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S
Distributed Regulation
Workshop
Susanne P. Lajoie
McGill University
PhD Candidate
Eric Poitras
MD, MA Candidate
Dr Kevin Waschke
PhD Candidate
John Ranellucci
PhD Candidate
Ilian Cruz-
Panesso
tlas@
advanced technologies for
learnin g in aut hent ic settings
PhD Candidate
Laura Naismith
Research Associate
Dr. Jeff Wiseman
Principal Investigator
Dr. Susanne P. Lajoie
PhD Candidate
Yuan-Jin Hong
MA Candidate
Tara Tressel
MA Candidate
Maedeh Kazemi
MA Candidate
Christina
Summerside
PhD Candidate
Mandana Bassiri
ATLAS LAB
MA Candidate
Lila Lee
Outline
S Definitions of shared or distributed regulation
S Examples of distributed regulation from our data in
medical problem solving
S What analytical techniques were used?
Definitions
S SRL, metacognition and co-regulations
S Shared Mental Models
Definitions:Self-
Regulation, Metacogniton and
Co-regulation
S Metacognition-private cognitions influenced by social
experiences (Hacker & Bol, 2004; Salonen, Vauras &
Efklides, 2005)
S Co-regulation: Social environment supports individual
participation and learning (McCaslin, 2004)
S Requires awareness of own metacognitive experience as well
as that of partners engaging in task (Salonen et al.)
S Sociocognitive and affective behaviours intersect ---co-
regulation may decline when imbalances occur due to
understanding (low prior knowledge) or content or mismatch in
relations (bossy vs wallflower)
S Groups can be multiple self-regulating agents that socially
regulate each other’s learning (Volet, Summers &
Thurman, 2009)
Definitions: Co-Regulation
S Volet (2009)—continuum of social regulation from individual
regulation within group to co-regulation as a group; calls for
coding both social and content
S High level Content processing: can be observed within an
individual or group as :
elaborating, interpreting, reasoning, building on
ideas, explaining in one’s own words or help seeking for
understanding
S Low-Level Content processing: seeking help for details or
facts, reading verbatim from text
S Individual regulation features one speaker, co-regulation
represents verbal contributions from multiple group members
S Shared understanding of task goals and relevant knowledge
(Orasanu, 2005;Klein et al., 1993;Cannon-Bowers, Salas &
Converse, 93); shared explicit communication (closed loop
communication- that once SMM developed communication can
decrease); situation-specific metacognitive skills (awareness of what is
needed in dynamically changing situations; mutual trust that ―others‖ are
doing their job.
S SMM in medicine: shared understanding of goals, plans and actions for
managing the patient effectively, shared situation awareness requires
both metacognition and co-regulation
Mutual Trust
Definition: Shared Mental Models
Examples
S Example 1. Co-regulation in collaborative groups solving
a role play in technology and non-technology supported
setting (Lajoie & Lu; 2006; Lu, Lajoie & Wiseman, 2007)
S Example 2. Co-regulation in problem based learning
activity (Hmelo et al.,2012; Lajoie et al,2012)
S Example 3. Shared Mental Models in Trauma Team
(Cruz-Panesso, Lajoie & Lachapelle, 2012.
EG in
stage 2
EG in
stage 3
EG work on
the laptop
CG is
discussing
Receiver
Example 1: Co-regulation in collaborative groups technology and non-technology supported
(Lajoie & Lu; 2006; Lu, Lajoie & Wiseman, 2007)
Coding
S Based on the Volet’s assumption that groups can be
multiple self-regulating agents that socially regulate
each other’s learning
S Group discourse analyzed by speaker turns and for
episodes that revealed metacognitive activity
(planning, executing, monitoring, evaluation, elabora
tion) adapted from Meijer, Veenman & Van Hout-
Wolters, 2006)
Analytics
S Each metacognitive activity coded and converted to
percentages per group for comparisons
S Summed the total number of turns coded and
divided by the total number of turns in the transcript.
