Post Acceptance Model for Online Teleconsultation services: An Empirical Study in Malaysia

open access journalMost nations across the world are actively pursuing equal access to healthcare services. Teleconsultation technology is a substantial improvement in terms of an effective framework for the provision of healthcare services. However, a lack of understanding of people’s willingness towards the use of this technology has been observed. The goal of this study is to investigate the factors affecting the post-acceptance of teleconsultation services in Malaysia. This study developed a theoretical model which involves the combination of the second generation of Unified Theory of Acceptance and Use of Technology (UTAUT2) and Expectation Confirmation Theory (ECT), with the inclusion of several other constructs. An online survey was used to collect data from 154 university students and partial least squares (PLS) approach was used for data analysis. The research findings indicate that confirmation, performance, effort expectancy, usefulness, and satisfaction were the key factors that affect the post-acceptance of teleconsultation services. Furthermore, actual use, ease of use, technology readiness, and facilitating conditions did not impact participants' post intention in the continuous usage of teleconsultation facilities

Evaluation of Islamic websites’ content reliability

Internet is an open platform for anyone to publish and share information without being subjected to the authenticity of information. For Muslims, religious information crucially should be reliable due to the very reason that many Muslims consider the Internet as a source in getting Islamic knowledge. Unfortunately, the assessment on reliability of the information provided by the Internet is complex. The huge amounts of data available and lack of knowledge among Muslims contribute to the users’ incapability to recognize existences of unreliable information. Focusing on the reliability of information, this paper presents a software prototype, which uniquely automates and processes the reliability evaluation through inspections of references and scholars that are cited in the Islamic websites. Those references indicate that the Islamic websites derived their information from reliable religious sources

Students’ intention to use emotion-aware virtual learning environment: Does a lecturer’s interaction make a difference?

Purpose: This study explored students' perspective of using emotion aware Vertual Learning Environment (VLE) in Malaysia's higher education institutions. The purpose is to investigate the relationships among dimensions of Technology Readiness Index (TRI), attitude, intention to use VLE, and lecturer interaction. The outcomes concerned the emotions involved in the educational process of Malaysia's higher education institutions. Methodology: Quantitative data were collected via an online survey from 260 students. An empirical analysis was then conducted using structural equation modelling (Smart PLS) in two phases: (1) examining the direct effect of students' attitude on VLE adoption intention and (2) examining the indirect effect of constructs using lecturer interaction as a mediator. Findings: The findings revealed a significant mediating role of lecturer interaction on the relationship between attitude and intention to use VLE across the student cohort. Inhibitors, such as insecurity and discomfort, were less significant in affecting students' attitude towards emotion aware VLE. The results indicate that students are motivated to use VLE when lecturers understand their emotions and react accordingly. Significance: This is one of the studies pertaining to emotions in VLE and lecturer interaction in higher education institutions. The results facilitate an understanding of the pedagogical role of lecturer interaction as a practical learning motivation. It is of particular interest to curriculum and e-learning stakeholders looking to improve students' interactions with the VLE systems. Apart from extending the current literature, this study has significant practical implications for education management in higher learning institutions

Students' intention to use emotion-aware virtual learning environment: does a lecturer's interaction make a difference?

Purpose: This study explored students’ perspective of using emotion-aware Vertual Learning Environment (VLE) in Malaysia’s higher education institutions. The purpose is to investigate the relationships among dimensions of Technology Readiness Index (TRI), attitude, intention to use VLE, and lecturer interaction. The outcomes concerned the emotions involved in the educational process of Malaysia’s higher education institutions. Methodology: Quantitative data were collected via an online survey from 260 students. An empirical analysis was then conducted using structural equation modelling (Smart PLS) in two phases: (1) examining the direct effect of students’ attitude on VLE adoption intention and (2) examining the indirect effect of constructs using lecturer interaction as a mediator. Findings: The findings revealed a significant mediating role of lecturer interaction on the relationship between attitude and intention to use VLE across the student cohort. Inhibitors, such as insecurity and discomfort, were less significant in affecting students’ attitude towards emotion-aware VLE. The results indicate that students are motivated to use VLE when lecturers understand their emotions and react accordingly. Significance: This is one of the studies pertaining to emotions in VLE and lecturer interaction in higher education institutions. The results facilitate an understanding of the pedagogical role of lecturer interaction as a practical learning motivation. It is of particular interest to curriculum and e-learning stakeholders looking to improve students’ interactions with the VLE systems. Apart from extending the current literature, this study has significant practical implications for education management in higher learning institutions

The perception of Muslim users on reliability of Islamic websites

The Internet offers a new medium for Muslims to conduct da’wah (preaching) and it is a direct channel to obtain Islamic knowledge anywhere at any time. However, online content can be questionable unless there is a certain level of commitment to the recommendations stated in the literature. Similarly, Islamic websites should be reliable to Muslim users as a major source of Islamic knowledge. This paper reports the findings of a study conducted to measure Muslim users’ perceptions on the reliability of Islamic websites. Around 50 participants answered online open-ended questions, although only 40 returns were considered. Content analysis was used to analyze the data and revealed that the reliability of Islamic websites must be represented in the content, endorsement, interface, and references. In addition, respondents recommended for utilizing IT technology to ensure the reliability of Islamic websites and to make cross-cultural Islamic websites which reflect the various cultures of Muslims from different races and nations, as well as to deliver the message to non-Muslims in various languages. Respondents emphasized on the neutrality of the website when discussing the perceptions of madhahāb, the availability of endorsement from well-known scholars or Islamic organizations, and the agility and accessibility of user interface. They considered that citing appropriate references will enhance the reliability of the content. Since, Muslims are distributed around the world and they come from different nations and cultures, having multi-language option for the websites is considered as a good sign of reliability. Participants suggested an application or system that could evaluate and produce reports on the reliability of Islamic websites. Keywords: Islamic website, reliability, user perceptio

Comparative Study of SMOTE and Bootstrapping Performance Based on Predication Methods

Recently, there has been a renewed interest in smart health systems that aim to deliver high quality healthcare services. Prediction methods are very essential to support these systems. They mainly rely on datasets with assumptions that match the reality. However, one of the greatest challenges to prediction methods is to have datasets which are normally distributed. This paper presents an experimental work to implement SMOTE (Synthetic Minority Oversampling Technique) and bootstrapping methods to normalize datasets. It also measured the impact of both methods in the performance of different prediction methods such as Support vector machine (SVM), Naive Bayes, and neural network(NN) The results showed that bootstrapping with native bays yielded better prediction performance as compared to other prediction methods with SMOTE