Automaticity and the notion of interference

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Automaticity and the notion of interference

Assessing word reading automaticity as freedom from interference in a Visual World Paradigm

Dzan Zelihić

Master’s Thesis in Special Needs Education Department of Special Needs Education

Faculty of Educational Sciences

Spring 2020

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“If you always put limit on everything you do, physical or anything else, it will spread into your work and into your life. There are no limits, there are only plateaus, and you must not stay there,

you must go beyond them”

- Bruce Lee

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Abstract

Efficient word processing requires rapid activation of phonological and semantical codes, assumed to be achieved by developing automaticity at the word-level. Researchers have by this definition conceptualized automaticity as a component of speed, facilitating the rate at which individual words could be recognized. Although speed is undoubtedly a valid index of word reading automaticity, it overlooks an important factor. When we read, we do not see words in isolation, but in the presence of other words. Skilled readers do not process individual words one by one, but in parallel with other words. Simultaneous processing entails that individual words are processed attention free, not being susceptible to

interference. However, if attention is required at the word-level, then parallel processing is assumed to be challenging due to interference from adjacent words. The aim of the present study is to develop a new measure of word reading automaticity to investigate the idea that a word is read automatically to the extent it is not susceptible to interference from adjacent words. Considering the possibility that measuring lexical activation in the context of other words might provide a better index of word reading automaticity, as opposed to measures utilizing single word presentations.

Method

Subjects were 62 students and nonstudents (M = 25 years, SD = 3.20) with no reading or learning difficulty (established by self-report). To assess word reading automaticity, the present study incorporated an Eye-tracking experiment, introducing a masked and flanked presentation of words in a Visual Word Paradigm. The experiment featured a total of 120 trials (with and addition of six practice trials), divided by three blocks of 40 trials each. The target appeared in one of three conditions for a duration of 75ms. The conditions consisted of presenting the target being flanked bilaterally by either nothing (baseline), nonverbal symbols (%%) or other words (e.g., pan dog duck). The target word corresponded to one of four pictures displayed on a computer screen. Participants were required to click on the picture depicting the target word, while their gaze was tracked to see how quickly they fixated on the correct picture.

Results

The results showed that the rate of lexical activation for words presented in the Word flanker condition, differed significantly from the Baseline and Visual flanker condition. Participants

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spent on average significantly less time fixating the target image within the Word flanker condition for both high and low frequency words, due to interference from adjacent words.

Suggesting that an automatic process is to some degree susceptible to spatial interference and does involve attentional processing.

Conclusion

Current findings present a valid case for the argument that high-level word recognition automaticity is to some extent susceptible to interference. However, the present study

included only a limited sample of skilled readers and may not have uncovered the true effect of interference from adjacent words. Considering that it would require a larger sample with additional comparisons between skilled and less skilled readers. In sum, based on current results. I propose that the importance of automaticity should go beyond the role of speed and address automaticity as a resource-based approach.

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Preface

First and foremost, I want to express my gratitude to professor Athanassios Protopapas. No amount of words can describe how grateful and fortunate I am to have you as my supervisor for this thesis. Your immense knowledge has inspired me to develop my own thinking and accomplish things I never thought I would have accomplished on my own. Thank you for giving me the opportunity to be a part of such an amazing project, and all the support you have provided me throughout this period. I owe acknowledgement to my Eye-tracking instructor Laoura Ziaka, thank you for sharing your knowledge on the technicalities of the Eye-tracker, training and preparing me for my first real experiment. I appreciate that you always took the time to assist me with additional questions whenever I was in need. I want to thank my fellow student Caroline Nordlie for her involvement in the project, making sure we could deliver our best. Your cooperation was highly appreciated!

Thank you, professor Bob McMurray and Keith Apfelbaum for providing an extensive list of images which we could implement and utilize for the experimental task. I also wish to thank Kelly Nisbet for scheduling an Eye-tracking session with me upon her visit to Norway and the University of Oslo, I learned a lot of useful tips!

I am forever grateful to all the participants who took part in this study. Thank you for taking time of your busy schedule, this would not have been possible without your involvement.

From the bottom of my heart, I appreciate each and every one of you.

Finally, I want to thank my family for their support and motivation to never give up. I specifically want to thank my brother Deniz Zelihić for constantly sharing his advice, aspiring me to push forward. To my classmates, thank you for the memories and company throughout my masters.

Oslo, June 2020 Dzan Zelihić

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1 Introduction

1.1 Background and purpose of this study

Seidenberg (2017) philosophically quoted that being an expert reader doesn’t make you an expert about reading. There is an entire science field devoted to understanding this

multifaceted skill at levels that intuition cannot easily penetrate. Reading is among the highest expressions of human intelligence and the human culture has evolved to the point where this skill is critical for our ability to thrive. For most of human history people were considered to be illiterate and yet functioned well enough in society, but that is not the case for modern society. The spoken language evolved in humans well before writing was invented and children’s development resembles this. Their use of the spoken language

precedes that of reading and writing, reading is therefore considered a highly complex skill to develop (Rayner, Pollatsek, Ashby & Clifton, 2012).

There are various theories, definitions and models which attempt to explain the complex phenomenon of reading. The simple view of reading initially presented by Gough and Tunmer (1986) proposed that reading is composed of two main components. That is, word recognition and linguistic comprehension. Both are necessary for successful reading, neither being sufficient by itself (Hoover & Gough, 1990). The theory assumes that there are specific skills required in order to deal with written language. The first relates to word recognition, the ability to accurately identify printed symbols. The second relates to linguistic

comprehension, the ability to successfully derive information from printed symbols and understand language. The initial stages of reading development focus primarily on the development of word recognition skills for successful comprehension. As readers develop and read difficult linguistic texts, attention transitions from decoding toward the aspect of comprehension. Text comprehension is assumed to require a great deal of attentional resources, that are of limited supply (Adolf, Hugh & Little, 2006). The rate at which words are recognized could potentially influence the success of comprehension. If a great deal of attention is devoted toward word processing, then not enough recourses are left for

comprehension. Ultimately, the universal goal of reading is to understand and if comprehension is to effortful, then reading is not an enjoyable task.

