A conceptual framework for measuring the usability characteristics of mobile learning (m-Learning)
application has been developed. Furthermore, a software prototype for smartphones to assess usability
issues of m-Learning applications has also been designed and implemented. This prototype has been
developed, using Java language and the Android Software Development Kit, based on the recommended
guidelines of the proposed conceptual framework. The usability of the proposed model was compared to a
generally available similar mobile application (based on the Blackboard) by conducting a questionnairebased survey at Western University. The two models were evaluated in terms of ease of use, user
satisfaction, attractiveness, and learnability. The results of the questionnaire showed that the participants
considered the user interface based on our proposed framework more user-friendly as compared to the
Blackboard-based user interface.
SOCIO-DEMOGRAPHIC DIFFERENCES IN THE PERCEPTIONS OF LEARNING MANAGEMENT SYSTE...ijseajournal
Learner centred design (LCD) focuses on creating an e-learning system that can fulfil individual needs
through personalization, nevertheless there are still many technical challenges. Besides, losing balanced
focus on both of the learners and the instructors does not help to create a successful e-learning system.
User-centred design helps to improve the usability of a system as it integrates requirements and user
interface designs based on users’ needs. The findings of this research prove that even the users are
provided with the same LMS, not everyone has the same perceptions or tolerance levels of the seven design
factors that may cause frustrations to the users, and not everyone has the same satisfaction level of
navigation experience and interface design. It is important for the LMS developers to understand that the
variations between roles, genders, experiences and ages exist and should not be ignored when designing
the system.
Generating a Domain Specific Inspection Evaluation Method through an Adaptive...Waqas Tariq
The growth of the Internet and related technologies has enabled the development of a new breed of dynamic websites and applications that are growing rapidly in use and that have had a great impact on many businesses. These websites need to be continuously evaluated and monitored to measure their efficiency and effectiveness, to assess user satisfaction, and ultimately to improve their quality. Nearly all the studies have used Heuristic Evaluation (HE) and User Testing (UT) methodologies, which have become the accepted methods for the usability evaluation of User Interface Design (UID); however, the former is general, and unlikely to encompass all usability attributes for all website domains. The latter is expensive, time consuming and misses consistency problems. To address this need, new evaluation method is developed using traditional evaluations (HE and UT) in novel ways.
The lack of a methodological framework that can be used to generate a domain-specific evaluation method, which can then be used to improve the usability assessment process for a product in any chosen domain, represents a missing area in usability testing. This paper proposes an adapting framework and evaluates it by generating an evaluation method for assessing and improving the usability of a product, called Domain Specific Inspection (DSI), and then analysing it empirically by applying it on the educational domain. Our experiments show that the adaptive framework is able to build a formative and summative evaluation method that provides optimal results with regard to the identification of comprehensive usability problem areas and relevant usability evaluation method (UEM) metrics, with minimum input in terms of the cost and time usually spent on employing UEMs.
Investigating a theoretical framework for e-learning technology acceptance IJECEIAES
E-learning has gained recognition and fame in delivering and distributing educational resources, and the same has become possible with the occurrence of Internet and Web technologies. The research seeks to determine the factors that influence students' acceptance of E-learning and to find out the way these factors determine the students' intention to employ E-learning. A theoretical framework was developed based on the technology acceptance model (TAM). To obtain information from the 270 university students who utilized the E-learning system, a questionnaire was formulated. The results revealed that “social influence, perceived enjoyment, self-efficacy, perceived usefulness, and perceived ease of use” are the strongest and most important predictors in the intention of and students towards E-learning systems. The outcomes offer practical implications for practitioners, lawmakers, and developers in effective E-learning systems implementation to improve ongoing interests and activities of university students in a virtual E-learning atmosphere, valuable recommendations for E-learning practices are given by the research findings, and these may turn out to be as guidelines for the efficient design of E-learning systems.
SOCIO-DEMOGRAPHIC DIFFERENCES IN THE PERCEPTIONS OF LEARNING MANAGEMENT SYSTE...ijseajournal
Learner centred design (LCD) focuses on creating an e-learning system that can fulfil individual needs
through personalization, nevertheless there are still many technical challenges. Besides, losing balanced
focus on both of the learners and the instructors does not help to create a successful e-learning system.
User-centred design helps to improve the usability of a system as it integrates requirements and user
interface designs based on users’ needs. The findings of this research prove that even the users are
provided with the same LMS, not everyone has the same perceptions or tolerance levels of the seven design
factors that may cause frustrations to the users, and not everyone has the same satisfaction level of
navigation experience and interface design. It is important for the LMS developers to understand that the
variations between roles, genders, experiences and ages exist and should not be ignored when designing
the system.
Generating a Domain Specific Inspection Evaluation Method through an Adaptive...Waqas Tariq
The growth of the Internet and related technologies has enabled the development of a new breed of dynamic websites and applications that are growing rapidly in use and that have had a great impact on many businesses. These websites need to be continuously evaluated and monitored to measure their efficiency and effectiveness, to assess user satisfaction, and ultimately to improve their quality. Nearly all the studies have used Heuristic Evaluation (HE) and User Testing (UT) methodologies, which have become the accepted methods for the usability evaluation of User Interface Design (UID); however, the former is general, and unlikely to encompass all usability attributes for all website domains. The latter is expensive, time consuming and misses consistency problems. To address this need, new evaluation method is developed using traditional evaluations (HE and UT) in novel ways.
The lack of a methodological framework that can be used to generate a domain-specific evaluation method, which can then be used to improve the usability assessment process for a product in any chosen domain, represents a missing area in usability testing. This paper proposes an adapting framework and evaluates it by generating an evaluation method for assessing and improving the usability of a product, called Domain Specific Inspection (DSI), and then analysing it empirically by applying it on the educational domain. Our experiments show that the adaptive framework is able to build a formative and summative evaluation method that provides optimal results with regard to the identification of comprehensive usability problem areas and relevant usability evaluation method (UEM) metrics, with minimum input in terms of the cost and time usually spent on employing UEMs.
Investigating a theoretical framework for e-learning technology acceptance IJECEIAES
E-learning has gained recognition and fame in delivering and distributing educational resources, and the same has become possible with the occurrence of Internet and Web technologies. The research seeks to determine the factors that influence students' acceptance of E-learning and to find out the way these factors determine the students' intention to employ E-learning. A theoretical framework was developed based on the technology acceptance model (TAM). To obtain information from the 270 university students who utilized the E-learning system, a questionnaire was formulated. The results revealed that “social influence, perceived enjoyment, self-efficacy, perceived usefulness, and perceived ease of use” are the strongest and most important predictors in the intention of and students towards E-learning systems. The outcomes offer practical implications for practitioners, lawmakers, and developers in effective E-learning systems implementation to improve ongoing interests and activities of university students in a virtual E-learning atmosphere, valuable recommendations for E-learning practices are given by the research findings, and these may turn out to be as guidelines for the efficient design of E-learning systems.
Usability of User Interface Styles for Learning Graphical Software ApplicationsWaqas Tariq
This paper examines usability of different user interface styles for learning graphical software applications, namely Adobe Flash CS4 and Microsoft Expression blend 4. An empirical study was performed to investigate the usability attributes of effectiveness, efficiency and satisfaction scores for learning the graphical software applications. There were 32 participants recruited whom consist of interface designers and software developers. A set of 7 tasks was designed to compare the different effects of user interface styles including graphical user interface (GUI) and command line interface (CLI). User Performance variables (effectiveness, efficiency, duration, number of errors and number of helps) were measured for tasks performed by all the participants in the test. Satisfaction score was measured using QUIS (Questionnaire for User Interface Satisfaction) tool. The result revealed that the average effectiveness scores are higher than 75% for both software applications. Although Adobe Flash CS4 gained slightly higher on effectiveness, Microsoft Expression Blend 4 obtained better results in terms of efficiency, duration, errors and helps. The user satisfaction rates also showed Microsoft Expression Blend 4 gained higher satisfaction comparing Adobe Flash CS4. Generally, both software applications gained scores above average (>3.5) for majority of the user interface satisfaction attributes of software regardless of users’ background.
A Literature Survey on Mobile-Learning Management SystemsAM Publications
In today’s digital era, due to development in wireless communication technology, proliferation of electronics gazettes usage especially smartphones is at peak point across the globe. Without smartphone, most of the individuals feel inconvenience in their daily routine India is not an exception for it, today; India has the second-biggest smartphone market in terms of active unique smartphone users, which crossed 220 million users. These innovations and developments in mobile technologies have an impact on education and learning systems which in turn resulted into the potential to develop an education system that enables individuals and groups to learn bypassing the time and place constraints. This paper gives a glimpse on characteristics, elements, security risks, design issues and challenges of mobile learning management system.
