presentation tips

PresentationtipsMarco D’Ambros

95% of presentations SUCK

“”—Guy Kawasaky

—Guy Kawasaky

OK, maybe I’m exaggerating.“”It is actually 99%

99%

1%

suck

don’t suck

Examples?

Ok, but be prepared for what follows

Death by Powerpoint

Preparation Design Delivery

Preparing a 30-slide presentation takes 36-90 hours

“

”—Nancy Duarte

Start with the goal

What is the message?

Know youraudience

Simplify

to the essential(but not more)

—John Maeda

Simplicity is aboutsubtracting the obvious,and adding the meaningful

“

”

—John Maeda

More appears like lesssimply moving it far, far away

“”

Get alone

Multitasking, when it comes to paying attention, is a myth

“

We are biologically incapable of processing attention-rich inputs simultaneously”

—Dr. Medina

People who are interrupted:

50%Make

moreerrors

50%Take

longer tocomplete a task

Being always onlineis being always distracted and

unproductive

You need time off the grid to prepare

Go analog

Use post-it

Use whiteboard

Brainstorming andmind mapping

If you are stuck go for a walk or a run...just move!


why?

How the brain works in 12 rules

Exercise boost brain power

Rule #1

By Dr. Medina

Examples of anti-brain environmentsaccording to Dr. Medina

Lecture hall

Classroom

Office

Exercise is not just good for general health, it actuallyimproves cognition

Exercise increases oxygen flow into the brain, which reduces brain-bound free radicals [...] an increase in oxygen is always accompanied by an uptick in mental sharpness.

“

Exercise acts directly on the molecular machinery of the brain itself. It increases neurons’ creation, survival, and resistance”

—Dr. Medina

Even more benefits!

• Reduces depression

• Treats dementia

• Improves reasoning

• Improves long-term memory

• Improve fluid intelligence

• Helps you solve problems

• and more...

Your audience will haveto seat and listen

think from their perspective

Create a scalable structure

5min

presentation

solutionkey point

key point

key point

15min

presentation

solutionkey point

explanation

explanation

explanation

45min

presentation

key pointexplanation

detail

detail

detail

Create thestory

We do not pay attention to boring things

Rule #4

If keeping someone’s attention in a lecture was a business, it would have an 80% failure rate.

“

”— Dr. John Medina

Good stories are:

simple

Concre

te

Credible

Emotional

• story

• exposition

• conflict & climax

• resolution

How should the story be?

exposition

conflict & climax

resolution

• pick another perspective

Take another perspective

In the beginner’s mind there are many possibilities, in the expert’s mind there are few

—Shunryu Suzuki

Adopt a beginner’s mind

“

”

Common mistakes

People tend to put every word they are going to say on their PowerPoint slides. Although this eliminates the need to memorize your

talk, ultimately this makes your slides crowded, wordy, and boring. You will loss your

audience’s attention before you even reach the bottom of your ...

1. T E L E P R O M P T I N G

Slide from Don McMillan, “Life After Death by PowerPoint”: http://bit.ly/aYxegN

http://bit.ly/aYxegN


2. Spelling mistakes

Many people do not run spel cheek before there presentation

BIG MISTAK!!! Nothing makes you lok stupder than speling erors




3. Bullet pointing


• Avoid• Excesive• Buller-Pointing• Only• Bullet• Key• Points• Too• Many

• Bullet-Points• And• Your• Key• Messages• Will• NOT• Stand• Out



4. Too many levels

• What is worst

• Too many bullet point levels are shown

• Type size gets smaller and smaller

• Until it is utterly unreadable

• Even for audiences in the 4th row

• So you better have just one bulletpoint level

• Better yet, forget about bullets (bullets, not guns, kill people. Don’t you know?)

• Use them sparingly

• There are many other ways of detailing your ideas!




5. Color schemes gone wrong

• Distraction• Confusion • Headache• Nausea• Vomiting• Loss of bladder control

schemesbadcolor

canlead to...




6. Stick to the default template

7. Use things people won’t understand

In the fist time interval t1, we have a total of 4 changes,and the change frequencies of the files (i.e., their probabilityof change) are pA = 2

4 , pB = 14 , pC = 1

4 . The entropy in t1is therefore H = �(0.5 ⇥ log2 0.5 + 0.25 ⇥ log2 0.25 + 0.25 ⇥log2 0.25) = 1. In the second time interval t2 the entropy ishigher: H = �( 2

7 ⇥log227 + 1

7 ⇥log217 + 4

7 ⇥log247 ) = 1.378. In

addition, we take into account the amount of change per fileby measuring the size of change (lines added and/or deleted).Hassan also defined the Adaptive Sizing Entropy as:

H 0 = �nX

k=1

pk ⇥ logn̄ pk (2)

where n is the number of files in the system and n̄ is thenumber of recently modified files. To compute the set of re-cently modified files we use previous periods (e.g., modifiedin the last six time intervals), whereas also time can be used(e.g., modified in the last six months). To use the entropyof code change as bug predictor, Hassan defined the Historyof Complexity Metric (HCM) of a file j as

HCM{a,..,b}(j) =X

i2{a,..,b}

HCPFi(j) (3)

where {a, .., b} is a set of evolution periods and HCPF isdefined as:

HCPFi(j) =

⇢cij ⇥H 0

i, j ⇤ Fi

0, otherwise(4)

where i is a period with entropy H 0i, Fi is the set of files mod-

ified in the period i and j is a file belonging to Fi. Accordingto the definition of cij , there are three types of HCM :

1. (1) cij = 1, every file modified in the considered periodi gets the entropy of the system in the considered timeinterval. This defines approach HCM.

2. (2) cij = pj , each modified file gets the entropy of thesystem weighted with the probability of the file beingmodified, defining WHCM.

3. (3) cij = 1|Fi|

the entropy is evenly distributed to allthe files modified in the i period. We do not use thisdefinition since Hassan showed that it performs lesswell than the other.

Concerning the periods used for computing the History ofComplexity Metric, we use fixed time intervals of two weeks.

Variants. We define three further variants based onHCM, with an additional weight for periods in the past.In EDHCM (Exponentially Decayed HCM) , entropies forearlier periods of time, i.e., earlier modifications, have theircontribution reduced exponentially over time, modelling anexponential decay model. EDHCM was introduced by Has-san. Similarly, LDHCM (Linearly Decayed) and LGDHCM(LoGarithmically decayed), have their contributions reducedover time in a respectively linear and logarithmic fashion.Both are novel. The definition of the variants follow:

EDHCM{a,..,b}(j) =P

i2{a,..,b}HCPFi(j)

e�1⇥(|{a,..,b}|�i) (5)

LDHCM{a,..,b}(j) =P

i2{a,..,b}HCPFi(j)

�2⇤(|{a,..,b}|+1�i) (6)

LGDHCM{a,..,b}(j) =P

i2{a,..,b}HCPFi(j)

�3⇤ln(|{a,..,b}|+1.01�i)(7)

where �1, �2 and �3 are the decay factors.

4.5 Churn of Source Code MetricsUsing churn of source code metrics to predict post release

defects is a novel approach that we propose. The idea isthat higher-level metrics may better model code churn thansimple metrics like addition and deletion of lines of code.The idea is to sample the history of the source code everytwo weeks and to compute the deltas of source code metricsfor each consecutive pair of samples. To do so, we first haveto create “delta matrices”, one per each source code metrics,by performing the following steps:

1. We check out one version of the system from the CVSrepository for each two weeks time interval, and parsethe source code of every version and, for each class,compute the CK+OO source code metrics.

2. For each source code metric, we create a matrix wherethe rows are the classes, the columns are the sampledversions, and each cell is the value of the metric forthe given class at the given version. If a class does notexist in a version, we indicate that by using a defaultvalue of -1. We only consider the classes which existat release x for the prediction.

3. We generate a matrix of deltas, where each cell is theabsolute value of the di�erence between the values ofa metric for a class in two subsequent version. If theclass does not exist in one of the two versions (or bothof them), i.e., at least one value is -1, then we use thedefault value of -1 also for the delta.

10Class Foo

Class Bar 42

Class Bas -1

2 weeks

Release X

50

32

50

22

70

22

48

40

10 15

Version from

1.1.2005

Version from

15.1.2005

Version from

29.1.2005

Time

10

-1

0

10

5

Figure 5: Computing metrics deltas from versionsof a software system sampled every two weeks.

Figure 5 shows an example of deltas matrix computa-tion for three classes. The numbers in the squares arethe values of the metrics in the corresponding versionsof the system, while the numbers in the circles are thedeltas.

Once we have computed the deltas matrices for each sourcecode metric, we compute the churn measures as follows:

CHU(i) =CX

j=1

⇢0, deltas(i, j) = �1PCHU(i, j), otherwise

(8)

PCHU(i, j) = deltas(i, j) (9)

where i is the index of a row in the deltas matrix (corre-sponding to a class), C is the number of columns of the ma-trix (corresponding to the number of samples considered),


4 , pB = 14 , pC = 1


7 ⇥log227 + 1

7 ⇥log217 + 4

7 ⇥log247 ) = 1.378. In


H 0 = �nX

k=1



HCM{a,..,b}(j) =X

i2{a,..,b}

HCPFi(j) (3)