To calculate percent of different metacognitive
activity types, we divided the sum of each type by
the total number of codes for each transcript
Example 2: Co-regulation in
PBL
S Analyzed individual and group discourse using Volet’s
framework
S High and low content processing
S Co-regulation and individual regulation
S Coding unit: coded an episode with more than 2 speaker
turns that have similar topics
Lajoie, S. P. Teaching and Learning
through TRE's. Presented at
SALTISE, 2013
AdobeConnect- PBL dialogues with medical tutors in Canada and Hong Kong:
Learning Objective was to learn how to communicate bad news to patients
S
Co-regulation High-level content
Processing
· Elaborating [EAL]
· Interpreting [INT]
· Reasoning [REA]
· Building on ideas [BLE]
· Help seeking for understanding [HSU]
· Explaining in one’s own words [EXP]
Low-level content
processing
· Reading text [RT]
· Repeating [REP]
· Paraphrasing [PAR]
· Clarifying [CLA]
· Agreement [AGR]
· Seeking help for facts [SEE]
Individual
regulation
High-level content
Processing
· Elaborating [EAL]
· Interpreting [INT]
· Reasoning [REA]
· Building on ideas [BLE]
· Help seeking for understanding [HSU]
· Explaining in one’s own words [EXP]
Low-level content
processing
· Reading text [RT]
· Repeating [REP]
· Paraphrasing [PAR]
· Clarifying [CLA]
· Agreement [AGR]
· Seeking help for facts [SEE]
No Code: Does not fit in the above
SV: And of course, we have to note the emotion and the condition of the patient. [ELABORATING]
SM: So what do you mean on knowing the emotion, could you expand that a little bit? [HELP SEEKING FOR
UNDERSTANDING]
SV: Say if the patient enters in the consultation room, and she is very depressed, so may be at that time, it
may not be appropriate for us to break the news at that moment. [ELABORATING]
SM: Ok, so then once you have right setting and knows the emotion of the condition of the patient then what
would you do? What kind o things that you would have to start to say? [HELP SEEKING FOR
UNDERSTANDING]
SE: I think it would be good before getting straight to the bad news, you ask any questions that you might
need to ask, like new symptoms or complaints or anything, because once given any bad news then it would
be very difficult after that point to ask them relevant questions or gather information that you might need.
[REASONING]
SK: Also perhaps, ask the patient what her expectation of the consulation is. [BUILDING ON IDEAS]
SM: Yeah, it makes a lot of sense. [AGREEMENT]
SE: I think I would also ask the patient what their concerns are, or depending on the test that you would’ve
done, of course. But ar, in most cases I think it is something or information you cannot get after you gave the
bad news. [ELABORATING]
SK: Maybe also ask the patient being accompanied by anyone, so that there’ll be a spouse, or a son, or
daughter outside the consultation room, which might be of use later. [BUILDING ON IDEAS]
High-Level Co-Regulation
S
VM
Regulation Low vs. High Content
High-Level Co-Regulation
EK
W
Instructor
Student
0
1
2
3
4
5
M K E V W
Low
High
S K: Yeah. [NO CODE]
S W: Couldn’t hear you, K. [NO CODE]
S K: Yes yes, I can, I am thinking about it, I too agree there’s
like everything are all three ideas, facts, and learning
objectives are there but um… see the thing, I am not quite
sure is some of the ideas but is actually I think is a
fact, because it works like it is being documented in
literature lots of doctors practice it and and and that’s what
separates an ideas from facts, that facts is when idea is
being exercise and brings results and it becomes facts like
you can document it. So I mean, some of the points being
proposed that sounds a bit more factual to me, but well
for, it’s to mix with idea and certainly learning objectives.
[REASONING]
High-Level Individual
Regulation
S
0
1
2
3
4
5
M K E V W
Low
High
VM
Regulation Low vs. High Content
High-Level Individual-Regulation
EK
W
Instructor
Student
S L: So [NO CODE]
S K: Sssso [NO CODE]
S L: Establish the connection with patient obtain patient’s expectation, demonstrate
empathy, okay um, what are the actual, what are other points that we have um
covered. Ar, sensitivity to the patient, I think K also mentioned that right?
