robust patient public involvement seen successful by radiographers.ConclusionAI is progressing within radiography, but without customised key stakeholder engagement new roles created, it will be hard harness its benefits minimise risks.Implications practiceThe results this highlight relation adoption, namely need developing frameworks providing optimal
Язык: Английский
Процитировано
13