1. Exploring collaborative groups’ emotional states with video and physiological data
Tiina Törmänen, Hanna Järvenoja, Kristiina Kurki, Ricardo Devai, and Sanna Järvelä

2. Background
EmReg – Emotion regulation in secondary school pupils’ learning
PhD study: Tracking the Role of Socially Shared Emotion Regulation for Collaborative Learning Progress
Aim: To explore..
the reciprocal relationship between individual students’ affective states (which contribute to collaborative groups’ emotional atmosphere) and emotion regulation within groups
the role of emotion regulation for collaborative learning progress
How to capture situation specificity and interconnection between emotional states and emotion regulation?
Multiple process-oriented data sources that provide versatile information from authentic situations
Can physiological data be used to evaluate students’ emotional states?

3. Academic emotions?
Emotions: multifaceted phenomena consisting of multiple psychological processes including affective, cognitive, physiological, motivational and expressive components (Boekaerts & Pekrun, 2016; Pekrun, 2016).
Academic emotions: emotions experienced in academic setting and related to learning, classroom instruction, and achievement (Pekrun, Goetz, Titz, & Perry, 2002).
Two dimensions of affective states (Pekrun, 2016):
Valence: positive/negative
Activation: How much physiological arousal emotion is causing  activating/de-activating
Activation
Anger
Enjoyment
Negative activating
Positive activating
Anxiety
Hope
Shame
Pride
Negative
Positive
Hopelessness
Relief
Boredom
Negative De-activating
Positive De-activating
De-activation
Example of a circumplex model
(e. g. Pekrun, Goetz, Titz, & Perry, 2002; Russell & Barrett, 1999)

4. Physiological arousal?
While the valence of the groups’ socio- emotional state can be detected from students’ interaction and communication, the level of activation (i.e. arousal level) is not directly observable
Measuring electrodermal activity (EDA)
EDA is related to function of sweat glands and through that it tells about the activity of sympathetic nervous system (Dawson, Schell, & Filion, 2007).
EDA is correlated to cognitive and emotional processes (Pijeira-Díaz, Drachsler, Järvelä, & Kirschner, 2016).
Skin Conductance Response (SCR) is defined as a response following an unexpected and significant external stimulus (Boucsein, 2012; Dawson et al., 2007).
(picture from Dawson et al., 2007)

5. Research questions
How is collaborative groups’ emotional state varying in terms of observed valence and activation during a collaborative learning session?
Is there an association between groups’ observed emotional activation level and physiological activation level measured with EDA?
In what kind of situations is group members’ physiological activation level in synchrony?
3.1 Is there a need for group level emotion regulation in those situations?

6. Participants and context
6th grade students, n = 41
 12 groups
LeaForum, University of Oulu
Science assignment
Heat energy
“Design and construct a model of a house that is highly energy efficient and makes use of the solar energy”
Four phases
Individual (15 min)
Brainstorming (10 min)
Planning (20 min)
Building (60 min)

7. In LeaForum EmA 360° VIDEO Empatica E4 Wristband EDA EmA At School
Collaborative working – sharing knowledge
360°
VIDEO
Empatica E4
Wristband
EDA
Collaborative working – constructing house
Individual working– own expertise
Teaching session – Heat energy
EmA
At School
At School
- Prior Knowledge test
- Self-efficacy and interest in science
- SRL
Presenting the results to classmates

8. Positive de-activating
Analysis
Phase 3. Analyzing the EDA data in relation to the video coding
Phase 2. Observing valence and activation level of groups’ emotional states
Phase 1. Locating socio-emotional segments
Sequencing the video data in 30s segments
30s segments
Yes
Positive activating
Positive de-activating
Negative activating
Negative
de-activating
Mixed activating
Mixed
Unclear activating
Unclear No
Included verbal or other signs of positive or negative emotions, or negatively or positively charged interaction
RQ 1
Clear positive signs from at least two group members
Clear negative signs from at least two group members
Mixed signs between group members
Unclear signs ?
RQ 2 & 3
Physiological arousal

9. Preliminary results A1 67 % 14 % 2 % 42 % 5 % 12 % 20 % A2 60 % 27 %
Group
Yes/Whole session
Positive Activating
Positive De-activating
Negative Activating
Negative De-activating
Mixed Activating
Mixed
De-activating
Unclear Activating
Unclear De-activating A1
67 %
14 %
2 %
42 %
5 %
12 %
20 % A2
60 %
27 %
6 %
34 %
7 %
1 %
0 %
11 % A3
94 %
30 %
3 %
17 % B1
62 %
18 %
13 % B2
68 %
9 %
29 %
8 % B3
31 %
25 % B5
74 %
61 % C1
89 %
44 %
4 % C2
76 %
36 %
21 % C3
72 %
10 % C4
58 %
28 % C5
22 %
16 %
40 %

12. Preliminary results A1 67 % 14 % 2 % 42 % 5 % 12 % 20 % A2 60 % 27 %
Group
Yes/Whole session
Positive Activating
Positive De-activating
Negative Activating
Negative De-activating
Mixed Activating
Mixed
De-activating
Unclear Activating
Unclear De-activating A1
67 %
14 %
2 %
42 %
5 %
12 %
20 % A2
60 %
27 %
6 %
34 %
7 %
1 %
0 %
11 % A3
94 %
30 %
3 %
17 % B1
62 %
18 %
13 % B2
68 %
9 %
29 %
8 % B3
31 %
25 % B5
74 %
61 % C1
89 %
44 %
4 % C2
76 %
36 %
21 % C3
72 %
10 % C4
58 %
28 % C5
22 %
16 %
40 %

15. Conclusions
Groups’ emotional state varies quite much during one learning session
Groups’ coded emotional state was activating more often than de-activating
Most often groups’ emotional state was coded as negative activating
However, there were differences between groups in terms of the amout of socio- emotional expressions, and valence and activation of socio-emotional segments
Next steps:
Differences between groups?
How is EDA related? How it can be used in relation to the video coding?

16. References
Boekaerts, M., & Pekrun, R. (2016). Emotions and Emotion Regulation in Academic Settings. In L. Corno & E. M. Anderman (Eds.), Handbook of educational psychology (3rd ed., pp. 76–90). New York, NY: Routledge. Pekrun, R. (2016). Academic Emotions. In K. R. Wentzel & D. B. Miele (Eds.), Handbook of motivation at school (2nd ed., pp. 120–144). New York, NY: Routledge. Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic Emotions in Students’ Self-Regulated Learning and Achievement: A Program of Qualitative and Quantitative Research. Educational Psychologist, 37(2), 91– Russell, J. A., & Barrett, L. F. (1999). Core affect, prototypical emotional episodes, and other things called emotion: Dissecting the elephant. Journal of Personality and Social Psychology, 76(5), 805– Boucsein, W. (2012). Electrodermal activity. Springer Science & Business Media., 1–8. Dawson, M. E., Schell, A. M., & Filion, D. M. (2007). The Electrodermal System. In J. Cacioppo, L. G. Tassinary, & G. G. Berntson (Eds.), Handbook of Psychophysiology (3rd ed., pp. 159–181). Cambridge: Cambridge University Press. Pijeira-Díaz, H. J., Drachsler, H., Järvelä, S., & Kirschner, P. A. (2016). Investigating collaborative learning success with physiological coupling indices based on electrodermal activity. Proceedings of the Sixth International Conference on Learning Analytics & Knowledge - LAK ’16, 64– 73.

17. Thank you! Tiina Törmänen PhD Student Learning and Educational Technology Research Unit (LET) EmReg Project University of Oulu Contact: