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Slovak University of Technology in Bratislava
Faculty of Informatics and Information Technologies
FIIT-5212-52606
Lenka Kutlíková
EVALUATION OF INTRUSIVENESS OF NOTIFICATIONS
Bachelor thesis
Degree Course: Informatics
Field of study: 9.2.1 Informatics
Place of development: Institute of Applied Informatics, FIIT STU Bratislava
Supervisor: Ing. Andrej Fogelton
May 2015
Assignment
Evaluation of intrusiveness of notifications
Computer users often suffer from eye conditions caused by low eye blink rate. An application
is being developed as part of project Eyeblink which will remind people to blink more often.
The frequency of notifications is crucial because of a goal to avoid distraction during work.
Analyze research on human computer interaction about notifications with more frequent
use. Focus on different types of notifications and the type of response required from the
user. Suggest different models of notifications and test them on a representative sample of
users. Users will assess subjective intrusiveness of individual types of notifications during
their work. Objective testing will be based on the specific task which will be done with and
without notifications with time blink measured.
ANOTÁCIA
Slovenská technická univerzita v Bratislave
FAKULTA INFORMATIKY A INFORMACNÝCH TECHNOLÓGIÍ
Študijný odbor: Informatika
Autor: Lenka Kutlíková
Bakalárska práca: Vyhodnocovanie rušivosti notifikácií
Vedúci bakalárskej práce: Ing. Andrej Fogelton
máj, 2015
Bakalárska práca sa zaoberá vyhodnocovaním rušivosti notifikácií. Pri každonennej práci
s pocítacom sa stretávame s rôznymi typmi upozornení, ktoré môžu mat’ rušivý efekt. Ich
dôsledkom môže byt’ strata pozornosti alebo robenie chýb pri práci. Ciel’om bakalárskej
práce je otestovat’ rôzne typy upozornení z hl’adiska rušivosti a efektivity. Notifikácie sú
zamerané na zvýšenie frekvencie žmurkania.
Zníženie frekvencie žmurkania spôsobuje ocné problémy. Úvod tejto práce je zameraný
na prejavy a prevenciu Syndrómu pocítacového videnia (angl. Computer vision syndrome),
kde patrí aj Syndróm suchého oka (angl. Dry eye syndrome). Analýza sa zaoberá štúdiami v
súvislosti s upozornovaním na žmurkanie. Ukazuje aj súvis medzi žmurkaním a zat’ažením
pamäte. Sú v nej spomenuté aj dostupné softvérové a hardvérové riešenia. V závere analýzy
sa nachádza zhodnotenie súcasného stavu danej problematiky.
ANNOTATION
Slovak University of Technology Bratislava
FACULTY OF INFORMATICS AND INFORMATION TECHNOLOGIES
Degree Course: Informatics
Author: Lenka Kutlíková
Bachelor thesis: Evaluation of intrusiveness of notifications
Supervisor: Ing. Andrej Fogelton
2015, May
The bachelor thesis focuses on evaluation of intrusiveness of notifications. During computer
work different types of notification are used. Intrusive effect can be caused by them. These
notifications can result in loss of attention and making mistakes. The goal of this bachelor
thesis is to test different types of notification in terms of intrusiveness and effectiveness. No-
tifications are focused on increase of blink rate.
Decreasing blink rate causes eye-related problems. For this reason introduction of this thesis
is focused on symptoms and prevention of Computer Vision Syndrome which include Dry
Eye Syndrome. Analysis describes studies related to blinking reminder. It shows the relation
between blinking and the memory load. Available software and hardware solutions are also
mentioned. At the end of the analysis there is a conclusion of the current state of the art.
Declaration of Honor
I honestly declare that I wrote this thesis independently under professional supervision of
Ing. Andrej Fogelton with citated bibliography.
May, 2015 in Bratislava signature
Acknowledgement
I would like to thank my supervisor Ing. Andrej Fogelton for his guidance, patience and
effort. He was always supportive during work on this thesis and his advices were very useful
to me.
Contents
1 Introduction 1
1.1 Computer Vision Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1.1 Symptoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1.2 Prevention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Notifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 State of The Art 5
3 Methodology 9
3.1 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.2 Task Categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.3 Types of Notification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4 Evaluation of Experiment 15
4.1 Evaluation of Intrusiveness . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.2 Evaluation of Effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . 17
4.3 Subjective Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
5 Conclusion 25
A Technical Documentation 29
B User Guide 33
C Resumé 35
D DVD Contents 39
Contents Lenka Kutlíková
ii
List of Figures
3.1 Example of reading comprehension task. . . . . . . . . . . . . . . . . . . . 10
3.2 Example of image comprehension task. . . . . . . . . . . . . . . . . . . . 11
3.3 Example of counting task. . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.4 Example of adding task in Slovak language. . . . . . . . . . . . . . . . . . 12
3.5 Example of rewriting task. . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4.1 Correctness of answers of reading comprehension task. . . . . . . . . . . . 16
4.2 Correctness of answers of image comprehension task. . . . . . . . . . . . . 16
4.3 Correctness of answers of counting words task. . . . . . . . . . . . . . . . 17
4.4 Correctness of answers of adding task. . . . . . . . . . . . . . . . . . . . . 18
4.5 Error rate during rewriting task. . . . . . . . . . . . . . . . . . . . . . . . 18
4.6 Correctness in general. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.7 An average blink rate. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.8 An average blink rate for single type of tasks. . . . . . . . . . . . . . . . . 20
4.9 An average response time in general in seconds. . . . . . . . . . . . . . . . 21
4.10 An average response time for single type of tasks in seconds. . . . . . . . . 21
4.11 An average response rate in general. . . . . . . . . . . . . . . . . . . . . . 22
4.12 An average response rate for single type of tasks. . . . . . . . . . . . . . . 23
4.13 An average number of ratings. . . . . . . . . . . . . . . . . . . . . . . . . 23
List of Figures Lenka Kutlíková
iv
List of Tables
1.1 Mean number of correct fields entered per minute after interruption [Storch
1992] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1 Results of the stimulus user study [Crnovrsanin et al. 2014] . . . . . . . . . 7
2.2 Results of response time [Crnovrsanin et al. 2014] . . . . . . . . . . . . . . 7
2.3 An average difference in time of the interrupted task and uninterrupted one.
[Bailey et al. 2000] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
4.1 An average blink rate for single type of tasks. . . . . . . . . . . . . . . . . 20
4.2 An average response time for single type of tasks in seconds. . . . . . . . . 21
4.3 An average response rate for single type of tasks. . . . . . . . . . . . . . . 22
List of Tables Lenka Kutlíková
vi
Chapter 1
Introduction
Nowadays computers are integral parts of our lives. Many people spend several hours a dayworking with computer. Due to long-term staring at Video Display Terminals (VDT) peo-ple are experiencing ocular symptoms like blurred vision, eyestrain, dry eyes or headaches[Blehm et al. 2005]. These symptoms are collectively called Computer Vision Syndrome(CVS). They can be caused by decreasing of eye blink rate during work with computer.CVS can be alleviated by use of visual stimulus (notifications) to increase the user blinkrate. Some notifications can be aggressive or intrusive and get attention from work. For thisreason ordinary tasks can take more time and people are less effective or even make moremistakes. From this point of view non-intrusiveness of notifications is crucial.