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However, to efficiently reduce the amount of attentional requirement that is necessary for word processing, readers need to achieve a certain level of word fluency. That is, developing automaticity at the word-level, facilitating rapid and effortless processing of individual words without attentional involvement. When word processing becomes automatized, then

attentional resources could be allocated toward semantical processing (LaBerge & Samuels, 1974; Logan, 1997). However, despite the acknowledgement of automaticity in the context of fluent reading, there are surprisingly few studies who actually propose to or can measure it independently. A study conducted by Roembke, Hazeltine, Reed and McMurray (2018) measured word reading automaticity on single word presentations, but assessing word reading automaticity for words presented in isolation, is arguably not a valid index of automaticity. Taking into account that under normal reading conditions words are not displayed in isolation, rather the opposite. Thus, measuring word recognition on isolated words does not capture the true essence of word reading automaticity. The purpose of the present study is to develop a new measure of word reading automaticity assessed in the context of other words. Based on the hypothesis that adjacent words are assumed to interfere with the processing of a fixated word, when word recognition is not automatic. Non-

automatic processes cause readers to deplete valuable resources, limiting their attentional capacity to process words in parallel. Although some evidence implies that crowding, letter flanking and inter-word spacing may cause interference and influence recognition of a central word, no study has measured this in a task closer to normal reading (Bouma, 1970; Eriksen &

Eriksen, 1974).

1.2 Research question

The aforementioned hypothesis has led to the following research question:

“To what extent does the presence of adjacent words affect the rate of lexical activation in visual word recognition”

The research question intends to investigate the idea that a word is read automatically to the extent it is not susceptible to interference from adjacent words. More specifically, if adjacent words affect the rate of lexical activation.

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1.3 Structure of this thesis

The content within this thesis is divided into five main chapters. Chapter 1 gives a brief introduction into the background and purpose of the present study, subsequently introducing the research question for which the study aims to provide a reliable answer to. Chapter 2 presents a detailed description of the theoretical framework and rationale of the study.

Chapter 3 gives insight into the methodological approach, containing a detailed description of the materials and steps taken in the procedure for running the experimental task. Chapter 4 highlights the major findings, providing further interpretation of the results obtained. Chapter 5 presents a general discussion on new findings in light of the theoretical framework

presented in Chapter 2. Subsequently at the end of chapter 5, I reflect on and discuss the reliability and validity of the present study.

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2 Theoretical framework

2.1 Reading Fluency

The term fluency was originally derived from the Latin word fluere, which means to “flow”

(Cummings & Petscher, 2016). When thinking of the word “flow”, I relate it to something that moves or behaves effortlessly within a coherent manner. Much like how a professional basketball player dribbles the ball, or how a musician plays an instrument.

The concept of fluency has been widely used in the context of defining skilled reading, with respect to how written information is processed. For longer than a decade there has been an ongoing debate in the literature, and a lack of agreement on what exactly promotes the ability to read text fluently. The general consensus amongst researcher’s regard fluency as a critical component of skilled reading (Wolf & Katzir-Cohen, 2001; Hudson, Pullen, Lane, Torgesen, 2009; Kuhn, Schwanenflugel, Meisinger, 2010; Rasinski, Reautzel, Chard, Thompson, 2011).

Further, indicated by its definition, “the ability to process text quickly, accurately and with proper expression” (National Reading Panel, 2000). The literature highlights two main criteria underlying fluent reading. The first criterion is strongly related to automatic word recognition. Automatic word recognition refers to the transition from decoding words to recognizing print by sight. Ehri (1995) argued that the key to acquiring sight word reading lies in developing full knowledge of the alphabetic system. The alphabetic system links connections that can be formed between graphemes in spelling and phonemes in the

pronunciation of words. Alphabetic connections enable readers to store thousands of words uniquely in their mental lexicon, by accessing phonological and semantical codes of these words accurately and automatically. If words and the sounds they represent are not

recognized automatically, the whole decoding process will suffer and become less efficient (Hudson et al, 2009). Developing automatic word recognition also facilitates the ability to read text with proper expression. Prosody implies reading text with appropriate intonation, combined with phrasing. As children become more fluent, they make shorter and less

variable pauses, have larger pitch declinations and display a more adultlike intonation (Kuhn et al, 2010). Although prosody is undoubtedly an important aspect of fluency and overall reading ability, it will not be discussed in further detail in this thesis. Mainly due to the aim of the present study being limited to word recognition.

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The ability to read text fluently is considered to be a highly complex and multifaceted skill.

The complexity of reading makes it unclear within the literature on what exactly constitutes the development of fluency. What most researchers seem to agree on, is that the ability to process text fluently involves automaticity at the sub-lexical and lexical level. To understand how automaticity is acquired, researchers have commonly referred to theoretical models underlying the development of automaticity in reading (Wolf & Katzir-Cohen, 2001; Hudson et al, 2009; Kuhn et al, 2010; Rasinski et al, 2011).

2.2 Automaticity Theory

LaBerge and Samuels (1974) and Logan (1997) developed theories on automaticity, in an attempt to present relevant models expanding on the nature of automaticity and the conditions under which it may be acquired. Reading is an example of a complex activity consisting of many processes that must be quickly and accurately coordinated. If enough of these processes become automatic, attentional demands become tolerable and skilled reading is possible.

However, supposing that component processes require attention, it would limit a reader’s attentional capacity and cause difficulties in developing fluency. Automaticity is therefore considered a critical component of fluency, because it helps the reader to free up cognitive load and distribute attention across multiple levels of processing.

Automaticity is often identified as being a well-developed skill, consisting of highly “trained”

processes that operate with little effort and minimal conscious thought. Logan (1997) describes the notion of unconscious processing as looking at a passage and almost see its meaning without much effort or awareness of the processes that produce the intended effect.

Samuels (2006) referred to unconscious processing as facilitating the ability to decode and comprehend simultaneously, indicating that skilled readers are able to operate two difficult skills in parallel. La Berge and Samuels (1974) claimed that beginner readers may not be able to read for meaning, until automaticity is sufficiently developed at the lexical and sub-lexical level. Taking into account that automaticity is important for rapid identification of single letters and recognizing them as whole words.

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2.2.1 The Single-Capacity model

LaBerge and Samuels (1974) argued that humans were limited in their capacity to attend to more than one cognitive task at a time, but we may be able to process several things at a time as long as no more than one requires attention. They further proposed that processes involved in reading developed in two stages. At the accuracy stage, attention is required for successful performance. At the automatic stage, attention is not necessary for successful performance.

LaBerge and Samuels (1974) introduced a model presenting five alternative routes a visually presented word could take as it proceeds toward activating its semantic code. I will highlight two of the five alternative routes.

1. The graphemic stimulus is automatically coded into a visual word code, which automatically activates the phonological code (although this stage can be skipped).

The phonological code automatically excites the semantic code and proceeds to be stored in episodic memory.

2. The graphemic stimulus is automatically coded into two spelling patterns. The patterns then proceed to activate the two phonological codes. The two codes are then blended with attention into the phonological word code. Then attention is required to activate the episodic code. The episodic code is then activated by attention to excite the semantic code.

The main difference between the routes is in the amount of attention that is required for successful processing. The first route operates at an automatic level and is typical for skilled readers. The second route is more resource demanding, because more attention is required at various levels of processing. LaBerge and Samuels (1974) defined automatic processing as a reader’s ability to maintain attention continuously on the meaning units of semantic memory, while the decoding from visual to semantic systems proceeds automatically. They further argued that word recognition is based on learning the distinctive features of letters and words, to prompt unitization. Unitization of letters into whole words is acquired through extensive practice and repetition. Repeated encounters with familiar letter patterns provide the basis for consolidating letters into larger units (Ehri, 1995).

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2.2.2 The Instance Theory

Logan (1988, 1997) proposed a theory which relates automaticity to memory retrieval. He argued that performance is considered automatic, when based on a direct single-step retrieval of past solutions from memory. The theory assumes that novices often rely on an algorithmic approach to solve a task. Each time a specific task is encountered, they move on to discover a variety of solutions required to solve different problems. Multiple encounters with a specific task, facilitate the ability to either retrieve the solution from memory or stick to the computed algorithm. At a certain stage in development, memory retrieval becomes a reliable factor and the algorithmic approach may entirely be abandoned.

The instance theory proposed by Logan (1988, 1997) presents a different view to how written information could be processed. It expands on the transition from an inefficient solution to an efficient one. The theory accounts for three main elements: obligatory encoding, obligatory retrieval and instance representation. First, the theory assumes that encoding into memory is obligatory and unavoidable. All words which have been encountered at some point in time will be encoded, independently of how well or poorly the word was remembered. Second, the theory assumes that memory retrieval is an obligatory and unavoidable consequence of attention, independently of what has been associated with the word in the past. Just by attending to the word is enough to retrieve it from memory. Retrieving a word from memory may not always posit a strong connection, but it occurs nevertheless. Encoding and retrieval are considered to be associated trough attention. The same operational process of attention that causes encoding, is equivalent to what causes retrieval. Third, the theory assumes that each individual encounter with a word is encoded, stored and retrieved separately.

As outlined above, the theory presents a new learning mechanism. Logan (1988, 1997) argues that each experience with a task produces a memory trace or an instance

representation, retrieved as a result of repeated encounters. The number of instances stored in memory increases and facilitates development of a task-relevant knowledgebase. In order for a performance to be considered automatic, it must be based on retrieval of past instances of past solutions to task-relevant problems. Rather than rely on algorithmic approaches which require increased amount of attentional resources.

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2.2.3 Properties of Automaticity

Logan (1988, 1997) proposed a list of properties which mainly distinguishes automatic processing from non-automatic processing. The list contains four properties that are commonly implemented by researchers to define the criteria for automaticity. The main properties are Speed, Effortlessness, Autonomy, and Lack of conscious awareness.

Speed

Automatic processing is considered to be fast and non-automatic processing is slow. Speed is an important criterion because an increase in speed decreases reaction time. Although an exact criterion for how fast an automatic process should be, remains unclear and is not properly defined. Considering that speed varies continuously, depending on the amount of practice with a certain task. According to the power law, reaction time decreases as a function of practice, until it reaches an irreducible limit. A gain in speed is often noticeable early on but diminishes with extensive practice. The power law is considered important because it clarifies that the criteria for speed is relative to automaticity. Performance is considered to be faster after ten trials than after one, suggesting that a performance becomes more automatic with repeated encounters. When applied to reading, high frequency words are processed more rapidly than low frequency words. Taking into account that high frequency words are

encountered and practiced more often.

Effortlessness

Automatic processing is considered to be effortless and non-automatic processing is effortful.

Effortlessness is defined by a sense of ease in the ability to do another task while performing an automatic one. For example, decoding and comprehending text at the same time. The main idea is that if two tasks can be done simultaneously, then at least one of them must be

automatic.

Autonomy

Automatic processing is considered an autonomous process, it begins and proceeds to completion without intention. Non-automatic processing does not begin and end without intention. Autonomous processing is exemplified within the Stroop effect. The Stroop effect showed that participants who were instructed to name the color of the ink in which words are written, could not stop themselves from reading the words (Logan, 1997).

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Consciousness

Automatic processing is considered to not be available to consciousness, non-automatic processing is. Logan (1997) assumes that we type and read words without much awareness of the processing involved. Beginner readers are considered to be more aware of the steps involved, because they execute them deliberately. Although this theory is difficult to measure, the theory presumes that automatic processing does not give rise to conscious awareness.