[REPEATING]
S K: Ar…Yeah, well, just adjusting your sensitivity before hand or something.
[REPEATING]
S E: I can ar, ar put at the top. [CLARIFYING]
S L: so so it’s a [NO CODE]
S K: um [NO CODE]
S L: um [NO CODE]
Low-Level Co-Regulation
S
VM
Regulation Low vs. High Content
Low-Level Co-Regulation
EK
L
Instructor
Student
0
1
2
3
4
5
M K E V L
Low
High
S K: Yeah. [NO CODE]
S V: That’s perfectly fine, maybe I can start first because that is me who
talk about it at the moment. Well, um maybe we can go through them
one by one. The first one is ―S‖, is means the setting of the
environment, which is already mentioned by E yesterday, and I think
um, and many literature um um has documented that setting up an
appropriate environment is important for breaking a bad news because
a comfortable environment can help the patient to um prepare for what
he is going to perceive. And the second thing ―P‖ stands for
perception, that means um the patient’s perception um because um
this is important because um before we really um go to into the bad
news we have to assess the patient how he or she feels that would
help us to how much detail we are going to go at the patient at the
moment, so this are the ―S‖ and ―P‖ for ―SPIKES‖. [PARAPHRASING]
S V: Anyone wants to talk about ―I‖ and ―K‖? [NO CODE]
Low-Level Individual
Regulation
S
VM
Regulation Low vs. High Content
Low-Level Individual Regulation
EK
L
Instructor
Student
0
1
2
3
4
5
M K E V L
Low
High
Analytics
S Using Volet’s framework each episode was coded and
counted using codes for high and low content processing
for both individual and group regulation
S Next step will be to calculate percentage of individual vs.
co-regulation and high vs. low content regulation in each
type. The calculations will divide the coded total number
in each category by the total number of turns in the
transcript.
Example 3. Shared Mental Models in Trauma Teams
Cruz-Panesso, 2011; Cruz-Panesso, Lajoie &
Lachapelle, 2012
S Videotapes of actual simulations were reviewed to extract
representative behaviors of SMMs
S We coded:
- Development of common understanding of the own role
and other team members’ roles
- Anticipation of other team members’ needs
- Provision of information without explicit request
S
L: “Mi put the airway”. (―Mi‖ is the participant playing the role of the airway) When the leader
orders ―Mi‖ to put the airway, this member was already looking for the instruments to do it.
While ordering this, the team leader signals what procedures should be applied. For
instance, when he is ordering the airway he signals to the head of the patient and gets them to
approach the airway position,
L: “Mo put the IVs”. Again, when the leader orders an IV he signals the arm of the
patient.
The patient arrives with a partner (is an actor) and the leader asks him some questions about
the patient. The patient starts coughing and the leader goes up to assist the airway while at the
same time assesses the level of consciousness of the patient, and informs the patient about
the procedures: “I am putting some oxygen here”
L: ―Mary (the patient) can you heard me?‖
IV: reports “the IVs are in” After connecting the patient to the IVs, this participant gets ready
to start revising the vital signs
L: Looks at the IV and says “OK”
IV: Opens the shirt of the soldier to examine the chest and the vital signs
L: Moves from the airway to the chest and starts revising the vital signs with the
stethoscope, while at the same time verbalizes what he is finding.
L: Moves to the airway again and says: “I am going to intubate her” “ It may be a problem
with the airway” and starts the intubation.
