Reading text with and without diacritics alters brain activation: The case of Arabic

Al-Samarraie, Hosam; Sarsam, Samer Muthana; Alzahrani, Ahmed Ibrahim; Alalwan, Nasser

doi:10.1007/s12144-019-00493-6

Cited by 8 publications

(3 citation statements)

References 50 publications

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“…Personality traits are already considered significant in affecting outcomes of social and economic interactions between humans (Cobb-Clark and Schurer, 2012;Rustichini et al, 2016;Proto et al, 2019;Sofianos, 2022). Given our findings, the personality traits of users could be taken into account in developing more effective interactions between humans and computers (Alves et al, 2020): for example, researchers are considering how elements of a user interface can be influenced by personality traits (Al-Samarraie et al, 2018), with the aim of designing more personalised systems that lead to more effective engagement from users. The findings from our study could be used to inspire AI interaction design that activates, or caters to, user traits of Honesty-Humility and Agreeableness which may in turn promote reciprocity.…”

Section: Discussionmentioning

confidence: 75%

In bot we trust? Personality traits and reciprocity in human-bot trust games

Upadhyaya,

Galizzi

2023

Front. Behav. Econ.

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People are increasingly interacting with forms of artificial intelligence (AI). It is crucial to understand whether accepted evidence for human-human reciprocity holds true for human-bot interactions. In a pre-registered online experiment (N = 539) we first replicate recent studies, finding that the identity of a player's counterpart in a one-shot binary Trust Game has a significant effect on the rate of reciprocity, with bot counterparts receiving lower levels of returned amounts than human counterparts. We then explore whether individual differences in a player's personality traits—in particular Agreeableness, Extraversion, Honesty-Humility and Openness—moderate the effect of the identity of the player's counterpart on the rate of reciprocity. In line with literature on human-human interactions, participants exhibiting higher levels of Honesty-Humility, and to a lesser extent Agreeableness, are found to reciprocate more, regardless of the identity of their counterpart. No personality trait, however, moderates the effect of interacting with a bot. Finally, we consider whether general attitudes to AI affect the reciprocity but find no significant relationship.

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Section: Discussionmentioning

confidence: 75%

In bot we trust? Personality traits and reciprocity in human-bot trust games

Upadhyaya,

Galizzi

2023

Front. Behav. Econ.

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“…The authors suggest their data support the hypothesis that Arabic text is more visually complex than other writing systems ( Carreiras et al, 2013 ; Yassin et al, 2020 ), which impacts reading fluency. To date, a few studies have investigated the VWFA’s response to Arabic print, primarily using EEG ( Al-Samarraie et al, 2020 ; Simon et al, 2006 ; Taha et al, 2013 ; Taha & Khateb, 2013 ). These prior studies consistently report an N170 response to Arabic print.…”

Section: Introductionmentioning

confidence: 99%

Neural Specialization for English and Arabic Print in Early Readers

Centanni

2023

Neurobiology of Language

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Learning to read requires the specialization of a region in the left fusiform gyrus known as the visual word form area (VWFA). This region, which initially responds to faces and objects, develops specificity for print over a long trajectory of instruction and practice. VWFA neurons may be primed for print because of their pre-literate tuning properties, becoming specialized through top-down feedback mechanisms during learning. However, much of what is known about the VWFA comes from studies of Western orthographies, whose alphabets share common visual characteristics. Far less is known about the development of the VWFA for Arabic, which is a complex orthography and is significantly more difficult to achieve fluency in in reading. In the current study, electroencephalography responses were collected from first grade children in the United Arab Emirates learning to read in both English and Arabic. Children viewed words and false font strings in English and Arabic while performing a vigilance task. The P1 and N1 responses to all stimulus categories were quantified in two occipital and two parietal electrodes as well as the alpha band signal across all four electrodes of interest. Analysis revealed a significantly stronger N1 response to English compared to Arabic and decreased alpha power to Arabic compared to English. These findings suggest a fundamental difference in neural plasticity for these two distinct orthographies, even when instruction is concurrent. Future work is needed to determine whether VWFA specialization for Arabic takes longer than more well-studied orthographies and if differences in reading instruction approaches help accelerate this process.

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“…This is where the role of culture can at most be a modest one in a complex web of interacting factors in the design of mHealth apps (Alsswey et al, 2018a). In addition, modern technology is currently designed to satisfy its users' demands and preferences (Al-Samarraie et al, 2019a). Nisbett and Masuda (2003) agreed that members of a certain cultural group share similar ways of observing and processing information.…”

Section: Introductionmentioning

confidence: 99%

Culture in the design of mHealth UI

Alsswey

Al-Samarraie

El-Qirem

et al. 2020

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Purpose Designers of mobile applications have long understood the importance of users’ preferences in making the user experience easier, convenient and therefore valuable. The cultural aspects of groups of users are among the key features of users’ design preferences, because each group’s preferences depend on various features that are culturally compatible. The process of integrating culture into the design of a system has always been an important ingredient for effective and interactive human computer interface. This study aims to investigate the design of a mobile health (mHealth) application user interface (UI) based on Arabic culture. It was argued that integrating certain cultural values of specific groups of users into the design of UI would increase their acceptance of the technology. Design/methodology/approach A total of 135 users responded to an online survey about their acceptance of a culturally designed mHealth. Findings The findings showed that culturally based language, colours, layout and images had a significant relationship with users’ behavioural intention to use the culturally based mHealth UI. Research limitations/implications First, the sample and the data collected of this study were restricted to Arab users and Arab culture; therefore, the results cannot be generalized to other cultures and users. Second, the adapted unified theory of acceptance and use of technology model was used in this study instead of the new version, which may expose new perceptions. Third, the cultural aspects of UI design in this study were limited to the images, colours, language and layout. Practical implications It encourages UI designers to implement the relevant cultural aspects while developing mobile applications. Originality/value Embedding Arab cultural aspects in designing UI for mobile applications to satisfy Arab users and enhance their acceptance toward using mobile applications, which will reflect positively on their lives.

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Reading text with and without diacritics alters brain activation: The case of Arabic

Cited by 8 publications

References 50 publications

In bot we trust? Personality traits and reciprocity in human-bot trust games

In bot we trust? Personality traits and reciprocity in human-bot trust games

Neural Specialization for English and Arabic Print in Early Readers

Culture in the design of mHealth UI

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