Luz Rello
email: luzrello@acm.org

Ricardo Baeza-Yates

Laura Dempere
email: laura.dampere@upf.edu

Horacio Saggion
email: horacio.saggion@upf.edu

Frequent Words Improve Readability and Short Words Improve Understandability for People with Dyslexia

Keywords: Textual accessibility, dyslexia, eye-tracking, lexical simplification, readability, understandability, word frequency, word length

Around 10% of the population has dyslexia, a reading disability that negatively affects a person's ability to read and comprehend texts. Previous work has studied how to optimize the text layout, but adapting the text content has not received that much attention. In this paper, we present an eye-tracking study that investigates if people with dyslexia would benefit from content simplification. In an experiment with 46 people, 23 with dyslexia and 23 as a control group, we compare texts where words were substituted by shorter/longer and more/less frequent synonyms. Using more frequent words caused the participants with dyslexia to read significantly faster, while the use of shorter words caused them to understand the text better. Amongst the control group, no significant effects were found. These results provide evidence that people with dyslexia may benefit from interactive tools that perform lexical simplification.

Introduction

Dyslexia is a neurological reading disability that is characterized by difficulties with accurate and/or fluent word recognition and by poor spelling and decoding abilities [START_REF] Topac | The development of a text customization tool for existing web sites[END_REF]. Secondary consequences include problems in reading comprehension and reduced reading experience that can impede vocabulary growth and background knowledge [START_REF]Definition of dyslexia[END_REF]. Since a great amount of information is presented as text, this condition makes more difficult to people with dyslexia to use well standard information systems. According to the literature, people with dyslexia specifically encounter problems with less frequent words and long words [START_REF] Cuetos | Modelos de lectura y dislexias (Reading models and dyslexia)[END_REF][START_REF] Hyönä | Eye fixation patterns among dyslexic and normal readers: Effects of word length and word frequency[END_REF][START_REF] Wimmer | Characteristics of developmental dyslexia in a regular writing system[END_REF]. The goal of this paper is to study to which extent word frequency and word length impacts text readability and understandability for native Spanish speakers with dyslexia. Readability refers to the legibility of a text, that is, the ease with which text can be read. Understandability refers to comprehensibility, that is, the ease with which text can be understood. Likewise to lexical simplification, which often involves replacing difficult words by their simpler synonyms [START_REF] Bott | Can Spanish be simpler? LexSiS: Lexical simplification for Spanish[END_REF], we replaced nouns by synonyms with diverse lengths and frequencies to study its effect on readability and understandability.

This research is motivated by [START_REF] Al-Wabil | Web navigation for individuals with dyslexia: an exploratory study. Universal Access in Human Computer Interaction[END_REF] the social relevance of its results and, (2) the challenge of revealing whether people with dyslexia could benefit from lexical simplification tools, such as a browser plug-in which allows interactive substitution of complex words by simpler synonyms.

First, dyslexia is universal and frequent. Depending on the language, the estimation of the prevalence of dyslexia varies from 10-17.5% for the population in the U.S.A. [START_REF]Learning Disabilities: A Report to the U.S. Congress[END_REF] to 8.6-11% for the Spanish speaking population [START_REF] Carrillo | Evaluación de la dislexia en la escuela primaria: Prevalencia en español (Evaluation of dyslexia in primary school: The prevalence in Spanish)[END_REF][START_REF] Jiménez | Prevalencia de las dificultades específicas de aprendizaje: La dislexia en español (The prevalence of specific learning difficulties: Dyslexia in Spanish)[END_REF][START_REF] Rello | The presence of English and Spanish dyslexia in the Web[END_REF].

Dyslexia-related difficulties are also shared by other groups with special needs, such as people with low vision [START_REF] Evett | Text formats and web design for visually impaired and dyslexic readers-clear text for all[END_REF]. Moreover, symptoms of dyslexia are common to varying degrees among most people [START_REF] Dixon | Comparative study of disabled vs. non-disabled evaluators in user testing: dyslexia and first year students learning computer programming[END_REF]. Another example of how research on dyslexia is useful for a broader public is the overlap of dyslexic-friendly recommendations with more general textual accessibility recommendations [START_REF] Mccarthy | What we know about dyslexia and web accessibility: a research review[END_REF]. Hence, this investigation is extensible to general usability problems and to other target groups.

Second, given that dyslexia is a disability that affects language, we can assume that textual accessibility can be approached from two dimensions: form, i.e. customizing the text layout, and content, i.e. simplifying the text. Although there are applications that modify the text layout for users with dyslexia, such as Claro ScreenRuler Suite [8], SeeWord [START_REF] Gregor | Seeword: a personal word processing environment for dyslexic computer users[END_REF] or IDEAL e-Book reader [START_REF] Kanvinde | IDEAL: a dyslexic-friendly e-book reader (poster)[END_REF], these only modify its design but not its content. Our experiments emulate possible lexical simplification strategies [START_REF] Bott | Can Spanish be simpler? LexSiS: Lexical simplification for Spanish[END_REF] and our results motivate the development of tools that simplify the textual content for people with dyslexia.

To the best of our knowledge, this is the first time that lexical complexity is measured in terms of readability and understandability for people with dyslexia using a methodology that combines eye-tracking and questionnaires. Therefore, this paper presents the following main contributions:

• A study about the effect of word frequency in readability and understandability, where the main result is that frequent words improve readability for people with dyslexia.

• A study about the effect of word length in readability and understandability, where the main result is that shorter words improve understandability for people with dyslexia. • A comparison of both studies with a control group without dyslexia, where the effect of word length and frequency is not significant.

The rest of the paper is organized as follows. Section 2 covers related work while Section 3 presents the problem and the hypotheses of our research. Section 4 details the experimental methodology and Section 5 presents the results, which are subsequently discussed in Section 6. Finally, conclusions and future challenges are explained in Section 7.

Related Work

Since readability strongly affects text comprehension, sometimes both terms have been used interchangeably. However, previous research with people with dyslexia have shown that both concepts need to be taken into consideration separately. For instance, in [START_REF] Rello | Lexical quality as a proxy for web text understandability (poster)[END_REF] comprehension has been found to be independent of readability for people with dyslexia, while text readability can be used as an indicator of comprehension for people without dyslexia. Hence, in this study we distinguish between readability and understandability. Notice also that in the definition of dyslexia reading abilities and reading comprehension are treated separately [START_REF]Definition of dyslexia[END_REF]. Most research in this area focus on English, but our study considers Spanish language. Dyslexia manifestations vary depending on different language orthographies [START_REF] Brunswick | Unimpaired reading development and dyslexia across different languages[END_REF]. Since English and Spanish have different orthographies findings from one language do not necessarily apply to the other language. In fact, English has a deep orthography where the relationships between letters and sounds are inconsistent and many exceptions are permitted. On the other hand, Spanish has a shallow orthography with a more regular alphabetic system that contains consistent mappings between letters and sounds, the second shallowest of European languages [START_REF] Seymour | Foundation literacy acquisition in European orthographies[END_REF].

We chose to study word frequency and word length because they are related to the word's processing time [START_REF] Rayner | Lexical complexity and fixation times in reading: Effects of word frequency, verb complexity, and lexical ambiguity[END_REF][START_REF] Sereno | Measuring word recognition in reading: eye movements and event-related potentials[END_REF], and they are strongly related to the difficulties that people with dyslexia find [START_REF] Cuetos | Modelos de lectura y dislexias (Reading models and dyslexia)[END_REF][START_REF] Hyönä | Eye fixation patterns among dyslexic and normal readers: Effects of word length and word frequency[END_REF][START_REF] Wimmer | Characteristics of developmental dyslexia in a regular writing system[END_REF]. Previous work related to our research can be divided into: (a) studies from experimental psychology about eye-movement of readers with dyslexia, (b) work about comprehension abilities of people with dyslexia, and (c) interfaces for people with dyslexia.

Eye-movements of readers with dyslexia.

There is an extensive body of knowledge about eye-movements of readers with dyslexia using eye-tracking. Most of these studies focus on finding ways to diagnose dyslexia. However, the nature of eyemovements of people with dyslexia is currently under debate. While some found differences [START_REF] Eden | Differences in eye movements and reading problems in dyslexic and normal children[END_REF] among the two populations, others did not [START_REF] Stanley | Eye-movements and sequential tracking in dyslexic and control children[END_REF]. The closest work to ours comes from experimental psychology [START_REF] Hyönä | Eye fixation patterns among dyslexic and normal readers: Effects of word length and word frequency[END_REF], which studies the effect of word length and word frequency in relation with eye fixation patterns among readers. Their results show that low frequency and long words present longer gaze durations and more re-inspections. Their approach focuses on finding eye-movement patterns to study particular words with the aim to discard the oculomotor dysfunction hypothesis of dyslexia [START_REF] Hyönä | Eye fixation patterns among dyslexic and normal readers: Effects of word length and word frequency[END_REF]. They analyze single words while we analyze the whole text.