Airw: Assist the leader with the intubation
L: The partner of the patient –an actor- falls down and the leader says “Mo he needs some
help” Provision of information without
explicit request
The leader helps team members to
develop common understanding of their
own role and other team members’
roles
Example 4. Shared Mental
Models
L: ―I can’t take more time, I’m going to make a surgical
airway‖
Airw: (This team member was already looking for the
intubation kit)
Anticipation of other team members’ needs:
Summary
S Provided several definition and examples from our work
S Still think the definitions are ―under-development‖
S I look forward to the broader discussion of these terms
S Thank you for your attention

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CSCL2013 - Lajoie

  • 2. PhD Candidate Eric Poitras MD, MA Candidate Dr Kevin Waschke PhD Candidate John Ranellucci PhD Candidate Ilian Cruz- Panesso tlas@ advanced technologies for learnin g in aut hent ic settings PhD Candidate Laura Naismith Research Associate Dr. Jeff Wiseman Principal Investigator Dr. Susanne P. Lajoie PhD Candidate Yuan-Jin Hong MA Candidate Tara Tressel MA Candidate Maedeh Kazemi MA Candidate Christina Summerside PhD Candidate Mandana Bassiri ATLAS LAB MA Candidate Lila Lee
  • 3. Outline S Definitions of shared or distributed regulation S Examples of distributed regulation from our data in medical problem solving S What analytical techniques were used?
  • 4. Definitions S SRL, metacognition and co-regulations S Shared Mental Models
  • 5. Definitions:Self- Regulation, Metacogniton and Co-regulation S Metacognition-private cognitions influenced by social experiences (Hacker & Bol, 2004; Salonen, Vauras & Efklides, 2005) S Co-regulation: Social environment supports individual participation and learning (McCaslin, 2004) S Requires awareness of own metacognitive experience as well as that of partners engaging in task (Salonen et al.) S Sociocognitive and affective behaviours intersect ---co- regulation may decline when imbalances occur due to understanding (low prior knowledge) or content or mismatch in relations (bossy vs wallflower) S Groups can be multiple self-regulating agents that socially regulate each other’s learning (Volet, Summers & Thurman, 2009)
  • 6. Definitions: Co-Regulation S Volet (2009)—continuum of social regulation from individual regulation within group to co-regulation as a group; calls for coding both social and content S High level Content processing: can be observed within an individual or group as : elaborating, interpreting, reasoning, building on ideas, explaining in one’s own words or help seeking for understanding S Low-Level Content processing: seeking help for details or facts, reading verbatim from text S Individual regulation features one speaker, co-regulation represents verbal contributions from multiple group members
  • 7. S Shared understanding of task goals and relevant knowledge (Orasanu, 2005;Klein et al., 1993;Cannon-Bowers, Salas & Converse, 93); shared explicit communication (closed loop communication- that once SMM developed communication can decrease); situation-specific metacognitive skills (awareness of what is needed in dynamically changing situations; mutual trust that ―others‖ are doing their job. S SMM in medicine: shared understanding of goals, plans and actions for managing the patient effectively, shared situation awareness requires both metacognition and co-regulation Mutual Trust Definition: Shared Mental Models
  • 8. Examples S Example 1. Co-regulation in collaborative groups solving a role play in technology and non-technology supported setting (Lajoie & Lu; 2006; Lu, Lajoie & Wiseman, 2007) S Example 2. Co-regulation in problem based learning activity (Hmelo et al.,2012; Lajoie et al,2012) S Example 3. Shared Mental Models in Trauma Team (Cruz-Panesso, Lajoie & Lachapelle, 2012.
  • 9. EG in stage 2 EG in stage 3 EG work on the laptop CG is discussing Receiver Example 1: Co-regulation in collaborative groups technology and non-technology supported (Lajoie & Lu; 2006; Lu, Lajoie & Wiseman, 2007)
  • 10. Coding S Based on the Volet’s assumption that groups can be multiple self-regulating agents that socially regulate each other’s learning S Group discourse analyzed by speaker turns and for episodes that revealed metacognitive activity (planning, executing, monitoring, evaluation, elabora tion) adapted from Meijer, Veenman & Van Hout- Wolters, 2006)
  • 11.
  • 12.
  • 13. Analytics S Each metacognitive activity coded and converted to percentages per group for comparisons S Summed the total number of turns coded and divided by the total number of turns in the transcript. To calculate percent of different metacognitive activity types, we divided the sum of each type by the total number of codes for each transcript
  • 14.