2.3 Automaticity as Parallel processing

Researchers have predominantly focused on the efficiency of processing single words as an indication of fluency, often assessed by measures tapping accuracy and rate (Wolf & Katzir- Cohen, 2001; Hudson et al, 2009; Kuhn et al, 2010; Rasinski et al, 2011). At the word level, automatic processing is commonly referred to as the ability to process words by sight. Sight word reading facilitates activation of a words pronunciation and meaning immediately in memory, allowing readers to focus their attention on comprehension rather than word recognition (Ehri, 2014). However, efficiently processing single words as if they were isolated and independent from one another cannot be the only factor indicating automaticity in reading. There have been studies examining processing of items and words in discrete versus serial tasks, as valid measures of fluency in skilled and less skilled readers

(Protopapas, Altani & Gergiou, 2013; Altani, Protopapas, Katopodi & Georgiou, 2019)

2.3.1 Discrete Naming

Discrete naming refers to tasks where items are presented in an isolated format, usually on a computer screen for a set amount of time. Items are displayed either as colours, objects, digits or letters. The metric for the discrete task is measured by the average time it takes to name an item after it is first presented (Logan, Schatschneider, Wagner, 2011). Discrete naming tasks are predominantly used because they offer a “purer” measure of lexical access speed,

reflecting the rapid retrieval of a phonological code from memory (Bowers & Swanson, 1991; De Jong, 2011). Reading isolated words is also a commonly used discrete task, assumed to index a reader’s level of sight word processing. De Jong (2011) argued that the correlation between discrete naming and discrete word reading was higher than that of serial naming. Indicating that discrete tasks specifically tap the ability of efficiently processing isolated items and words.

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2.3.2 Serial Naming

The most commonly known serial naming task is Rapid automatized naming (RAN). RAN is a task involving rapid timed naming of familiar stimuli, such as objects, colours, letters and numbers. The items are presented repeatably in random order, in left-to-right serial fashion.

The key dependent variable is the total time taken to the name the items (Norton & Wolf, 2012). RAN is considered to be a complex task involving more cognitive components, due to the serial format. All items are presented simultaneously, and the reader has to successfully coordinate amongst items in a strict sequence as opposed to discrete tasks. Word list fluency measures are also considered to tap the serial aspect of RAN. Instead of naming digits, children have to read out aloud a list of unrelated words as quickly as possible.

2.3.3 The Difference between Serial and Discrete processing

Discrete and serial tasks including naming and word reading form up distinct dimension.

Studies have shown that RAN performance better predicts performance on word list reading speed compared to measures on discrete word reading for higher graders (Protopapas et al, 2013). Suggesting that efficient processing of individual words alone arguably is not the main indication of fluent reading. Studies have shown that there are some important differences between the serial and discrete format, indicative of their unique relation to reading (Logan et al, 2011). RAN is considered to be a better predictor of overall reading ability when items are presented in a serial format, compared to items presented in isolation (Protopapas et al, 2013). A potential factor separating serial and discrete tasks, is in their capability to effectively measure a reader’s ability to manage multiple items simultaneously.

Protopapas et al (2013) argued that individual word accuracy performance in reading isolated words predicted fluency better in the beginning stages of reading. Beginner readers (Grade 1- 2) typically deal with individual words one at a time, moving on to the next word in a

sequence only after they have completed processing the previous one. However, as readers grow older (Grade 6) fluency measures were more strongly predicted by serial digit naming than discrete word reading. Suggesting that once words are processed more efficiently, managing multiple words in a sequence becomes a dominant factor beyond the efficiency of processing individual words (Altani et al, 2019). As beginner readers word recognition develops and reaches an automatic level, they become more capable to process words sequentially. The sequential aspect of serial tasks is therefore considered to correlate more

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toward a person’s overall reading ability than that of discrete tasks. Figuring that processing items serially involves more cognitive components, similar to what is required for text- reading. The skilled reader deals with multiple words simultaneously in situations like reading a sentence or a passage. Requiring a multitude of brain area systems supported by phonology, morphology, syntax, semantics, working memory, visual and orthographic processes (Norton & Wolf, 2012). Serial and discrete tasks tap many of the same cognitive components, but serial tasks require oculomotor control and coordination among successive items. An ability which is not required for processing items in a discrete format.

2.4 Controlling Eye-movements in Parallel processing

Skilled readers are thought to be better at managing sequences of words simultaneously, based on their ability to obtain information outside the direct focal point (Logan et al, 2011).

Indicating that parallel processing requires additional skills, such as rapid eye-movements and coordination amongst successive words. The ability to process one word while

preprocessing an adjacent word not directly presented in the center field of vision, is arguably dependent on overall reading ability.

2.4.1 The Visual Span

The Visual span for reading refers to the range of letters in a given text that can be

recognized reliably without moving the eyes (Kwon, Legge & Dubbels, 2007). Skilled and less skilled readers extract the same amount of visual information during an eye fixation, but skilled readers have faster access to letter name codes and process information more

efficiently through a memory system. Visual processing is considered to be a critical

component of print reading, due to the size of the Visual span. A larger Visual span facilitates recognition of more letters and longer words in one single fixation. It also facilitates the ability to recognize letters of an adjacent word, if the fixated word is short enough (e.g., Parafoveal preview). If more letters are recognized per fixation, readers are able to make larger saccades which in turn enables them to rapidly and efficiently process text. A study conducted by Kwon et al (2007) investigated the Visual span of school aged children. Their study showed that the Visual span increased in size similar to adults as children’s reading skill developed.

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2.4.2 The Eye-Voice Span

Buswell (1921) hypothesized that the eyes always moved ahead of the voice in reading. The Eye-voice span refers to the distance between the viewed and spoken word. A skilled reader tends to maintain a wider span between the eye and the voice of approximately two words (Inhoff, Radach, Solomon, Seymour, 2011). A less skilled reader tend to keep the eye and voice very close together, not moving the eyes from the word until the voice has pronounced it. The significance of a wider Eye-voice span is that it provides a wider specter for the interpretation of meaning, before the voice reacts. Protopapas et al (2013) theorized that skilled readers process one word while articulating the previous one and simultaneously viewing the next word in line, previewing the one further down, effectively buffering (i.e., temporarily storing) information about the words that have already been viewed but not yet pronounced.

The main assumption is considering that skilled reading arguably does not consist in processing individual words one by one, moving on to the next word in line only after processing the previous one. Instead, skilled readers deal with words in a parallel fashion, an multi word process. Studies have shown that individual word performance does not predict text reading efficiency for readers past the beginning stages (Protopapas et al, 2013). Reading ability was more predictable by performance on serial tasks where items are presented

serially and have to be processed simultaneously. Suggesting that fluency is determined by additional skills, such as managing sequences of words and the ability to successfully move the eyes from one word to another without interruption. Importantly, parallel processing requires that individual words are processed automatically to the extent they are processed as whole units, that is, without attention. If attention is not required for processing at the word level, skilled readers are not only able to process individual words, but they have the ability to deal with multiple words simultaneously without interference. Less skilled readers are limited to single word processing due to extensive use of attention, making them more prone to interference. Studies have shown that skilled readers handle sequences better than less skilled readers due to benefits from parafoveal preview of adjacent letters and words (Logan et al, 2011). However, I hypothesize the opposite for less skilled readers, considering the possibility that adjacent words may hinder rather than facilitate processing when word reading is not automatic.

