Analysis of Artificial Intelligence subject results by gender DOI
Gábor Kiss, Susana Bastos

Опубликована: Ноя. 11, 2024

Язык: Английский

Beyond the hype: exploring faculty perceptions and acceptability of AI in teaching practices DOI Creative Commons
Kingsley Ofosu‐Ampong

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

Опубликована: Апрель 23, 2024

Abstract Limited studies exist on faculty members or lecturers’ perception and behavioural acceptance of artificial intelligence (AI) (e.g. ChatGPT) for their students' benefit. Teachers are the decision-makers teaching classroom activities. In this regard, study examined use AI-powered tools factors that influence AI in learning universities. An online survey was conducted using a cross-sectional design, results were analysed SPSS SmartPLS. The findings revealed more than two-thirds (84%) lecturers willing to accept students, while 16% stated non-acceptance students. Factors such as years experience, institutional support use, attitude towards proved be significant predictors education. Key influencing lecturers' students include perceived pedagogical affordances, organisational policies incentives, complexity usability socio-cultural context. By addressing teacher concerns through supportive policies, user-friendly interfaces, alignment with goals, higher education institutions can create fertile ground adoption.

Язык: Английский

Процитировано

15

“ChatGPT 4.0 Ghosted Us While Conducting Literature Search:” Modeling the Chatbot’s Generated Non-Existent References Using Regression Analysis DOI
Dharel P. Acut, Nolasco K. Malabago,

Elesar V. Malicoban

и другие.

Internet Reference Services Quarterly, Год журнала: 2024, Номер unknown, С. 1 - 26

Опубликована: Ноя. 13, 2024

The integration of AI technologies like ChatGPT has transformed academic research, yet substantial gaps exist in understanding the implications AI-generated non-existent references literature searches. While prior studies have predominantly focused on medical and geography fields using descriptive statistics, a systematic investigation into 4.0's effectiveness generating accurate within realm science technology education remains unexplored, highlighting significant dearth research this critical area. This study, therefore, investigates reliability writing utilizing 4.0. Employing non-experimental correlational design, examines impact prompt specificity citation accuracy across various types prompts, including general, specific, methodological, review, interdisciplinary prompts. findings indicate that prompts correlate positively with references, while general frequently result references. Visualizations, confusion matrix precision-recall curve, illustrate model's performance. Ultimately, study underscores necessity well-structured to enhance reference quality cautions against AI-induced hallucinations produce which can significantly undermine credibility.

Язык: Английский

Процитировано

10

Unlocking the power of machine learning in big data: a scoping survey DOI Creative Commons
Fadil Mohammed Surur,

Abiy Abinet Mamo,

Bealu Girma Gebresilassie

и другие.

Data Science and Management, Год журнала: 2025, Номер unknown

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1

Evaluating the Societal Impact of AI: A Comparative Analysis of Human and AI Platforms Using the Analytic Hierarchy Process DOI Creative Commons
Bojan Srdjević

AI, Год журнала: 2025, Номер 6(4), С. 86 - 86

Опубликована: Апрель 20, 2025

A central focus of this study was the methodology used to evaluate both humans and AI platforms, particularly in terms their competitiveness implications six key challenges society resulting from development increasing use artificial intelligence (AI) technologies. The list compiled by consulting various online sources cross-referencing with academics 15 countries across Europe USA. Professors, scientific researchers, PhD students were invited independently remotely challenges. Rather than contributing another discussion based solely on social arguments, paper seeks provide a logical evaluation framework, moving beyond qualitative discourse incorporating numerical values. pairwise comparison conducted two groups participants using multicriteria decision-making model known as analytic hierarchy process (AHP). Thirty-eight performed comparisons after they listed distributed questionnaire. same procedure carried out four platforms—ChatGPT, Gemini (BardAI), Perplexity, DedaAI—who responded requests human participants. results grouped compared, revealing interesting differences prioritization challenges’ impact society. Both agreed highest importance data privacy security, well lowest cultural resistance, specifically clash existing norms societal

Язык: Английский

Процитировано

1

Applications of Artificial Intelligence in Contemporary Sociology DOI
Guillermo Alfredo Jiménez Pérez, José Manuel Hernández de la Cruz