Comprehension in people with dyslexia. Previous research has studied the effect of long sentences with difficult structures [START_REF] Simmons | The reading comprehension abilities of dyslexic students in higher education[END_REF], sentence context [START_REF] Nation | Individual differences in contextual facilitation: Evidence from dyslexia and poor reading comprehension[END_REF], and the incorporation of graphical schemes [START_REF] Rello | Graphical schemes may improve readability but not understandability for people with dyslexia[END_REF], among others, on text comprehension of readers with dyslexia. More related to our work are [START_REF] Simmons | The reading comprehension abilities of dyslexic students in higher education[END_REF][START_REF] Rüsseler | Recognition memory for high-and lowfrequency words in adult normal and dyslexic readers: an event-related brain potential study[END_REF] who have suggested that the text could be made more difficult by the inclusion of low frequency and long words.

Interfaces for people with dyslexia.

There are number of existing applications for people with dyslexia that alter the presentation of the text such as SeeWord 1 [START_REF] Gregor | Seeword: a personal word processing environment for dyslexic computer users[END_REF], Colour Explorer, 2 Text4All 3 [START_REF] Topac | The development of a text customization tool for existing web sites[END_REF], and Penfriend XL. 4 Other tools also incorporate text-to-speech technology such as Claro Screen Ruler Suite, 5 or the IDEAL eBook reader 6 [START_REF] Kanvinde | IDEAL: a dyslexic-friendly e-book reader (poster)[END_REF]. Dyseggxia 7 [START_REF] Rello | What is wrong with this word? Dyseggxia: a game for children with dyslexia (demo)[END_REF] is a game for children with dyslexia that uses as a basis word modification, but, to the extent of our knowledge; there is no interface which modifies the text content to be read by people with dyslexia.

What is missing in previous research is knowledge about two factors of lexical complexity -word frequency and word length-in the Spanish language, and their impact on the reading performance and the comprehension of people with dyslexia, as well as the integration of these findings in tools for people with dyslexia.

Word Frequency and Length in Dyslexia

Among the language difficulties that people with dyslexia find, the additional difficulty that less frequent words (e.g. pristine) and longer words (e.g. prestidigitation) has been specially stressed [START_REF] Cuetos | Modelos de lectura y dislexias (Reading models and dyslexia)[END_REF][START_REF] Hyönä | Eye fixation patterns among dyslexic and normal readers: Effects of word length and word frequency[END_REF][START_REF] Wimmer | Characteristics of developmental dyslexia in a regular writing system[END_REF]. The role of word frequency is so crucial in dyslexia that there is even a diagnosis of dyslexia based on the performance while reading frequent words [START_REF] Lachmann | Different letter-processing strategies in diagnostic subgroups of developmental dyslexia[END_REF].

Since word frequency and word length are naturally related in language, we studied them in two different experiments. The correlation originates from the fact that frequently used expressions tend to become shorter over time [START_REF] Jurafsky | Evidence from reduction in lexical production[END_REF]. As stressed by Rayner et al. [START_REF] Rayner | Lexical complexity and fixation times in reading: Effects of word frequency, verb complexity, and lexical ambiguity[END_REF], to unveil cause and effect relationships, these dimensions have to be studied individually. Hence, our hypotheses are:

• H1.1: A larger number of high frequency words increases readability for people with dyslexia. • H1.2: A larger number of high frequency words increases understandability for people with dyslexia. • H2.1: The presence of short words compared to long words increases readability for people with dyslexia. • H2.2: The presence of short words compared to long words increases understandability for people with dyslexia.

To the best of our knowledge, the rest of the dyslexia-related difficulties regarding words involve: irregular words 8 [START_REF] Coltheart | Phonological dyslexia: Past and future issues[END_REF], orthographic similar words, e.g. addition and 1 http://www.computing.dundee.ac.uk/projects/seeword/ 2 http://colour-explorer.software.informer.com/9.0/ 3 http://www.text4all.net/ 4 http://www.penfriend.biz/pf-xl.html 5 http://www.clarosoftware.com/index.php?cPath=348. 6 https://play.google.com/store/apps/details?id=org.easyaccess.epubreader 7 https://itunes.apple.com/es/app/dyseggxia/id534986729?mt=8 8 Words in which there is no consistent correspondence between grapheme and phoneme, e.g. vase, pronounced as /vaz/.

audition [START_REF] Ellis | Reading, writing and dyslexia[END_REF], homophonic words or pseudo homophonic words, e.g. weather and whether [START_REF] Patterson | Surface dyslexia: Neuropsychological and cognitive studies of phonological reading[END_REF], foreign words [START_REF] Cuetos | Modelos de lectura y dislexias (Reading models and dyslexia)[END_REF], new words, e.g. fantabulous [START_REF] Cuetos | Modelos de lectura y dislexias (Reading models and dyslexia)[END_REF], words with errors [START_REF] Coltheart | Phonological dyslexia: Past and future issues[END_REF], non-words,9 e.g. happisfaction [START_REF] Coltheart | Phonological dyslexia: Past and future issues[END_REF], and numerical expressions [START_REF] Rello | One half or 50%? An eye-tracking study of number representation readability[END_REF]. In the experimental design we did not use words of such characteristics to control other possible effects.

Methodology

We study word frequency and word length as two independent variables in two different experiments. Nonetheless, the inherent relationship between frequency and length has constrained the selection criteria of the target words, i.e. long words are inevitably less frequent.

In the experiments, 46 participants (23 with dyslexia) had to read four texts, which were altered to include more/less frequent and longer/shorter words.

Design

For each experiment there were two conditions. In the first experiment, wordfrequency [±frequent] served as independent variable with two levels: [+frequent] denotes the condition where suitable words were replaced by more frequent synonyms and [-frequent] denotes the condition where suitable words were replaced by less frequent synonyms. In the second experiment, word-length [±long] served as independent variable with two levels: [-long] denotes the condition where suitable words were replaced by shorter synonyms and [+long] denotes the condition where suitable words were replaced by longer synonyms.

The experiments followed a within-subjects design, so every participant contributed to each of the conditions in both experiments. The order of conditions was counter-balanced to cancel out sequence effects. To measure readability and understandability, we consider reading time, eye fixations duration, and a comprehension score as dependent variables. Next, we explain them in detail.

Reading Time. Shorter reading durations are preferred to longer ones since faster reading is related to more readable texts [START_REF] Vellutino | Specific reading disability (dyslexia): What have we learned in the past four decades[END_REF]. Therefore, we use Reading Time, i.e. the time it takes for a participant to completely read one text, as a measure of readability. This measure is extracted from the eye-tracking data.

Fixation Duration. When reading a text, the eye does not move contiguously over text, but alternates saccades and visual fixations, that is, jumps in short steps and rests on parts of the text. Fixation duration denotes how long the eye rests still on a single place of the text. Fixation duration has been shown to be a valid indicator of readabil-ity. According to [START_REF] Just | A theory of reading: From eye fixations to comprehension[END_REF][START_REF] Rayner | Lexical complexity and fixation times in reading: Effects of word frequency, verb complexity, and lexical ambiguity[END_REF][START_REF] Rüsseler | Recognition memory for high-and lowfrequency words in adult normal and dyslexic readers: an event-related brain potential study[END_REF], shorter fixations are associated with better readability while longer fixations can indicate that processing loads are greater.

Hence, we use fixation duration as a readability measure in addition to the reading time.

Comprehension Score. To measure text comprehension we used inferential items, that is, questions that require a deep understanding of the content of the text. We used multiple-choice questions with three possible choices, one correct choice, one partially correct choice, and one wrong choice. To compute the text comprehension score, the choices counted 100%, 50%, and 0%, respectively.

Design

We had 23 Spanish speakers (12 female, 11 male) with a confirmed diagnosis of dyslexia (group D) that participated in our study. They were asked to bring their diagnoses to the experiment, to guarantee that dyslexia was diagnosed in an authorised centre or hospital. Their ages ranged from 13 to 37, with a mean age of 20.74 years (s = 8.18). Three of these participants were also diagnosed with attention deficit disorder. All participants were frequent readers; per day, eleven read less than four hours per day, nine read between four and eight hours per day, and three participants read more than eight hours. 10 Ten people were studying or already finished university degrees, eleven were attending school or high school, and two had no higher education.

A control group of 23 Spanish speakers (13 female, 10 male) without dyslexia also participated in the study (group N). Their ages ranged from 13 to 35, with a mean age of 20.74 years (s = 8.18). That is, overall, we had 46 participants (25 female, 21 male).

Materials

To study the effects of word length and frequency, we need to study target words in context, that is, as part of a text. The rationale behind this is that readability and understandability pertain to longer segments of texts [START_REF] Huenerfauth | Comparing evaluation techniques for text readability software for adults with intellectual disabilities[END_REF]. To isolate the effects of these variables, the texts need to be comparable in complexity. In this section, we describe how we designed the texts, the target words, and the questionnaires that were used in this study.

Base Texts. As basis for our tests, we picked four short texts with an average length of 60.63 words. For word-frequency, we used two texts about the consequences of wars in Pakistan and Somalia. These were the most similar pairs of texts we could find in the Spanish Simplex corpus [START_REF] Bott | Text simplification tools for Spanish[END_REF]. For word-length, we created two mystery stories, one about a wizard and one about a car. In the following, we denote these texts with Pakistan, Somalia, Wizard, and Car.