1.1 Computer Vision Syndrome
CVS is described as a group of eye and vision-related problems results from long-term useof computers1.
1.1.1 Symptoms
Symptoms are categorized into several groups [Blehm et al. 2005]:
• Astenophic:
– eyestrain,
– tired eyes,
– sore eyes.
• Ocular surface-related:
– dry eyes,
– watery eyes,
– irritated eyes,
1http://www.aoa.org/patients-and-public/caring-for-your-vision/protecting-your-vision/computer-vision-syndrome?sso=y [last access: October 2014]
Chapter 1. Introduction Lenka Kutlíková
– contact lens problems.
• Visual:
– blurred vision,
– slowness of focus change,
– double vision,
– Presbyopia.
Eyestrain is described as a non-specific ocular discomfort.
Blurred vision - loosing sharpness of vision.
Presbyopia is characterized as a difficulty of focusing on close objects.
Tired, sore, dry and irritated eyes are caused by intense use of eyes. People feel discomfortand unpleasant feelings in eyes.
Watery eyes occurs when the tears flow out from the eyes. It can be caused by excess tearsor blocked tear duct.
Contact lens problems can be described as higher sensibility to ocular discomfort2.
Dry Eye Syndrome
Dry eye syndrome (lat. keratoconjunctivitis sicca)3 is part of CVS, defined as a lack ofsufficient lubrication and moisture on the surface of the eye. It occurs when the eye producessmaller amount of tears or with poor quality tears. It can be caused by faster evaporation oftears or by a damage of lacrimal glands. Common symptoms are:
• red eyes,
• dry eyes,
• blurred vision,
• contact lens problems,
• scratchiness,
• burning.
In order to maintain normal eye lubrication, a frequency of 10 to 15 blinks per minute [Blehmet al. 2005] should be preserved.
1.1.2 Prevention
In order to preserve healthy eyes several factors take place [Yan et al. 2008]:
2http://www.nlm.nih.gov/medlineplus/ency/article/003029.htm last access: October 2014]3http://www.aoa.org/patients-and-public/eye-and-vision-problems/glossary-of-eye-and-vision-
conditions/dry-eye?sso=y [last access: October 2014]
2
Chapter 1. Introduction Lenka Kutlíková
• Environmental factors – Smoke and air condition can damage the natural eye surfaceby accelerating the evaporation of tears.
• Reduced blink rate – Due to working with a computer up to 70% of people blinkconsiderable less.
• Increased exposure – Looking downwards reduces non-covered surface of the eyewhich reduces the evaporating of tears. While working with a computer, bigger surfaceof eye is exposed to evaporation.
• Sex – Generally, women have CVS symptoms more frequently than men due to morefrequent hormonal changes.
• Age – CVS is part of aging process. A lot of older people have some symptoms ofCVS due to decreased tear production.
• Medical conditions – Some of the diseases like diabetes or arthritis can cause CVSproblems. The major problems have people suffering from eye diseases.
• Medications – Certain medicines can reduce production of tears e.g. antihistamines,decongestants, blood pressure medications and antidepressants.
• Other factors – Use of contact lenses or eye surgery can also cause CVS problems.
For prevention of CVS it is important to follow good habits on computer use. There areseveral strategies to it [Yan et al. 2008]:
1. Viewing distance between eyes and monitor should be at least 50 cm.
2. Position of computer screen should be 10-20 degrees below the eye level.
3. It is recommended to maintain 20/20/20 rule. After 20 minutes of using computer, theuser should look at something 20 feat (about 6 m) away for at least 20 seconds.
4. Computer users should pay attention to lighting conditions (screen and room lighting)and screen characteristics like contrast, brightness or reflection.
5. To avoid problems with neck or back during computer use, it is recommended to followgood sitting position.
6. Users with eye problems should have regular eye exams.
7. If you work more than 3 hours a day with computer, a warm eyelid massage is recom-mended.
1.2 Notifications
Different computer programs use different types of notifications. We can divide them intotwo basic groups.
1. Notifications which need confirmation.
2. Notifications which disappear after some time without confirmation.
There are a lot of programs which need to notify people e.g. instant messaging or emailclients. The goal of notification is to get user attention. Therefore visual notifications areoften accompanied by sound. Different notifications can have different disruptive effect.
3
Chapter 1. Introduction Lenka Kutlíková
Table 1.1: Results of testing of performance after interruption. Mean number of correctfields entered per minute after interruption [Storch 1992]
Interruption form 1st minute 2nd minuteScreen 4.29 5.14Walk-in 4.71 5.57Telephone 5.14 5.29
Notifications are considered as interruption during computer use. They can be aggressiveor intrusive for people and therefore they can have negative effect on human attention. Onthe other side being interrupted is sometimes useful. Interruptions affect behavior of people.According to Zeigarnik effect people have tendency to remember better an interrupted taskthan uninterrupted one [Sasse et al. 1999].
Intrusiveness is affected by many characteristics of interruptions e.g. length, similarity tothe main task or complexity. According to [Gillie – Broadbent 1989] length of the interrup-tion have not influence to disruptive effect but similarity to the main task and complexitydoes. In contrast research of [Bailey et al. 2000] shows that similarity to the main task doesnot affect a disruption. Another characteristic is the form of the interruption. In the researchof [Storch 1992] different forms of interruptions are compared:
• Telephone call – A telephone call is made by secretary from adjacent office.
• Walk-in – An experimenter is going around the screen and asks a question.
• Screen – On-screen message is sent to the subject.
Screen interruption is the most disruptive between them. For people it is difficult to resumeinterrupted task. Number of correct fields entered after interruption is measured. As shownin Table 1.1 performance is worse in the first minute after interruption than in the secondone.
4
Chapter 2
State of The Art
Nowadays computer-related eye problems are widespread. Researchers try to find methodsto alleviate them. In this chapter we focus on studies related to this problem.
One possibility to alleviate CVS symptoms is to get regular breaks during computer work.There are some software reminders e.g. Protect Your Vision1 or Eye Pro2 which support sev-eral modes for regular breaks. Another possibility is to blink more often. There is not a lot ofhardware or software systems for this purpose. Blink Now3 is a device consisting of a smalldisplay with animation of blinking eye. It is a reminder which blinks 10 times per minute.Authors argue that it is based on the idea that a human who sees a blinking eye blinks moreoften. We did not find the study that confirm this statement. This is one way how to increasethe blink rate. One of the available software solutions is iVisionGuard4. It is a computerprogram focused on prevention of dry eyes which detects eye blinks using webcam. Basedon collected data, it evaluates degree of eye dryness. If the subject can not be detected (ithappens quite often), iVisionGuard changes the icon to red. Balloon notification (small bub-ble in the bottom right corner of the screen) is used as a blink reminder. A graph of blinkrate during a day is part of the application. Another software solution is Blinzle Digital EyeDrops5. It encourages user to blink by visual stimulus. Animation of flowing drops is usedas a notification. Purpose of this system is to ensure regular lid closure. Based on theirevaluation, by using this system, lid closure activity can be increased by 139% on average.Unfortunately intrusiveness is not measured.
