Heuristic Evaluation and Usability Testing of G-MoMo Applications

Ali, Guma

doi:10.55267/iadt.07.12296

Cited by 3 publications

(10 citation statements)

References 45 publications

(87 reference statements)

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“…At the same time, the G-MoMo IT Support Application had the least usability issues with 10 minor and 8 major (Ali et al, 2022). Figure 41 shows the number of usability issues among the three G-MoMo applications.…”

Section: Table 24mentioning

confidence: 94%

“…The "user control and freedom (H3)" and "help and documentation (H10)" account for 57.1% of the usability problems and were considered minor and major issues. The "match between system and the real world (H2)," "consistency and standards (H4)," "error prevention (H5)," "recognition rather than recall (H6)," "flexibility and efficiency of use (H7)," and "help users recognize, diagnose, and recover from errors (H9)" principles were categorised as a minor problem with a mean severity score of 2.0 (6.3%), 2.0 (7.9%), 2.0 (4.8%), 2.0 (6.3%), 2.5 (9.5%), and 2.0 (4.8%), respectively (Ali et al, 2022). Figure 42 shows the frequency of severity of usability issues among the 10 heuristic guidelines used to evaluate the user interfaces of the three G-MoMo applications.…”

Section: Table 24mentioning

confidence: 99%

“…The G-MoMo Agent Application, on the other hand, had few usability issues related to "recognition rather than recall (H6)", "flexibility and efficiency of use (H7)", "help users recognize, diagnose, and recover from errors (H9)", but more usability issues with the "match between system and the real world (H2)", "consistency and standards (H4)", "user control and freedom (H3)", and "help and documentation (H10)". In addition, G-MoMo Customer Application had a few usability issues related to the "visibility of system status (H1)", "error prevention (H5)", "recognition rather than recall (H6)", "help users recognize, diagnose, and recover from errors (H9)", but more usability issues with "flexibility and efficiency of use (H7)", "user control and freedom (H3)", and "help and documentation (H10)" (Ali et al, 2022). Figure 43 shows the distribution of the usability issues among the user interfaces of the three G-MoMo applications.…”

Section: Table 24mentioning

confidence: 99%

“…(i) Lack of forward navigation buttons: The interfaces of the three native G-MoMo applications have backward navigation buttons but lack forward navigation buttons, making it difficult for mobile money subscribers to move forward. Instead, they had to go to the home page and select the pages they wanted to access, thus, affecting user control and freedom (Ali et al, 2022).…”

Section: Table 24mentioning

confidence: 99%

“…(ii) Lack of uniformity in the applications menu titles: The menu titles or headings of the user interfaces were not uniformly aligned. Some headings are aligned to the left and others centre, affecting consistency and standards in the G-MoMo applications (Ali et al, 2022).…”

Section: Table 24mentioning

confidence: 99%

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Development of a secure multi-factor authentication algorithm for mobile money applications

Guma¹

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With the evolution of industry 4.0, financial technologies have become paramount and mobile money as one of the financial technologies has immensely contributed to improving financial inclusion among the unbanked population. Several mobile money schemes were developed but, they suffered severe authentication security challenges since they implemented two-factor authentication. This study focused on developing a secure multi-factor authentication (MFA) algorithm for mobile money applications. It uses personal identification numbers, one-time passwords, biometric fingerprints, and quick response codes to authenticate and authorize mobile money subscribers. Secure hash algorithm-256, Rivest-Shamir-Adleman encryption, and Fernet encryption were used to secure the authentication factors, confidential financial information and data before transmission to the remote databases. A literature review, survey, evolutionary prototyping model, and heuristic evaluation and usability testing methods were used to identify authentication issues, develop prototypes of native genuine mobile money (G-MoMo) applications, and identify usability issues with the interface designs and ascertain their usability, respectively. The results of the review grouped the threat models into attacks against privacy, authentication, confidentiality, integrity, and availability. The survey identified authentication attacks, identity theft, phishing attacks, and PIN sharing as the key mobile money systems’ security issues. The researcher designed a secure MFA algorithm for mobile money applications and developed three native G-MoMo applications to implement the designed algorithm to prove the feasibility of the algorithm and that it provided robust security. The algorithm was resilient to non-repudiation, ensured strong authentication security, data confidentiality, integrity, privacy, and user anonymity, was highly effective against several attacks but had high communication overhead and computational costs. Nevertheless, the heuristic evaluation results showed that the G-MoMo applications’ interface designs lacked forward navigation buttons, uniformity in the applications’ menu titles, search fields, actions needed for recovery, and help and documentation. Similarly, the usability testing revealed that they were easy to learn, effective, efficient, memorable, with few errors, subscriber satisfaction, easy to use, aesthetic, easy to integrate, and understandable. Implementing a secure mobile money authentication and authorisation by combining multiple factors which are securely stored helps mobile money subscribers and other stakeholders to have trust in the developed native G-MoMo applications.