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2.5 Automaticity and the notion of Interference

Automatic processing of individual words as described by LaBerg and Samuels (1974) and Logan (1997, 1998) is assumed to be free of attention. Repeated encounters facilitate readers to learn the distinctive features of letters and words, prompting unitization. When unitization is developed, words are assumed to be processed by sight (i.e., automatic). Sight word reading requires minimal attention, to the point where attentional resources can be

sufficiently allocated to other processes. Thus, enabling readers to absorb more words to be processed simultaneously.

2.5.1 Limited Attentional Capacity

LaBerge and Samuels (1974) argued that humans were limited in their capacity to attend to more than one cognitive task at a time, but they are able to process several things at a time as long as no more than one requires attention. It is assumed that different stages in processing vary in the amount of attentional capacity that is required. For less skilled readers the issue of parallel processing arises due to attentional capacity being limited to one single area of concentration, overloading attention. Factor in that automatic processes use minimal

attentional capacity (i.e., effortless), they are assumed to run in parallel with other concurrent automatic or non-automatic processes with no interference. Suggesting that skilled readers are able to process a fixated word, while simultaneously preprocessing adjacent words.

However, because non-automatic processes are effortful and require substantial amount of attention, parallel processing is assumed to be more challenging.

For the present study it is hypothesized that difficulties with parallel processing arise due to other words being positioned close to the momentary point of fixation. When reading normal text, other words are positioned both to the right and left of the target word(s), above and below. It is assumed that words present close to the fovea can disrupt or delay the recognition of a central word, when word processing is not automatic. Taking into account that less skilled readers use increased effort when processing individual words, adjacent words are thought to interfere with that processing, overloading attention. Studies examining letter interreference have shown that nearby letters can interfere in processing of a target letter (Bouma, 1970; Eriksen & Eriksen, 1974). Bouma (1970) proposed that letters appearing towards the periphery of the target caused more interference compared to letters closer to fixation. The study conducted by Eriksen and Eriksen (1970) used letters as target items.

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Their experiment consisted of using three distracting letters, which deliberately flanked the target letter from each side (left and right). Their study showed that processing of a target was delayed when flanking letters were assigned to competing responses. For less skilled readers the sense of flanking becomes visible with the parafovea being occupied by nearby words in text reading. Based on this notion, the presence of adjacent words is assumed to delay the rate of lexical activation for a central word processed in the presence of other words.

2.5.2 Studies on Word reading Automaticity

Roembke and colleagues (2018) recently developed a new measure for word reading automaticity, independent from factors such as general speed of processing and prior knowledge of words and letters. Their study featured three experimental tasks Find the picture, Find the Rhyme and Verify. Find the picture involved participants reading a word and selecting its picture from a screen containing four pictures. As the target word was presented orthographically, it required mapping of the written word onto one of the corresponding pictures, competitors were orthographically similar to the target. Find the Rhyme required participants to read a word or nonword and select which of eight printed competitors rhymed with it. Verify was an identification task in which participants heard a word and saw a written word that could either match or mismatch it. Automaticity was assessed by using backward masking. Backward masking refers to the reduction of a targets visibility by a mask presented after the target. Backward masking is used as a tool to

investigate temporal sequencing and various levels of information processing (Breitmeyer &

Ogmen, 2000). Backward masking is commonly used as measure of automaticity seeing that the mask acts to erase visual information or interrupt its further processing. For a reader to achieve strong activation of a target and generate a correct response, it requires rapid activation of semantic or phonological codes before the mask appears. Findings from the study suggests that automaticity potentially is a separate measurable component contributing to fluency. Although speed is undoubtedly an important aspect indexing automaticity, it overlooks other aspects as well.

The study conducted by Roembke and colleagues (2018) measured word reading

automaticity only on single-word presentations. They did not account to measure lexical activation for words presented in the context of other words, a task closer to normal reading.

Under normal reading conditions other words are positioned both to the left and right of a

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fixated word. Assessing word reading automaticity for words presented in isolation is by this notion not assumed to be a strong index of a reader’s overall word automaticity level,

because it limits the ecological validity of the measure. The present study proposes that automaticity should instead be assessed with an experimental task tapping parallel

processing, subsequently introducing the aspect of interference. Seeing that freedom from interference could provide a better estimate of a reader’s overall level of word reading automaticity.

2.6 The Visual World Paradigm

In order to investigate whether automatic word recognition is affected by the presence of adjacent words, the present study developed an experimental task simulating an authentic reading experience. This was done by employing Eye-tracking technology linked with the Visual World Paradigm. Eye-tracking utilizes a close temporal link between gaze and cognition to study automatic processing (Berends, Brouwer & Sprenger, 2015).

The Visual World Paradigm (VWP) is an experimental method in which participants eye movements to real objects and pictures on a display are monitored as they listen to or produce spoken language (Salverda & Tanenhaus, 2017). With computer screens, pictures are

typically used, but some studies also use words (see Figure 1). Researcher are frequently concerned with what point in time after the participant is exposed to a stimulus, a shift in visual attention occurs. The shift in visual attention is typically measured by a saccadic eye- movement to an object or a word.

Figure 1. An illustration of a Visual World experiment with a four-object display and a printed word display (Huettig et al., 2011, p. 153 after Huettig & McQueen, 2007).

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The experimental paradigm was originally introduced by Cooper and Tanenhaus in 1974 (Huettig, Romers & Meyers, 2011). The initial experiment consisted of participants listening to short narratives while looking at a display. The display showed common objects that were referred to in the spoken text, while participants eye movements were tracked. Cooper (1974) discovered that participants eye gaze was drawn to objects mentioned in the narratives.

