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KnowledgeSkills
KnowledgeSkills
KnowledgeSkills
KnowledgeSkills
30 + 10 = ____
Find the sum
BASIC SKILLS
BASIC FACTS
Writing
stores
information
Computers
manipulate
information
Writing
outsources
memory
Computation
outsources
thinking
Computation
outsources
thinking
outsources
outsources
outsize
outskirts
outsmart
outsold
outsole
outsource
outsourcing
outspan
outspend
outspoken
outspread
outstand
omputation
C outsources simple thinking
so we can do more complex thinking
1.Place the decimal point in quotient
2.Count off in groups of two in both directions from
the decimal point.
3.Ask yourself, "What is the largest perfect square
equal to or just below (near) the first group of
numbers to the left side in the dividend?"
4."What is the square root of that number?" Write
the square root in the quotient.
5.Work like division --- multiply the quotient by the
divisor. Then bring down the next group of numbers.
In division you bring down one number, but in
square root you bring down two numbers.
6.Bring down the next group of numbers. In division
you bring down one
number, but in square root you bring down two
numbers.
7.You must create a new divisor by doubling the
quotient or by adding the last digit in the quotient to
the last divisor. When you get your next divisor,
write it with a space to the right of it.
8.Find a number that goes in the space to the right of
the divisor and will go in the quotient so the number
you put in the quotient times the divisor is less then
the current dividend.
9.Repeat steps 5 thru 6 if you run out of digits add
zeros like in division except add 2 zeros at a time
instead of one.
28.5
1 + = 3
f(x) = ax2 + bx + c
1 + = 3
f(x) = ax2 + bx + c
1 + = 3
1 + = 3
f(x) = ax2 + bx + c
1 + = 3
f(x) = ax2 + bx + c
1 + = 3
Why do we
need to know
this, man?
Details
Why do we
need to know
this, man?
Big Picture
Details
Why do we
need to know
this, man?
Big Picture
Details
Big Picture
Details
Big Picture
Details
Big Picture
Details
Big Picture
Details
Big Picture
Details
Cool!
Communities of Practice
Communities of Practice
Communities of Practice
Communities of Practice
Communities of Practice
Communities of Practice
culture
culture
culture
culture
culture
culture
Epistemic Frame
Games are cultures
1. Apply virtual communication
tools and facilitation techniques
to more effectively connect
people from around the world.
2. Use collaborative spaces to
gather knowledge, express
ideas and concerns and share
passions.
3. Spend more time on setting
organizational context and
communicating where the
organization needs to go.
4. Improve the visibility of both
formal and informal skills.
5. Use dashboards linked to
collaborative tools to capture
key realtime information about
people, activities and outcomes.
6. Provide more frequent
guidance and link performance
to recognition.
The environmental factors
within MMORPGs can be
applied to enhance
leadership effectiveness
for the globally integrated
enterprise
75%
Game v Corporate Skills
0
20
40
60
80
100
0 20 40 60 80 100
Game Skills
CorporateSkills
The skills and techniques
of the gaming leader
cannot be transferred
directly to the leadership
of the virtual corporation
61%
eflection-in-action
R
thinking that reshapes
what we are doing
while we are doing it
T
ways of
knowing
thinking that reshapes
what we are doing
while we are doing it
K
ways of
doing
ways of
knowing
thinking that reshapes
what we are doing
while we are doing it
D
practicum
ways of
doing
ways of
knowing
P
action
A
practicum
reflection-
on-action
R
practicum
action
reflection-
on-action
practicum
action
reflection-
on-action
eflection-in-action
Rpracticum
practicum
task task task
action
reflect reflect reflecttask task task
reflection-on-action
task task taskreflect reflect reflect
tool tool tool
tool tool tool
task task taskreflect reflect reflect
person person person
tool tool tool
person person person
task task task
activity system or participant structure
reflect reflect reflect