According to [Holland – Tarlow 1975] blinking is related to cognitive processes. Duringmental activities like solving arithmetic tasks or daydreaming blink rate is low. Blink occurstogether with cognitive change. During solving arithmetic problems people are not blinkingat all. In the moment of achieving solution blink occurs. Another example is reading. Mostblinks occur at marks of punctuation and between fixations. In contrast, emotional excite-ment and frustration are related to high blink rate.
Another research of [Holland – Tarlow 1972] shows that different mental states have dif-
1http://www.protectyourvision.org/ [last access: November 2014]2http://classlesoft.in/eye-pro [last access: November 2014]3http://www.blinknow.co.uk/ [last access: October 2014]4http://www.ivisionguard.com/ [last access: November 2014]5http://blinzle.com/en [last access: November 2014]
Chapter 2. State of The Art Lenka Kutlíková
ferent blink rate. Blinking is affected by changes in mental load. There are two studiesrequiring concentration. Non-visual tasks are used. In the first study subjects have to re-member series of numbers of 4, 6 or 8 digits. In the second one, they have to sum seventwo-digit numbers. Both studies confirm the statement that during high mental load blinkrate is low and vice versa. Relation between blinking and incorrect task is also showed.Blink rate is higher when answers are incorrect. Possible explanation is loss of memory loadwhich result in increase of blinking.
Researchers try to find different ways to get people blink more often. The prototype sys-tem monitoring blink rate have been presented in the research of [Crnovrsanin et al. 2014].If the subject does not blink in a while, system triggers visual stimulus to get the subjectto blink. Four types of blink stimulus: screen blurring, screen flashing, border flashing andpop-up window were designed.
Some experiments related to this problem were conducted. First, they were interested inmedia type with the lowest blink rate. 13 participants (8 males, 5 females) who work withcomputer on average 8 hours per day participated the media type user study. Duration of thestudy is from 20 to 30 minutes for each subject. The experiment consisted of six tasks, two(active and passive) for each media type (video, image and text). Passive text task consistsof reading of paragraphs from Wikipedia. In contrast, active text task consists of text on theleft side of the screen and related questions on the right side. Active text task requires moreattention because the subject has to find answers in the text so move with eyes from the leftto the right and vice versa. Passive image task is a memory test. Several images are shownto people for 30 seconds and afterward, the right images from a collection of 20 images haveto be chosen. Active image task consists of finding differences between two images. Passivevideo task represents watching a presentation and the active video task watching an actiontrailer [Crnovrsanin et al. 2014].
Research of [Crnovrsanin et al. 2014] shows that there is a significant difference betweenactive and passive image task. Active image task has lower blink rate than the passive im-age task and also the lowest between the others. Between text and video tasks there is nosignificant difference. Second, four types of notifications were designed to analyze which isthe best suitable one. Participants (24-33 years old) work with computer on average 8 hoursper day. One task lasts from 3 to 5 minutes. Duration of this study is approximately 30minutes. For blink detection they have created prototype system which implement the algo-rithm of [Divjak Majtaz 2009]. Blinks are detected using a webcam. The prototype countsdouble-blink as one blink. For better accuracy blinks are counted manually from recordedvideos. Average blink rate is 10-15 blinks per minute [Blehm et al. 2005]. To keep this countof blinks, it is needed to notify people every 4 seconds. Constant time can be unnatural forpeople and they can feel annoyed because of high frequency. Frequency of notifications haveto be sufficient to keep the eyes naturally moisturized and not disturbing users. Research of[Crnovrsanin et al. 2014] shows that the interval from 4 to 8 seconds is good enough. In thisstudy four types of notifications are used:
• White flash – The screen turns into white for a period of time (15ms). This periodshould be long enough to be noticed but short enough to be non-intrusive.
• Blur – Blur simulates state when the eye has lost a focus. The user has to respond witha blink to suppress the blur effect.
6
Chapter 2. State of The Art Lenka Kutlíková
Table 2.1: Results of the stimulus user study [Crnovrsanin et al. 2014]Visual stimulus Effectiveness Intrusiveness SatisfactionWhite Flash - 2.46 2.00Blur 4.31 3.46 3.69Flashing Border - 3.31 2.69Pop-up 2.62 4.38 2.69
Table 2.2: Results of response time [Crnovrsanin et al. 2014]Visual stimulus TimeWhite Flash 1.5sBlur 2.13sFlashing Border 1.69sPop-up window 2.24s
• Flashing border – Task window borders start flash from white to black to remind usersto blink. Blink is crucial to stop flashing.
• Pop-up window – Pop-up notification create a small window in the bottom right cornerof the screen. It cancels itself after some time.
Flash and blur should encourage the eye into blink, flashing border and pop-up window areonly reminders. Participants were asked to do several tasks while measuring their blink rate.If the user does not blink for a while, notification will show. After experiment people filledout a form with rating of notifications on scale from 1 to 5. Response rate (if the subjectblinks after visual stimulus or not) and response time (time between visual stimulus andblink) are also measured.
Visual stimuli are evaluated in terms of effectiveness, intrusiveness and satisfaction. Par-ticipants of experiments evaluated from 1 to 5, where 5 is very effective, non-intrusive andvery satisfied. As shown in Table 2.1 there are significant differences between types of noti-fications. In terms of effectiveness Blur is the best. Flash is the least intrusive and in terms ofsatisfaction Blur is the best people’s choice. Participants have also chance to comment usednotifications. According to comments Flash is annoying, Flashing Border is less noticeablethan the Flash and position of the Pop-up window should be optional.
Response time should be as close as possible to 0s. As shown in Table 2.2 flash has the bestresults and pop-up the worst. Response rate should be as high as possible. Result of theexperiment from the best to the worst is [Crnovrsanin et al. 2014]:
1. blur,
2. flashing border,
3. pop-up window,
4. flash.
Notifications can disrupt people during computer use. As a result of interruption duringwork people can be slower and less effective or even make more mistakes. In the research of[Bailey et al. 2000] effects of interruptions on task performance are measured. Time on taskwith interruptions and without them are measured. An experiment with six different task
7
Chapter 2. State of The Art Lenka Kutlíková
Table 2.3: An average difference in time of the interrupted task and uninterrupted one. [Bai-ley et al. 2000]
Task category TimeAdding 6.3377sCounting 8.890sImage comprehension 3.431sReading comprehension 2.556sRegistration 1.249sSelection 8.417s
categories: adding, counting, image comprehension, reading comprehension, registrationand selection was conducted. Two types of interruptions of approximately 10-30s durationwere used: reading comprehension and stock decision. Reading comprehension consistsof short text and three optional titles. The subject has to choose the most suitable title.In stock decision interruption task the subject has to analyze the scenario and choose oneof five options. 25 participants (15 male, 10 female) with at least one year of computerexperience have to complete 3 tasks (without interruption, with stock decision interruptionand with reading comprehension interruption) per each of 6 categories (18 tasks in total).According to research of [Bailey et al. 2000] an interrupted task take more time to completethan non-interrupted one within the same task category. As shown in Table 2.3 there is asignificant difference between time of the interrupted task and time of the uninterrupted one.Small difference at registration task is probably caused by low memory load. Tasks withgreater memory load have greater disruptive effect in connection with task performance.This hypothesis is only partially confirmed.