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Section: Table 24mentioning

confidence: 94%

Section: Table 24mentioning

confidence: 99%

Section: Table 24mentioning

confidence: 99%

Section: Table 24mentioning

confidence: 99%

Section: Table 24mentioning

confidence: 99%

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Development of a secure multi-factor authentication algorithm for mobile money applications

Guma¹

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Usability of Mobile Applications: A Consolidated Model

Weichbroth

2024

IEEE Access

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Mobile devices have become an integral part of the digital ecosystem, connecting people, businesses, and information around the world in ways never before possible. In particular, smartphones, tablets and other handheld devices equipped with mobile applications have changed every aspect of our lives. Today, a user can choose from nearly five million applications available for both Android and iOS operating systems. However, only 0.5 percent of applications succeed in the marketplace. Many factors contribute to their failure, including poor design, lack of value, privacy violations, and usability issues. While usability is often identified as a major concern, there seems to be no agreement between researchers and practitioners on its nature, although many models have been developed. This paper attempts to find a consensus by synthesizing the state of the art literature. More specifically, we aim to develop a consolidated, universal usability model for mobile applications, through the lens of existing human computer interaction theory. In order to achieve this goal, our study uses a mix of qualitative and quantitative methods. Overall, the research methodology consisted of two steps. First, we conducted a systematic literature review to identify, collect, and analyze current research on mobile usability. Second, we used the meta-analysis approach to quantitatively describe the extracted data and summarize the findings. The PACMAD+3 model was developed and discussed in light of the results obtained and the PACMAD model. While our model borrows seven attributes from its ancestor, the remaining three attributes were derived from the synthesis of other studies, along with three external factors adopted from the ISO 9241-11 standard. In addition, we reviewed existing definitions of usability attributes. We expect that this unified approach will lead to a better understanding of mobile usability, including all relevant attributes and factors, thus making a significant contribution to theory. On the other hand, in practice, the PACMAD+3 model can be used to translate abstract attributes into tangible terms, which is particularly useful in empirical research focused on measuring and evaluating the usability of mobile applications.INDEX TERMS model, usability, mobile application, meta-analysis, review

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Task Automation Intelligent Agents: A Review

Wali

Mahamad

2023

Future Internet

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As technological advancements increase exponentially, mobile phones become smarter with machine learning and artificial intelligence algorithms. These advancements have allowed mobile phone users to perform most of their daily routine tasks on mobile phones; tasks performed in daily routines are called repetitive tasks and are performed manually by the users themselves. However, machine learning and artificial intelligence have enabled those tasks to be performed automatically, known as task automation. The users can perform task automation, e.g., through creating automation rules or an intelligent agent, e.g., conversational agents, virtual personal assistants, etc. Several techniques to achieve task automation have been proposed, but this review shows that task automation by programming by demonstration has had massive developmental growth because of its user-centered approach. Apple Siri, Google Assistant, MS Cortana, and Amazon Alexa are the most known task automation agents. However, these agents are not widely adopted because of their usability issues. In this study, two research questions are evaluated through the available literature to expand the research on intelligent task automation agents: (1) What is the state-of-the-art in task automation agents? (2) What are the existing methods and techniques for developing usability heuristics, specifically for intelligent agents? Research shows groundbreaking developments have been made in mobile phone task automation recently. However, it must still be conducted per usability principles to achieve maximum usability and user satisfaction. The second research question further justifies developing a set of domain-specific usability heuristics for mobile task automation intelligent agents.

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Heuristic Evaluation and Usability Testing of G-MoMo Applications

Cited by 3 publications

References 45 publications

Development of a secure multi-factor authentication algorithm for mobile money applications

Development of a secure multi-factor authentication algorithm for mobile money applications

Usability of Mobile Applications: A Consolidated Model

Task Automation Intelligent Agents: A Review

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