ADVANCEMENT IN THE MOBILE APP REVIEW SYSTEM TO ENHANCE QUALITY OF MOBILE APPL...csandit
The market for mobile applications has enormously increased in the past five years. According
to the App Annie reports, the gross annual revenue is projected to exceed $189 billion by 2020.
Developing and enhancing mobile applications will vastly facilitate in increasing the market for
mobile applications. User reviews of mobile apps play a vital role in enhancing the quality of currently existing mobile applications, and, in the development of new high quality mobile applications. Typically, user reviews are either in the form of several lines of text or numerical
rating or both. Both forms of rating are meant to aid the prospective users in app installation/purchasing. User reviews also assist the developers in identifying technical glitches (if any) and in providing further advanced updates to the mobile app. The objective of this paper is twofold. Firstly, this paper identifies the currently existing app review systems and analyzes each of these app review systems in detail. Secondly, based on the analysis, we have introduced a four-step app review system that will be instrumental in enhancing the quality of mobile applications. In addition, we have presented the results of a survey (sample size = 100) that was administered to comprehend the effectiveness of the proposed app review system.
This paper introduces the competency models for Operations Manager, User Interface
Designer, and Application Developers. It will serve as a guide for Information Systems students
to identify which among the three of the offered tracks would be most suited for them to pursue
according to their knowledge, skills, values and interests. The Holland’s RIASEC model and the
Values Search model of Bronwyn and Holt were utilized to determine the most dominant interest
and most dominant values of the industry computing experts. Survey assessment forms were sent
to IT Operations Manager, User Interface Designer, and Application Developer. Most dominant
values and interests of industry computing experts were determined as well as the knowledge
and skills which are mostly required by the industry in their particular area. Based on the result
of the survey, it shows that application developer and user interface designer have a closely
related values. Thus a second round of a survey would be needed to come up with the most
exclusive dominant values for the particular information systems specialization track.
MEASURING UTILIZATION OF E-LEARNING COURSE DISCRETE MATHEMATICS TOWARD MOTIVA...AM Publications
In the implementation of learning E-Learning which has been implemented by the Mercu Buana University in recent years had a positive impact on students and lecturer. However, in some course such as Discrete Mathematics perceived by lecturer and student have several problems such as difficulty from lecturer to explain some of the logic material or analysis algorithm problem. Students also do not understand clearly if only read from the text that is presented through the e learning process. Effectiveness basically is attainment of precise goal or selecting the appropriate objectives from a series of alternative or choice of ways and determine the choice of several other options. Effectiveness can also be interpreted as a measure of success in achieving the goals that have been determined. As an example if a task can finish with choice of ways which is already determine, then that way is correct or effective.
Alcatel-Lucent Cloud Classroom in the Cloud White Paper + InfographicAlcatel-Lucent Cloud
Alcatel-Lucent Classroom in the Cloud strategic white paper explains how a classroom in the cloud building on service provider infrastructure and business models to create a k-20 Education platform that reduces cost, improves engagement and measures student success. Transformational change is required in the area of education to improve outcomes for students. Telecommunications service providers are in a unique position to help educational institutions harness the rapidly expanding base of mobile and connected devices to accelerate the use of digital content in the classroom. By provisioning reliable network infrastructure, supplying standardized devices to all students, and partnering with a flexible teaching and learning application, service providers can create high-value opportunities while delivering effective new digital resources that help educators reduce costs, improve teaching tools, access more meaningful performance analytics, recast student engagement, and remodel educational standards worldwide.
LearningMate’s GoClass is a subscription-based, teacher-centered, classroom workflow- management application. Teachers use GoClass to develop and store lesson-plans in the cloud. In the classroom, they project those lesson-plans at the front of the room and broad- cast them to students’ mobile devices. Students can save content in their own accounts, and can annotate that content and collaborate around it with classmates. They can also access or buy additional related content. GoClass links students notes and annotations to the related lesson plan element by design. Students can elect to share this work with their teacher and can also collaborate with other students working on the same material.
Affordable Multi-touch Teaching Station for Engineering ClassesWaqas Tariq
The purpose of this paper is to present the development of a cost effective multi-touch teaching station that support existing educational applications and the custom-made Multi-touch Teaching Module that are being used by instructor to teach undergraduate engineering laboratory class in Multimedia University. The technology-enhanced teaching station was developed based on optical tracking technique known as Frustrated Total Internal Refraction (FTIR) to achieve multi-touch capabilities on the table surface. The Adobe Flash-based Multi-touch Teaching Module supports popular multi-touch gestures including panning, rotating, zooming in and out on multimedia educational content such as streaming video lecture, animation and schematic diagram. The Multi-touch Teaching Module enhances the way lecturers manipulate teaching material such as enlarging a complex electronic circuitry with just fingers\' gesture when operating with the teaching station. When operating the multi-touch teaching station with existing educational applications, lecturers can use it as a normal touch screen to directly interact with the application instead of using a mouse or keyboard, making the interface more intuitive. Some lecturers have evaluated the teaching station and provided positive feedback over standard computer because it is much easier to operate. In short, the paper summarizes the experience in developing a universal multi-touch teaching station and Multi-touch Teaching Module as well as the system evaluation by instructors in an undergraduate engineering laboratory class, which is valuable for those who intend to enhance teaching platform with technology in a university.
https://jst.org.in/index.html
Our journal has Numbers tell stories, and in the world of research and development, mathematics is the universal language. Join us as we explore the elegant equations and mathematical models that underpin technological advancements and scientific breakthroughs.
Technopreneurship Mobile Application (TMA): A Support Mechanism for Flexible ...IJITE
Mobile phones are essential in our daily lives because of their benefits in communication, entertainment, and education. Students use their mobile phones in teaching-learning engagement, both synchronous and asynchronous. The study focused on developing and validating Technopreneurship Mobile Application (TMA) in its functionality, reliability, usability, efficiency, and User interface/user experience. The study engaged with developmental research using the mobile app development cycle, including requirement specification, development modeling, design and development, testing, and deployment. Online data gathering and analysis were used for mobile application validation, evaluation performance, and mobile deployment. A total of 95 information technology students evaluated the application. The results showed that the application is functional, reliable, usable, efficient, and the user interface is helpful. The overall results obtained a 4.20 with an excellent evaluation that shows that developing a mobile application can be a great tool in the flexible learning delivery for students due to its accessibility and usefulness.
An analysis of Mobile Learning Implementation in Shinas College of Technology...ijcnes
In the past decade, technology has grown exponentially, especially the speed of the Internet and mobile technology have reached its peak it seems. This technology advancement also gives its impact to all the areas especially in the education sector. Researchers have to be interested in investigating how these technologies can be exploited for educational purposes aiming to enhance learning experiences. Subsequently, this has prompt an exploration slant which is ordinarily alluded to as Mobile Learning (M-Learning) in which specialists endeavors have meant to disseminate fitting learning encounters to learners considering their own flexibility needs, the universal usage of portable advances and the accessibility of data whenever � anyplace. By and by, m-learning is still in its start and extraordinary endeavors should be done as such as to explore the potential outcomes of educational outlook change from the conventional on-estimate fits-all illuminating ways to deal with a versatile and customized discovering that can be circulated by means of portable creations. This paper, presents the suitability and need of mobile learning facility in Shinas College of Technology(SHCT) and also presents the framework for implementing m-learning in SHCT.
Usability of User Interface Styles for Learning Graphical Software ApplicationsWaqas Tariq
This paper examines usability of different user interface styles for learning graphical software applications, namely Adobe Flash CS4 and Microsoft Expression blend 4. An empirical study was performed to investigate the usability attributes of effectiveness, efficiency and satisfaction scores for learning the graphical software applications. There were 32 participants recruited whom consist of interface designers and software developers. A set of 7 tasks was designed to compare the different effects of user interface styles including graphical user interface (GUI) and command line interface (CLI). User Performance variables (effectiveness, efficiency, duration, number of errors and number of helps) were measured for tasks performed by all the participants in the test. Satisfaction score was measured using QUIS (Questionnaire for User Interface Satisfaction) tool. The result revealed that the average effectiveness scores are higher than 75% for both software applications. Although Adobe Flash CS4 gained slightly higher on effectiveness, Microsoft Expression Blend 4 obtained better results in terms of efficiency, duration, errors and helps. The user satisfaction rates also showed Microsoft Expression Blend 4 gained higher satisfaction comparing Adobe Flash CS4. Generally, both software applications gained scores above average (>3.5) for majority of the user interface satisfaction attributes of software regardless of users’ background.
