Abstract
Affect detection is integral to creating affect-sensitive learning systems, but the impact of measurement methods needs further research. This paper uses ordered network analysis (ONA) to compare the affect dynamics of two suites of affect detectors trained on complementary data (i.e., labels from an in-the-moment self-reporting (SR) tool vs labels from field observations) in game-based learning. We then use ONA difference models to assess how divergence in learning and motivational measures impact affect dynamics.
| Original language | English (US) |
|---|---|
| Title of host publication | Advances in Quantitative Ethnography - 6th International Conference, ICQE 2024, Proceedings |
| Editors | Yoon Jeon Kim, Zachari Swiecki |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 195-203 |
| Number of pages | 9 |
| ISBN (Print) | 9783031763311 |
| DOIs | |
| State | Published - 2024 |
| Externally published | Yes |
| Event | 6th International Conference on Quantitative Ethnography, ICQE 2024 - Philadelphia, United States Duration: Nov 3 2024 → Nov 7 2024 |
Publication series
| Name | Communications in Computer and Information Science |
|---|---|
| Volume | 2279 CCIS |
| ISSN (Print) | 1865-0929 |
| ISSN (Electronic) | 1865-0937 |
Conference
| Conference | 6th International Conference on Quantitative Ethnography, ICQE 2024 |
|---|---|
| Country/Territory | United States |
| City | Philadelphia |
| Period | 11/3/24 → 11/7/24 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Keywords
- Affect Dynamics
- Epistemic Network Analysis
- Transition Analysis
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