tool tool tool
person person person
task task taskreflect reflect reflect
rooms
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Year 1 Year 2 Year 3
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Year 1 Year 2 Year 3
d = + 0.28
d = + 0.28
d = + 0.91
d = + 0.91
We value what we can
measure
—Don Norman
We value what we can
measure
^
EpistemologyValuesIdentityKnowledgeSkills
EpistemologyValuesIdentityKnowledgeSkills
Epistemic Network Analysis
(ENA)
A
B
A
B
A
B
C
D
©2005, 2008 David Williamson Shaffer
A
B
C
D
E
F
A
B
C
D
E
F
©2005, 2008 David Williamson Shaffer
A
B
E
D
C
F
A
B
E
D
F
C
©2005, 2008 David Williamson Shaffer
A
B
©2005, 2008 David Williamson Shaffer
A
B
C
©2005, 2008 David Williamson Shaffer
A
B
F
C
©2005, 2008 David Williamson Shaffer
A
B
D
F
C
©2005, 2008 David Williamson Shaffer
A
B
E
D
F
C
©2005, 2008 David Williamson Shaffer
A
B
E
D
F
C
©2005, 2008 David Williamson Shaffer
A
E
D
F
C
B
©2005, 2008 David Williamson Shaffer
A
E
D
F
C
B
©2005, 2008 David Williamson Shaffer
A
E
D
F
C
B
©2005, 2008 David Williamson Shaffer
A
E
D
F
C
B
Chat Discourse
Utterance
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
Epistemology of Design
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
Value of Client
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
Skill of Data Analysis
Human Agreement with AutoCoder
E and AC N1 and N2 E1 and E2
E/Data 0.521463 0.321308 0.697609
E/Design 0.64044 0.479389 0.54518
E/Clients 0.746846 0.796759 0.746846
E/Consultants 0.764168 0.566491 0.853813
V/Clients 0.538768 0.663687 0.663311
V/Consultants 0.493692 0.663311 0.663311
S/Data 0.76369 0.615417 0.940922
S/Design 0.801079 0.466942 0.728728
S/Professionalism 0.645465 0.456452 0.72107
S/Collaboration 0.694157 0.666465 0.888954
I/Engineer 0.479239 0.824869 0.560584
I/Intern 0.921389 0.816862 0.853813
K/Nanotech 1 0.796759 1
K/Surfactants 0.95827 0.965993 0.919605
K/Attributes 0.981197 0.900837 0.990646
K/Data 0.63988 0.784384 0.869369
K/Design 0.728741 0.771417 0.774949
K/Clients 1 0.945658 1
K/Materials 0.637786 0.916048 0.984033
K/Processes 0.364711 0.811285 0.95827
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
Codes by Utterance
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
Codes by Utterance
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
Codes by Utterance
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
Codes by Utterance
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
Codes by Utterance
Stanza
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
E6V4S5 I2 K1K2K3
1 0 1 0 1 0 0
Codes by Utterance
Stanza
Codes by Stanza
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
E6V4S5 I2 K1K2K3
1 0 1 0 1 0 0
Codes by Utterance
Stanza
Codes by Stanza
E6V4S5 I2 K1K2K3
1 1 0 0 0 1 0 0
2 0 0 0 0 1 1 0
3 0 0 0 0 0 0 0
4 1 0 1 0 1 0 0
5 1 0 0 0 0 0 0
6 0 0 0 0 0 0 1
7 0 0 0 0 1 0 0
8 0 0 0 1 0 0 1
E6V4S5 I2 K1K2K3
1 0 1 0 1 0 0
Codes by Utterance
Stanza
Codes by Stanza
E6V4S5 I2 K1K2K3
1 0 1 0 1 0 0
Codes by Stanza
E6V4S5 I2 K1K2K3
1 0 1 0 1 0 0
E6 V4 S5 I2 K1 K2 K3
E6 0 0 1 0 1 0 0
V4 0 0 0 0 0 0 0
S5 1 0 0 0 1 0 0
I2 0 0 0 0 0 0 0
K1 1 0 1 0 0 0 0
K2 0 0 0 0 0 0 0
K3 0 0 0 0 0 0 0
Codes by Stanza
Adjacency Matrix for the Stanza
E6V4S5 I2 K1K2K3
1 0 1 0 1 0 0
E6 V4 S5 I2 K1 K2 K3
E6 0 0 1 0 1 0 0
V4 0 0 0 0 0 0 0
S5 1 0 0 0 1 0 0
I2 0 0 0 0 0 0 0
K1 1 0 1 0 0 0 0
K2 0 0 0 0 0 0 0
K3 0 0 0 0 0 0 0
Codes by Stanza
Adjacency Matrix for the Stanza
E6V4S5 I2 K1K2K3
1 0 1 0 1 0 0
E6 V4 S5 I2 K1 K2 K3
E6 0 0 1 0 1 0 0
V4 0 0 0 0 0 0 0
S5 1 0 0 0 1 0 0
I2 0 0 0 0 0 0 0
K1 1 0 1 0 0 0 0
K2 0 0 0 0 0 0 0
K3 0 0 0 0 0 0 0
Codes by Stanza
Adjacency Matrix for the Stanza
E6V4S5 I2 K1K2K3
1 0 1 0 1 0 0
E6 V4 S5 I2 K1 K2 K3
E6 0 0 1 0 1 0 0
V4 0 0 0 0 0 0 0
S5 1 0 0 0 1 0 0
I2 0 0 0 0 0 0 0
K1 1 0 1 0 0 0 0
K2 0 0 0 0 0 0 0
K3 0 0 0 0 0 0 0
Codes by Stanza
Adjacency Matrix for the Stanza
E6V4S5 I2 K1K2K3
1 0 1 0 1 0 0
E6 V4 S5 I2 K1 K2 K3
E6 0 0 1 0 1 0 0
V4 0 0 0 0 0 0 0
S5 1 0 0 0 1 0 0
I2 0 0 0 0 0 0 0
K1 1 0 1 0 0 0 0