Nowadays there are some software systems for prevention or alleviation CVS symptoms.Some of them are only reminders for regular breaks. The others detect blink rate. It isneeded to create the system which would detect blinks and trigger the stimulus only in thecase of need. Use of stimulus can have disruptive effect on work. Therefore non-intrusivenotifications are crucial for this system. In our experiments effectiveness and also intrusive-ness of visual stimuli are measured. In contrast of previous researches we will consider alsocorrectness of tasks in the intrusiveness evaluation.
8
Chapter 3
Methodology
In order to reach the best results in increase of blink rate, different types of notifications aredesigned. In terms of effectiveness and intrusiveness, notifications are tested in two separateexperiments with people.
3.1 Experiments
Experiments are focused on people who work with computer at least 5 hours per day. Dur-ing work people are notified with different types of notifications. After testing they fill in ashort form which contains questions about notifications. People will assess types of notifi-cations on a scale from 1 to 5 in terms of intrusiveness. Based on data from questionnairesintrusiveness will be evaluated.
• Long-term experiment – During ordinary work with computer a computer programeyeBlink detects blinking using webcam and displays notifications if it is needed. Re-sponse rate (if the subject blinks after visual stimulus or not) and response time (timebetween visual stimulus and blink) are measured. Based on this data effectiveness ofnotification is evaluated . Duration of this experiment is about 12-24 hours. Every typeof notifications is tested at least 4 hours.
• Short-term experiment – Participants in short-term experiment are asked to do severaltasks. There are five types of task: reading comprehension, image comprehension,adding, counting words and rewriting. During filling test tasks people are notifiedwith different types of notification: blur, pop-up, decreasing the screen brightness andblack flash. There are 20 tasks with notifications and 5 without them. The subjectdoes not have to do all of them. He can choose the type of task and notification. It isobligatory to do at least 2 tasks (without and with chosen notification). Response timeand response rate are measured. Evaluation consists of comparing the time and qualityof the finished tasks.
3.2 Task Categories
Different types of task will be used in short-term experiment. Duration of one single task isabout 5 minutes. There are 5 types of task:
Chapter 3. Methodology Lenka Kutlíková
Precítajte si daný text a odpovedzte na otázky:Experimentálny liek na vírus príbuzný ebole zachránil opice
BRATISLAVA. Na opiciach to zabralo. Šestnást’ makakov rézus rozdelili do niekol’kýchskupín a postupne ich nakazili smrtel’ným vírusom Marburg, príbuzným eboly. Prežili všetky,ktorým vedci potom podali experimentálny liek – aj tie, ktoré ho dostali až tri dni po infekcii. Všetkyneliecené zvieratá zomreli. Látku, ktorá funguje na rovnakom princípe ako testovaná TKM-Marburg,má kanadská farmaceutická spolocnost’ Tamira aj pre prípad nákazy ebolou. Na l’ud’och prebehliiba testy bezpecnosti a tie americké úrady v lete zastavili. Výskum v magazíne Science TranslationalMedicine ukazuje, ako a preco experimentválny liek na Marburg zabral. Kl’úcom je napadnút’ RNAvírusu v nakazenej bunke a zablokovat’ jej gény - a to by fungovalo aj v prípade eboly. “Týmto sazacína krok do skutocného sveta terapie,” hovorí pre Nature virológ Gene Olinger. “Nielen akésiliecenie následkov.”
1. Aký bol pocet opíc, na ktorých testovali nový liek?2. Ako sa volal vírus, ktorým nakazili tieto opice?3. V magazíne Science Translational Medicine tím odborníkov vysvetlil ako vyliecit’ smrtel’nú
chorobu – ebolu.– áno– nie
4. Všetky opice dostali lieky v rovnaký den.– áno– nie
Figure 3.1: Example of reading comprehension task in Slovak language. Questions arecreated based on the text2.
• Reading comprehension – A short paragraph (120-150 words) is presented to the sub-ject. The main task is to read the text and answer four questions related to it. Twoquestions are true/false type. In most cases, one question must be answered by wordand one by number. Example is shown on Figure 3.1.
• Image comprehension – Following the principles of reading comprehension task, thistype of task is structured as follows. The displayed image will be a graph associatedwith four questions upon it. Two questions are true/false type, the other two have to beanswered by numeric value. Example is shown on Figure 3.2.
• Counting words – The task (Figure 3.3) consists of one table which contains the set of36 words in 6×6 table. These words are chosen from the set of 6 words and randomlypositioned in the table. The task of the subject is to count words that match with theselected word. Then the subject enters the count into the text field.
• Adding – As we can see on Figure 3.4 the task contains two types of adding. The firstone is classic adding of two numbers where each number consist of three digits. Thesubject enter the correct sum into the text field which is positioned on the right sideof the math problem. The second part of this task is adding of four numbers whereeach number consist of four digits. The numbers are right aligned in a 4×1 table. Thesubject has to add these numbers and enter the correct sum into a field under numbers.Each exercise consists of six math problems of the first type and two math problems
2http://tech.sme.sk/c/7344888/experimentalny-liek-na-virus-pribuzny-ebole-zachranil-opice.html#ixzz3B496GTgn [last access: October 2014]
3http://slovak.statistics.sk/ [last access: December 2014]
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Chapter 3. Methodology Lenka Kutlíková
Prezrite si graf a odpovedzte na otázky:
1. Aká bola cena benzínu v poslednom týždni?2. Aká bola cena benzínu v prvom týždni?3. V štyroch týždnoch bola rovnaká cena benzínu.
– áno– nie
4. Najvyššia cena benzínu bola 3. týžden.– áno– nie
Figure 3.2: Example of image comprehension task3in Slovak language.
Spocítajte výskyt slova: Rušivost’Efektivita Rušivost’ Spokojnost’ Notifikácia Žmurknutie UpozornenieEfektivita Efektivita Žmurknutie Rušivost’ Notifikácia Spokojnost’Žmurknutie Notifikácia Efektivita Notifikácia Žmurknutie Rušivost’Žmurknutie Spokojnost’ Notifikácia Efektivita Upozornenie UpozornenieEfektivita Upozornenie Upozornenie Žmurknutie Rušivost’ Žmurknutie
Pocet výskytov: 4
Figure 3.3: Example of counting task. The task is created in Slovak language.
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Chapter 3. Methodology Lenka Kutlíková
Vypocítajte dané príklady:321 + 223 = 578 + 167 =225 + 345 = 356 + 245 =167 + 445 = 578 + 412 =
2222367524921256
2681975223563451
Figure 3.4: Example of adding task in Slovak language.