Participants were, for example, more likely to fixate a picture of a car when hearing the phrase “…suddenly the engine stopped” than a picture of a camera. Fixations to the targeted objects were often triggered before the spoken word was completed. Indicating that visual and language processing were closely timed-locked (Huetting et al, 2011). Expanding on the early studies of Cooper and Tanenhaus (1974), Huetting et al (2011) cite other studies

utilizing the main features of the VWP to study lexical activation in spoken word recognition.

A study conducted by Reinisch, Jesse and Macqueen (2010) examined when during word recognition Dutch listeners use suprasegmental stress information to resolve lexical competition. Their study showed that visual world participants can use lexical stress information to direct eye gaze. They found that when participants heard words with initial stress (e.g., OCtopus), fixations on printed target words with stress on first syllable were more frequent than fixations on differently stressed competitors (e.g., stress on second syllable). The study conducted by Huettig and Altmann (2005) found that participants directed overt attention towards a depicted object (such as trumped), when a semantically related target words was heard (e.g., piano). Their study showed that the probability of

fixating the semantic competitor correlated significantly with the semantic similarity between the spoken word and competitor object (e.g., trumped).

Examples from the studies conducted by Huettig and Altmann (2005) and Reinisch et al (2010), illustrate how the VWP can be used to capture the moment-to-moment dynamics of word recognition. The visual world experiment allows researchers to investigate whether and when people fixate at targeted objects. The paradigm allows to control for participants fixations to specific interest areas at different times during the experimental trial. Researches have the ability to manipulate certain relationships between objects, making them harder to distinguish due to phonological similarities and reveal small differences in the efficiency of word recognition. In addition, the paradigm allows to test specific theories of automaticity with respect to how written information is processed and accessed in the mental lexicon.

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2.6.1 Presentation of Stimuli

Each trial in a visual world experiment begins with presenting a display depicting a target (word/object), one or more competitors and a set of distractors. Unrelated distractors provide a baseline for studying effects on eye-movements, revealed by differences in fixation to the target, competitor and distractors. In order to avoid baseline differences that can complicate interpretation and increase noise in data, distractor objects should not share a direct or indirect relationship to the relevant information that might be activated by the target stimuli.

Distractors with visual properties that might attract participants attention should be avoided (Salverda & Tanenhaus, 2017). The structure of the visual world varies across experiments, from a grid with objects to less structured visual scenes. It is recommended to have an appropriate distance between objects (see Figure 1) to facilitate coding of eye movements. In some VW studies, a feature known as a preview phase is implemented where objects are presented one at a time or simultaneously. A preview phase allows participants to familiarize themselves with the objects on the screen before the intended target appears. Researchers commonly manipulate participants attention by having a target appear for a brief amount of time in a specific location (Salverda & Tanenhaus, 2017).

2.6.2 Data Analysis

Data analyses in visual world studies mainly concern the question of how likely participants are to fixate specific points of interests at different times during a trial (Huettig et al, 2011).

The points of interest within an experiment is dependent on the research question. The areas of interest might be a picture of a targeted object or a distractor object with a similar picture.

The time window of presentation might be 100ms, starting from the onset of the name of the target. Typical questions posited for the statistical analyses are whether two areas of interest differ in their likelihood of being fixated during the time window of target presentation.

Another question concerns whether an area of interest is fixated earlier in an experimental condition compared to a control condition. (Huettig et al, 2011). According to Huettig et al (2011) when interpreting results for a visual world experiment, it is important to keep in mind that fixations and saccades are relatively discrete events. By averaging across trials and participants, computations can be made to how likely participants are on average at a given moment in time to fixate an area of interest. Based on the data obtained, inferences about the time sequence of the underlying cognitive processes can be drawn.

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2.6.3 Using the VWP to study Word reading Automaticity

The aim of the present study is to incorporate the main features of the Visual World Paradigm, in an attempt to measure word reading automaticity.

The experiment will feature a total of four interest areas displayed in each quadrant of the screen, similar to the experimental display illustrated on the left in Figure 1. The

experimental task will feature a targeted word presented in the middle of the screen, flashed briefly for a duration of 75ms, followed by a mask. Automaticity was assessed with the implementation of backward masking, based on the notion that it acts to erase visual

information and interrupt its further processing. The target word will be displayed alongside a target-image, a competitor and two unrelated distractors. The competitor is introduced in order to create a direct competition for lexical activation, by matching the onset of the competitor with the onset of the target. The distractors consist primarily of images which are unrelated to the target. Distractors were implemented by the notion to occupy participants field of vision. The experimental task features a target image which is an accurate depiction of the target word. In order to study the effects of interference, the experimental task will utilize the concept of flanking as a distinct methodological feature linked with the Visual World Paradigm.

The target word will be displayed in one of three conditions, Baseline, Visual and Word.

Baseline serves as the control condition, presenting the target in isolation and eliminating the presence of flankers (e.g., dog). The first experimental condition displays the target in the presence of visual flankers (e.g., %% dog %%). The third and final condition displays the target in the presence of word flankers (e.g., pan dog duck). The aspect of flanking was introduced in order to approximate how a word is processed in the context of other words, simulating an authentic reading experience. The experimental conditions apply flanking as a feature that might affect gaze shifts within the experimental trial, potentially revealing whether lexical activation is affected as a result of having something in near proximity of the target. The study will use Eye-tracking in order to track the gaze while the correct picture is selected to study the effects of condition. Proportion of looks will be calculated and

compared for all three conditions.

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2.7 Synopsis of the Theory section

In the previous section, it has been explained that the notion of fluent reading is often defined by the ability to process text quickly, accurately and with proper expression (Wolf & Katzir- Cohen, 2001; NRP, 2002; Hudson et al, 2009; Kuhn et al, 2010; Rasinski et al, 2011).

