Ilias Pappas
Biographic Data
| ID | 9529901 |
|---|---|
| NAME | Ilias Pappas |
| GIVEN NAMES | Ilias |
| FAMILY NAME | Pappas |
| SIGNATURE | PAPPAS I |
| AFFILIATIONS | University of Agder |
| ORCID | 0009-0002-2259-7947 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Sleep tracking
Sleep tracking has become a growing area of self-tracking, yet the breadth of users’ interactions with sleep-tracking technology has not been comprehensively synthesised. To address this gap, this study analyzes 51 empirical research articles following a three-phase literature review process. Guided by a human–computer interaction framework, we organised the extant research into five components: (1) user, (2) sleep-tracking technology, (3) use co…
Tension in the data environment
AI-enabled adaptive learning systems
Mobile internet, cloud computing , big data technologies, and significant breakthroughs in Artificial Intelligence (AI) have all transformed education. In recent years, there has been an emergence of more advanced AI-enabled learning systems, which are gaining traction due to their ability to deliver learning content and adapt to the individual needs of students. Yet, even though these contemporary learning systems are useful educational platform…
No prominent works on this page.
AI-enabled adaptive learning systems
Mobile internet, cloud computing , big data technologies, and significant breakthroughs in Artificial Intelligence (AI) have all transformed education. In recent years, there has been an emergence of more advanced AI-enabled learning systems, which are gaining traction due to their ability to deliver learning content and adapt to the individual needs of students. Yet, even though these contemporary learning systems are useful educational platform…
Tension in the data environment
Sleep tracking
Sleep tracking has become a growing area of self-tracking, yet the breadth of users’ interactions with sleep-tracking technology has not been comprehensively synthesised. To address this gap, this study analyzes 51 empirical research articles following a three-phase literature review process. Guided by a human–computer interaction framework, we organised the extant research into five components: (1) user, (2) sleep-tracking technology, (3) use co…
Computer Science (2 works) · Data science (2 works) · Key (lock) (2 works) · Adaptive Learning (1 works) · Artificial Intelligence (1 works) · Big data (1 works) · Big Data and Business Intelligence (1 works) · Business (1 works) · Conceptual framework (1 works) · Conceptual model (1 works)