To meet the comparability requirements among the texts belonging to the same experiment, we adapted the texts maintaining as much as possible the original text. We matched the readability of the texts by making sure that the parameters commonly used to compute readability [START_REF] Drndarevic | Towards automatic lexical simplification in Spanish: an empirical study[END_REF], had the same or similar values: Text Layout. The presentation of the text has an effect on reading speed of people with dyslexia [START_REF] Gregor | An empirical investigation of ways in which some of the problems encountered by some dyslexics may be alleviated using computer techniques[END_REF]. Therefore, we used a text layout that follows the recommendations of previous research. As font type, we chose Arial, sans serif, as recommended by Al Wabil et al. [START_REF] Al-Wabil | Web navigation for individuals with dyslexia: an exploratory study. Universal Access in Human Computer Interaction[END_REF]. The text was left justified, as recommended by the British Association of Dyslexia [START_REF]Dyslexia style guide[END_REF]. Each line did not exceeded 62 characters/column, the font size was 20 point, and the colors used were black font with crème background, 11 as recommended by Rello et al. [START_REF] Rello | Layout guidelines for web text and a web service to improve accessibility for dyslexics[END_REF].

Target Words. Word length and frequency were selected taking into consideration the problems that people with dyslexia encounter. To control that other dyslexicrelated difficulties did not interfere in the selected target words, we also took into account linguistic criteria during the selection of the target word pairs of synonyms:

(a) We did not include ambiguous names because they require more processing than unambiguous words [START_REF] Rayner | Lexical complexity and fixation times in reading: Effects of word frequency, verb complexity, and lexical ambiguity[END_REF].

(b) We did not change compound nouns or collocations in the texts. Instances like secretario general, `secretary of state', which is composed by two tokens but one meaning, were discarded. (c) We did not use irregular words, foreign words, non-words, and new words [START_REF] Coltheart | Phonological dyslexia: Past and future issues[END_REF][START_REF] Cuetos | Modelos de lectura y dislexias (Reading models and dyslexia)[END_REF]. (d) We took into consideration only common names. Uncommon names were discarded because they are more likely to be irregular, foreign, or new words. (e) We did not take into consideration phonetically similar words, that is, homophonic words or pseudo homophonic words [START_REF] Patterson | Surface dyslexia: Neuropsychological and cognitive studies of phonological reading[END_REF] and orthographically similar words [START_REF] Ellis | Reading, writing and dyslexia[END_REF].

To apply our criteria (a) to (d) we used linguistic knowledge using the Royal Spanish Academy Dictionary [START_REF]Real Academia Española. Diccionario de la lengua española (Dictionary of the Spanish language)[END_REF]. To control for orthographic and phonetic similarity (e) of the target word, we consulted the database of indexes of frequency, length, and orthographic neighbours 12 in Spanish [START_REF] Pérez | Frecuencia, longitud y vecindad ortográfica de las palabras de 3 a 16 letras del diccionario de la lengua española (Frequency, length and orthographical neighborhood of the words from 3 to 16 letters of the dictionary of the Spanish language -RAE 1992)[END_REF], which enables us to determine how many neighbours the target word has and how frequent are those neighbours. We can assume that orthographic and phonetic similarities are related in Spanish, because, as we mentioned before, it has a shallow orthography.

Word Frequency. For creating the pair of [±frequent] synonyms we first extracted the nouns of the texts according to the previous selection criteria. Then, we checked their synonyms using a synonym dictionary 13 and created a list of synonyms for each target word. We discarded nouns with no synonyms such as million or kilometer. We subsequently computed the relative frequencies of each of the synonyms for each of the lists using the advanced search of a major search engine. 14 Then, we manually selected the pair of synonyms (most frequent and less frequent) for the context where the target noun occurred in the text. Each pair of [±frequent] has a frequency difference of at least one order of magnitude, for instance morada, 'house', is 67 times less frequent than casa, 'house'. In the Appendix we present the pairs of synonyms with their frequency ratio. To maintain both factors independent, short nouns with less than four letters were discarded. Still, we could only partially control for length differences: the average length per word in the high frequency synonyms is 7.62 letters while for the low frequency synonyms is 9.56 letters.

Word Length. Finding synonym pairs with a relatively large difference in word length is challenging for Spanish because 79% of the words in the dictionary have 12 Neighbours are all the words with the same length as the target word that differs in a single letter [START_REF] Coltheart | Access to the internal lexicon[END_REF], that is, the Hamming distance between them is one. For instance, the word casa has many neighbours like masa, cosa, cama and caso. 13 http://www.wordreference.com/sinonimos/ 14 http://www.google.com/advanced_search between 6 and 11 letters. Note that the average word length in Spanish is 8.78 letters per lemma, being similar to English where is 8.99 letters. 15Therefore, for creating the pair of [±long] synonyms we took all the Spanish lemmas from the Royal Spanish Academy Dictionary [START_REF]Real Academia Española. Diccionario de la lengua española (Dictionary of the Spanish language)[END_REF] and selected the longest words. Then, we looked up for the synonyms 16 of these words to create the lists of synonyms. However, the majority of the longest words in Spanish do not have synonyms, for example electroencefalograma, 'electroencephalogra'. From the list of synonyms we selected synonym pairs where the [+long] synonym at least doubled the length of its [-long] counterpart. For instance apartamento, 'flat', is 2.75 times longer than piso, 'flat'. In the Appendix, we present the pairs of synonyms with their length ratio.

Comprehension Questionnaires. We used multiple-choice questions with three possible choices, one correct choice, one partially correct choice, and one wrong choice. The questions were inferential, that is, answering it correctly required a deep understanding of the text content. An example question is given below: (a) ¿De qué trata el texto? 'What is the text about?'. a. Sobre la acción de la Cruz Roja en Somalia.

'About the Red Cross action in Somalia.' b. Sobre las consecuencias de la guerra en la población de Somalia.

'About the consequences of the war on the Somalia population.' c. Sobre el incremento del precio de los productos en Somalia.

'About the price increase of products in Somalia.'

Equipment

The eye tracker used was the Tobii T50 [START_REF]Product description Tobii 50 Series[END_REF] that has a 17-inch TFT monitor with a resolution of 1024x768 pixels. The time measurements of the eye-tracker have a precision of 0.02 seconds. The eye tracker was calibrated for each participant and the light focus was always in the same position. The distance between the participant and the eye tracker was constant (approximately 60 cm. or 24 in.) and controlled by using a fixed chair.

Procedure

The sessions were conducted at Universitat Pompeu Fabra and lasted from 30 to 40 minutes, depending on the amount of feedback given by the participant. In each session, the participant was alone with the interviewer in the quiet room prepared for the study, and performed the following three steps.

First, we began with a questionnaire that was designed to collect demographic information. Second, we conducted the two experiments, which were recorded using eye-tracking. Then, the participants were asked to read the texts in silence and to complete the comprehension tests after each completed text. Finally, we carried out a semi-structured interview, where we asked for feedback about the experiment and about the usefulness of lexical simplification.

Results

In this section we present the analyses of the data from the eye tracker (reading time and fixation duration) and the comprehension tests. First, we analyzed the differences among groups (D and N) and then the effect of the conditions within each group.

The results are shown in Tables 1 and2. A Shapiro-Wilk test showed that the three data sets were not normally distributed. However, a Barlett's test showed that they were homogeneous. Hence, we use Student's t-tests to show statistically significant effects.

Table 1. Results of the word-frequency experiment.

Table 2. Results of the word-length experiment.

Reading Time. We found a significant difference between the groups regarding reading time (t(124.707) = 5.434, p < 0.001). Group D had significantly longer reading times (µ = 31.86, s = 20.28 seconds) than the participants of group N (µ = 18.32, s = 10.53 seconds).

Word Frequency. For the participants with dyslexia we found a significant effect on reading time (t(33.488) = -2.120, p = 0.035). Using more frequent words lead to significantly shorter reading times (µ = 41.99, s = 13.00 seconds) than using less frequent words (µ = 53.35, s = 19.10 seconds). For the control group we found no significant effect on reading time (t(30.283) = -1.828, p = 0.077) (see Table 1).

Word Length. For group D, we found a significant effect on reading time (t(33.971) = 2.944, p = 0.006). Using shorter words lead to significantly shorter reading times (µ = 13.74, s = 6.05 seconds) than using longer words (µ = 21.23, s = 10.28 seconds). For the control group, there was no significant effect on reading time (t(38.569) = 1.957, p = 0.058$) (Table 2). Fixation Duration. There was a significant difference between the groups regarding fixation duration (t(140.111) = 8.209, p < 0.001). Participants with dyslexia had significantly longer fixation times (µ = 0.23, s = 0.05 seconds) than the participants without dyslexia (µ = 0.17, s = 0.03 seconds).

Word Frequency. For the participants with dyslexia, we found a significant effect on fixation duration (t(35.741) = -2.150, p = 0.038). Using more frequent words lead to significantly shorter fixation times (µ = 0.22, s = 0.04 seconds) than using less frequent words (µ = 0.25, s = 0.05 seconds). For the control group, no significant effect on fixation duration was found (t(37.402) = -1.035, p = 0.307) (see Table 1).

Word Length. We found no significant effect on the fixation duration in group D (t(40.002) = 0.763, p = 0.450), nor in group N (t(41.526) = 0.991, p = 0.327) (see Table 2).