Efficient processing of text implies having developed automaticity at the word level. LaBerge and Samuels (1974) argued that efficient word processing develops in two stages. At the accuracy stage, attention is necessary for successful performance. At the automatic stage, attention is not necessary for successful performance. Automaticity facilitates words to be processed by sight, activating the meaning of a word immediately in memory and allowing readers to focus their attention on comprehension rather than word recognition. By this definition, researchers have predominantly conceptualized automaticity as an index of rapid processing of individual letters and words. However, Protopapas et al (2013) argued that performance on tasks presenting word in isolation predicted fluency better at the beginning stages of reading. Suggesting that once words are processed more efficiently, managing several words sequentially becomes a dominant factor beyond the efficiency of processing words in isolation. In other words, once automaticity is sufficiently developed at the word- level, skilled readers have the ability to attend to more than one word simultaneously.

Importantly, parallel processing requires that individual words are processed without

attention, not being susceptible to interference. If attention is required, then word processing becomes more receptive to interference, limiting the ability of parallel processing. On the one hand, parafoveal preview of adjacent letters and words may facilitate efficient processing of words, but on the other hand it could also make it more challenging by delaying the process.

For the present study it is hypothesized that difficulties with parallel processing arise due other words being close the momentary point of fixation. The presence of nearby words is assumed to interrupt or delay the recognition of a central word, when word processing is not automatic. Considering that non-automatic readers use increasingly more effort when processing individual words, overloading attention.

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3 Methodology

3.1 Design

The design of the current study consisted of a masked and flanked presentation of words in a Visual World Paradigm. The main feature of the experimental design revolved around flanking the target stimulus in order to create an interfering effect on the rate of lexical activation. The task includes one control and two experimental conditions. The control serves as a Baseline condition which presents the target word in isolation, the experimental

conditions present the target word with Visual flankers and with Word flankers.

3.2 Participants

Sixty-two healthy adults (40 women and 22 men) consisting of both students from the

University of Oslo and nonstudents participated in this experiment, ranging in age from 19 to 30 years old (M = 25 years, SD = 3.20). The participants were recruited trough convenience sampling, in which the majority of the participants consisted of volunteering fellow students, friends, and acquaintances. Recruitment was restricted to adult native speakers of Norwegian with good eyesight, not wearing glasses or contact lenses and not having any type of reading or learning difficulty (established by self-report).

3.3 Apparatus

The core system comprises the EyeLink 1000 plus (SR Research, Toronto, ON, Canada) eye- tracking camera, which supports 2000 Hz monocular and 1000 Hz binocular sampling rate.

We used a 35 mm lens, which is recommended for set-ups utilizing a desktop mount and have an eye-camera viewing distance of 50-70 cm. The stimuli were generated by a Windows 7 PC under the control of Experiment Builder version 2.2.245 and were displayed on a Ben-q 24-inch LCD display screen (resolution: 1960 x 1080 pixels; refresh rate: 120 Hz). A SR research desktop mount supporting both chin and forehead, stabilized head position. A standard computer mouse was used to click on the selected picture.

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3.4 Materials

The target stimuli consisted of 120 disyllabic imageable nouns. Two-syllable words were chosen because they present with a large range of frequencies and are sufficiently short to have multiple orthographic neighbors (supporting lexical competition), occupy only a small part of the perceptual span (permitting spatial interference). The targets included 60 high frequency and 60 low frequency words. Frequency and other word properties were provided by the Norwegian orthographic analyzer, a corpus-based tool available at

http://npa.staging2.scify.org/. Target words were presented in font Consolas, style normal and size 20. Target words were controlled on the variables: Zip frequency (Zipfreq), Number of letters (Nlet), Neighbourhood distance (Old20) and Bigram frequency with end (Bigram w/end). Items varied widely orthographically, including digraphs (e.g., KJEGLE), long vowels (e.g., SILO), and short vowels (e.g., ØGLE).

Table 1 presents the descriptive statistics for the variables Nlet, Bigram, OLD20 and Zip Frequency

Table 1. Summary of descriptive statistics for the variables Nlet, Bigram, OLD20 and ZipFreq

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The variable (Zipfreq), refers to the familiarity of the words. The zip frequency scale extends from one (lowest) to seven (highest). Words with a value of three or less are considered to be low frequency. Words with a value of four or more are considered to be high frequency (Heuven, Mandera, Keuleers and Brysbaert, 2014). The average Zip frequency for words in the high frequency group (M = 4.36, SD = 0.35) and for words in the low frequency group (M

= 2.81, SD = 0.44).

Figure 2. Histogram of the mean Zip frequency

The variable (Nlet), refers to the number of letters in each word. The average number of letters for words in the high frequency group (M = 5.58, SD = 0.98). The average number of letters for words in the low frequency group (M = 5.42, SD = 0.96).

Figure 3. Histogram of the mean Number of letters

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The variable (Old20) refers to orthographic neighbourhood size. Orthographic neighbors are words that may be formed from one another by replacing one letter with another. The neighbourhood size of a word is the number of neighbors it has, if a word has a lot of close neighbors it may affect response time and accuracy (Adelman, 2012). The average distance of the nearest 20 words for words in the high frequency group was (M = 1.45, SD = 0.37) and (M = 1.61, SD = 0.39) for words in the low frequency group.

Figure 4. Histogram of the mean OLD20

The variable (bigram w/end) controls the frequency with which adjacent letter pairs are used (Adelman, 2012). Moreover, it refers to the number of different words that contain similar bigram ending. The average Bigram for high frequency words was (M = 3.40, SD = 0.22) and for low frequency words was (M = 3.31, SD = 0.24).

Figure 5. Histogram of the mean Bigram frequency w/end

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For each target, we defined two flanker words. They were chosen to be orthographically dissimilar to the corresponding targets. This was done in two ways: The flanker words ranged in length from one to three syllables. Flankers did not share similar onset or ending syllable with the target.

We included one competitor word for each target. The competitors consisted of 120

disyllabic imageable nouns. The words were chosen to resemble the target phonologically in order to create a direct competition for gaze-fixation. This was done by matching the onset of the competitor with the onset of the target (e.g., DIPLOM for the target DEMON).

For each target word, we featured two distractors. The distractors mainly related to the images. The images did not resemble the images of the target. The purpose of having distractor images is to try and distract the gaze away from the target.

The experiment featured a total of 480 images corresponding to 480 imageable nouns. The majority of images featured in the experiment were chosen from a list received from Bob McMurray and Keith Apfelbaum. Several other images were downloaded from the internet, primarily using google as the main search engine. All featured images were of color line drawings and were carefully inspected to ensure they correctly depicted the Norwegian target words.