HCPFi(j) =

⇢cij ⇥H 0

i, j ⇤ Fi

0, otherwise(4)





3. (3) cij = 1|Fi|




EDHCM{a,..,b}(j) =P

i2{a,..,b}HCPFi(j)

e�1⇥(|{a,..,b}|�i) (5)

LDHCM{a,..,b}(j) =P

i2{a,..,b}HCPFi(j)

�2⇤(|{a,..,b}|+1�i) (6)


i2{a,..,b}HCPFi(j)

�3⇤ln(|{a,..,b}|+1.01�i)(7)







10Class Foo

Class Bar 42

Class Bas -1

2 weeks

Release X

50

32

50

22

70

22

48

40

10 15

Version from

1.1.2005

Version from

15.1.2005

Version from

29.1.2005

Time

10

-1

0

10

5




CHU(i) =CX

j=1


(8)




4 , pB = 14 , pC = 1


7 ⇥log227 + 1

7 ⇥log217 + 4

7 ⇥log247 ) = 1.378. In


H 0 = �nX

k=1



HCM{a,..,b}(j) =X

i2{a,..,b}

HCPFi(j) (3)


HCPFi(j) =

⇢cij ⇥H 0

i, j ⇤ Fi

0, otherwise(4)





3. (3) cij = 1|Fi|




EDHCM{a,..,b}(j) =P

i2{a,..,b}HCPFi(j)

e�1⇥(|{a,..,b}|�i) (5)

LDHCM{a,..,b}(j) =P

i2{a,..,b}HCPFi(j)

�2⇤(|{a,..,b}|+1�i) (6)


i2{a,..,b}HCPFi(j)

�3⇤ln(|{a,..,b}|+1.01�i)(7)







10Class Foo

Class Bar 42

Class Bas -1

2 weeks

Release X

50

32

50

22

70

22

48

40

10 15

Version from

1.1.2005

Version from

15.1.2005

Version from

29.1.2005

Time

10

-1

0

10

5




CHU(i) =CX

j=1


(8)



Design the zen way

simplicity

clarity

uncluttered

Design right-brain slides

Design rightbrain slides

Be visual

Vision trumps all other senses

Rule #10

We have a better recall

for visual information

IRSYMCAWTFIBMKGBFBI

we are wired to pattern”—Dr. Medina“

Visual information are easier to remember

Oral

Visual

Oral &Visual

10%

35%

65%

3x6x

Source: Najjar, LJ (1998) Principles of educational multimedia user interface design (via Brain Rules by John Medina, 2008)

decoratedon’t

slides

communicationadd

values

90freshwater

%

of the

in the world is

Slide from Garr Reynolds: http://www.slideshare.net/garr/sample-slides-by-garr-reynolds

90of the

in our

%

planet isfreshwater

Inspired by www.slideshare.net/garr/sample-slides-by-garr-reynolds

http://www.slideshare.net/garr/sample-slides-by-garr-reynolds


ice

Source: SCAR

iceInspired by www.slideshare.net/garr/sample-slides-by-garr-reynolds

90 of the ice in our planet %

Antarcticais in




Antarctic

of the world’s freshwater80

Source: SCAR

%

is ice in the


80 of our planet’s freshwater%

Antarcticis ice in the




Eat onlyuntil80% full

Bring your message visually

foxy sad happy

angryundecidedsmiley

Use faces

Find beauty

Slide from Christina Quick : http://www.slideshare.net/ChrisQuick/new-rules-for-power-point-presentations

http://www.slideshare.net/ChrisQuick


Dramatize




2% of theworld

wealth50%owns

of the

Use metaphorical image




The poorest 50% of the world

owns 1% of the wealth




66% of Americansare obese or overweight.

All adults (66%)

Women 65 million (62%)

Men 69 million (71%)

134 million

OECD Factbook 2007

Be provocative


Text and fonts

No more than 2-3 types

Text and fonts

use color and size to build contrast

Text and fonts

Blinking, sparkling, or twirling text is just not cool

Rotation can make the slide more

interesting, but don’t overdo it

Text and fonts

Reduce to the maxText is redundant

People cannot listen andread at the same time

Simplicity means the achievement of maximum effect with minimum means

“

—Dr. Koichi Kawana”

Use quotes

Design principles

11 po

int

per

slid

e

Contrast

Repetition

Alignment

Proximity

Design principles

Contrast

R e p e t i t i o n

Repetition examples

Repetition of design elements gives a

cohesive look

Slide from Jesse Desjardins: http://www.slideshare.net/jessedee/steal-this-presentation-5038209

http://www.slideshare.net/jessedee/steal-this-presentation-5038209


Alignment

Proximity

no templatesor

the following one

Rule of third

Use color properly

Black: is all about elegance

White: is about trust

Apply a contrasting color palette

Choose with tools

http://kuler.adobe.com

www.colorschemer.com

http://www.colorschemer.com




















Do not forget that 7-10% ofpeople are color-blind

Use images properly

Do not useUgly clip art

Small images

Watermarked images

Distorted images

Go full quality

Have a neutralbackground

Make images transparent

oruse

Where to get good images?

www.istockphoto.com (pay)

http://www.istockphoto.com

http://www.istockphoto.com


google images


sxc.hu (free)

Do not omit the credits

Image from irishfireside.com

Be consistentStick to your settings

avoid clutter: make more slides

a slide costs 0$

use empty space

This is different from...