Prepíšte daný text:Krátkozrakost’ alebo myopia (z gréctiny) je refrakcná chyba zraku, pri ktorej sa lúce svetla usmernenéocnou šošovkou zbiehajú už pred sietnicou, a na sietnici tak nevzniká ostrý obraz. Jej prejavom je zláviditel’nost’ postihnutého na vzdialené predmety. Napravuje sa okuliarmi so šošovkou - rozptylkou.Opakom krátkozrakosti je d’alekozrakost’. Dalekozrakost’ je chyba oka, pri ktorej sa lúce svetlausmernené ocnou šošovkou zbiehajú až za sietnicou, preto na sietnici nevzniká ostrý obraz. Oko min-imálne odchýlky dokáže ciasto cne kompenzovat’ akomodáciou šošovky (zmenou mohutnosti). Taktopostihnutý clovek zle vidí blízke predmety, naopak celkom dobre vidí predmety vzdialené. Chyba sadá napravit’ použitím spojnej šošovky (okuliare alebo ocné šošovky). Opakom d’alekozrakosti jekrátkozrakost’. Chyba sa dá riešit’ aj operáciou.
Figure 3.5: Example of rewriting task4in Slovak language.
of the second type.
• Rewriting – Rewriting task (Figure 3.5) consists of long text on the left side of thewindow and empty text field on the right side. The main task of the subject is torewrite the most of the text during the given time. Number of characters per minuteand number of mistakes in the rewritten text are measured.
In these tasks several parameters will be evaluated. Number of finished tasks and number ofcorrect answers are measured in all types of task except the rewriting task. Time of one task ismeasured with and without notifications. Measured times are compared in order to measureintrusiveness. Evaluation of rewriting task is different in measured variables. Number ofcharacters per minute and number of mistakes in the rewritten text are measured in task withand without notifications. In order to find out if the subject does more mistakes or writes lesscharacters per minute these parameters are compared and evaluated.
3.3 Types of Notification
Four types of notification are used:
• Pop-up window – The pop-up stimulus creates small window in the upper right cornerof the screen. Animation of blinking eye is presented. Blink is crucial to suppress theeffect.
• Blur – If the subject does not blink for a while, the screen starts to blur. To suppress ablur effect the subject has to blink.
4http://sk.wikipedia.org/wiki/Kr%C3%A1tkozrakos%C5%A5 [last access: December 2014]
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Chapter 3. Methodology Lenka Kutlíková
• Decreasing screen brightness – The screen brightness slowly decrease to the half ofthe current value during 5 seconds. If the subject does not blink screen brightnessstarts to increase to the initial value. If the subject blinks screen brightness is set to theinitial value immediately.
• Black flash – The screen turns into black for a period of time (100ms). It is similar tothe state during a blink. A subconscious blink can be caused by this type of stimulus.
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Chapter 3. Methodology Lenka Kutlíková
14
Chapter 4
Evaluation of Experiment
An experiment is focused on measuring the effectiveness and the intrusiveness of suggestednotifications. The main goal of the experiment is to find out the best way to notify people toblink. Subjective assessment is also taken into consideration.
Eight university students from 20 to 25 years old are tested. All of them are advancedcomputer users and usually spend several hours per day working with computer.
Participants choose the type of task offered from five possible (reading comprehension, im-age comprehension, counting words, adding, rewriting). First the task without notificationtakes place to measure the blink rate. Then participants can choose the type of notificationoffered from four possible (pop-up window, black flash, decreasing screen brightness, blur)and continue with the task they choose in the first step. Testing of one type of task with allnotifications takes 25 minutes. If someone wants to do all possibilities an experiment takes125 minutes.
4.1 Evaluation of Intrusiveness
The main goal of this experiment is to measure the intrusiveness of notifications. Numberof correct answers and number of all answers are taken into consideration. In the evaluationof rewriting task a number of characters and an edit distance are considered. Edit distance isthe minimum number of editing operations: insertion, deletion and substitution1.
As shown in Figure 4.1 the most intrusive notification during reading comprehension taskis the blur. Correctness of answers decreased approximately by 10%. It can be caused byloosing position in the text because of visual interruption. It is possible that during findingthe last position in the text participants blink more often.
Evaluation of image comprehension task is quite different from evaluation of reading com-prehension task (Figure 4.2). For example during testing with pop-up window people achievebetter results as during testing without any notifications. Three of four types of notificationobtained better results than testing without them. This finding can be example of Zeigarnikeffect (people have tendency to remember better an interrupted task than uninterrupted oneSasse et al. [1999]).
1https://web.stanford.edu/class/cs124/lec/med.pdf [last access: May 2015]
Chapter 4. Evaluation of Experiment Lenka Kutlíková
Figure 4.1: Correctness of answers of reading comprehension task.
Figure 4.2: Correctness of answers of image comprehension task.
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Chapter 4. Evaluation of Experiment Lenka Kutlíková
Figure 4.3: Correctness of answers of counting words task.
As shown in Figure 4.3 and Figure 4.4 the evaluation of counting task and adding is similar.Correctness of answers are decreased by all types of notification. For counting task the mostintrusive notification is black flash. Correctness is decreased by approximately 25%. Foradding task all types of notification have comparable results.
As shown in Figure 4.5 the biggest error rate is caused by the blur notification. The blur is themost intrusive notification again in this task. Making mistakes or rewriting less charactersare caused by all types of notification.
Figure 4.6 shows a general results of the intrusiveness of notifications. All types of tasksare taken into consideration together excluding rewriting. In general black flash obtained theworst results so participants make the most mistakes during testing with black flash notifica-tion.
4.2 Evaluation of Effectiveness
The other goal of this experiment is to measure the effectiveness of notifications. Threeparameters are measured: response time (time between notification and blink), response rate(if the subject blinks or not) and blink rate (number of blinks per minute). As shown in Figure4.7 all types of notifications are effective in some way because all of them considerablyincrease the blink rate. An average blink rate without notification is 7.84. People shouldblink from 10 to 15 times per minute. This result confirms the statement that during computeruse people blink considerably less. The most effective notification is the blur improving theblink rate approximately by 10 blinks per minute. The least effective is black flash with anaverage 11.49 blinks per minute. Pop-up window and the decreasing screen brightness arecomparable in this way with approximately 15 blinks per minute. This value is suitable foreye health.
17
Chapter 4. Evaluation of Experiment Lenka Kutlíková
Figure 4.4: Correctness of answers of adding task.
Figure 4.5: Error rate during rewriting task.
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Chapter 4. Evaluation of Experiment Lenka Kutlíková
Figure 4.6: Correctness in general.
Figure 4.7: An average blink rate. All types of tasks are considered.
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Chapter 4. Evaluation of Experiment Lenka Kutlíková
Table 4.1: An average blink rate for single type of tasks.Notification Reading c. Image c. Counting Adding RewritingWithout notification 7.2 7.37 7.85 11.45 5.27Pop-up window 16.32 15.16 18.13 13.4 12.87Black flash 8.52 13.12 16 12.5 7.87Decreasing brightness 9.96 18.16 25.33 11.1 14.4Blur 17.04 17.6 22 18.3 20.33
Figure 4.8: An average blink rate for single type of tasks.
An average number of blinks per minute for every single type of task is shown in Table4.1. There are only small differences between them. Blink rate is mostly influenced by no-tifications. There are some exceptions. For example during testing of adding task withoutnotification the blink rate is greater than during other types of task. It can be caused byneeding more concentration for adding than for other tasks. During counting task with no-tification of decreasing screen brightness people blink considerably more. It is possible thatpeople loose their attention and they have to count again from the beginning.