The assignment of items to conditions was counterbalanced, such that a target stimulus that appeared in isolation (Baseline) for one participant, appeared either in a flanking condition with symbols or words for others. This was controlled by splitting the 120 targets into two separate groups, 60 high frequency and 60 low frequency. The 60 words for each group were shuffled separately and, three copies of the shuffled versions were then made. In the first copy, the first 20 targets were set to be present in isolation (Baseline), the second 20 targets were set to be presented with visual flankers and, the last 20 with word flankers. Thus, creating three target lists with the same order of targets but different assignment of targets to conditions. Finally, the three lists were individually shuffled such that each target would appear exactly once but in different order for each participant. This procedure was repeated 30 times, producing enough target lists for 90 participants in counterbalanced sets of three, with different groups of targets assigned to each condition and different orders of

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3.5 Procedure

The procedure consisted initially by placing participants in front of the eye-tracker, utilizing an adjustable table and headrest to ensure eyes were at 75% height of the display screen.

Camera focus was adjusted using the lens, in order to provide a clear image of the pupil.

Pupil and corneal reflection (CR) threshold levels were automatically computed by the Host- PC, this was done by clicking the auto-threshold button. Individual threshold levels were then separately fine-tuned. All participants were instructed to fixate at all four corners of the screen. This allowed to further control that the eyes were properly tracked.

The next step included performing calibration. Calibration was performed simultaneously for both eyes. This was done in order to link the recorded reflections to screen positions. For this set-up, we utilized a total of nine predefined calibration points. Successful calibration was determined by a specific gaze pattern. In case of poor calibration, recalibration was performed until desired pattern was achieved. Some participants did not achieve desired pattern, potentially due to anatomical factors (positioning of eyelashes).

When calibration was successful, the next procedure was to run validation. Validation displayed target positions to the participants and measured the difference between the target position and the computed fixation position for the target, based on the calibration model.

Spatial error was reported in degrees of visual angle, it reflected both the adequacy of the initial calibration model and participants ability to refixate the targets during validation. The functionality of the validation procedure was similar to calibration, by manually accepting calibration points. The data points were evaluated by checking average and maximum error estimates for each target point. The average error should not exceed 0.5° and the maximum error should not exceed 1°. If the accuracy of a fixation point was not acceptable, a

revalidation was performed. In some instances, a recalibration was necessary.

When measures of calibration and validation were successfully accepted, participants proceeded to the experimental trial. Prior to every individual trial screen, a drift check was issued. The drift check screen displayed a single fixation point to the participant and measured the difference between the computed fixation position and the current fixation point. The purpose of having a drift check is to evaluate whether adequacy of the calibration

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parameters have become invalidated. If the error is large, the participants won’t be able to proceed to the trial and another calibration/validation is required.

Participants were introduced to a block of six practice trials prior to the experimental blocks.

They received verbal instructions and had the opportunity to ask questions. The experiment consisted of 120 trials (with and addition of six practice trials), divided by three blocks of 40 trials each. The trial began with presenting four pictures, one in each of the four screen quadrants (see Figure 6). This was followed by a red dot appearing in center screen for a duration of 520ms, replaced immediately by a blue dot.

Figure 6. Trial presentation with blue dot

At this stage participants were given a pre-view period of 1500ms, for the pictures.

Subsequently participants shifted their gaze toward the center screen and proceeded to click on the blue dot. To ensure that participants were fixating on the blue dot while clicking, a fixation trigger was implemented. Participants had to fixate on the blue dot for a minimum duration of 100ms, in order for the target word to appear. The target word appeared for a duration of 75ms and was replaced by a mask, which appeared for 100ms. After the mask disappeared, participants were required to click on the picture corresponding to the target.

The mask used to cover both the target and flankers consisted of repeated symbols (see Figure 7), exceeding the number of letters of the longest word used.

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Figure 7. Target word covered by a mask

Figure 8. Target word appearing in Baseline condition

Figure 9. Target word appearing in Visual-flanking condition

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Figure 10. Target word appearing in Word-flanking condition

As displayed above, the target word appeared in one of three flanking conditions. The conditions consisted of presenting the target being flanked bilaterally by either nothing, baseline (see Figure 8), nonverbal symbols such as %% (see Figure 9) or other words (see Figure 10). Trials were successfully completed after having selected one of the four pictures.

No feedback was given based on response. Successive screens were a lateral progression and not an increase in difficulty level. A short break was scheduled after the completion of each 40-trial block. The experiment was administered jointly by myself and Caroline Nordlie, who were present together or individually for all sessions.

3.6 Validity and Reliability

The ultimate aim of a study is to establish a connection between one or more independent variables and a dependent variable (Bryman, 2016). In addition, it may be to generalize the results found with the participants used in the study to other groups of people. No design will achieve these goals perfectly, as researchers we have to be aware of how valid our design is for the particular goal of the research. It is quite possible for a measure to be relatively valid for measuring one kind of phenomenon, but entirely invalid for assessing other phenomena.

Thus, one validates not the measuring instrument itself, but the measuring instrument in relation to the purpose for which it is being used (Carmine & Zeller, 1974). Conducting a research project implies to adhere to methodological principles and guidelines to ensure the quality of the study. Validity and reliability are amongst the most important requirements for scientific research and will be further discussed in detail later in chapter 5.

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3.7 Ethical consideration

The objectives and methods of the project are in accordance with the ethical

Principles of the General Data Protection Regulation. Approval of study plans will be sought from the relevant authorities namely the Norwegian Center for Research Data (NSD) that regulates the use of personal data, data collection, privacy and research ethics. Informed consent was obtained in accordance with the requirements and guidelines of (NSD) and personal data will be treated without identification and published data will be fully

anonymized. The recruitment of participants was informal via personal and social networks, in which each participant received an approved inform consent detailing the project and the choice to give personal consent to store data. All participants had the ability to withdraw from the project at any given time with no repercussion to follow. Participation in the project did not cause any significant physical or mental risk. The project was approved by NSD on 08.10. 2019.

Automaticity and the notion of interference