Comprehension Score. Participants with dyslexia answered fewer questions correctly (µ = 82.74%, s = 28.51%) than participants without dyslexia (µ = 89.88%, s = 20.21%). However, the difference between the groups was not statistically significant (t(149.593) = -1.873, p = 0.063)).

Word Frequency. We did not found a significant effect on text comprehension for group D (t(37.764) = 0.370, p = 0.714) nor for group N (t(33.824) = 1.241, p = 0.223) (see Table 1).

Word Length. For the participants with dyslexia, we found a significant effect on the comprehension score (t(38.636) = -2.396, p = 0.022). Shorter words led to signifi-cantly higher text comprehension (µ = 88.64%, s = 26.42%) than longer words (µ = 65.91%, s = 35.81%). For the control group, changing the word length had no significant effect on text comprehension (t(41.16) = -0.707, p = 0.484) (see Table 2).

Discussion

In general, participants without dyslexia read significantly faster and had shorter fixation durations than participants with dyslexia. However, participants with dyslexia read significantly faster and have significantly shorter fixation durations using more frequent words. Using shorter words caused participants with dyslexia to read significantly faster and significantly increased their text comprehension. For the people without dyslexia, no differences in reading time, fixation duration, or text comprehension were found. Regarding the differences between the groups, our results are consistent with other eye-tracking studies to diagnose dyslexia that found statistical differences between the two populations [START_REF] Eden | Differences in eye movements and reading problems in dyslexic and normal children[END_REF].

Since shorter reading times and fixation durations are associated with better readability, our findings support H1.1 A larger number of high frequency words increases readability for people with dyslexia. The effect of frequency is more pronounced in people with dyslexia than in people without dyslexia, where non significant results were found. Our results are consistent with previous results for both groups. Word frequency was found to have a powerful influence on word recognition tasks for people with [START_REF] Hyönä | Eye fixation patterns among dyslexic and normal readers: Effects of word length and word frequency[END_REF] or without [START_REF] Rayner | Lexical complexity and fixation times in reading: Effects of word frequency, verb complexity, and lexical ambiguity[END_REF][START_REF] Sereno | Measuring word recognition in reading: eye movements and event-related potentials[END_REF] dyslexia and some reading experiments have demonstrated that readers spend more time looking at low-frequency words than at highfrequency words [START_REF] Hyönä | Eye fixation patterns among dyslexic and normal readers: Effects of word length and word frequency[END_REF].

In Figure 1 we consider the two visual behaviors that we use as surrogate variables for readability (reading time and fixation duration), visualizing the distribution of the data in such 2D space. A more meaningful feature emerges that can be obtained from a linear combination of both of them. 17 The emerging feature can be interpreted as a readability variable that defines the readability axis. Thus, any readability improvement that moves along the direction determined by the arrow approaches the "ideal situation", which is characterized by target values reached by people without dyslexia in the most favorable conditions (e.g. the behavior on people without dyslexia in texts with higher frequency words). The use of more frequent words bring the average fixation time of group D closer to group N.

Since word frequency had no significant effect on text comprehension, we cannot confirm H1.2: A larger number of high frequency words increases understandability for people with dyslexia.

Since shorter reading times are associated with better readability, our findings support H2.1: The presence of short words compared to long words increases readability for people with dyslexia. Although no statistical significance has been found for length regarding fixation duration, we can observe a qualitative improvement in the 17 One possible explanation of the lower significance of word length than word frequency is that Wizard might have been more difficult to read than Car. According to some of the comments of the participants during the open questions, the fact that there was an additive set in front of the noun in the text Wizard made it a bit more complicated for further reading. In Spanish, adjectives postponed to nouns are frequent and natural (unmarked syntactic structure for most of the cases), therefore this might be a new variable to take into consideration in further work.

Because participants with dyslexia had a significantly increased text comprehension with texts having shorter words, our findings support H2.2: The presence of short words compared to long words increases understandability for people with dyslexia.

One of the limitations of our study is that the inferences made from H2.1 and H2.2 could be due to the low frequency of long words and not to their length. Through the experimental design we maintained as much as possible both factors -frequency and length-separated for studying both effects independently. However a total dissociation was not possible, as we could not find long words that were more frequent than their shorter synonyms. Although Rayner and Duffy [START_REF] Rayner | Lexical complexity and fixation times in reading: Effects of word frequency, verb complexity, and lexical ambiguity[END_REF] explain the necessity to study both effects separately, such separation between token frequency of linguistic expressions and their length does not exist in natural language [START_REF] Bybee | Phonology and language use[END_REF]. Words [+long] are in average 59.45 less frequent than their correspondent [-long] synonyms. However this frequency ratio is not as high as in the experiment word frequency where [+frequent] were 1249.17 times more frequent in average than their [-frequent] synonyms (see Appendix for the frequency ratios for each pair). Since using shorter words usually implies more frequent words, H1.1 and H2.1 reinforce each other.

However, the reasons why longer and less frequent words receive longer fixations are different [START_REF] Hyönä | Eye fixation patterns among dyslexic and normal readers: Effects of word length and word frequency[END_REF], because while less frequent words require more processing, the word-length effect can be ascribed to acuity limitations of the visual system. 18 On the other hand, longer words may imply more fixations instead of longer fixations.

Conclusions and Future Work

We tested the effect of word length and frequency on readability and comprehension.

Our results show that more frequent words improve readability while shorter words may improve understandability, especially in people with dyslexia. The results also provide evidence about the potential of measuring fixation duration and reading time as a visual behavior surrogate for the readability of a text. The results suggest that people without dyslexia come closer to the ideal reading scenario with shorter fixations and reading time as well as better text comprehension. These findings can have great impact on interactive systems that rely on text as the main information medium, such as browsers, PDF viewers, or eBook readers. By applying our suggested lexical simplification strategies, namely substituting long and non-frequent words through shorter and frequent synonyms, these systems could make texts easier to read and understand for people with dyslexia. We implemented an automatic method for lexical simplification in Spanish [START_REF] Bott | Can Spanish be simpler? LexSiS: Lexical simplification for Spanish[END_REF] and tried two different interactive strategies with participants with dyslexia [START_REF] Rello | Simplify or help? Text simplification strategies for people with dyslexia[END_REF]. We found that showing simpler synonyms on demand had a better impact than substituting such synonyms. Further improvements on the user interactions are being done and final results will be integrated in DysWebxia 2.0 [START_REF] Rello | Dyswebxia 2.0!: Accessible text for people with dyslexia (demo)[END_REF], a tool that modifies text content and layout for people with dyslexia.

Since there is a correlation between word length and frequency, as frequently used words tend to be shorter, future work needs to investigate potential inter-dependencies between these two factors. We will explore also to what extent lexical simplifications can improve the readability of texts that people with dyslexia read as part of their daily life, such as news, Facebook entries, or Wikipedia articles.

  (a) They have the same number of target words: Fifteen [±frequent] word pairs for each of the texts in the word-frequency experiment and six [±long] word pairs for each of the texts in the word-length experiment. Only in Somalia (wordfrequency experiment) two target words are repeated in the text. (b) Within each experiment, the texts use the same genre, international news. (c) They are about similar topics. (d) They contain the same number of sentences: four sentences for each of the texts in the word-frequency experiment and three in the word-length experiment. (e) The texts of each experiment have the same number of words per text (93 words for both texts in the word-frequency experiment and 33 words in the word-length experiment). (f) All the texts have a similar word length, with an average length ranging from 4.89 to 5.50 letters. (g) They contain the same number of unique named entities and they do not contain foreign words, numerical expressions or acronyms.

  Doing a least squares linear regression we obtain the formula Reading time = 173.3 × Fixation time + 2.2 seconds (Pearson correlation of 0.51 and p < 0.001).readability through the use of shorter words since the mean fixation duration for group D also comes closer to the mean fixation duration for group N.

Figure 1 .

 1 Figure 1. Readability as a function of reading time and fixation duration.

A non-word is a word that has no meaning, is not known to exist, or is disapproved.

We think that the participants interpreted reading time as schooling time and that is why the numbers may seem exaggerated.

The CYMK are crème (FAFAC8) and black (000000). Color difference: 700, Brightness difference: 244[START_REF] Rello | Layout guidelines for web text and a web service to improve accessibility for dyslexics[END_REF].

We used the Royal Spanish Academy Dictionary[START_REF]Real Academia Española. Diccionario de la lengua española (Dictionary of the Spanish language)[END_REF] and the Longman Dictionary of Contemporary English[START_REF] Longman | Longman dictionary of contemporary English[END_REF].

[START_REF] Evett | Text formats and web design for visually impaired and dyslexic readers-clear text for all[END_REF] http://www.wordreference.com/sinonimos/

Long words extend beyond the fovea where the acuity is greatest, thus increasing the need for making a fixation and even a re-fixation on a word[START_REF] Hyönä | Eye fixation patterns among dyslexic and normal readers: Effects of word length and word frequency[END_REF].

Acknowledgments

We thank Maarten Janssen for facilitating us the dictionary entries and Giorgio Brajnik for his invaluable comments and advise. We thank Mari-Carmen Marcos for her assistance with the eye-tracker hardware and Joaquim Llisterri for his help distributing our experiments announcement among experts. This research was funded by the Spanish Ministry of Education and Science (Grant TIN2009-14560-C03-01) and the FI Catalonian scholarship program.