A Literature Survey on Mobile-Learning Management SystemsAM Publications
In today’s digital era, due to development in wireless communication technology, proliferation of electronics gazettes usage especially smartphones is at peak point across the globe. Without smartphone, most of the individuals feel inconvenience in their daily routine India is not an exception for it, today; India has the second-biggest smartphone market in terms of active unique smartphone users, which crossed 220 million users. These innovations and developments in mobile technologies have an impact on education and learning systems which in turn resulted into the potential to develop an education system that enables individuals and groups to learn bypassing the time and place constraints. This paper gives a glimpse on characteristics, elements, security risks, design issues and challenges of mobile learning management system.
ADVANCEMENT IN THE MOBILE APP REVIEW SYSTEM TO ENHANCE QUALITY OF MOBILE APPL...csandit
The market for mobile applications has enormously increased in the past five years. According
to the App Annie reports, the gross annual revenue is projected to exceed $189 billion by 2020.
Developing and enhancing mobile applications will vastly facilitate in increasing the market for
mobile applications. User reviews of mobile apps play a vital role in enhancing the quality of currently existing mobile applications, and, in the development of new high quality mobile applications. Typically, user reviews are either in the form of several lines of text or numerical
rating or both. Both forms of rating are meant to aid the prospective users in app installation/purchasing. User reviews also assist the developers in identifying technical glitches (if any) and in providing further advanced updates to the mobile app. The objective of this paper is twofold. Firstly, this paper identifies the currently existing app review systems and analyzes each of these app review systems in detail. Secondly, based on the analysis, we have introduced a four-step app review system that will be instrumental in enhancing the quality of mobile applications. In addition, we have presented the results of a survey (sample size = 100) that was administered to comprehend the effectiveness of the proposed app review system.
This paper introduces the competency models for Operations Manager, User Interface
Designer, and Application Developers. It will serve as a guide for Information Systems students
to identify which among the three of the offered tracks would be most suited for them to pursue
according to their knowledge, skills, values and interests. The Holland’s RIASEC model and the
Values Search model of Bronwyn and Holt were utilized to determine the most dominant interest
and most dominant values of the industry computing experts. Survey assessment forms were sent
to IT Operations Manager, User Interface Designer, and Application Developer. Most dominant
values and interests of industry computing experts were determined as well as the knowledge
and skills which are mostly required by the industry in their particular area. Based on the result
of the survey, it shows that application developer and user interface designer have a closely
related values. Thus a second round of a survey would be needed to come up with the most
exclusive dominant values for the particular information systems specialization track.
MEASURING UTILIZATION OF E-LEARNING COURSE DISCRETE MATHEMATICS TOWARD MOTIVA...AM Publications
In the implementation of learning E-Learning which has been implemented by the Mercu Buana University in recent years had a positive impact on students and lecturer. However, in some course such as Discrete Mathematics perceived by lecturer and student have several problems such as difficulty from lecturer to explain some of the logic material or analysis algorithm problem. Students also do not understand clearly if only read from the text that is presented through the e learning process. Effectiveness basically is attainment of precise goal or selecting the appropriate objectives from a series of alternative or choice of ways and determine the choice of several other options. Effectiveness can also be interpreted as a measure of success in achieving the goals that have been determined. As an example if a task can finish with choice of ways which is already determine, then that way is correct or effective.
Alcatel-Lucent Cloud Classroom in the Cloud White Paper + InfographicAlcatel-Lucent Cloud
Alcatel-Lucent Classroom in the Cloud strategic white paper explains how a classroom in the cloud building on service provider infrastructure and business models to create a k-20 Education platform that reduces cost, improves engagement and measures student success. Transformational change is required in the area of education to improve outcomes for students. Telecommunications service providers are in a unique position to help educational institutions harness the rapidly expanding base of mobile and connected devices to accelerate the use of digital content in the classroom. By provisioning reliable network infrastructure, supplying standardized devices to all students, and partnering with a flexible teaching and learning application, service providers can create high-value opportunities while delivering effective new digital resources that help educators reduce costs, improve teaching tools, access more meaningful performance analytics, recast student engagement, and remodel educational standards worldwide.
LearningMate’s GoClass is a subscription-based, teacher-centered, classroom workflow- management application. Teachers use GoClass to develop and store lesson-plans in the cloud. In the classroom, they project those lesson-plans at the front of the room and broad- cast them to students’ mobile devices. Students can save content in their own accounts, and can annotate that content and collaborate around it with classmates. They can also access or buy additional related content. GoClass links students notes and annotations to the related lesson plan element by design. Students can elect to share this work with their teacher and can also collaborate with other students working on the same material.
Affordable Multi-touch Teaching Station for Engineering ClassesWaqas Tariq
The purpose of this paper is to present the development of a cost effective multi-touch teaching station that support existing educational applications and the custom-made Multi-touch Teaching Module that are being used by instructor to teach undergraduate engineering laboratory class in Multimedia University. The technology-enhanced teaching station was developed based on optical tracking technique known as Frustrated Total Internal Refraction (FTIR) to achieve multi-touch capabilities on the table surface. The Adobe Flash-based Multi-touch Teaching Module supports popular multi-touch gestures including panning, rotating, zooming in and out on multimedia educational content such as streaming video lecture, animation and schematic diagram. The Multi-touch Teaching Module enhances the way lecturers manipulate teaching material such as enlarging a complex electronic circuitry with just fingers\' gesture when operating with the teaching station. When operating the multi-touch teaching station with existing educational applications, lecturers can use it as a normal touch screen to directly interact with the application instead of using a mouse or keyboard, making the interface more intuitive. Some lecturers have evaluated the teaching station and provided positive feedback over standard computer because it is much easier to operate. In short, the paper summarizes the experience in developing a universal multi-touch teaching station and Multi-touch Teaching Module as well as the system evaluation by instructors in an undergraduate engineering laboratory class, which is valuable for those who intend to enhance teaching platform with technology in a university.
https://jst.org.in/index.html
Our journal has Numbers tell stories, and in the world of research and development, mathematics is the universal language. Join us as we explore the elegant equations and mathematical models that underpin technological advancements and scientific breakthroughs.
Technopreneurship Mobile Application (TMA): A Support Mechanism for Flexible ...IJITE
Mobile phones are essential in our daily lives because of their benefits in communication, entertainment, and education. Students use their mobile phones in teaching-learning engagement, both synchronous and asynchronous. The study focused on developing and validating Technopreneurship Mobile Application (TMA) in its functionality, reliability, usability, efficiency, and User interface/user experience. The study engaged with developmental research using the mobile app development cycle, including requirement specification, development modeling, design and development, testing, and deployment. Online data gathering and analysis were used for mobile application validation, evaluation performance, and mobile deployment. A total of 95 information technology students evaluated the application. The results showed that the application is functional, reliable, usable, efficient, and the user interface is helpful. The overall results obtained a 4.20 with an excellent evaluation that shows that developing a mobile application can be a great tool in the flexible learning delivery for students due to its accessibility and usefulness.
An analysis of Mobile Learning Implementation in Shinas College of Technology...ijcnes
In the past decade, technology has grown exponentially, especially the speed of the Internet and mobile technology have reached its peak it seems. This technology advancement also gives its impact to all the areas especially in the education sector. Researchers have to be interested in investigating how these technologies can be exploited for educational purposes aiming to enhance learning experiences. Subsequently, this has prompt an exploration slant which is ordinarily alluded to as Mobile Learning (M-Learning) in which specialists endeavors have meant to disseminate fitting learning encounters to learners considering their own flexibility needs, the universal usage of portable advances and the accessibility of data whenever � anyplace. By and by, m-learning is still in its start and extraordinary endeavors should be done as such as to explore the potential outcomes of educational outlook change from the conventional on-estimate fits-all illuminating ways to deal with a versatile and customized discovering that can be circulated by means of portable creations. This paper, presents the suitability and need of mobile learning facility in Shinas College of Technology(SHCT) and also presents the framework for implementing m-learning in SHCT.