As shown in Figure 4.9 all notifications excluding pop-up window has an average responsetime up to 2 seconds. During testing with pop-up window an average response time is 3.36seconds.
Figure 4.10 shows an average response time for every task separately. Exact values we cansee in Table 4.2. Interesting result is response time of 5.70 seconds for rewriting task withpop-up notification.
As shown in Figure 4.11 the most successful notification is pop-up window. It is because thistype of notification do not disappear until participant blinks. Response rate of this type ofnotification is still 100% but results of response time is worse than other notifications. Theworst results has black flash with an average 52.75% response rate.
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Chapter 4. Evaluation of Experiment Lenka Kutlíková
Figure 4.9: An average response time in general in seconds.
Table 4.2: An average response time for single type of tasks in seconds.Notification Reading c. Image c. Counting Adding RewritingPop-up window 2.31 3.16 2.21 4.24 5.70Black flash 1.94 1.53 1.37 1.80 1.97Decreasing brightness 1.87 2.28 1.79 1.85 1.87Blur 1.77 1.98 1.51 2.13 1.40
Figure 4.10: An average response time for single type of tasks in seconds.
21
Chapter 4. Evaluation of Experiment Lenka Kutlíková
Figure 4.11: An average response rate in general.
Table 4.3: An average response rate for single type of tasks.Notification Reading c. Image c. Counting Adding RewritingPop-up window 100% 100% 100% 100% 100%Black flash 45.23% 43.59% 77.43% 57.62% 49.37%Decreasing screen brightness 62.87% 71.03% 86.28% 65.32% 61.03%Blur 90.62% 80.88% 87.66% 65.31% 100%
In Table 4.3 we can see an average response rate separately for every type of task. Graphicalrepresentation is shown on Figure 4.12.
4.3 Subjective Assessment
All participants of experiment are asked to fill in a short form which contains two questions.In the first one people should give a rating from 1 to 5. Number one means the least intrusivenotification and number five means the most intrusive notification. As shown in Figure 4.13the most intrusive notification is the blur.
In the second question people can write a short comment related to the notifications. Accord-ing to comments the blur is the most intrusive and induce eye pain. For some participantsdecreased screen brightness is better for working with computer. With flash notification peo-ple easily loose their attention for example during reading. Pop-up window obtained neutralcomments. The worst comments are related to the blur notification.
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Chapter 4. Evaluation of Experiment Lenka Kutlíková
Figure 4.12: An average response rate for single type of tasks.
Figure 4.13: Results of subjective assessment from participants. An average number ofratings.
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Chapter 4. Evaluation of Experiment Lenka Kutlíková
24
Chapter 5
Conclusion
This thesis is focused on the evaluation of the intrusiveness and the effectiveness of notifica-tions. The main goal is to find out how different notifications affect people. We want to findout whether people make more mistakes. Five types of task (reading comprehension, imagecomprehension, counting words, adding and rewriting) and four types of notification (pop-upwindow, black flash, decreasing screen brightness and blur) are suggested to test parameterslike response time, response rate and blink rate in terms of effectiveness and correctness ofanswers in terms of intrusiveness. We have implemented an application for testing whichcontain a lot of different tasks. We conducted an experiment in cooperation with people.
After processing results of the experiment notifications are compared among themselves.When we take into consideration all three aspects (intrusiveness, effectiveness and subjectiveassessment) all types of notification have some pros and cons. Pop-up window has the bestresponse rate, ideal blink rate and the best correctness of answers but on the other side ithas also the biggest response time. The blur notification has an average results in responsetime, response rate and also correctness of answers and the biggest increase of the blink rate.In contrast black flash has the lowest correctness of answers, insufficient blink rate and thelowest response rate. On the other side black flash has the best response time. And the lastnotification of decrease screen brightness has an average results in response rate, responsetime, correctness of answers and ideal blink rate. The blur and black flash obtained negativecomments.
Based on results of this experiment we recommend using pop-up notification and decreasingscreen brightness to reminder people to blink more often.
Chapter 5. Conclusion Lenka Kutlíková
26
Bibliography
BAILEY, B. – KONSTAN, J. – CARLIS, J. Measuring the effects of interruptions on task perfor-mance in the user interface. In Systems, Man, and Cybernetics, 2000 IEEE International Confer-ence on, volume 2, pages 757–762 vol.2, 2000. doi: 10.1109/ICSMC.2000.885940.
BLEHM, C. et al. Computer Vision Syndrome: A Review. Survey of Ophthalmology. 2005, 50,3, pages 253 – 262. ISSN 0039-6257. doi: http://dx.doi.org/10.1016/j.survophthal.2005.02.008. Available from: http://www.sciencedirect.com/science/article/pii/S0039625705000093.
CRNOVRSANIN, T. – WANG, Y. – MA, K.-L. Stimulating a Blink: Reduction of Eye Fatiguewith Visual Stimulus. In Proceedings of the 32Nd Annual ACM Conference on Human Fac-tors in Computing Systems, CHI ’14, pages 2055–2064, New York, NY, USA, 2014. ACM. doi:10.1145/2556288.2557129. Available from: http://doi.acm.org/10.1145/2556288.2557129. ISBN 978-1-4503-2473-1.
DIVJAK MAJTAZ, B. H. Eye Blink Based Fatigue Detection for Prevention of Computer VisionSyndrome. In MVA2009 IAPR Conference on Machine Vision Applications, pages 350–353, 2009.Available from: http://www.mva-org.jp/Proceedings/2009CD/papers/10-04.pdf.
GILLIE, T. – BROADBENT, D. What makes interruptions disruptive? A study of length, similarity,and complexity. Psychological Research. 1989, 50, 4, pages 243–250. ISSN 0340-0727. doi:10.1007/BF00309260. Available from: http://dx.doi.org/10.1007/BF00309260.
HOLLAND, M. K. – TARLOW, G. Blinking And Thinking. In Perceptual and Motor Skills, pages403–406, 1975. Available from: http://www.ncbi.nlm.nih.gov/pubmed/1187305.
HOLLAND, M. K. – TARLOW, G. Blinking And Mental Load. In Psychological Reports, pages 119–127, 1972. Available from: http://www.amsciepub.com/doi/pdf/10.2466/pr0.1972.31.1.119.
SASSE, A. – (EDITORS, C. J. – MCFARLANE, D. C. Coordinating the Interruption of People inHuman-Computer Interaction. In Human-Computer Interaction, pages 295–303, 1999. Availablefrom: http://www.interruptions.net/literature/McFarlane-Interact99-Coordinating.pdf.
STORCH, N. A. Does the User Interface Make Interruptions Disruptive?: A Study of Interface Styleand Form of Interruption. In Posters and Short Talks of the 1992 SIGCHI Conference on HumanFactors in Computing Systems, CHI ’92, pages 14–14, New York, NY, USA, 1992. ACM. doi:10.1145/1125021.1125034. Available from: http://doi.acm.org/10.1145/1125021.1125034.