Appendix: Synonyms Pairs

The list of the unique pairs of synonyms used in the experiment word-frequency is below. The frequency ratio appears in parenthesis after the [±frequent].

The list of the unique pairs of synonyms used in the experiment word-length is shown below. The frequency ratio appears in parenthesis after the [+long] word. The length ratio is shown after the frequency ratio.


Jennifer Pearson
email: j.pearson@swan.ac.uk

Simon Robinson
email: s.n.w.robinson@swan.ac.uk

George Buchanan

Matt Jones
email: matt.jones@swan.ac.uk

TicQR: Flexible, Lightweight Linking of Paper and Digital Content using Mobile Phones

Keywords: Paper documents, tick boxes, QR Codes

In this paper we introduce TicQR -a photo-based checkbox-enabled interface which bridges the physical and digital document domains, allowing automatic download or processing of useful data from paper documents. There is a long demonstrated need for people to be able to connect between printed material and digital information and services. By using a combination of image recognition and QR codes we are able to detect user marks on paper documents via a single photograph taken with a standard smart phone. This information can then be used to access the equivalent digital content, save contacts or URLs, or even order goods directly from local retailers.

Introduction

Digital services now permeate every aspect of our lives. However, printed materials predominate in many everyday situations, and are commonly used to gather or communicate vital information. But paper itself does not connect directly to digital services; for that reason many have sought to create links to the digital domain via a range of technologies. Most existing solutions require specialist equipment to connect paper and digital content, or suffer from relatively coarse information granularityfor example, connecting a whole page or document to a single digital item. While these approaches do indeed connect paper to digital, we argue that it would be preferable to be able to use more commonplace mobile technologies, and at the same time be able to provide finer-grained information, even considering specific marks or annotations by the user on the paper document.

To achieve this goal, we present a novel technologically and interactively lightweight approach that lets readers extract information from a printed document. Our approach -TicQR, allows people to tick boxes to select interesting sections directly on paper, and photograph the page using a standard cameraphone. Given both the document's identity and the specific selections made, TicQR can then undertake a variety of actions depending on how the document's designer has configured the support for their text. We thus provide a rich opportunity for interaction that embraces both print and digital media, but requires no additional hardware or specialist paper.

Background

Paper documents have been around for millennia, and despite the ever-growing popularity of digital reading, paper remains ubiquitous. The physicality of paper offers affordances that computer screens or eReaders do not -such as folding and scrib-Later that day... These articles are really interesting, I wish I could nd them online so I can read them later...

SNA P!

I'll just tick the best bits... Great! It's saved the ones I wanted bling, for example. Globally, for reasons such as cost, physicality, aesthetics and utility, paper remains a desirable medium in many cases [START_REF] Sellen | The Myth of the Paperless Office[END_REF]. Yet the digital medium has many advantages, including support for searches across content, links between items, and its physical space benefits. Mixed approaches offer a combination of the strengths of each form. The TicQR design aims to bridge the physical-digital document gap in a manner that is minimally intrusive to the user. The system allows people to read a paper document, mark which parts they are interested in, and archive them digitally by taking a single photograph using a standard smartphone handset (see Fig. 1). This approach allows multiple 'clippings' on a page to be recognised and interpreted simultaneously, then presented to the user for browsing or later use. We envisage many scenarios where TicQR could be useful, some of which are illustrated later in Fig. 2.

Related Work

Research into connecting physical and digital media is well established. An early example is the DigitalDesk [START_REF] Wellner | Interacting with paper on the DigitalDesk[END_REF], which combined a desk, and a camera and projectors mounted above, to provide digital augmentation of paper documents. A paper document was placed in a fixed location on the desk, and text was extracted using OCR, allowing cut-and-paste from paper into a digital medium. The DigitalDesk showed the potential benefits of linking print and electronic formats, but required a precisely controlled, calibrated environment. Digital paper and pens are a more direct combination of printed and electronic media, typified by Anoto's digital pen technology1 . PaperPoint used Anoto to support real-time annotation of on-screen presentations using a printout of the slideshow [START_REF] Signer | PaperPoint: a paper-based presentation and interactive paper prototyping tool[END_REF]. PaperLink [START_REF] Arai | PaperLink: a technique for hyperlinking from real paper to electronic content[END_REF] used a custom video pen to associate annotations with digital content. In contrast, Papiercraft [START_REF] Liao | PapierCraft: a command system for interactive paper[END_REF] used Anoto ink markup of the printout of a digital docu-ment to manipulate the digital original. Using Anoto and similar techniques can allow users to trigger specific digital actions from ink on paper documents. However, augmented, patterned paper is required, and a dedicated battery-powered pen must be used to annotate. Printing must also be carefully controlled so that the right layout is associated with each piece of paper.

The a-book [START_REF] Mackay | The missing link: augmenting biology laboratory notebooks[END_REF] also uses dedicated equipment to link paper and digital items. The system makes use of a graphics tablet placed under a paper document to allow manipulation (e.g., linking, searching) of handwritten content via a second display. Each of these systems demonstrates the potential for rich interaction and effective usability when using dedicated hardware. However, the associated costs and constraints impact on both developers and users. In response to such approaches, researchers have proposed solutions that use simpler, commonplace technologies, therefore allowing more individuals, organisations and communities to use such techniques.

One common contemporary example is QR codes, which allow direct links to digital material via a standard mobile phone camera. Scanning a QR code typically provides a single piece of information, however -for example, a single contact or a web link. If multiple pieces of information are required, then the user will need to scan multiple codes, or follow web links. Previous solutions to this issue have used one code or other identifier per page of media and then automatically downloaded all information from the page 2 . This approach could easily result in downloading unwanted information, and cause higher user task loads as this content is filtered out.

It is well documented that paper is the preferred medium for annotation (e.g., [START_REF] Marshall | Reading and Writing the Electronic Book[END_REF][START_REF] O'hara | A comparison of reading paper and on-line documents[END_REF]) and other small-scale information work. Our approach takes advantage of this fact, and allows users to mark on the document itself to select items. The mScan project [START_REF] Dell | Digitizing paper forms with mobile imaging technologies[END_REF] also uses camera phones and users' marks on paper, but to scan a specific, preset form with multiple-choice bubble fields, that is placed in a known position and orientation. While encouragingly reliable, the mScan format only supports very specific marks for data gathering. A dedicated stand is also required to fix the location of a form for analysis, much as with the DigitalDesk (cf. [START_REF] Wellner | Interacting with paper on the DigitalDesk[END_REF]) or a standard flatbed scanner.

To summarise, in contrast to dedicated equipment approaches, our technique uses QR codes to identify documents, and requires only a standard mobile phone camera for image processing. Our approach can also be used on-the-go, allowing the user to browse their clippings in a more 'laid-back' [START_REF] Jones | Using a mobile device to vary the pace of search[END_REF] manner than previous QR-powered document scanning designs. Finally, like PapierCraft, Paperpoint and the DigitalDesk, the TicQR technique allows richer physical-digital interaction with paper documents.

3

The TicQR system

The TicQR system offers richer experiences with physical documents by allowing people to tick items they are interested in on the paper itself. Our approach uses a combination of precisely-placed QR codes and image recognition to enable the system to determine both which document has been scanned; and, which checkboxes within the document have been selected. Fig. 2 illustrates several example usage scenarios and corresponding QR code-augmented paper documents that we have created Sally is reading a newspaper while waiting for a bus. She has read several interesting news stories and has also spotted an advert for a book she would like to buy as a gift. Using a regular pen, Sally ticks the useful news stories and book advert on the newspaper and takes a picture of the entire page using her mobile phone camera. Putting her phone away and leaving the newspaper on the seat, she heads on her way. Later that evening, she opens the TicQR app and checks her clippings library. Inside, she nds that a digital copy of the news stories and advert she ticked have been automatically downloaded and added to her library for easy browsing and manipulation. Sally now has an archive of news clippings and a link to the online retailer that was advertising the book.

Alex is planning a dinner party and needs to purchase several fresh ingredients. Earlier that week, he remembers an advert that was posted through his letter box from his local store. This yer consisted of a list of the products available with tick boxes alongside them. Alex reads through the paper list and ticks all the items he requires. He gets out his phone, takes a picture of the yer and goes to get ready. A short while later, Alex walks to his local shop where his basket of goods is there waiting to be paid for and collected.

It's Saturday night and Nathan and his friends want to order take-out for dinner. Deciding on Chinese, the group sift through the pile of take out menus they frequently get posted through their door and select one augmented with TicQR. They proceed to tick the items and quantities they want from the menu and complete the order by taking a photograph with the TicQR app. Using the address information Nathan added when he downloaded the application, the local take-away delivers the food to his door.

Scenario 1: Newspapers

Jill does one large online supermarket delivery every week. The interface of the supermarket website allows her to save her recurring items in a list for easy reordering, and has recently added TicQR functionality. The website allows her to print a TicQR enabled list of past items which she then sticks on her fridge. When something she regularly uses runs out, she immediately ticks the box on the paper list so she does not forget later. At the end of the week, Jill takes a picture of the list which automatically adds the items she requires to her online order. for the TicQR system. To retrieve digital content from a paper document, the user first positions their cameraphone to take a photo of the item. The TicQR application automatically takes a photograph when it detects two QR codes which are positioned at opposite corners of the object -one at the bottom left and another at the top right (see Fig. 2). The bottom left code contains the identifier for the item (e.g., the issue and page number of a newspaper), and the top right code is used for image alignment and coordinate calibration. Using the identifier from the QR code, the application queries an online database to retrieve the item's metadata, which contains the approximate coordinate of each of its checkboxes.

