Cross-cultural usability evaluation of AI-based adaptive user interface for mobile applications

With the widespread purchase of mobile communication devices and their extensive usage in every aspect of life, allied with global mobility and market penetration – a more culturally universally adaptable interface has become a priority. This pliable interface must conform continuously with the chan...

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Veröffentlicht in:Acta scientiarum. Technology Jg. 44; S. e61112
Hauptverfasser: Miraz, Mahdi, Ali, Maaruf, Excell, Peter Stuart
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Maringa Universidade Estadual de Maringa 28.07.2022
Editora da Universidade Estadual de Maringá - EDUEM
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ISSN:1807-8664, 1806-2563, 1806-2563
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Abstract With the widespread purchase of mobile communication devices and their extensive usage in every aspect of life, allied with global mobility and market penetration – a more culturally universally adaptable interface has become a priority. This pliable interface must conform continuously with the changing abilities of the end user and the person’s culture, irrespective of the prevailing ambient culture. The information required to customise this interface must be derived from the user’s actual digital footprint and not on their feedback. This treatise presents the usability evaluation results of a culturally inclusive and ubiquitous mobile learning (M-Learning) platform (‘Mobile Academy’), with an AI-based adaptive user interface which takes the snapshot of the installed apps on a smartphone as input, predicts the user’s cultural affiliation as well as the language preference and thus offer a culturally customised user interface as the output. The proof of concept (PoC) prototype has been developed based on the CIAUI (Culturally Inclusive Adaptive User Interface) framework, using plasticity of user interface techniques. This approach was taken to test the affordability of developing inclusive applications, considering the ever growing large global culturally diverse user base. Usability evaluation was then conducted and the results carefully analysed. The results indicated that the PoC exhibited enhanced cross-cultural usability and affordability of such techniques. The evaluation results of the PoC also advocates in favour of the user’s cultural profiling based on the mobile usage data, particularly a single snapshot of installed apps. The research provides direction for future research and application development.
AbstractList With the widespread purchase of mobile communication devices and their extensive usage in every aspect of life, allied with global mobility and market penetration – a more culturally universally adaptable interface has become a priority. This pliable interface must conform continuously with the changing abilities of the end user and the person’s culture, irrespective of the prevailing ambient culture. The information required to customise this interface must be derived from the user’s actual digital footprint and not on their feedback. This treatise presents the usability evaluation results of a culturally inclusive and ubiquitous mobile learning (M-Learning) platform (‘Mobile Academy’), with an AI-based adaptive user interface which takes the snapshot of the installed apps on a smartphone as input, predicts the user’s cultural affiliation as well as the language preference and thus offer a culturally customised user interface as the output. The proof of concept (PoC) prototype has been developed based on the CIAUI (Culturally Inclusive Adaptive User Interface) framework, using plasticity of user interface techniques. This approach was taken to test the affordability of developing inclusive applications, considering the ever growing large global culturally diverse user base. Usability evaluation was then conducted and the results carefully analysed. The results indicated that the PoC exhibited enhanced cross-cultural usability and affordability of such techniques. The evaluation results of the PoC also advocates in favour of the user’s cultural profiling based on the mobile usage data, particularly a single snapshot of installed apps. The research provides direction for future research and application development.
With the widespread purchase of mobile communication devices and their extensive usage in every aspect of life, allied with global mobility and market penetration - a more culturally universally adaptable interface has become a priority. This pliable interface must conform continuously with the changing abilities of the end user and the person´s culture, irrespective of the prevailing ambient culture. The information required to customise this interface must be derived from the user´s actual digital footprint and not on their feedback. This treatise presents the usability evaluation results of a culturally inclusive and ubiquitous mobile learning (M-Learning) platform (`Mobile Academy´), with an AI-based adaptive user interface which takes the snapshot of the installed apps on a smartphone as input, predicts the user´s cultural affiliation as well as the language preference and thus offer a culturally customised user interface as the output. The proof of concept (PoC) prototype has been developed based on the CIAUI (Culturally Inclusive Adaptive User Interface) framework, using plasticity of user interface techniques. This approach was taken to test the affordability of developing inclusive applications, considering the ever growing large global culturally diverse user base. Usability evaluation was then conducted and the results carefully analysed. The results indicated that the PoC exhibited enhanced cross-cultural usability and affordability of such techniques. The evaluation results of the PoC also advocates in favour of the user´s cultural profiling based on the mobile usage data, particularly a single snapshot of installed apps. The research provides direction for future research and application development.
With the widespread purchase of mobile communication devices and their extensive usage in every aspect of life, allied with global mobility and market penetration--a more culturally universally adaptable interface has become a priority. This pliable interface must conform continuously with the changing abilities of the end user and the person's culture, irrespective of the prevailing ambient culture. The information required to customise this interface must be derived from the user's actual digital footprint and not on their feedback. This treatise presents the usability evaluation results of a culturally inclusive and ubiquitous mobile learning (M-Learning) platform ('Mobile Academy'), with an AI-based adaptive user interface which takes the snapshot of the installed apps on a smartphone as input, predicts the user's cultural affiliation as well as the language preference and thus offer a culturally customised user interface as the output. The proof of concept (PoC) prototype has been developed based on the CIAUI (Culturally Inclusive Adaptive User Interface) framework, using plasticity of user interface techniques. This approach was taken to test the affordability of developing inclusive applications, considering the ever growing large global culturally diverse user base. Usability evaluation was then conducted and the results carefully analysed. The results indicated that the PoC exhibited enhanced cross-cultural usability and affordability of such techniques. The evaluation results of the PoC also advocates in favour of the user's cultural profiling based on the mobile usage data, particularly a single snapshot of installed apps. The research provides direction for future research and application development. Keywords: Artificial intelligence (AI); CIAUI (culturally inclusive adaptive user interface) framework; cross-cultural inclusivity; digital footprint; plasticity of user interface design; SVM classifiers; usability evaluation.
Audience Academic
Author Miraz, Mahdi
Ali, Maaruf
Excell, Peter Stuart
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SubjectTerms Applications programs
Culture
Mobile computing
Smartphones
Usability
User interface
Title Cross-cultural usability evaluation of AI-based adaptive user interface for mobile applications
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