Establishment of Educational Network among the Undergraduate with Mobile Appl...Cahit Berkay Kazangirler
Abstract— It is easier and faster for students to learn from knowledgeable students. The speed of information age and evolving educational technology have changed the way of teaching and the level of knowledge acquired during teaching. In this study, we present establishment of educational network among the undergraduate with mobile application. Students will be trained on the mobile application using smart devices which are present in almost every university student today. For this training, firstly the teams will be established and the target group will be reached for the education given by the knowledgeable student. With the mobile application to be prepared, students will be able to enroll in courses that are opened, will be notified about the lessons from the instructors and will be able to access the necessary source documents easily. The application will also be a website at the same time and all the operations performed in the application will also be available on the website.
User experience improvement of japanese language mobile learning application ...IJECEIAES
Advances in smartphone technology have led to the strong emergence of mobile learning (m-learning) on the market to support foreign language learning purposes, especially for the Japanese language. No matter what kind of m-learning application, their goal should help learners to learn the Japanese language independently. However, popular Japanese m-learning applications only accommodate on enhancing reading, vocabulary and writing ability so that user experience issues are still prevalent and may affect the learning outcome. In the context of user experience, usability is one of the essential factors in mobile application development to determine the level of the application’s user experience. In this paper, we advocate for a user experience improvement by using the mental model and A/B testing. The mental model is used to reflect the user’s inner thinking mode. A comparative approach was used to investigate the performance of 20 highgrade students with homogenous backgrounds and coursework. User experience level was measured based on the usability approach on pragmatic quality and hedonic quality like effectiveness (success rate of task completion), efficiency (task completion time) and satisfaction. The results then compared with an existing Japanese m-learning to gather the insight of improvement of our proposed method. Experimental results show that both m-learning versions proved can enhance learner performance in pragmatic attributes. Nevertheless, the study also reveals that an m-learning that employs the conversational mental model in the learning process is more valued by participants in hedonic qualities. Mean that the proposed m-learning which is developed with the mental model consideration and designed using A/B testing is able to provide conversational learning experience intuitively.
The paper has been presented with a system that is
created on the android platform targeting the students studying in
an engineering institute. The application is created for effortless
day to day official work in an institute. Students will be served
with the benefits like compilation of branch wise question papers,
general aptitude questions, video lectures, newspapers, with
some interesting features like parent-teacher portal, feedback
system and ask your queries block. The application is designed
using core java coding, layout is fabricated with xml extension,
complete creation is done on android studio. Login authentication
is developed via Firebase Auth, newspapers have been linked
through their URL, video lectures are engrossed with API and
a separate website is created for parent-teacher interaction.
Based on the above mentioned ideology, We are fabricating an
application using android design studio kit which is majorly
concerned for the effortless access of all the essentials required
in an institute.
Comparative Study and Analysis of Multiplatform Mobile Application DevelopmentIJMTST Journal
There are varieties of mobile platforms for smart-devices, such as iPhones, Android, Blackberry etc.
becoming ubiquitous. Mobile development application that can work across all mobile platforms has led to
invention of Cross platform. Multiplatform framework gives simplified development process using different
emerging technology (Cross platform tool Phone-gap). Here we introducing Smart College System application
provides interface for maintenance of student information and activities. This system deals with execution of
academic operation in smart and simplest way and provides information related to complaints, notices
(general, department related), and placement activity. It also have facility to maintain student details with
report generation and automated email notification and text messages for the users (Student, Faculty, T.P.O.,
H.O.D and Principal). The system helps us to maximize optimization, minimal manual work along with
increase in security.
A Critical Evaluation of Popular UX Frameworks Relevant to E-Health Appsrinzindorjej
This research paper aims to evaluate the usability, accessibility, and effectiveness of the current User Experience (UX) frameworks relevant to mobile health apps, with a specific focus on the FitBit app. The selected UX frameworks for evaluation include Nielsen Norman Group's 10 Usability Heuristics, Don Norman's Three Levels of Design, and Human-Centered Design. A mixed-method approach, comprising both qualitative and quantitative analyses, was employed to evaluate these frameworks. The FitBit app was assessed based on the selected frameworks, and the obtained results were compared with existing literature and industry standards. The main subject of this study is the critical evaluation of popular UX frameworks in the context of e-health apps, with a specific emphasis on the FitBit app. The evaluation factors considered include usability, accessibility, and effectiveness. By utilizing the selected UX frameworks, the paper seeks to identify the strengths and limitations of each framework in evaluating e- health apps. The achieved results reveal that Nielsen Norman Group's 10 Usability Heuristics are valuable in identifying usability issues within the FitBit app. Don Norman's Three Levels of Design effectively evaluate the overall user experience, providing insights into the app's design quality. Human- Centered Design, on the other hand, offers a comprehensive and holistic approach to designing for the user, encompassing various aspects of the FitBit app. Through this research, a comprehensive understanding of the strengths and limitations of the evaluated UX frameworks in relation to e-health apps, specifically the FitBit app, is attained. The findings contribute to the existing literature on UX evaluation and provide insights for designers and developers to enhance the user experience of mobile health applications.
The International Journal of Computational Science, Information Technology an...rinzindorjej
The International Journal of Computational Science, Information Technology and Control Engineering (IJCSITCE) is an open access peer-reviewed journal that publishes quality articles which make innovative contributions in all areas of Computational Science, Mathematical Modeling, Information Technology, Networks, Computer Science, Control and Automation Engineering. IJCSITCE is an abstracted and indexed journal that focuses on all technical and practical aspects of Scientific Computing, Modeling and Simulation, Information Technology, Computer Science, Networks and Communication Engineering, Control Theory and Automation. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced techniques in computational science, information technology, computer science, chaos, control theory and automation, and establishing new collaborations in these areas.
The International Journal of Computational Science, Information Technology an...rinzindorjej
The International Journal of Computational Science, Information Technology and Control Engineering (IJCSITCE) is an open access peer-reviewed journal that publishes quality articles which make innovative contributions in all areas of Computational Science, Mathematical Modeling, Information Technology, Networks, Computer Science, Control and Automation Engineering. IJCSITCE is an abstracted and indexed journal that focuses on all technical and practical aspects of Scientific Computing, Modeling and Simulation, Information Technology, Computer Science, Networks and Communication Engineering, Control Theory and Automation. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced techniques in computational science, information technology, computer science, chaos, control theory and automation, and establishing new collaborations in these areas.
A GUIDELINE FOR AN EFFECTIVE USER INTERFACE FOR EDUCATIONAL SEMANTIC APPLICATIONijma
ABSTRACT
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A Study of The Interface Usability Issues of Mobile Learning Applications for Smart Phones from the User’s Perspective
1. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.4, December 2014
DOI :10.5121/ijite.2014.3401 1
A STUDY OF THE INTERFACE USABILITY ISSUES OF
MOBILE LEARNING APPLICATIONS FOR SMART
PHONES FROM THE USER’S PERSPECTIVE
Abdalha Ali, Muasaad Alrasheedi, Abdelkader Ouda and Luiz Fernando Capretz
Department of Electrical and Computer Engineering, Western University, London
Ontario, N6A5B9, Canada
ABSTRACT
A conceptual framework for measuring the usability characteristics of mobile learning (m-Learning)
application has been developed. Furthermore, a software prototype for smartphones to assess usability
issues of m-Learning applications has also been designed and implemented. This prototype has been
developed, using Java language and the Android Software Development Kit, based on the recommended
guidelines of the proposed conceptual framework. The usability of the proposed model was compared to a
generally available similar mobile application (based on the Blackboard) by conducting a questionnaire-
based survey at Western University. The two models were evaluated in terms of ease of use, user
satisfaction, attractiveness, and learnability. The results of the questionnaire showed that the participants
considered the user interface based on our proposed framework more user-friendly as compared to the
Blackboard-based user interface.
KEYWORDS
Mobile Learning; Quality Issues; Usability Issue; User interface; User-Centred Design; Empirical Study
1.INTRODUCTION
Mobile devices are increasingly becoming integrated into various aspects of our daily lives. One
area is in the educational sector, where mobile phones are being used as the platform for teaching
and learning. However, unlike personal computers, the screen size and resolution restrict mobile
phones in displaying content [1]. Learning by using specifically smartphones, is being integrated
within existing education systems to support real-time communication and deliver learning
materials.
For instance, smartphones are being used in many universities as a classroom tool to engage and
support students in communicative, collaborative, supportive, and constructive activities.
Additionally, mobile technologies enable individual learners to build knowledge and construct
understandings; in this they facilitate a change in the pattern of work activity/learning [2].
However, mobile applications used for educational purposes have a complex user interface (UI)
with many hidden options. There is already a great interest in designing and developing attractive,
user-friendly mobile applications to gain the acceptance of end user. Further, in order to be
acceptable to a wider audience, the applications need to be both robust and of a very high quality
[3].
2. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.4, December 2014
2
Due to the significant diffusion of mobile technologies, most students today already own mobile
devices. Hence, the technology is a strong contender to be the next “big thing” in educational
platforms [4]. Mobile technology can deliver educational content in several ways. For instance,
Wang et al. [5] reported that mobile phones could be used to deliver online courses to university
students. In fact, the multitude of ways in which mobile technology can be used in the educational
sector, prompted Prensky [6] to note that students will be able to learn “anything, if developers
designed it right”.
Also, the demand for learning anywhere and anytime has specified the need for a new type of
electronic learning known as m-Learning to take advantage of mobile devices which are
becoming increasingly popular [7]. M-learning is an education mode in which students can use
mobile communication terminals to assist them in learning [8].
One of the key components of a successful and acceptable educational application is ease of use.
Several high quality applications available in the market actually lose out because of their
complex application and unattractive and confusing user interface. Thus, when designing a user
interface for mobile phones, especially for education purposes, the user requirements of these
devices should be considered [3].
Many usability guidelines are used for designing desktop applications [9][10]. However, these
guidelines cannot be utilized to design and develop m-learning applications, simply because
neither addresses the aspect of mobility not the obvious limitations of the mobile devices, like
such as screen size, and the need for wireless connectivity [1]. There is a singular lack of reliable
usability guidelines, specifically meant for designing and developing m-learning with user-
friendly interfaces. While research conducted on the success factors of m-Learning clearly show
that usability and related aspects are one the core requirements, the specific ways in which this
can be addressed is are lacking [12]. In fact, usability has been less extensively covered than the
technological aspects of the m-learning. Mobile technology can be successful as an educational
platform only when the future research into the area of m-Learning includes fruitful discussion in
of all the aspects of usability: – learnability, understandability, ease of use, effectiveness, and
efficiency of mobile applications [13].
The experience of end users is extremely important to the success of m-Learning. Therefore, a
mobile phone application targeted towards education must be designed and developed keeping in
mind ease of use, usefulness, and attitude and intention to use that will help ensure a high level of
acceptance [14]. Assessment must be conducted to precisely identify where improvement is
required. Therefore, the main purpose of this research study is to develop a framework for
measuring the quality aspects of m-Learning. Using this framework, existing m-Learning
applications can be assessed in terms of their usability. In addition, a prototype application has
been developed composed of two user interfaces, Model A and Model B. Model A has been
designed and developed based on a user interface adopted from the Blackboard website [15],
while Model B has been developed following the Android SDK recommendation and using the
proposed framework as a guideline. The prototype has been used for assessing the framework by
empirical evaluation, validation, and comparison of usability issues of the model using the
proposed framework as a guideline.
The paper is organized into the following sections. Section 2 presents the literature review on the
subject as well as work in related areas. Section 3 describes the development and theoretical
assessment of the theoretical framework. Section 4 presents the assessment methodology used for
evaluating the framework. Section 5 presents the results of an analysis, and the discussion of the
3. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.4, December 2014
3
results is presented in section 6. Research conclusions and possible directions of future research
work are presented in section 7.
2.LITERATURE REVIEW
In this section we discuss literature that deals with the usability and summarize a selection of the
most relevant findings. To start, in the ISO 9241-11 (1997) [16] standard, usability is defined as
“the extent to which a product can be used by specified users to achieve specified goals with
effectiveness, efficiency and satisfaction in a specified context of use”. However, ISO/IEC 9126-
1 (2001) [17], states that usability is “the capability of the software product to be understood,
learned, used and attractive to the user, when used under specified conditions.” [18], on the other
hand, emphasize that there is a great deal of literature available that addresses usability, user
interface design, and related topics for mobile devices. A mobile application must be developed
and designed with respect to user technological ability, skills, and language proficiency. This
forces developers to be very careful with design issues in order to maximize the level of usability
with all of its sub-characteristics. Ziefle and Bay [19] demonstrate that awareness of user
interface structure is one of the most important issues concerning cell phones.
On the other hand, Jarvela et al. [20] studied how to help users participate in collaborative
learning using smartphones. The researchers utilized a mobile lecture interaction tool to
encourage students in higher education to participate in a class discussion. This tool enabled
participants to ask and answer questions, as well as to rate classmate questions. The main purpose
of this survey was to get student feedback on the usability of the tool. The feedback showed that
mobile tools with a high level of usability will definitely increase their engagement in
discussions. Mobile technology allows the users to communicate instantly; this characteristic
plays a vital role in a successful m-Learning environment. However, usability issues are found to
be important factors in the learners’ high satisfaction level with the cooperative learning available
through the system.
The Mobile System Analysis and Design (MOSAD) application [21] is a mobile application used
as a revision tool for the System Analysis and Design (SAD) course at University Technology
Petronas. The researchers’ main goal was to design an m-Learning application that allows
students to review and read notes during their spare time, and more importantly, to evaluate this
application by considering some design issues that could be modified to improve its usability.
After the application was designed, a heuristic evaluation was completed to measure its level of
usability. Many tests were conducted, and the purpose of those tests was to receive feedback from
participants so the level of usability of this application could be determined. The results indicate
that adding some features to the design will be useful and will improve the overall usability of the
application.
3.DEVELOPMENT OF THEORETICAL FRAMEWORK
In this section, the development of framework for assessment of the m-Learning platform is
described. First, the technical and non-technical quality aspects, the basis of an m-Learning
platform assessment, are discussed. This information will be used to develop the actual
framework. A general theoretical analysis of the framework is also presented in this section.
4. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.4, December 2014
4
3.1.Development of Theoretical Framework Assessing Usability of M-Learning
Platform
The framework is shown in Figure 1 below. Basically, this framework is a combination of
structural factors [23]: rules, goals, outcomes, competition, interaction, and representation. It also
integrates dimensions of the learning context [24]: identity, time-location, facility (mobile
phones), activity, learner on the move, and community. A similar framework has been introduced
by Parsons and Ryu, [13]; however, we have identified three design issues: usability,
communication, and interactivity.
These three design issues can be added to previous design issues identified by Parsons and Ryu
[13]: learning on the move, media type, collaboration, user role, and profile. First, these design
issues have been linked to the dimensions of learning context and then to the structural factors.
From these two steps we target social skills and team building, new knowledge, and improved
skills. Key features of the framework are that it identifies the importance of design issues, the
dimensions of the learning context, and structural factors in order to address learning objectives
that have both a user focus and a platform focus. The usability design issue, which includes ease
of use and understanding, can be achieved if users are able to use the applications (usability
design issue). This can also be achieved by using identifiers of each user that must be unique in
the name space, and that are accessed by the application via a log-on system (with a user name,
password, and/or special devices such as smart cards or fingerprint reader). All these identifiers
are classified under the “identity dimension” within the learning context. Furthermore, ease of use
and the ability to utilize specific identifiers for each user will enable them to perform tasks – such
as reviewing the lessons, doing assignments, and participating in group sessions with other users
– with, of course, the support of mobile devices (structural factors: business rules and learning
roles).
Finally, the learning objectives are addressed; these may include improving skills, acquiring new
knowledge, social skills, or team building. However, as we have mentioned in this paper, each
design issue may be linked with more than one of the dimensions within the learning content. In
summary, most of the components of this framework will relate to each other in one way or
another. For example, usability factors can be affected by more than one of the learning contexts
that include identity, learner, activity, time-location, facility (mobile phone), and the software
engineering community [25] [26]. On the other hand, each dimension of the learning context may
be linked to more than one of the structural factors, which in turn, are linked to different learning
objectives.
5. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.4, December 2014
5
Figure 1. A Conceptual Framework for Measuring Quality Aspects of m-Learning.
3.2. Theoretical Analysis of Proposed Framework
The relationships among the quality of use, internal quality, and external quality metrics are
shown in Figure 2 below. We can see that if extensions are applied to the ISO/IEC metrics [18], it
is possible to map these metrics with our framework in order to measure the design issues related
to learning on the move, user roles and profiles, media type, and usability issues. However,
additional metrics are needed to complement the context of the use dimensions of the quality in
use metrics.
