Multilevel Modeling of Training Needs in Artificial Intelligence
Bibliographic Data
| ID | 11716289 |
|---|---|
| Authors | Veronica Distefano (0000-0001-7592-5583), Sabrina Maggio (0000-0002-9727-2410), Sandra De Iaco (0000-0003-1820-2068) |
| Year | 2025 |
| Volume | 178 |
| Issue | 3 |
| Pages | 1411-1439 |
| Publication date | 2025-03-31 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Indicators Research (JOURNAL) |
| Journal identifiers | ISSN: 0303-8300 • E-ISSN: 1573-0921 |
| Publisher | Springer Science+Business Media (PUBLISHER • DE) |
| DOI | 10.1007/s11205-025-03544-7 |
| OpenAlex | W4409069361 |
| Language | EN |
| References cited | 44 |
Nowadays, Artificial Intelligence (AI) is playing a rapidly increasing role in several fields of research and in almost all sectors of real life. However, few studies have assessed the effects of AI applications on training needs. This paper proposes an innovative multilevel modeling in order to investigate Awareness, Attitude and Trust towards AI and their reflections on learning needs. In particular, it is shown how a machine learning variable selection algorithm can support the definition of the optimal subset of all relevant covariates with respect to the outcome variable and improve the multilevel model performance for estimating the probability of educational needs. Thus, starting from a complex web survey to European citizens distributed in eight countries, the estimation of a multilevel binary model, defined on the basis of covariates selected through the Boruta random forest algorithm, is proposed. A discussion on the gender differences of the related estimated multilevel logit models is presented. A sensitivity analysis is also included in order to assess the prediction accuracy of the proposed multilevel logit modeling
Geography · Human geography · Machine learning · Multilevel model · Public health · Quality of Life Research · Social science · Sociology · Training (meteorology · Cognitive Science and Mapping · Computer Science · Engineering Education and Technology · Medicine · Nursing · Psychology · Technology and Human Factors in Education and Health · Artificial Intelligence
Artificial Intelligence
Use of Ranks in One-Criterion Variance Analysis
Influences of artificial intelligence (AI) awareness on career competency and job burnout
Feature Selection with the Boruta Package
Assessing the Performance of Prediction Models
Strictly Proper Scoring Rules, Prediction, and Estimation
One country with two systems
Cyberpsychology research and Covid-19
Diversification in the age of the 4th industrial revolution
Improving spatial clustering through a weight system on multilevel permanent museum attraction probability
Fear of Autonomous Robots and Artificial Intelligence
Multilevel Analysis
Gender and attitudes toward technology use
Multilevel Statistical Models
A Latent Auto-Regressive Approach for Bayesian Structural Equation Modeling of Spatially or Socially Dependent Data
The impact of automation and artificial intelligence on worker well-being
A Multilevel Multinomial Model for the Dynamics of Graduates Employment in Italy
| Citation velocity | historical |
|---|---|
| Highly cited | No |