The current setup requires that the server side (for example, a newspaper publisher) provides a web service that the TicQr application can query to determine checkbox positions, as well as the content that should be attributed to the selection of each checkbox. If at the time the photo was taken there is no internet connectivity, the application simply saves the photo and performs these operations when a connection is available.

When the item's metadata has been downloaded, the image is then processed to determine if any of its boxes have been marked. When a list of marked boxes has been generated, the application performs actions based on the specific items selected (see Fig. 2 for examples). 3 Any downloaded content is saved locally in the application's clippings repository for later use (see Fig. 1 and Fig. 3). All processing happens in the background of the application -we currently use the OpenCV 4 library for checkbox processing, which takes less than one second to complete.

Evaluation

We performed a lab study in order to help understand both the TicQR system's recognition accuracy and its reception by users. 33 participants (16M 17F, aged 18-53) took part in individual 30 min trials. The metrics used were the accuracy rate of tick box detection, and qualitative data in the form of interview responses.

Prototype Media

We selected two types of prototype media to use in the evaluation -a newspaper (as described in Scenario 1 in Fig. 2), and a shop order form (as described in Scenario 2 in Fig. 2). The newspaper was chosen as its form offers a wide selection of different clipping types (e.g., articles, products, events), and typically includes several types on a single page. The mock-up newspaper used in the study included five news stories, one event advert, one product advert, one URL and one contact. The shop order form used was designed as an extensive product list, which allows consumers the freedom to order specific quantities of a particular product, but also has the benefit of "stresstesting" the recognition system with a closely-spaced grid of checkboxes.

Procedure

At the start of each session the participant was welcomed and led through an ethically-approved consent procedure. Following this, the system was demonstrated once to the participant, and they scanned an example pre-ticked document as a form of training. We explained the two use case scenarios that would be examined in the study to provide participants with a context in which the system could be used. Participants were then given three identical blank copies of each type of prototype document (i.e., six documents in total), and asked to mark a selection of boxes of their choice. After ticking any number of boxes on a form, participants used the TicQR application to take a photograph of the document and either navigate the clippings library (newspaper), or order the list of marked products (order form). Participants were not told which boxes to mark, nor were they instructed on how to mark them (e.g., whether to tick, cross, scribble etc.). We recorded the accuracy rate of the system's checkbox recognition based on the total number of boxes marked, and the number of false positives (i.e., un-ticked boxes detected as ticked) and false negatives (i.e., ticked boxes not detected). To conclude the study we conducted a short semi-structured interview to gather participants' existing document markup behaviours and their opinions of the TicQR system. The participant was then given a gift voucher as token of our appreciation.

Results and Discussion

Robustness A total of 1324 ticked boxes were recorded over all participants in the study (an average of seven per document). The overall checkbox recognition accuracy was 98.2%. Of the incorrectly recognised checkboxes, 17 were false positives (1.28%) and 7 were false negatives (0.52%). These mis-recognised boxes were rarely due to problems with the algorithm used to detect user marks, however. The majority of false positives were caused by factors which were out of our control, including the way in which participants marked up the paper documents -for example, when the end of a tick from one box inadvertently passed through another (see Fig. 4 (a) and (b) for examples taken from actual study participants).

Another minor issue that caused some of the false positive results during the study involved the way in which participants took the initial photograph. That is, if the photograph was taken when the image was slightly rotated, this could mean that some checkboxes at the edges of the document were only partially included in the photograph. The checkbox recognition algorithm used for the study ignored boxes which were completely outside the image, but detected boxes partially outside the image as ticked (we have since refined the algorithm to mark partial boxes as unticked). Of the 17 false positives observed, 9 were as a result of participants' marks running through multiple boxes, 4 were caused by the corners of the box being occluded due to participants rotating the camera, and a further 4 were true false positives. Several of the false negatives recorded were due to participants intentionally trying to fool the system. For example, the mark shown in Fig. 4 (m) was drawn by a participant who stated immediately after drawing it "let's see how well it gets this one", while another with a similar marking stated "I want to see if I can break the app". That said, however, the system was able to pick up on the majority of users' marks, regardless of how they were drawn. Fig. 4 (c-n) illustrates a representative selection of marks observed during the study, ranging from ticks, to lines, to crosses, scribbles and even a smiley face. With the exception of the small dot shown in Fig. 4 (n), all other marks shown were recognised by the TicQR system.

(c) (d) (e) (f ) (g) (h) (i) (j) (k) (l) (m) (n) (a) (b)
The majority of inaccuracies within the study were recorded on the order form rather than the newspaper, and in fact all false positives caused by rotation issues or user marks running through multiple boxes were recorded on the order form. We attribute this to the close proximity of the checkboxes to one another and to the edge of the form. This document was designed to test the recognition of the system, and is therefore not necessarily an accurate representation of a real order form. However, to reduce these issues, checkboxes could be placed further apart from each other, and away from the top left and bottom right corners of the document.

Subjective Responses All participants spoke favourably about the TicQR technique, giving an average score of 8.1 out of 10 (lowest 6, highest 10) for the usefulness of the system. Comments made by participants on the topic included: "I do love my shortcuts so anything to make my life easier is great" "it's very simple and intuitive -I really 'got' it"; "it [TicQR] is great -I often take photos of documents myself to look back at later, so an interactive photo to source things you're interested in is very efficient"; and, "The app does all the legwork for you -you don't have to trawl the internet to find things".

A majority of participants (88%; 29 of 33) reported finding themselves in a situation where they had read something on a physical document and later wanted to locate a digital version. The most common reason for this was to allow them to email, search or archive the digital copy. More interestingly, however, when asked if they did actually manage to locate a digital copy only 21% (6 participants) of these 29 had done so without some level of difficulty. The remainder had either not managed to locate a digital copy at all (14%; 4 participants), only managed to locate it on some occasions (44%; 13 participants), or had found the digital copy only after some time or effort (21%; 6 participants). Some even described alternatives for locating a proper digital version such as taking a photograph of the physical document for later reference (21%; 6 participants).

Conclusions and Future Work

The TicQR technique enables automatic downloads of user-selected digital content from a paper document. While previous mobile phone-based methods required either the use of a search engine to locate related digital material, or the download of a complete package of digital content via a single QR code, TicQR affords the freedom to select only the information required via marks on the physical medium itself, and downloads selected content automatically in a single step. In contrast to previous interaction techniques, TicQR uses a standard cameraphone, which can be exploited with a much lower investment by individuals and small organisations.

Our prototype and user study demonstrate that the TicQR technique is practical and effective both technologically and in terms of usability. We have evaluated two concrete use cases for the TicQR technique, and provided several supplementary scenarios where it would also be beneficial. TicQR is thus a powerful and affordable tool for delivering richer interactive services than many existing techniques.

Our next step is to collaborate with a local produce market to provide a TicQR augmented ordering system. We hope that a longitudinal evaluation such as this will provide a fuller picture of the benefits of the system, and show how the combination of physical documents and digital ordering can provide richer user interaction.

Fig. 1 .

 1 Fig. 1. Using TicQR to interact with a newspaper. Left: reading a newspaper, finding and then ticking interesting content. Right: browsing saved items at a later time.

Fig. 2 .

 2 Fig. 2. Potential usage for the TicQR system. For scenarios 1-3, a TicQR-augmented paper document is also shown. Scenarios 1 and 2 were evaluated in our study.

Fig. 3 .

 3 Fig. 3. Example TicQR interfaces. Left: a selection of newspaper clippings; Middle: a grocery order from a local market; Right: a sample order from a take-away menu.

Fig. 4 .

 4 Fig. 4. Sample tick marks made by study participants. Top: participants occasionally ticked multiple boxes with one tick. All other marks except (n) were recognised correctly.