  • 15. Example 2: Co-regulation in PBL S Analyzed individual and group discourse using Volet’s framework S High and low content processing S Co-regulation and individual regulation S Coding unit: coded an episode with more than 2 speaker turns that have similar topics
  • 16. Lajoie, S. P. Teaching and Learning through TRE's. Presented at SALTISE, 2013 AdobeConnect- PBL dialogues with medical tutors in Canada and Hong Kong: Learning Objective was to learn how to communicate bad news to patients
  • 17. S Co-regulation High-level content Processing · Elaborating [EAL] · Interpreting [INT] · Reasoning [REA] · Building on ideas [BLE] · Help seeking for understanding [HSU] · Explaining in one’s own words [EXP] Low-level content processing · Reading text [RT] · Repeating [REP] · Paraphrasing [PAR] · Clarifying [CLA] · Agreement [AGR] · Seeking help for facts [SEE] Individual regulation High-level content Processing · Elaborating [EAL] · Interpreting [INT] · Reasoning [REA] · Building on ideas [BLE] · Help seeking for understanding [HSU] · Explaining in one’s own words [EXP] Low-level content processing · Reading text [RT] · Repeating [REP] · Paraphrasing [PAR] · Clarifying [CLA] · Agreement [AGR] · Seeking help for facts [SEE] No Code: Does not fit in the above
  • 18. SV: And of course, we have to note the emotion and the condition of the patient. [ELABORATING] SM: So what do you mean on knowing the emotion, could you expand that a little bit? [HELP SEEKING FOR UNDERSTANDING] SV: Say if the patient enters in the consultation room, and she is very depressed, so may be at that time, it may not be appropriate for us to break the news at that moment. [ELABORATING] SM: Ok, so then once you have right setting and knows the emotion of the condition of the patient then what would you do? What kind o things that you would have to start to say? [HELP SEEKING FOR UNDERSTANDING] SE: I think it would be good before getting straight to the bad news, you ask any questions that you might need to ask, like new symptoms or complaints or anything, because once given any bad news then it would be very difficult after that point to ask them relevant questions or gather information that you might need. [REASONING] SK: Also perhaps, ask the patient what her expectation of the consulation is. [BUILDING ON IDEAS] SM: Yeah, it makes a lot of sense. [AGREEMENT] SE: I think I would also ask the patient what their concerns are, or depending on the test that you would’ve done, of course. But ar, in most cases I think it is something or information you cannot get after you gave the bad news. [ELABORATING] SK: Maybe also ask the patient being accompanied by anyone, so that there’ll be a spouse, or a son, or daughter outside the consultation room, which might be of use later. [BUILDING ON IDEAS] High-Level Co-Regulation
  • 19. S VM Regulation Low vs. High Content High-Level Co-Regulation EK W Instructor Student 0 1 2 3 4 5 M K E V W Low High
  • 20. S K: Yeah. [NO CODE] S W: Couldn’t hear you, K. [NO CODE] S K: Yes yes, I can, I am thinking about it, I too agree there’s like everything are all three ideas, facts, and learning objectives are there but um… see the thing, I am not quite sure is some of the ideas but is actually I think is a fact, because it works like it is being documented in literature lots of doctors practice it and and and that’s what separates an ideas from facts, that facts is when idea is being exercise and brings results and it becomes facts like you can document it. So I mean, some of the points being proposed that sounds a bit more factual to me, but well for, it’s to mix with idea and certainly learning objectives. [REASONING] High-Level Individual Regulation
  • 21. S 0 1 2 3 4 5 M K E V W Low High VM Regulation Low vs. High Content High-Level Individual-Regulation EK W Instructor Student
  • 22. S L: So [NO CODE] S K: Sssso [NO CODE] S L: Establish the connection with patient obtain patient’s expectation, demonstrate empathy, okay um, what are the actual, what are other points that we have um covered. Ar, sensitivity to the patient, I think K also mentioned that right? [REPEATING] S K: Ar…Yeah, well, just adjusting your sensitivity before hand or something. [REPEATING] S E: I can ar, ar put at the top. [CLARIFYING] S L: so so it’s a [NO CODE] S K: um [NO CODE] S L: um [NO CODE] Low-Level Co-Regulation
  • 23. S VM Regulation Low vs. High Content Low-Level Co-Regulation EK L Instructor Student 0 1 2 3 4 5 M K E V L Low High