Figure 2. The Relationships between the Quality metrics based on ISO/IEC
To analyze our framework, we consider a case study and the metrics that ISO/IEC provides. The
most suitable example is the Busuu project [27]. The Busuu project is an online social network
application in which learners can assist each other to improve their language skills. The
application provides learning units for twelve different languages, and it can be downloaded for
use on mobile phones. This application was designed to enable users to set up a profile and
practice (quality metrics of user roles and profiles). Software developers were careful with the
learning content that displayed on screens; they targeted as much learning content as possible
(quality metric of media type). On the other hand, since the application can be downloaded to
mobile phones, users are free to use it wherever network connectivity is available (quality metrics
of learning on the move). In addition, each individual user of this application is not only a student
of a foreign language, but also a tutor of his or her own mother tongue. One user can
communicate and interact with other users (quality metrics of communication, collaboration, and
interactivity). However, by using some of the appropriate metrics from ISO/IEC (e.g.,
functionality, scalability, and service quality), we will be able to measure the quality of m-
Learning applications.
6. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.4, December 2014
6
Table 1 shows the analysis of the Busuu project based on our framework. In this case, the analysis
walks us through from the objectives to the design issues. The purpose of this reverse engineering
is to measure the success of the Busuu project and also to determine the design issues our
framework can assess and address.
Table 1. Analysis of Busuu Project Based on our Framework.
Objective Learning Experience Learning Contests Design Issues
Initial Interaction:
1. Exploring,
discovering and
becoming
familiar with the
software.
2. Communicating,
interacting, and
collaborating
with peers by
asking and
answering
questions.
Rules: Business rules,
learning roles:
Different users meet in
the context of a
simulation.
Outcome and
Feedback: Asking
questions and getting
answers.
Goals and objectives:
To become familiar
with the application.
Conflict, competition,
challenge, opposition:
Discussing and
challenging opinions
(teamwork and new
skills).
Interaction, blogs,
wikis, discussion
groups, test,
framework: One to
one, one to many, and
many to one.
Identity: User name
and password for each
individual user.
Learner: Different
users.
Activity: To engage
in participatory
simulation of a
dynamic system.
Time-Location: Co-
located same time and
different time.
Facility: Different
mobile devices.
Community:
Different users with
different backgrounds
using the mobile
devices with the
support of wireless
connectivity can
discuss many different
topics in order to
improve. language
skills
User roles and
profiles:
New Users: Few ideas
on how to use the
application.
Learn on the move:
Mobile devices with the
support of wireless
connectivity.
Media type: Text,
images, comprehensive
audio-visual learning
material with photos
and recordings by
native speakers, avoid
information overload
Communication,
collaboration and
interactivity: Users can
communicate and
collaborate using text,
verbal, and video-chat
communication support
Learning New
Language:
By sharing and
exchanging
information between
users provides new
knowledge that will
help them to
improve language
skills and to
improve the
following
objectives:
1. Team building
2. Social skills
3. New knowledge
4. Improved skills.
Rules: Business rules,
learning roles:
Lessons, tutorials,
assignments, and group
sessions with the
support of mobile
devices.
Goals and objectives:
To get and give
answers and to engage
in participatory
simulation to learn a
new language and/or
improve language
skills.
Conflict, competition,
challenge, opposition:
Discussing and
challenging opinions.
Interaction, blogs,
wikis, discussion
groups, test,
framework: One to
one, one to many, and
many to one.
Identity: Different
users.
Learner: Different
users.
Activity: Explaining
and discussing
participative
experience.
Time-Location: Co-
located same time and
different time.
Facility: Different
mobile devices.
Community:
Different users with
different backgrounds
using the mobile
devices with the
support of wireless
connectivity can
discuss many different
topics in order to
improve language
skills.
User role: Participant
in group discussion
(users).
Learn on the move:
Mobile devices with the
support of wireless
connectivity.
Media type: Text,
images, comprehensive
audio-visual learning
material with photos
and recordings by
native speakers,
vocabulary and key
phrases, dialogues,
audio, podcasts and
PDFs and avoid
information overload.
Communication,
collaboration and
interactivity: Users can
communicate and
collaborate using text,
verbal, and video-chat
communication support.
7. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.4, December 2014
7
The results indicate that the Busuu project is successful since it has met all of the requirements of
our framework. Also, the success of this project can be determined by the number of downloads.
In less than two years, the Bussu project’s applications have already been downloaded more than
10 million times [27]. However, one of the goals of our framework is that it should be used to
support forward engineering and be used as a design guideline for developing m-Learning
applications. Usability has been stated as one of the most important fundamentals of m-Learning
applications [28][29]. These weaknesses in an application will prevent users from being efficient,
effective, and productive: i) difficult to use, ii) a difficult-to-learn user interface, iii) user interface
that is difficult to remember how to reuse; iv) learning content structure that is unclear; v) a
process workflow that is difficult to perform [22][30]. The user interface must be effective and
easy to use; this will help users to focus on their learning goals, learning content, and activities
instead of how the system works; moreover, utilizing design guidelines are vital in developing
learning systems [22][31].
3.3. Development of Prototype for Assessing the Framework
The interface of the Main Menu of the developed application is shown in Figure 3. The prototype
application consists of two user interfaces named Model A and Model B. Model A was designed
and developed based on a user interface adopted from the Blackboard website, while Model B
was developed following Android SDK recommendations and using our framework as a
guideline.
Figure 3. Main Menu of the Prototype Application
The prototype uses familiar terminologies in this prototype application that could be seen on most
of WebCT such as “Course Map”, “Course Information”, “Assignments”, “Announcements”,
“Discussion Board”, “Media”, “Grades”, and “Blogs”. This can be seen in Figures 4 and 5 below
for Model A (Blackboard based) and Model B (based on our framework) respectively. A
comparison of UI for Model A in Figure 4 and UI for Model B in Figure 5 shows that Model B’s
UI is distinctive and easier to understand with large and self-explaining icons. In contrast Model
A’s user interface has smaller and less easily understood options. This is also evident in the Blog
icons for Model A and Model B in Figure 6 and Figure 7 respectively: Model B is distinctive and
easier to understand. The purpose for developing these different user interfaces is to find the best
way to design and develop a user-friendly user interface for mobile applications to increase the
usability level of these applications.
8. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.4, December 2014
8
Figure 4. Model A based on Blackboard
Figure 5. Model B based on Android
Recommendations and our framework as a
guideline
Figure 6. Blog’s Icon in Model A
Figure 7. Blog’s Icon in Model B
4.RESEARCH METHODOLOGY
4.1Research participants
The sample population of the result was undergraduate students at Western University in Canada.
The population was limited to second- and third-year students in the undergraduate program in
the Software Engineering department. Questionnaires were handed to the students and a total of
96 completed questionnaires from the complete population of the present study. These students
were in the 19-23 age group and were both male and female students enrolled in the software
engineering program
.
9. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.4, December 2014
9
4.2. Instrument
The instrument used for analysis was a questionnaire survey handed out to interested participants
who took part in a live assessment of the two Models of m-Learning developed as a part of this
study. The m-Learning platform prototype developed for this study has used for a heuristic
evaluation as a technique to measure usability factors. Heuristic evaluation is an engineering
method for easy, quick, and cheap evaluation of a user interface design [11]. It is known as one of
the most popular usability inspection methods, and it is done as a systematic inspection of user
interface design for usability [11]. As mentioned, a usability questionnaire was conducted to
evaluate the usability issues of the prototype application among 96 students. However, using this
technique and giving the participants real mobile devices, allowed participants to use this
application to share opinions regarding their experiences while interacting with the real prototype
application. Participants rated each question from 1 to 5 on a Likert scale (1=very easy, 5=very
difficult).
After they were given the questionnaire survey form they were provided with real smartphones.
The main goal here was to compare the two user interfaces in the four sections and determine
which one of these interfaces is better, in terms of usability sub-characteristics.
4.3. Assessment Method
Upon collecting the data, the level of usability was investigated by evaluating the application user
interfaces, which include ease of use, user satisfaction, and attractiveness and learnability. A
comparison will be made to determine the more user-friendly interface between the two models
that form a part of the prototype.
5.DATA ANALYSIS
The data analysis aims at comparing user interfaces Model A and Model B for smartphone
applications. The specific areas of comparing the two models will be: ease of use, user
satisfaction, attractiveness, and learnability. The sample contains 96 students who used the UI for
the application and finished the survey correspondingly. First a descriptive analysis of the data
collected is presented. After this a comparative analysis of the responses of participants using
Model A and Model B will be presented based on the four aspects mentioned earlier. This will be
followed by the reliability and validity of data. Finally, the association analysis is presented to
ensure that the user evaluates both models independently.
5.1. Descriptive Analysis of Data
For the purpose of analysis, the participant responses for both user interfaces (Model A and
Model B) have been gathered on four aspects of usage: ease of use, user satisfaction,
attractiveness, and learnability. Table 2 below presents the mean and standard deviations of the
participant responses for the four aspects of usage.