Veg Spring Roll £1.40 Crispy Duck Rolls (2) £2.20 Spare Ribs Szechun Style £4.90 Pork Balls in Chili Sauce £4.50 Prawn Crackers £1.30 Seasame Prawn Toast (12) £2.80 Hot Thai Fish Cakes (4) £3.40 Garlic Mushrooms £3.10 APPETIZERS SOUP RICE CHOW MEIN CURRY CHICKEN BEEF PORK Chicken Noodle Soup £2.00 Chicken & Mushroom Soup £2.00 Tom Yum Goong £3.00 Won Ton Soup £2.40 Boiled Rice £1.90 Egg Fried Rice £2.30 Special Fried Rice £3.60 Thai Coconut Rice £4.10 Mixed Veg Rice £3.10 Plain Chow Mein £2.90 Mushroom Chow Mein £3.40 Beef Chow Mein £4.10 Chicken Chow Mein £4.10 Chicken Curry £3.90 King Prawn Curry £4.70 Beef Curry £3.90 Chicken with Mixed Veg £4.00 Chicken with Mushroom £4.00 Chicken in Oyster Sauce £4.80 Kung Po Chicken £4.80 Chicken Satay £4.80 Beef Peking Style £4.80 Beef with Ginger £4.70 Crispy Beef £4.80 Salt & Pepper Beef £5.10 Beef with Onion £4.10 Char Sui with Mushroom £4.10 Sweet and Sour Pork £4.20

	Market Store
	FRUIT
	Bananas (£0.20/ea)	1	2	3	4	5	6
	Apples (£0.30/ea)	1	2	3	4	5	6
	Oranges (£0.30/ea)	1	2	3	4	5	6
	Pears (£0.35/ea)	1	2	3	4	5	6
	Lemons (£0.30/ea)	1	2	3	4	5	6
	Limes (£0.25/ea)	1	2	3	4	5	6
	Grapes (£4/kg)	100g	200g	350g	500g		750g
	Strawberries (£8/kg) 100g	200g	350g	500g		750g
	VEGETABLES
	Potatoes (£1.50/kg)	500g	750g	1kg	2.5kg	5kg
	Onions (£0.90/kg)	200g	500g	750g	1kg		2.5kg
	Carrots (£1/kg)	200g	500g	750g	1kg		2.5kg
	Leeks (£3/kg)	200g	350g	500g	750g		1kg
	Mushrooms (£4/kg) 100g	200g	400g	500g		750g
	Peppers (£0.80/ea)	1	2	3	4	5	6
	Cabbage (£0.85/ea)	1	2	3	4	5	6
							1	2	3	4	1	2	3	4	1	2	3	4
							Pancake Roll
							£1.40

2

For example, see kooaba-shortcut.com or augmentation examples such as aurasma.com

See: anoto.com

A video illustrating the technique is also available -see: goo.gl/QBucU

Acknowledgements

This work was funded by EPSRC grant number EP/J000604/2.


Andrea Kohlhase
email: a.kohlhase@jacobs-university.de

Human-Spreadsheet Interaction

Keywords: Spreadsheets, repertory grid, information model of spreadsheets, human-spreadsheet interaction, information objects

Spreadsheets have become very popular tools for analyzing and visualizing data from business and science. To better understand human-spreadsheet interaction, we explore readers' information models, but in contrast to most studies we focus on spreadsheet readers rather than spreadsheet authors. We conducted a study using the repertory grid technique and analyzed the result with the help of a Generalized Procrustes Analysis yielding a deeper understanding of human's information model of spreadsheets. Based on this we envision new human-spreadsheet interactions to increase the readibility and thus, usability of spreadsheets.

Introduction

The intuitive, flexible, and direct approach to computation in spreadsheets has led to widespread use and reuse. In particular, spreadsheets have become very popular to create, modify, and visualize numeric business and science data. In turn complexity and impact increased dramatically over the years. It has been estimated that each year tens of millions professionals and managers create hundreds of millions of spreadsheet programs [START_REF] Panko | Spreadsheet errors: what we know. what we think we can do[END_REF]. This intensity yields not only more and more shared, complex spreadsheet programs, but also high-impact errors on the data level (up to 90% are affected according to [START_REF] Panko | Spreadsheet errors: what we know. what we think we can do[END_REF]) and on the comprehension level (see [START_REF] Powell | A critical review of the literature on spreadsheet errors[END_REF]). The losses caused by formula errors and misinterpretation have even led to an international task force to battle them [START_REF] Eusprig | European spreadsheet risks interest group[END_REF].

Previous Approaches

The standard research addressing such usability problems is based on Panko's influential report on error states and types in [START_REF] Panko | Spreadsheet errors: what we know. what we think we can do[END_REF], that mainly considers the data level, e.g., computational errors based on faulty formulae.

Lewis and Olson gave a critical cognitive psychology account for the success of spreadsheets [START_REF] Lewis | Can principles of cognition lower the barriers to programming[END_REF]. In particular, the barriers to programming are lowered, since the spreadsheet model can be used as visual programming language, enabling programming with low entry costs and early experience of success through effective displays and operations. Consequently, an abundance of research was directed towards enduser programming (EUP), i.e., "programming to achieve the result of a program primarily for personal […] use" [10, p. 4]. Unfortunately, from the point of view of EUP, a spreadsheet user is reduced to an end-user, that is simply any computer user who creates a spreadsheet program.

Spreadsheet Readers as Spreadsheet Users But Nardi and Miller noticed another feature of spreadsheets in [START_REF] Nardi | An ethnographic study of distributed problem solving in spreadsheet development[END_REF]: they are not "single-user applications". In particular, they are used in the work environment on the one hand as collaboration tool on the other as means of communication to exchange and combine domain knowledge and programming expertise. In [START_REF] Hendry | Creating, comprehending and explaining spreadsheets: a cognitive interpretation of what discretionary users think of the spreadsheet model[END_REF] Hendry and Green highlight the fact that spreadsheet use is also a matter of understanding. They report their informants' missing comprehension (even of their own spreadsheet) and trace it to lacking comprehensibility support by spreadsheets, i.e., a specific usability issue for people reading spreadsheets. Such "readers" are, for instance, people that make use of existing templates by simply putting in new data, review data developments on different abstraction levels (like supervisors), assess data to base further decisions upon, want to understand their own spreadsheet program after a while, or look for reusable parts of a spreadsheet program, therefore browsing available ones. This means that an essential part of the spreadsheet user base is not yet addressed by current research. Many reports about bad decisions caused by misinterpretation and difficulties of spreadsheet comprehension confirm this observation (e.g. [START_REF] Chambers | Struggling to excel: a field study of challenges faced by spreadsheet users[END_REF][START_REF] Caulkins | Spreadsheet errors and decision making: evidence from field interviews[END_REF][START_REF] Scaffidi | Estimating the numbers of end users and end user programmers[END_REF]).

Our Approach Sometimes it is said that spreadsheets can be considered data interfaces that display and allow to play with data. Note though that data by itself is not interesting. In particular, Probst et al. suggested in [START_REF] Probst | Wissen managen[END_REF] a knowledge management model. It differentiates information into four distinct traits. GLYPHS are just a set of characters without any structure, combined with a syntax they become DATA, additionally enriched by context they become INFORMATION, and finally, they turn into KNOWLEDGE if a semantic net or a global context is present. The question, in how far readers really consider spreadsheets merely as DATA interfaces, is the starting point for this paper. Moreover, we were interested in the evaluation criteria of readers with respect to a spreadsheet's information value. Based on such an analysis we are able to understand more deeply the information model of spreadsheets and can suggest innovative human-spreadsheet interactions.

Methodology: Repertory Grids and General Procrustes Analysis Spreadsheet readers distinguish interface objects that carry information ("information objects").

To better understand what spreadsheet readers perceive as information units, what meaning they assign to these information objects, and how they discriminate between them, we conducted a study using the Repertory Grid Interview (RGI) Technique [START_REF] Kelly | International handbook of personal construct technology[END_REF][START_REF] Jankowicz | The easy guide to repertory grids[END_REF]. RGI explores personal constructs, i.e., how persons perceive and understand the world around them. McKnight was the first to suggest RGI as a semiempirical method for exploration of an information space [START_REF] Mcknight | The personal construction of information space[END_REF]. By now RGI is a wellestablished method to explore users' personal constructs when interacting with software artifacts (see [START_REF] Tan | The repertory grid technique: a method for the study of cognition in information systems[END_REF] for a list of examples). A crucial advantage over other methods is that a small sample size can be used.

A repertory grid is a grid consisting of "elements", i.e., the objects under consideration, and "constructs", i.e., pairs of antithetical properties that separate elements. The constructs serve as a bipolar dimension on which the elements are evaluated. Elements as well as constructs can be elicited from the test persons themselves or can be provided by the interviewer. Comparison of multiple repertory grids is simplified if the individual ratings are given on a fixed set of elements or/and constructs, but a free elicitation explores the cognitive space. For our main RGI we decided to fix the set of elements, but to elicit individual constructs to better understand the information space.

We analyzed the repertory grid data obtained in the main study with "Idiogrid" and followed the analysis as described by Grice in [START_REF] Grice | Generalized procrustes analysis example with annotation[END_REF]. In particular, we performed Gower's "Generalized Procrustes Analysis (GPA)".

2

The RGI Study 1 In a first RGI we explored which information objects were discerned by spreadsheet readers in common spreadsheets. From this we extracted the most relevant ones to be included in the fixed set of elements for our main RGI study (see Table 1). Note that "diagrams" are missing, which may be due to the fact, that they were not part of our standard spreadsheet example. To broaden this set of elements, we added information objects which are not traditionally used in spreadsheets (see Table 2). In particular, we looked for such objects that contain spreadsheet-related information not usually available to spreadsheet readers. For this we made use of the semantic spreadsheet extension "SACHS" [START_REF] Kohlhase | Towards user assistance for documents via interactional semantic technology[END_REF]. The union of both sets of information objects were used as the given, fixed set of elements, for which in this RGI study constructs were to be elicited by the interviewees.

Table 1. Common Information Objects of Spreadsheets

Interview Procedure In the study we presented each subject a simple, but complexly structured spreadsheet. Each element was explained by the interviewer and SACHS was introduced where necessary. Following traditional RGI, the interviewee was then 1 A full description can be found at http://jpubs.jacobs-university.de/handle/579/2453.

