Are justification and hyphenation good or bad for the reader? Leyla - - PowerPoint PPT Presentation

Are justification and hyphenation good or bad for the reader?

Leyla Akhmadeeva Rinat Gizatullin Boris Veytsman

Bashkir State Medical Univeristy, Ufa, Russia George Mason University, USA

TUG’2016

Introduction

We all used to consider justified text “better”. Compare:

As any dedicated reader can clearly see, the Ideal of practical reason is a representation

• f, as far as I know, the things in them-

selves; as I have shown elsewhere, the phe- nomena should only be used as a canon for

• ur understanding. The paralogisms of prac-

tical reason are what first give rise to the ar- chitectonic of practical reason. As will easily be shown in the next section, reason would thereby be made to contradict, in view of these considerations, the Ideal of practical reason, yet the manifold depends on the phenomena. Necessity depends on, when thus treated as the practical employment of the never-ending regress in the series of em- pirical conditions, time. Human reason de- pends on our sense perceptions, by means

• f analytic unity. There can be no doubt that

the objects in space and time are what first give rise to human reason. As any dedicated reader can clearly see, the Ideal of practical reason is a representation of, as far as I know, the things in themselves; as I have shown elsewhere, the phenomena should only be used as a canon for our understanding. The paralogisms of practical reason are what first give rise to the architectonic of practical reason. As will easily be shown in the next section, reason would thereby be made to contradict, in view of these considerations, the Ideal of practical reason, yet the manifold depends on the

• phenomena. Necessity depends on, when

thus treated as the practical employment

• f the never-ending regress in the series of

empirical conditions, time. Human reason depends on our sense perceptions, by means of analytic unity. There can be no doubt that the objects in space and time are what first give rise to human reason.

But is it really better for reading and comprehension?

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Experiment setup

N = 300 healthy volunteers. T wo texts, A and B. ParaT ype Cyrillic, standard L

AT

EX setup. Half volunteers get A justified, B ragged. Another half gets A ragged, B justified.

• 1. Each volunteer reads text A, and then text B.
• 2. The speed of reading is measured.
• 3. Volunteers answer 10 multiple choice questions about each

text (immediate test).

• 4. After 60 min the test is taken again (delayed test).

Comparisons: speed of reading, immediate test, delayed test.

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Direct comparisons and t-test

Speed of reading, J − R

• −100

50 200 Words per min

No difference (p = 0.12)

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Immediate test, J − R

• −4

2 Correct answers

No difference (p = 0.17)

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Delayed test, J − R

• −4

2 Correct answers

Ragged is better (p = 0.001). Mean −0.26, standard deviation 1.36.

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Problems with t-test

Individual differences are large. Differences between texts’ diffi- culty level are smaller but essential. T ypographic differences are

• small. We use paired tests, but

1000000000000000000 − 1000000000000000000 + .00001 =?

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Problems with t-test

Individual differences are large. Differences between texts’ diffi- culty level are smaller but essential. T ypographic differences are

• small. We use paired tests, but

1000000000000000000 − 1000000000000000000 + .00001 =? Bayesian statistics: Bayesian modeling:

• 1. Construct a model of the effect
• 2. Start with broad assumption of the parameters
• 3. Using Bayesian theorem get updated values of model

parameters.

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Bayesian statistics

Model

Speed of reading: a linear model V = Vindividual + (Correction if text B) + (Correction if ragged)

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Bayesian statistics

Model

Speed of reading: a linear model V = Vindividual + (Correction if text B) + (Correction if ragged) Cannot do the same with probability to answer a question p: we can get p > 1 or p < 0.

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Bayesian statistics

Model

Speed of reading: a linear model V = Vindividual + (Correction if text B) + (Correction if ragged) Cannot do the same with probability to answer a question p: we can get p > 1 or p < 0. Let us introduce log odds: L = ln

• p

1 − p

• Linear model again

L = Lindividual + (Correction if text B) + (Correction if ragged)

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Method

Gaussian prior for the individual contribution and wide uniform priors for the other parameters. Multiple Chain Monte Carlo simulations (16 chains with 10,000 sam- ples each) for each model.

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Results: speed of reading

60 70 80 90 0.00 0.02 0.04 0.06 0.08 0.10

• Individ. diff

Words per min 5 10 15 20 25 30 35 0.00 0.04 0.08 0.12

A−B

Words per min −5 5 10 15 20 0.00 0.04 0.08 0.12

J−R

Words per min 95%

Justified is faster: about 7 words per minute difference.

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Results: immediate test

0.6 0.7 0.8 0.9 1.0 1.1 1.2 1 2 3 4 5

• Individ. diff

Log odds −0.2 0.0 0.2 0.4 1 2 3 4

A−B

Log odds −0.4 −0.2 0.0 0.2 1 2 3 4

J−R

Difference J−R, log odds 95%

A suggestion that ragged is better. . .

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Results: delayed test

0.8 1.0 1.2 1.4 1 2 3 4 5

• Individ. diff

Log odds −0.2 0.0 0.2 0.4 1 2 3 4

A−B

Log odds −0.6 −0.4 −0.2 0.0 1 2 3 4

J−R

Difference J−R, log odds 95%

Ragged is definitely better. . . On a 100 questions test with 90% correct answers the difference would be about 4 points.

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Discussion

• 1. What does this tell us about “whole word” reading?
• 2. Is the effect culture dependent?
• 3. What is the role of Cyrillic script? Does this work with Latin

script?

• 4. Does the effect depend on the language proficiency?

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Conclusions

• 1. We have a quite strange result: ragged is better for reading

comprehension, but slightly worse for speed of reading.

• 2. We still do not quite understand the meaning and implications
• f this result.

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