Table 2. Statistical Analysis of Data
Mean and SD
Usability sub-characteristics
Ease of Use User satisfaction Attractiveness Learnability
Model A Mean 2.47 2.23 3.16 2.17
Model A SD 0.37 0.27 0.27 0.1
Model B Mean 1.74 1.76 2.05 1.71
Model B SD 0.14 0.19 0.13 0.09
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5.2. Comparative Analysis of Data
As multiple questions were used to evaluate both models in each section the same weight was
given to every question for overall evaluation.
The statistics of “ease of use” sub-characteristic from Table 2 shows that Model B, with a mean
of 1.74, has a lower score than Model A, with a mean of 2.47. This means that participants
consider the user interface of Model B to be easier to use as compared to the user interface of
Model A. The results are corroborated by the standard deviation (SD) of the two models. Model
B with SD 0.14 is lower than the SD of Model A, which is 0.37. This shows that the Model B
responses are more consistent.
The statistics of “user satisfaction” sub-characteristic from Table 2 shows that Model B, with a
mean of 1.76, has a lower score than Model A, with a mean of 2.23. This means that participants
are more satisfied with the user interface of Model B as compared to the user interface of Model
A. The results are corroborated by the standard deviation of the two models. Model B with SD
0.19 is lower than the SD of Model A, which is 0.27. This shows that the Model B responses are
more consistent.
The statistics of “attractiveness” sub-characteristic from Table 2 shows that Model B, with a
mean of 2.05, has a lower score than Model A, with a mean of 3.16. This means that participants
consider the user interface of Model B to be better looking as compared to the user interface of
Model A. The results are corroborated by the standard deviation of the two models. Model B with
SD 0.13 is lower than the SD of Model A, which is 0.27. This shows that the Model B responses
are more consistent.
The statistics of “learnability” sub-characteristic from Table 2 shows that Model B, with a mean
of 1.71, has a lower score than Model A, with a mean of 2.17. This means that participants
consider that it is easier to learn a topic utilizing the user interface of Model B as compared to
learning with the user interface of Model A. The results are corroborated by the SD of the two
models. Model B with SD 0.09 is lower than SD of Model A, which is 0.1. This shows that the
Model B responses are more consistent.
The results of the four sub-characteristics can be averaged to find the overall comparative
performance of Model A and Model B.
5.3. Reliability and validity of data
In order to validate our intuitive understanding regarding the comparison between Model A and
Model B, a paired T-test and F-test is used to test the different scores between Model A and
Model B, as well as the variance differences between the two models. The hypothesis for the test
shown in Table 3 below is that Model B performs the same as Model A. This is tested for each of
the sub-characteristics, resulting in a total of four hypotheses (H1, H2, H3, and H4) to be tested.
In addition to the four hypotheses, a general case hypothesis, H5, is also created by averaging the
results from the four sub-characteristics.
Table 3. Hypothesis for usability sub-characteristics.
Sub Characteristics Hypothesis Statement to be Tested
Ease of Use
Model B performs the same as Model A
User satisfaction
Attractiveness
Learnability
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The outcomes of the reliability and validity analysis are shown in Table 4. For each of the
usability sub-characteristics the test statistics and confidence intervals for both T-test and F-test
are given in the table.
Table 4. Analysis of data using T-test and F-test.
Hypotheses
Paired T-Test Paired F-Test
Test Statistics Test Statistics
Ease of Use 15.0* 1.32*
User satisfaction 10.5* 1.30*
Attractiveness 20.7* 0.70*
Learnability 7.9* 1.37*
General Case 27.3* 1.32*
(*) Significant at p-value < 0.05, and (**) Insignificant at p-value > 0.05
• Ease of Use – From Table 4 above it can be seen that this sub-characteristic, the hypothesis that
Model A and Model B perform the same, is rejected. The hypothesis is rejected because of the
test statistic that is statistically significant at p-vale < 0.05. This indicates that Model A and
Model B have significantly different performance levels from this perspective. In order to
perform variance and consistency analysis, again the hypothesis that Model A and Model B
perform the same is used. In this case, too, the hypothesis is rejected as the test statistic is
significant at p < 0.05. This means that the consistency situation for Model A and Model B is
different in terms of ease of use.
• User Satisfaction – From Table 4 above it can be seen that this sub-characteristic, the hypothesis
that Model A and Model B perform the same, is rejected. The hypothesis is rejected because of
the test statistic that is statistically significant at p-vale < 0.05. This indicates that Model A and
Model B have significantly different performance levels from the user satisfaction perspective. In
order to perform variance and consistency analysis, again the hypothesis that Model A and Model
B perform the same is used. In this case, too, the hypothesis is rejected as the test statistic is
significant at p < 0.05. This means that the consistency situation for Model A and Model B is
different in terms of user satisfaction.
• Attractiveness – From Table 4 above it can be seen that this sub-characteristic, the hypothesis
that Model A and Model B perform the same, is rejected. The hypothesis is rejected because of
the test statistic that is statistically significant at p-vale < 0.05. This indicates that Model A and
Model B have significantly different performance levels from the attractiveness perspective. In
order to perform variance and consistency analysis, again the hypothesis that Model A and Model
B perform the same is used. In this case, too, the hypothesis is rejected as the test statistic is
significant at p < 0.05. This indicates that Model A shows more consistency than Model A in
terms of responses for attractiveness. When the reasons for this result are analyzed, it is found
that attractiveness is more of a subjective judgement and is dependent on an idiosyncratic factor
for each user. Yet another reason for this outcome can be due to the fact that the evaluation of
Model A was more concentrated and focused. Several of the questions in this section were
regarding the colour of the interface. Most of the user interface of Model B has different shades
of red, and the feedback from the users showed an aversion to the colour with several participants
suggesting this colour should not be used.
• Learnability – From Table 4 above it can be seen that for this sub-characteristic, the hypothesis
that Model A and Model B perform the same is rejected. The hypothesis is rejected because of the
test statistic that is statistically significant at p-vale < 0.05. This indicates that Model A and
Model B have significantly different performance levels from the learnability perspective. Thus
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these statistics validate our intuitive understanding that Model B performs better than Model A
(as per the comparative analysis of data in the previous section). In order to perform variance and
consistency analysis, again the hypothesis that Model A and Model B perform the same is used.
In this case, too, the hypothesis is rejected as the test statistic is significant at p < 0.05.
• General Validation - From Table 4 above it can be seen that from the overall general
perspective, the hypothesis that Model A and Model B perform the same is rejected. The
hypothesis is rejected because of the test statistic that is statistically significant at p-vale < 0.05.
This indicates that Model A and Model B have significantly different performance levels from an
overall general perspective. In order to perform variance and consistency analysis, again the
hypothesis that Model A and Model B perform the same is used. In this case, too, the hypothesis
is rejected as the test statistic is significant at p < 0.05. This means that the consistency situation
for Model A and Model B is different in terms of user satisfaction. This indicates that Model B
shows more consistency than Model A
5.4. Association Analysis
For the purpose of this study, the evaluation of both Models A and B has been conducted
simultaneously. Hence, it is essential that the association levels between the evaluation of Models
A and B are tested. This is to check whether the user evaluates Model A and Model B
independently or not. The test is performed on the five hypotheses (H1, H2, H3, H4, and H5) for
each of the four usability sub-characteristics, as depicted in Table 3. One of the methods to check
for association levels in the parametric statistics is to find the Pearson correlation coefficient
between Model A and Model B. Since this is a statistical test, the p-value – i.e., the probability of
obtaining a test-statistic – is observed. The lower the p-value, the less likely that the result if the
null hypothesis is true and, accordingly, the more “significant” is the result in terms of its
statistical significance [36]. The Spearman Coefficient is the counterpart of the Pearson
Coefficient in non-parametric analysis, which defines the correlation between the two models.
The results for the Pearson correlation coefficient and the Spearman Correlation Coefficient are
displayed in Table 5 below.
Table 5. Analysis of the Data Using Pearson and Spearman Correlation Methods.