Title

A phrase describing the content of the spreadsheet Headers A (short) phrase supporting the interpretation of values of a regionally close range of cells (e.g. a column header)

Legends

A list of content properties and resp. layouts (as in a map legend)

Values

The content of a cell container Formulae A computational rule that yields a cell value (sx:)ColorCoding The use of color hinting at additional information Tables A possibly multidimensional homogenous structural layout of cells, that is perceived as an object of its own handed three randomly selected element cards and asked to name one way in which two of the selected elements -considered as information objects -are similar or different from the other one. The label for the sameness was noted in the grid as left row header (the emergent pole), the label for the difference as right row header (the implicit pole) -yielding a construct. Then all elements were evaluated with respect to this construct with a binary rating scale: does this element rather belong to the implicit pole or the emergent pole?

Table 2. Extra Information Objects of Spreadsheets

Interview Summary For our investigation we interviewed 14 people, of which 10 were male and 4 female. The age distribution was the following: 5 persons were under the age of 20, 6 between 20 and 30, 2 between 30 and 40, and 1 between 40 and 50. One subject had authored spreadsheets on a professional basis, 4 subjects were familiar with authoring simple spreadsheets, the other 9 only had occasional contact. All were explicitly asked to take up the role of a spreadsheet reader. Their background and education varied, but 3 were familiar with the MS Excel add-in SACHS before the interview. The rating scale was binary. In 1,5 to 3hr sessions participants reported an average of 8.2 construct pairs (SD = 1.4) ranging between 5 and 11 pairs. A total of 115 constructs were elicited.

The first component of our GPA returned a rather high similarity (.68%). It was tested for statistical significance with the help of a randomization test based on 500 trials, which yielded an observed proportion p ≤ 0.00 -verifying statistical significance. A subsequent standard Principal Components Analysis (PCA) produced {PC 1…11 }. The first component explains ca 33.7%, the second 22.2% and the third 14.4% of the variance in the data. To approximate the meaning of the PCs, we looked at elicited similar -i.e., more salient (84%) -constructs and determined dimensions that can serve as common denominator constructs. As a result the PC 1 dimension is interpreted to range from "DATA Tool" to "KNOWLEDGE Tool" (interface perception), PC 2 aligns to "Represented DATA-Implicit KNOWLEDGE" (info perception), and PC 3 differentiates between spreadsheet use by authors or readers. The reliability of this qualitative analysis was ensured by following the procedure given in [8, 155ff.]. A node in sx:DependencyGraph representing a dependent subconcept, that additionally serves as a link to corresponding spreadsheet cells

Towards an Information Model of Spreadsheets

Fig. 2 visualizes the element distribution according to the PCA, which we will discuss in the following. The x-axis corresponds to the interpretation of PC 1 as readers' perception of the interface, the y-axis to PC 2 as their perception of information.

Fig. 1. Interpretation of Results

Perception Dimensions Our interviewees perceived information objects differently when considered as tools (interface perception) or with respect to their information content (information perception). As tools, e.g., two sources can offer the same kind of information (Tables and sx:Localized Info provide INFORMATION), but with respect to their content they can be rated quite differently (Tables represents information as DATA whereas sx:Localized Info provides it as KNOWLEDGE).

Role Specificity Our investigation showed certain information objects strongly associated with authors vs. readers. Interestingly, this indicates that readers only consider formulae (calculation), values (database data), tables (database views) and block arrangements (structural design) as creative options for the author. All the other information is intrinsically determined by the other elements. This suggests automation opportunities for spreadsheet applications of the future.

Information Environment The information services offered by the SACHS extension and common spreadsheet applications do not overlap in the perception of readers. We can even acknowledge a progression between these element sets, where the common element set from Table 1 serves as a DATA-to-INFORMATION interface, whereas the SACHS set from Table 2 provides an INFORMATION-to-KNOWLEDGE interface (see Fig. 2).

Neighborhood of Information

The position of information sources inside or outside the frame of the application was explicitly observed by our interviewees. Elements were clustered according to the position of their respective point of reference.

Metaphoric Boundaries

In office suites the desktop metaphor prevails: Documents (like text files) are managed and can be accessed via players (like text processors). A player "plays" data, whereas a document "documents" data. For spreadsheets this very distinction by readers is rather surprising, as neither spreadsheet programs(!) are typical documents nor spreadsheet applications(!) typical players. Moreover, the desktop metaphor is rather limiting For spreadsheets, since the context-dependency of numbers is neglected. Finally, for readers the document/player metaphor is also restrictive as from their perspective the main purpose of spreadsheets consists in their communication, not in their documentation functionality.

Innovative Human-Spreadsheet Interactions

Based on the found dimensions we like to suggest new interactions to increase the usability of spreadsheets especially for readers:

1. The perception of distinct dimensions of information objects points to a frequently neglected media-theoretic topic that also concerns spreadsheets: Information objects are media and as such they do not only contain a message, they also are the message [START_REF] Mcluhan | Understanding media: the extensions of man[END_REF]. When using e.g. the information object Tables, then input data are perceived as DATA by readers. As DATA they need a context to become meaningful, but at the same time Tables as a structured, formal notation carries a 'truth' statement. Therefore, readers trust the information they get, even though the information object itself delivers no context to turn the DATA into INFORMATION. As a consequence authors should be compelled to create context, e.g. respective Headers or Legends if the spreadsheet is meant to be distributed, and readers should be required to understand the context before interpreting the DATA. The former is realized in many spreadsheet extensions/applications already, but the latter is not. 2. The perceived differentiation of spreadsheet users into authors and readers allows a much better fine-tuning of services. Even though the existence of both groups has been recognized, the interface design for players has not yet seriously taken this distinction into account. We will need more role-specific information services for readers. If readers, for instance, want to understand specific parts of a spreadsheet, these parts could be rendered separately on the fly as a spreadsheet view. This can reduce the cognitive overload when interpreting numbers in a big spreadsheet, particularly if information is scattered over multiple worksheets. Another reader specific service consists of a better navigation within spreadsheets, e.g. a semantically driven navigation as already prototypically presented with CogMap [6] or with SACHS' semantic navigation [START_REF] Kohlhase | Towards user assistance for documents via interactional semantic technology[END_REF]. 3. Our interviewees distinguished between information environments that turn DATA into INFORMATION and ones that turn INFORMATION into KNOWLEDGE. This induces the question how we can further enhance a data interface with "meta level" information objects. For instance, we could provide a reader access to the provenance of data or we could help the reader to assess information. 4. Following a communication metaphor for a reader, a communication mode of spreadsheets can be enabled, that provides on the one hand access to document-specific experts, background ontologies, or fora and on the other hand access to topic-driven discussions, domain knowledge e.g. in standard financial text books, help fora, or other domain services. 5. If we set the document/player metaphor aside then spreadsheets can also make use of already developed, open-standard, but non-spreadsheet-specific format guidelines: mathematical formatting of formulae. 2 For this, we can imagine a math editor and viewer, which takes input e.g. in LaTeX form -commonly used by mathematicians (which are typically non-programmers) for writing complex formulae -, converts it into MathML and renders it for reading in a browser window in standard mathematical notation. As our study indicated a neighborhood-of-information framing, we envision the window to be close to the cell for which such a formula is created.

Note that many of the envisioned interactions may be generalized to other office suite members to improve readability, that is, the communication aspect.

Conclusion

Interpretation and comprehension of spreadsheets constitute a rather neglected usability issue in research concerned with spreadsheets. In this paper, we presented a repertory grid study and subsequent General Procrustes Analysis that explore qualitative properties of information objects in spreadsheets from the point of view of spreadsheet readers. We discussed five framings of information sources in spreadsheets that readers perceived: Perception Dimensions: Interface vs. information perception, Role-Specificity: Information objects for authors vs. readers, Information Environment: From DATA to INFORMATION with e.g. MS Excel, but from INFORMATION to KNOWLEDGE with e.g. SACHS, Neighborhood of Information: Positioning of information sources inside or outside the frame of the application, and Metaphoric Boundaries: A desktop vs. communication metaphor. These dimensions of information from the readers' point of view represent relations between the set of information objects. Thus, they can serve as a first information model of spreadsheets and based on this we envisioned some innovative forms of human-spreadsheet interaction in the last section. As our study was only exploratory, we cannot conclude this information model to be complete. Nevertheless, it has become clear by this study that readers have their own interesting perspective on information offered in spreadsheets.

All in all, the information model of spreadsheets (by readers) presented in this paper is the entry door for a better, more complete understanding of human-spreadsheet interaction and a new source for according design inspirations.

  sx:LocalizedInfo A local look-up (data and text) of relevant information for cells on a by-cell-click basis sx:FunctionalBlock A local border indicating all cells functionally associated to the currently selected cell sx:DependencyGraph An overview graph (in a different window) of concepts showing on which the corresponding (selected) cell is ontologically dependent sx:RelationalArrows An arrow indicating a dependency relation between concepts in sx:DependencyGraph sx:ConceptNodes

We are fully aware that this might not be the best for a spreadsheet author, even though for complex formulae the typical spreadsheet formula language is not visual enough.

Acknowledgements This work has been funded by the German Research Council under grant KO-2484-10-1.