  • 24. S K: Yeah. [NO CODE] S V: That’s perfectly fine, maybe I can start first because that is me who talk about it at the moment. Well, um maybe we can go through them one by one. The first one is ―S‖, is means the setting of the environment, which is already mentioned by E yesterday, and I think um, and many literature um um has documented that setting up an appropriate environment is important for breaking a bad news because a comfortable environment can help the patient to um prepare for what he is going to perceive. And the second thing ―P‖ stands for perception, that means um the patient’s perception um because um this is important because um before we really um go to into the bad news we have to assess the patient how he or she feels that would help us to how much detail we are going to go at the patient at the moment, so this are the ―S‖ and ―P‖ for ―SPIKES‖. [PARAPHRASING] S V: Anyone wants to talk about ―I‖ and ―K‖? [NO CODE] Low-Level Individual Regulation
  • 25. S VM Regulation Low vs. High Content Low-Level Individual Regulation EK L Instructor Student 0 1 2 3 4 5 M K E V L Low High
  • 26. Analytics S Using Volet’s framework each episode was coded and counted using codes for high and low content processing for both individual and group regulation S Next step will be to calculate percentage of individual vs. co-regulation and high vs. low content regulation in each type. The calculations will divide the coded total number in each category by the total number of turns in the transcript.
  • 27. Example 3. Shared Mental Models in Trauma Teams Cruz-Panesso, 2011; Cruz-Panesso, Lajoie & Lachapelle, 2012 S Videotapes of actual simulations were reviewed to extract representative behaviors of SMMs S We coded: - Development of common understanding of the own role and other team members’ roles - Anticipation of other team members’ needs - Provision of information without explicit request
  • 28. S L: “Mi put the airway”. (―Mi‖ is the participant playing the role of the airway) When the leader orders ―Mi‖ to put the airway, this member was already looking for the instruments to do it. While ordering this, the team leader signals what procedures should be applied. For instance, when he is ordering the airway he signals to the head of the patient and gets them to approach the airway position, L: “Mo put the IVs”. Again, when the leader orders an IV he signals the arm of the patient. The patient arrives with a partner (is an actor) and the leader asks him some questions about the patient. The patient starts coughing and the leader goes up to assist the airway while at the same time assesses the level of consciousness of the patient, and informs the patient about the procedures: “I am putting some oxygen here” L: ―Mary (the patient) can you heard me?‖ IV: reports “the IVs are in” After connecting the patient to the IVs, this participant gets ready to start revising the vital signs L: Looks at the IV and says “OK” IV: Opens the shirt of the soldier to examine the chest and the vital signs L: Moves from the airway to the chest and starts revising the vital signs with the stethoscope, while at the same time verbalizes what he is finding. L: Moves to the airway again and says: “I am going to intubate her” “ It may be a problem with the airway” and starts the intubation. Airw: Assist the leader with the intubation L: The partner of the patient –an actor- falls down and the leader says “Mo he needs some help” Provision of information without explicit request The leader helps team members to develop common understanding of their own role and other team members’ roles Example 4. Shared Mental Models
  • 29. L: ―I can’t take more time, I’m going to make a surgical airway‖ Airw: (This team member was already looking for the intubation kit) Anticipation of other team members’ needs:
  • 30. Summary S Provided several definition and examples from our work S Still think the definitions are ―under-development‖ S I look forward to the broader discussion of these terms S Thank you for your attention

Editor's Notes

  1. High stress teams (air crews) Klein, Orasanu, Calde
  2. Elaborating [EAL]Interpreting [INT]Reasoning [REA]Building on ideas [BLE]Help seeking for understanding [HSU]Explaining in one’s own words [EXP
  3. Elaborating [EAL]Interpreting [INT]Reasoning [REA]Building on ideas [BLE]Help seeking for understanding [HSU]Explaining in one’s own words [EXP]Reading text [RT]Repeating [REP]Paraphrasing [PAR]Clarifying [CLA]Agreement [AGR]Seeking help for facts [SEE]