Hypotheses Correlation Coefficients
Section Pearson Correlation
Coefficient
Spearman Correlation
Coefficient
H1 Ease of Use 0.06** 0.09*
H2 User satisfaction 0.20* 0.21*
H3 Attractiveness -0.010** -0.008**
H4 Learnability 0.22* 0.24*
H5 General Case 0.16* 0.17*
(*) Significant at p-value < 0.05, and (**) Insignificant at p-value > 0.05
• Ease of Use – From Table 5 above it can be seen that the outcomes of the analysis for this sub-
characteristic regarding the association between Model A and Model B are not consistent. In fact
the outcomes are contradictory. The Pearson Correlation Coefficient test is positive (0.06) at P-
Value > 0.05, hence, the hypothesis cannot be rejected. The Spearman Correlation Coefficient
test, on the other hand, is (0.09) at P-Value < 0.05; therefore, the hypothesis is rejected. However,
if we take a closer look at the P-value, we can see that the P-Value for the Spearman coefficient is
(0.027), which is close to the boundary of 0.05. This situation indicates the inaccuracy of this test.
Another possible cause for this situation is that the Spearman coefficient is a non-parametric
association estimation. Therefore, the sample size plays a very important role in the accuracy of
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this coefficient estimation. Our sample is limited to the 96 students who participated in the
survey. The limited sample size will make the coefficient less accurate. Thus in this case, the
outcome of the Pearson coefficient, which indicate that the evaluation of these two models is
independent, must be accepted as the actual outcome.
• Usage Satisfaction – In the user satisfaction section, The Pearson Correlation Coefficient
between Model A and Model B is positive (0.20) (P-Value < 0.05), and the Spearman Correlation
Coefficient test is also positive (0.21) (P-Value < 0.05). Since the P-Values for the two
Coefficients indicate the significance of the test, it can be seen that both the Pearson Coefficient
and the Spearman Coefficient indicate that we should reject the hypothesis. Therefore, the
evaluation of Model A has a positive relationship with that of Model B, which indicates that the
users who evaluate Model A with a higher score will also tend to evaluate Model B with a higher
score.
• Attractiveness – From the outcomes of the attractiveness section, we find that the P-value for
the Pearson Coefficient and the Spearman Coefficients are negative (-0.010, -0.008) with P-Value
> 0.05. Since the P-Values for the two Coefficients indicate the insignificance of the test, both the
Pearson Coefficient and Spearman Coefficient indicate that the null hypothesis about the
independence situation between these two Models cannot be rejected. However, since
attractiveness is purely a subjective judgment towards the models, the evaluation between Model
A and Model B will be independent.
• Learnability – For the learnability, the Pearson correlation coefficient between Model A and
Model B is positive (0.22) (P-Value < 0.05). Furthermore, the Spearman Correlation Coefficient
test is also positive (0.24) (P-Value < 0.05); the p-values for the two coefficients indicate the
significance of the test. Therefore, the Pearson Coefficient and Spearman Coefficient suggest that
we should reject the hypothesis. Moreover, the evaluation of Model A has a positive relationship
with that of Model B, which suggests that users who evaluated Model A with a higher score also
tend to evaluate Model B with a higher score.
• General Case – Finally, in the general case section, the Pearson Correlation Coefficient between
Model A and Model B is positive (0.16) (P-Value < 0.05), and the Spearman Correlation
Coefficient test is also positive (0.17) (P-Value < 0.05). Since the P-Values for the two
coefficients indicate the significance of the test, the Pearson Coefficient and Spearman
Coefficient indicate that we should reject our hypothesis. Also, the evaluation for Model A has a
positive relationship with that of Model B, suggesting that the users who evaluate Model A with a
higher score also tend to evaluate Model B with a higher score.
6.DISCUSSION OF RESULTS
The prime objective of this work is to propose a conceptual framework for measuring the
usability aspects of m-Learning. Further, the framework was used as a guideline to build a
prototype model of a prototype application for smartphones. This model was compared with
another model based on the Blackboard website on the basis of questionnaire responses from a
survey conducted at the University of Western Ontario. The comparative analysis shows that the
distribution of Model B was smaller than that of Model A. According to our pre-defined options
for the questions, practitioners tend to rank Model B better than model A. In order to support our
intuitive idea of the data, a validation test of the Models was performed.
As the evaluation of the two Models A and B was paired together, the paired T-test was used to
evaluate the difference between the mean of Model A and Model B for each question and the
general case. The F-test was then used to test whether the variance of Model A will be the same
14. International Journal on Integrating Technology in Education (IJITE) Vol.3, No.4, December 2014
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as that of Model B in different sections. The results of the analysis showed that the p-value of the
T-test and F-test was less the 0.05, the null hypothesis (i.e., the difference between the mean of
Models A and B is 0) should be rejected.
The samples were further analyzed using the association test to examine whether there is
relationship between when students evaluate Model A and Model B. The key statistics used for
determining this were the Pearson Correlation Coefficient and the Spearman Correlation
Coefficient. After testing the hypothesis it was found that for some questions, students evaluate
Model A and Model B independently. However, the overall results demonstrated the existence of
a positive correlation between the evaluation of Model A and Model B. This means that students
who evaluate Model A higher tend to evaluate Model B higher.
In conclusion, the analysis pointed clearly that Model B would give a superior usability
performance as compared to Model A in terms of the four sub-characteristics used to evaluate
usability: ease of use, user satisfaction, attractiveness, and learnability.
7. CONCLUSION
M-learning applications must be easy to use, learnable, understandable, and attractive as well as
provide an enjoyable experience for users. It is important to meet usability needs for the m-
Learning applications, since user interface plays the most important role for each individual
interaction between the user and his/her smartphone application. However, little attention has
been paid to researching the usability assessment in the area of m-Learning application design.
One of the key contributions of this work is the development of a conceptual framework for
measuring the quality aspects of m-Learning. In addition, a prototype application for smartphones
using the Java Language and an Android Software Development Kit has also been developed by
following the proposed framework as a guideline. We also conducted a questionnaire survey at
Western University to compare this prototype with a model based on the Blackboard website.
While performing the comparative analysis, it was discovered that our model – developed using
our framework as a guideline – performed better than the model developed based on the
Blackboard website in terms ease of use, user satisfaction, attractiveness, and learnability.
This framework can be used as a guideline to support forward and reverse engineering and for use
in the future while developing mobile applications. The key limitation of the analysis is the
limited demographics used (comprising only undergraduate software engineering students) while
conducting the research questionnaire, which means that the results cannot be deemed as
universal. Future research could involve the quality perspective of the learning material itself.
The research can also be extended to assess the design issues of learning-on-the-move,
collaboration, and communication and interactivity.
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Authors
Mr. Abdalha Ali is graduated with a Masters degree in Software Engineering in the
Department of Electrical and Computer Engineering at Western University. He
received his B.A.Sc. in Electrical and Computer Engineering from the University of
Al Jabal Al Gharbi, Libya, in 2005. His research interest includes technology tools
for teaching and the use of mobile devices in education. Mr. Ali worked for more
than 3 years in the Higher Ministry of Education in Libya, where he gained good
experience in project Management. He can be reached at: aali252@uwo.ca
Mr. Muasaad Alrasheedi is a Ph.D. Candidate in the department of Electrical and
Computer Engineering (Software Engineering Program) at Western University,
London, Canada. Mr. Alrasheedi has a Bachelor of Science degree in Information
Technology and Computing From Arab Open University, Saudi Arabia and Master
of Engineering in Technology Innovation Management from Carleton University,
Ottawa, Canada. His research interest is in the mobile learning and emerging
educational technology. He can be reached at: malrash@uwo.ca.
Dr. Abdelkader Ouda is an Assistant Professor in the Department of Electrical and
Computer Engineering at Western University. He received his B.Sc. (Hons) and
M.Sc. degrees in Computer Science and Pure Mathematics from Ain Shams
University, Cairo, Egypt, in 1986, and 1993 respectively, and his Ph.D. degree in
Computer Science from the Western University, Canada in 2005. Dr. Ouda has been
studying, researching, and teaching software engineering at Western University for
12 years. His current research is mainly in Information and networking security. Dr.
Ouda was working for over 14 years in the software development industry, involving
project management, system analysis/consulting, and database design. He can be
reached at: aouda@uwo.ca.
Dr. Luiz Fernando Capretz is a Professor of Software Engineering and Assistant
Dean (IT & e-Learning) at Western University, London, Canada. His research
interests include software engineering, technology-enhanced learning, human factors
in software engineering, and software engineering education. Dr. Capretz has a PhD
in computing science from the University of Newcastle upon Tyne. He is a senior
member of the IEEE, a distinguished member of the ACM, an MBTI certified
practitioner, and a Professional Engineer in Ontario (Canada). He can be reached at:
http://www.eng.uwo.ca/people/lcapretz/default.htm. Email: lcapretz@uwo.ca