YAN, Z. et al. Computer Vision Syndrome: A widely spreading but largely unknown epidemicamong computer users. Computers in Human Behavior. 2008, 24, 5, pages 2026 – 2042. ISSN
Bibliography Lenka Kutlíková
0747-5632. doi: http://dx.doi.org/10.1016/j.chb.2007.09.004. Available from: http://www.sciencedirect.com/science/article/pii/S0747563207001501. Including theSpecial Issue: Internet Empowerment.
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Appendix A
Technical Documentation
An application is implemented in C++ language. It uses OpenCV library version 2.4.6. The front endis in Slovak language. An application contain functions for:
• GUI control (hide/show screens),
• using notifications (start/stop them),
• generating tasks,
• checking answers.
GUI control functions are used for hiding or showing different applications screens. For example:
• hideTaskMenu,
• showTaskMenu,
• showTask,
• hideTask,
• showRewriteTask,
• hideRewriteTask,
• showCounting,
• hideCounting,
• showAdding.
Notification functions serve for starting/stopping notification effect. Between them belong for exam-ple:
• flash,
• startBlur,
• stopBlur.
Appendix A. Technical Documentation Lenka Kutlíková
Listing A.1: Generating reading tasks
/* function for generating reading tasks
*/void MainWindow:: generateReading(){
showTask();if (order == 26)
order = 1; //restart reading tasksQString url = QString ("res/Reading%1.html").arg(order);QUrl qurl = QUrl::fromLocalFile(QFileInfo(url).absoluteFilePath());QString url1 = QString ("res/Reading%1_1.html").arg(order);QUrl qurl1 = QUrl::fromLocalFile(QFileInfo(url1).absoluteFilePath());QString url2 = QString ("res/Reading%1_2.html").arg(order);QUrl qurl2 = QUrl::fromLocalFile(QFileInfo(url2).absoluteFilePath());QString url3 = QString ("res/Reading%1_3.html").arg(order);QUrl qurl3 = QUrl::fromLocalFile(QFileInfo(url3).absoluteFilePath());QString url4 = QString ("res/Reading%1_4.html").arg(order);QUrl qurl4 = QUrl::fromLocalFile(QFileInfo(url4).absoluteFilePath());
ui->webView->load(qurl);ui->webView_uloha1->load(qurl1);ui->webView_uloha2->load(qurl2);ui->webView_uloha3->load(qurl3);ui->webView_uloha4->load(qurl4);
}
Example of notification function is on Listing A.2.
Generating task functions serve for creating tasks for people. Some of them is used for loading htmlfiles. Example is shown on Listing A.1. Between functions of this type belong also:
• generateRewriting,
• generateAdding,
• generateCounting,
• generateImage.
Checking answers functions are used for checking inputs from people. Example is shown on ListingA.3. For checking rewrite task we use C++ library dtl. It is based on An O(NP) Sequence ComparisonAlgorithm and it is used for comparing two sequences of characters. Between others belong:
• checkImageAnswers,
• checkAnswers,
• checkReadAnswers.
An application creates .csv and .txt files as an output from users. An application also contains classesfor blink detection and control notifications by my supervisor Ing. Andrej Fogelton. Source codes areattached on DVD.
30
Appendix A. Technical Documentation Lenka Kutlíková
Listing A.2: Black flash notification/*start black flash notification
*/void MainWindow::flash(){
stream_anotation << time.elapsed();stream_anotation << " black flash\n";
QWidget *widget = new QWidget();widget->setStyleSheet("background:black");widget->showFullScreen();QTimer::singleShot(100, widget, SLOT(close()));
}
Listing A.3: Check Adding answers/*check adding answers
*/int MainWindow::checkAddAnswers2(int a, int b, int answer){
if (a + b == answer)return 1;
elsereturn 0;
}
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Appendix A. Technical Documentation Lenka Kutlíková
32
Appendix B
User Guide
The front end of this application is in Slovak language so some buttons or GUI elements are desribedin it. Run an application by double click on eyeBLINK.exe. Enter the name and click on button OK.For start of testing select one task:
• Cítanie s porozumením - Reading comprehension consists of short text and four questions.
• Obrázok s porozumením - A graph with four questions.
• Pocítanie slov - Counting of occurrence of given word.
• Pocítanie - Adding of two or four numbers.
• Prepisovanie - Rewriting of short texts.
For the next task click the button Pokracuj. For interupt the task click on the button Prerušit’. Afterstart of testing do tasks according to instructions. After end of first part of testing choose notificationand continue with the task:
• Pop-up - pop-up window in the upper right corner of the screen.
• Preblik - black flash.
• Stmavenie - decreasing screen brightness.
• Rozmazanie - blur notification.
After trying all types of notification please fill in a short form in the main menu.
Appendix B. User Guide Lenka Kutlíková
34
Appendix C
Resumé
Úvod
V dnešnej dobe sú pocítace neoddelitel’nou súcast’ou nášho života. Mnoho l’udí denne strávi niekol’kohodín prácou s pocítacom. Dlhodobé pozeranie na displeje môže zaprícinit’ symptómy ako rozmazanévidenie, bolest’ ocí, suché oci alebo bolest’ hlavy. Tieto symptómy nazývame Syndróm pocítacovéhovidenia. Môžu byt’ zaprícinené poklesnutím poctu žmurknutí pocas práce s pocítacom. Použitímvizuálnych stimulov (upozornení) môžme pocet žmurknutí zvýšit’. Niektoré notifikácie však môžubyt’ rušivé a vyrušovat’ pri práci. Preto bežné úlohy môžu zabrat’ viac casu a l’udia sú menej efektívnialebo robia viac chýb. Z tohto dôvodu je nutné, aby notifikácie nevyrušovali.
Syndróm pocítacového videnia
Syndróm pocítacového videnia je opísaný ako skupina ocných problémov a problémov s videním,ktorá vychádza z dlhodobého používania pocítaca.
Syndróm suchého okaSyndróm suchého oka je súcast’ou Syndrómu pocítacového videnia definovaný ako nedostatocnezvlhcený povrch oka. Vyskytuje sa s nízkou produkciou slz alebo so zlou kvalitou slz. Môže byt’zaprícinený rýchlym odparovaním slz alebo znicením slznej žl’azy.
Notifikácie
Rôzne pocítacové programy používajú rôzne typy notifikácií. Môžme ich rozdelit’ do dvoch základ-ných skupín:
1. Notifikácie, ktoré potrebujú potvrdenie.
2. Notifikácie, ktoré nepotrebujú potvrdenie.
Všeobecne sú považované za prerušenie pocas práce s pocítacom. Môžu pôsobit’ rušivo a môžu mat’negatívny efekt na l’udskú pozornost’.
Appendix C. Resumé Lenka Kutlíková
Súvisiace práce
V súcasnosti sú problémy s videním pocas práce s pocítacom rozšírené. Vedci sa snažia nájst’ spôsobako sa týmto problémom vyhnút’. Jednou z možností je robit’ si pravidelné prestávky pocas práces pocítacom. Existujú pripomienkovace, ktoré nám pripomenú, kedy je potrebné dat’ si prestávku.Druhou možnost’ou je žmurkat’ castejšie. Existujú softvérové aj hardvérové riešenia pre pripomenutiežmurkania. Vedci vykonali niekol’ko experimentov v spolupráci s l’ud’mi, ktorí pravidelne používajúpocítac. Zist’ovali ako l’udia žmurkajú pocas rôznych typov úloh a ako reagujú na rôzne notifikácie.