K2 0 0 0 0 0 0 0
K3 0 0 0 0 0 0 0
Codes by Stanza
Adjacency Matrix for the Stanza
E6V4S5 I2 K1K2K3
1 0 1 0 1 0 0
E6 V4 S5 I2 K1 K2 K3
E6 0 0 1 0 1 0 0
V4 0 0 0 0 0 0 0
S5 1 0 0 0 1 0 0
I2 0 0 0 0 0 0 0
K1 1 0 1 0 0 0 0
K2 0 0 0 0 0 0 0
K3 0 0 0 0 0 0 0
Codes by Stanza
Adjacency Matrix for the Stanza
©2005, 2008 David Williamson Shaffer
A
B
E
D
F
C
A
B
E
D
F
C
Cumulative Adjacency Matrix
Cumulative Adjacency Matrix
A
B
E
D
F
C
A
B
E
D
F
C
Cumulative Adjacency Matrix
Cumulative Adjacency Matrix
A
B
E
D
F
C
A
B
E
D
F
C
Cumulative Adjacency Matrix
Cumulative Adjacency Matrix
©2005, 2008 David Williamson Shaffer
A
B
E
D
F
C
d = + 0.28
Collaboration
Collaboration
Design
Collaboration
Design
Data
Collaboration
Design
Data
Collaboration
Design
Data
Collaboration
Design
Data
Collaboration
Design
Data
Collaboration
Design
Data
Collaboration
Design
Data
EpistemologyValuesIdentityKnowledgeSkills
EpistemologyValuesIdentityKnowledgeSkills
EpistemologyValuesIdentityKnowledgeSkills
ames toG
eachT
ames areG
ulturesC
ames can createG
ultures of innovationC
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)
How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)

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How Computer Games Help Children Learn (Stockholm University Dept of Education Sept 2013)

Notas do Editor

  1. As we saw earlier, in Nephrotex, students communicate with their team members and their design advisor through an internal chat program.
  2. We segment the chat data by utterance, everytime a person types something and hits send. And we code each utterance for epistemic engineering frame elements.
  3. Every utterance was represented as a row in a matrix and each column is a code. The coding scheme was based on professional elements in the engineering epistemic frame using previous ethnographic studies and ABET criteria. For example,
  4. This first code represents epistemology of design– every time a student is justifying a design decision.
  5. This code represents valuing the client’s needs
  6. And this code represents the skill of data analysis. There were actually 21 codes in this analysis but for the sake of explaining the ENA method I have selected a few as examples.
  7. So, let’s take a closer look at the data.
  8. This utterance is coded for E6 and K1
  9. This utterance is coded for K1 and K2
  10. And this utterance is coded for E6, S5, and K1
  11. Now we can segment the data further and decide that this set of utterances is a stanza. We make the argument that everything that occurs with in this collection of utterances is linked. The discourse is all about one topic. And then, we collapse over these stanzas and do a binary sum.
  12. So, if it occurs within the stanza, then it gets a 1 and if not then a 0.
  13. So, if it occurs within the stanza, then it gets a 1 and if not then a 0.
  14. So, if it occurs within the stanza, then it gets a 1 and if not then a 0.
  15. Let’s take this stanza as a example for the next step of the analysis. It was coded for three codes. We want to measure how players are making connections with elements and so we look at when the codes are occurring together.
  16. The completed adjacency matrix for that stanza
  17. The completed adjacency matrix for that stanza
  18. The completed adjacency matrix for that stanza
  19. The completed adjacency matrix for that stanza
  20. The completed adjacency matrix for that stanza
  21. The completed adjacency matrix for that stanza
  22. The completed adjacency matrix for that stanza
  23. The completed adjacency matrix for that stanza
  24. The completed adjacency matrix for that stanza
  25. The completed adjacency matrix for that stanza
  26. The completed adjacency matrix for that stanza
  27. The completed adjacency matrix for that stanza
  28. The completed adjacency matrix for that stanza
  29. The completed adjacency matrix for that stanza
  30. The completed adjacency matrix for that stanza
  31. The completed adjacency matrix for that stanza