... this

Show the data

A must see:www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen.html

http://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen.html




Make the data memorable

2005 2007 2008

11M

9M

2M

World of Warcraft users worldwide

Not memorable

1.4 times the swiss population

World of Warcraft users worldwide

Facebook users

800Mil l ions

Not memorable

307M

800M

1,170M

1,333M

World most populated countries

800M

iPod capacity

5 GB

vs

1,000 songs

Break the rules, but do it sparingly

Slide from Eduardo S. de la Fuente: http://www.slideshare.net/eduardo.delafuente/the-art-of-presentation-following-the-zen-path-why

Some before/after examplesby presentation guru Garr Reynolds

before

after

Slide from Garr Reynolds: www.slideshare.net/garr/sample-slides-by-garr-reynolds



before

after after




before

after




RehearseRehearseRehearseRehearse



Spend some time in the light table view

• show your passion

Show your passion

Introduce yourself

Start strong

Be confident

Keep it shortAudience attention steadily drops after 10 minutes

Minutes of class time

10 20 30 40 50

High

Low

Attention

The 10-minute rule

Source: www.brainrules.net/attention

Source: www.brainrules.net/attention

The 10-minutes rule

Attention

Minutes of class time

at each 10-minute markto regain attention

do something

emotionally relevant

End on a high note

Move away from the podium

audience

youlaptop

screen

• use the presenter view

Use a remote

Make

pauses

• do not apologize

Do notapologize

Use Keynote presenter display

actually no

BRem

embe

r th

e B

key

Make good eyecontact

• keep the lights on

Keeplightson

Be prepared

Check the beamer beforehand

55%7% 38%

Body language matters

content voicebody language

Be slightly more elegant than the audience


Always recap

Share your work

www.slideshare.net

speakerdeck.com

http://www.slideshare.net

http://www.slideshare.net

http://www.ted.com

http://www.ted.com

www.ted.com

Resources

www.garrreynolds.com

http://www.ted.com

http://www.ted.com

http://www.ted.com

http://www.ted.com

Brain RulesTakeaways & Quotes

from Dr. John Medina’s

What all presenters need to know

A presentation (of sorts)

by Garr Reynolds

Sample slidesHere are a few before/after slides

Garr Reynolds

http://slidesha.re/fausgs

http://slidesha.re/8Ykmry

http://slidesha.re/3mMo3c

http://slidesha.re/i8QMa

Credits

SEMINAR (I)

Alberto de Vega Eduardo S. de la Fuente

Zen Rocks by Lane Pierce

Following the ZEN path

http://slidesha.re/17P2Hh





http://www.slideshare.net/garr/brain-rules-for-presenters

http://www.slideshare.net/garr/brain-rules-for-presenters

http://www.slideshare.net/ChrisQuick/new-rules-for-power-point-presentations

http://www.slideshare.net/ChrisQuick/new-rules-for-power-point-presentations



Marco D’AmbrosComputer science researcher

Marco earned a PhD in Informatics from the University of Lugano (Switzerland), and MSc degrees from both Politecnico di Milano (Italy) and the University of Illinois at Chicago (USA).

His research interests lie in software engineering, software evolution, and software visualization. He authored more than 30 technical papers, and is the creator of several software visualization and program comprehension tools.

Marco is passionate about presentations: He distilled his experience, gained by giving more than 30 talks at international conferences, in this presentation.

www.linkedin.com/in/dambros

www.slideshare.net/marcodambros

twitter.com/marquitodambros

www.inf.usi.ch/phd/dambros/ On the Evolution ofSource Code andSoftware Defects

amzn.com/1460953568

http://www.linkedin.com/in/dambros

http://www.linkedin.com/in/dambros

http://www.slideshare.net/marcodambros

http://www.slideshare.net/marcodambros

http://twitter.com/marquitodambros

http://twitter.com/marquitodambros

http://www.inf.usi.ch/phd/dambros/

http://www.inf.usi.ch/phd/dambros/

http://amzn.com/1460953568

http://amzn.com/1460953568

presentation tips

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