Metodológia
Navrhli sme niekol’ko typov upozornení, aby sme dosiahli co najlepšie výsledky v zvýšení poctužmurnutí za minútu. Notifikácie otestujeme v dvoch experimentoch z hl’adiska rušivosti a efektivity.
Kategórie úloh
Trvanie jednej úlohy je 5 minút. Existuje 5 typov úloh:
• Cítanie s porozumením - Úloha sa skladá z krátkeho textu (120-150 slov) a 4 otázok súvisiacichs ním. 2 otázky sú na doplnenie, d’alšie 2 sú áno/nie.
• Obrázok s porozumením - Úlohou používatel’a je prezriet’ si graf a odpovedat’ na 4 otázky (2doplnovacie, 2 áno/nie).
• Pocítanie slov - Úlohou používatel’a je spocítat’ výskyt zadaného slova v tabul’ke.
• Pocítanie - Úloha sa skladá zo 6 príkladov na spocítavanie trojciferných císel a 2 príklady naspocítavanie dvojciferných císel.
• Prepisovanie - Úlohou používatel’a je prepísat’ krátky text.
Typy notifikácií
Navrhli sme 4 typy notifikácií:
Pop-up okno - Pop-up stimul zobrazí okno v pravom hornom rohu obrazovky. Okno obsahuje žmurka-júce oko. Pre zmiznutie tejto notifikácie je potrebné žmurknút’.
Rozmazanie - Ak používatel’ nežmurkne, obrazovka sa zacne rozmazávat’. Žmurknutie je nutné kdeaktivácií notifikácie.
Zníženie jasu obrazovky - Jas obrazovky sa pocas 5 sekúnd zníži na polovicu. Ked’ používatel’žmurkne, jas sa vráti na pôvodnú hodnotu.
Cierny preblik - Obrazovka preblikne na cierno na krátky cas (100ms).
Vyhodnotenie experimentu
Experiment sa zameriava na odmeranie efektivity a rušivosti navrhnutých upozornení. Jeho hlavnýmciel’om je nájst’ najlepší spôsob ako l’udí upozornovat’ na žmurknutie. Berieme do úvahy aj subjek-tívne hodnotenie.
36
Appendix C. Resumé Lenka Kutlíková
Otestovali sme 8 vysokoškolských študentov, všetci vo veku 20-25 rokov. Všetci boli pokrocilí vpráci s pocítacom a bežne strávia niekol’ko hodín denne pri práci s pocítacom.
Úcastníci experimentu si vybrali jeden typ úlohy z piatich ponúkaných (citanie s porozumením, obrá-zok s porozumením, pocítanie slov, pocítanie, prepisovanie). Najprv urobili úlohu bez notifikácieza úcelom zmerania poctu žmurknutí za minútu. Potom si mohli vybrat’ typ notifikácie zo štyrochponúknutých (pop-up okno, cierny preblik, zníženie jasu obrazovky, rozmazanie) a pokracovat’ vtestovaní úlohy, ktorú si vybrali v prvom kroku. Testovanie jednej úlohy so všetkými notifikáciamizaberie 25 minút. Ak niekto chce urobit’ všetky možnosti, experiment zaberie 125 minút.
Vyhodnotenie rušivosti
Pri vyhodnocovaní rušivosti sme brali do úvahy pomer poctu správnych odpovedí a poctu všetkýchodpovedí. Pri vyhodnocovaní prepisovacej úlohy sme brali do úvahy editovaciu vzdialenost’ a pocetprepísaných znakov. Editovacia vzdialenost’ je minimálny pocet editovacích operácií: vloženie, vy-mazanie a substitúcia.
Vyhodnotenie efektivity
Pri vyhodnotení efektivity sme merali cas odozvy notifikácie, úspešnost’ odozvy notifikácie a pocetžmurknutí za minútu.
Subjektívne hodnotenie
Všetci úcastníci experimentu boli požiadaní o vyplnenie krátkeho formulára, ktorý mal 2 otázky. Vprvej otázke bolo potrebné ohodnotit’ jednotlivé notifikácie na škále od 1 do 5, pricom 1 znamenánajmenej rušivé a 5 najviac rušivé. Najrušivejšiou notifikáciou podl’a subjektívneho hodnotenia jerozmazanie obrazovky.
V druhej otázke bolo možno napísat’ krátky komentár k notifikáciám. Najhoršie komentáre získalorozmazanie, pretože najviac rušilo a vyvolávalo bolest’ ocí. Pre niektorých používatel’ov bolo stmave-nie obrazovky dokonca lepšie pre prácu s pocítacom. S notifikáciou prebliknutia používatelia l’ahkostratili pozornost’, napríklad pri cítaní s porozumením. Pop-up notifikácia získala neutrálne hodnote-nia. Najhoršie komentáre získalo rozmazanie obrazovky.
Záver
Bakalárska práca je zameraná na vyhodnotenie rušivosti a efektivity notifikácií. Hlavným ciel’om jezistit’ ako rôzne notifikácie vplývajú na l’udí. Navrhli sme 5 typov úloh a 4 typy notifikácií, aby smeotestovali cas odozvy, úspešnost’ odozvy a pocet žmurknutí za minútu z hl’adiska efektivity a pocetsprávnych odpovedí z hl’adiska rušivosti. Navrhli a implementovali sme aplikáciu na testovanie, ktoráobsahovala mnoho rôznych úloh.
Po spracovaní výsledkov experimentu sme porovnali notifikácie medzi sebou. Ak berieme do úvahyvšetky tri aspekty (rušivost’, efektivitu, subjektívne hodnotenie) všetky notifikácie majú svoje výhodyaj nevýhody. Pop-up notifikácia má najlepšiu úspešnost’ odovzy, ideálny pocet žmurknutí za minútua najväcšiu úspešnost’ odpovedí, ale na druhej strane má najväcšiu dobu odozvy. Rozmazanie mápriemerné výsledky v dobe odozvy, úspešnosti odozvy, správnosti úloh a najväcší prírastok poctu
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Appendix C. Resumé Lenka Kutlíková
žmurknutí za minútu. Cierny preblik má najmenšiu úspešnost’ odpovedí, nedostatocný pocet žmurknutíza minútu a najmenšiu úspešnost’ odozvy. Na druhej strane, cierny preblik má najlepší cas odozvy.Posledná notifikácia, zníženie jasu obrazovky, má priemerné výsledky v case odozvy, úspešnostiodozvy, správnosti úloh a ideálny pocet žmurknutí za minútu.
Na základe výsledkov tohto experimentu odporúcame použit’ pop-up notifikáciu a zníženie jasu obra-zovky na prípomínanie l’ud’om, aby žmurkali castejšie.
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Appendix D
DVD Contents
/application/ - an executable application/source/ - source code of an application/tasks/ - created tasks for an application/pdf/ - pdf version of bachelor thesis/results/ - evaluation of results in Excel
