Ilker Cingillioglu
Biographic Data
| ID | 1502640 |
|---|---|
| NAME | Ilker Cingillioglu |
| GIVEN NAMES | Ilker |
| FAMILY NAME | Cingillioglu |
| SIGNATURE | CINGILLIOGLU I |
| AFFILIATIONS | The University of Adelaide |
| ORCID | 0000-0002-2971-140X |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Structural workplace factors contributing to Australia’s persistent gender pay gap
Purpose This study aims to investigate the organisational factors that contribute to Australia’s persistent gender pay gap (GPG), which remains a challenge despite existing legislation. By analysing structural workplace factors like industry division and employer size, the authors use machine learning to build predictive models, moving beyond simply describing the problem to proactively identifying and addressing the specific drivers of pay dispa…
Adapting to AI-mediated workplaces
Purpose The integration of artificial intelligence in workplaces is rapidly transforming employment structures, skill requirements, and decision-making processes. This study examines how AI-mediated workplaces (AI-MWP) impact STEM trainees entering the workforce. Specifically, it explores their preparedness, the challenges and opportunities presented by AI-MWP, and the role of socio-digital skills in shaping their career trajectories. Design/meth…
Running a double-blind true social experiment with a goal oriented adaptive AI-based conversational agent in educational research
This study introduces an innovative AI-facilitated interview-like survey system generating a combination of qualitative and quantitative data insights for higher education research. We employed a goal oriented adaptive AI-based Conversational Agent (AICA) which collected data directly from 1223 participants globally and ran a double-blind true social experiment online. During interviews, the AI established strong rapport with the participants, of…
What impacts matriculation decisions? Identifying students’ university choice factors on a global scale with Artificial Intelligence
This study provides an empirical approach to utilizing an Artificial Intelligence (AI)-based system for identifying students’ university choice factors that impact their matriculation decision. We created an AI-based chatbot that gathered both qualitative and quantitative data from nearly 1200 participants worldwide. The entire human-AI interaction process was managed autonomously by the AI without researcher intervention. We analysed all data co…
No prominent works on this page.
Running a double-blind true social experiment with a goal oriented adaptive AI-based conversational agent in educational research
This study introduces an innovative AI-facilitated interview-like survey system generating a combination of qualitative and quantitative data insights for higher education research. We employed a goal oriented adaptive AI-based Conversational Agent (AICA) which collected data directly from 1223 participants globally and ran a double-blind true social experiment online. During interviews, the AI established strong rapport with the participants, of…
What impacts matriculation decisions? Identifying students’ university choice factors on a global scale with Artificial Intelligence
This study provides an empirical approach to utilizing an Artificial Intelligence (AI)-based system for identifying students’ university choice factors that impact their matriculation decision. We created an AI-based chatbot that gathered both qualitative and quantitative data from nearly 1200 participants worldwide. The entire human-AI interaction process was managed autonomously by the AI without researcher intervention. We analysed all data co…
Adapting to AI-mediated workplaces
Purpose The integration of artificial intelligence in workplaces is rapidly transforming employment structures, skill requirements, and decision-making processes. This study examines how AI-mediated workplaces (AI-MWP) impact STEM trainees entering the workforce. Specifically, it explores their preparedness, the challenges and opportunities presented by AI-MWP, and the role of socio-digital skills in shaping their career trajectories. Design/meth…
Structural workplace factors contributing to Australia’s persistent gender pay gap
Purpose This study aims to investigate the organisational factors that contribute to Australia’s persistent gender pay gap (GPG), which remains a challenge despite existing legislation. By analysing structural workplace factors like industry division and employer size, the authors use machine learning to build predictive models, moving beyond simply describing the problem to proactively identifying and addressing the specific drivers of pay dispa…
AI in Service Interactions (2 works) · Mathematics education (2 works) · Online Learning and Analytics (2 works) · Psychology (2 works) · Adaptability (1 works) · Agency (philosophy) (1 works) · AI and HR Technologies (1 works) · Applied Psychology (1 works) · Artificial Intelligence in Healthcare and Education (1 works) · Autonomy (1 works)