Dynamics of affective states during complex learning
By S. D’Mello, A. Graesser. 2012
1,000 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Cognitive Neuroscience, Computer Science Applications
View Paper: https://www.semanticscholar.org/paper/fb8007d427c192d8c953890862dcce62ff944dbf
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Lisa Knörzer
- Babette Park
- Roland Brunken
- Shrimai Prabhumoye
- E. G. Peterson
- Cara A. Singh
- Alan W. Black
- Marianne Chevrier
In Cognitive Neuroscience
- E. G. Peterson
- Cara A. Singh
- Alan W. Black
- Babette Park
- Marianne Chevrier
- J. Cohen
- David B. Miele
- Roland Brunken
In Computer Science Applications
- E. G. Peterson
- Cara A. Singh
- Marianne Chevrier
- J. Cohen
- David B. Miele
- Abigail A. Scholer
- Krista R. Muis
Citations in the corpus
- Facilitators or suppressors: Effects of experimentally induced emotions on multimedia learning (2016, background): “The assumed short duration of emotions can lead to short-term changes of emotional state (e.g., during a learning phase; D'Mello & Graesser, 2012) whereas the overall mood state might stay the same (c.f. Russell, 2003).”
- A Case for Domain-Specific Curiosity in Mathematics (2019, background): “Both confusion and frustration may present as heightened arousal with manifestations similar to those that characterize curiosity (Baker et al. 2010; D’Mello and Graesser 2012).”
- The Role of Metamotivational Monitoring in Motivation Regulation (2018, methodology): “…methods such as experience sampling (e.g., Nett et al., 2011), affect annotation of facial expressions captured during task engagement (e.g., D’Mello & Graesser, 2012), and even automated assessments based on “machine-readable behavioral and physiological signals” (D’Mello, Dieterle, &…”