LatIA, Год журнала: 2024, Номер 1, С. 12 - 12

Опубликована: Июль 23, 2024

Язык: Английский

Процитировано

7

Artificial Intelligence in the Classroom: Revolutionizing English Language Teaching DOI Creative Commons

Hari Prasad Tiwari

Journal of English Teaching and Linguistics Studies (JET Li), Год журнала: 2024, Номер 6(1), С. 42 - 59

Опубликована: Апрель 30, 2024

This qualitative study investigates the integration of Artificial Intelligence (AI) in English Language Teaching (ELT) within university settings, with a specific focus on viewpoints and experiences university-level teachers Nepal. The research was conducted Lumbini Province, Nepal, where 14 were purposively selected from seven constituent campuses. Through unstructured smartphone interviews, participants shared insights AI ELT. findings reveal diverse range expectations concerns among regarding AI’s role language instruction. While expressed optimism about potential to revolutionize learning through personalized immediate feedback, they also voiced apprehensions. These encompassed job displacement, erosion human interaction, ethical implications related usage. To address these challenges, employed various strategies. They navigated considerations by raising awareness, engaging reflection, advocating for guidelines. emphasizes importance balanced approach integration-one that harnesses its promises while addressing pitfalls. Responsible inclusive usage education necessitates thoughtful consideration both benefits challenges.

Язык: Английский

Процитировано

6

A Revolutionary Artificial Intelligence Framework for a Business Value-Centric Living Laboratory DOI
Cristiane Chaves Gattaz, Fuad Gattaz Sobrinho, Joaquim Campos

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Enhancement of responsivity and self-powered on-chip LNOI integrated Bi₂Te₃ photodetector array DOI

Qiaonan Dong,

Xinxing Sun,

Tingfei YUAN

и другие.

Optics Letters, Год журнала: 2025, Номер 50(5), С. 1711 - 1711

Опубликована: Фев. 5, 2025

The topological insulator Bi 2 Te 3 possesses an extraordinary optoelectronic property for wide-band optoelectronics device applications. In this study, we demonstrate a high-responsivity and self-powered on-chip lithium niobate on (LNOI) waveguide-integrated photodetector array operating at 1550 nm. Enhancement of responsivity is attributed to the decreased /Au contact resistance, which facilitated by electrothermal annealing. post-electrothermal annealed was demonstrated photocurrent response increased four orders magnitude, reaching as high 5.5 µA. It features photoresponsivity 60 mA/W time 10 µs. uniform performance fabricated arrays integrated with 4× multi-mode interference same LNOI photonic chips proves its potential applications in high-efficiency optical communication, computing, large-scale data processing.

Язык: Английский

Процитировано

0

A Method for Estimating Tree Growth Potential with Back Propagation Neural Network DOI Open Access
Jianfeng Yao, Chunyan Zhao, Xuefan Hu

и другие.

Sustainability, Год журнала: 2025, Номер 17(4), С. 1411 - 1411

Опубликована: Фев. 9, 2025

Tree growth potential is crucial for maintaining forest health and sustainable development. Traditional expert-based assessments of are inherently subjective. To address this subjectivity improve accuracy, study proposed a method using Backpropagation Neural network (BPNN) to classify tree potential. 60 Pinus tabulaeformis (Carr.) Platycladus orientalis (Linn.) were selected as experimental trees in the Miyun Reservoir Water Conservation Forest Demonstration Zone Beijing, 95 massoniana (Lamb.) Cunninghamia lanceolate Jigongshan Nature Reserve. The average annual ring width outermost 2 cm xylem measured by discs or increment cores, wood volume each recent years calculated. According increment, was divided into three levels: strong, medium, weak. Using height, breast height diameter, crown input variables, level output four sub models species established; species, generalized model established these species. test results showed that accuracy tabulaeformis, orientalis, massoniana, 68.42%, 77.78%, 86.21%, 78.95%, respectively, 71.19%. These findings suggested employing BPNN viable approach accurately estimating

Язык: Английский

Процитировано

0

What percentage of secondary school students do their homework with the help of artificial intelligence? - A survey of attitudes towards artificial intelligence DOI Creative Commons
Mátyás Turós

Computers and Education Artificial Intelligence, Год журнала: 2025, Номер unknown, С. 100394 - 100394

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0