Wei Wei Goh

Examining the antecedents of persuasive eWOM messages in social media

Purpose – Numerous electronic word-of-mouth (eWOM) studies have been conducted to examine the effectiveness of persuasive eWOM messages. Despite the impact of eWOM messages in decision-making processes, few researches have directly tested potential antecedents of persuasive eWOM messages among message recipients in social media context. The purpose of this paper is to critically discuss and examine the determinants of persuasive eWOM messages when message recipients intend to accept and use eWOM messages. Design/methodology/approach – The authors reviewed extant literature of eWOM and proposed hypotheses regarding persuasive eWOM messages in social media context. A survey of 78 respondents was conducted and the data were analysed using SmartPLS. Findings – This study found that argument quality, source credibility, source attractiveness, source perception and source style are critical antecedents of persuasive eWOM messages. The PLS results suggested that source credibility (trustworthiness), source perce...

Conceptualizing Persuasive Messages Using ELM in Social Media

Elaboration Likelihood Model (ELM) assumes that consumers interpret persuasive messages by applying central and peripheral routes in a particular environment. Companies are trying to maximize the potential of social media in their marketing communication strategies. This study aims to conceptualize persuasive messages using ELM in a social media perspective, propose a conceptual framework, and systematically review and analyze extant theories and models pertinent to persuasive communications. ELM is considered a feasible and useful approach to elucidate the persuasive information process by consumers in the social media context. Findings revealed that there were an increasing number of studies using ELM in the social media context. The authors believed that this study shed light on further potential studies in ELM in the social media environment. The proposed conceptual framework underlined critical constructs and parameters of information processing so that marketers could formulate effective communication strategies in the social media environment.

Exploring students' perceptions of learning management system: An empirical study based on TAM

This research aims to explore the perceptions of students in using learning management system (LMS) in order to enhance the learning process of students. The research also identifies issues that students faced when using LMS in order to improve the ease of use of LMS. Technology Acceptance Model (TAM) is used as the theoretical framework to explain the adoption of LMS in term of perceived ease of use and perceived usefulness. Respondents agree that LMS is easy to use and useful to them as a repository. However, results indicate that there is a lack of interaction among lecturers and peers.

Persuasive Communication: A Study of Major Attitude-Behavior Theories in a Social Media Context

Although numerous studies on attitude-behavior theories exist in the social media context, few extensive studies have been conducted in reviewing and classifying the extant literature. This study aims to critically review, discuss, and examine five major attitude-behavior theories in the social psychology field. Theory of Planned Behavior, Elaboration Likelihood Model, Heuristic-Systematic Model, Cognitive Dissonance Theory, and Social Judgment Theory have been empirically dissected and reviewed in a systematic manner, after which criticisms and compliments of these theories have been observed and evaluated. The significance of the study is to identify the trend of applying attitude-behavior theories to manifesting practical social media marketing implications. This study found that Elaboration Likelihood Model studies are trending upward among persuasive communication studies in the context of social media.

Ontological based webpage segmentation

In World Wide Web, images come together with valuable surrounding contextual information such as texts. There are very few efforts performed to address problems in mining of the images with their surrounding contextual information; although this information has long been extracted for wide range of uses such as image annotation, clustering of images, inference of image semantic content and image indexing. In this proposal, a genuine ontology based webpage segmentation algorithm is developed for extracting web images with its associated contextual information according to its semantic characteristics (e.g. synonymous words) as they appear on webpages.

Region based data extraction

Wrappers are tools used to extract relevant information from HTML pages. Current approaches use DOM tree, visual cue, and ontology to extract data. DOM tree based techniques are fast and simple. However, they are not as accurate as visual based wrappers due to lack of additional information needed to perform data extraction. Visual based wrappers, on the other hand, are slow due to the extra processing needed to obtain visual cue from the underlying browser rendering engine. Ontology based wrappers are accurate, but they are also slow and need manual tuning to operate them. In this paper, we propose a novel visual based wrapper to extract information from HTML pages. Our wrapper uses visual cue to eliminate unnecessary regions, hence reduces the running time of extraction task as our wrapper only needs to consider the relevant region for extraction. Then, our wrapper removes irrelevant data from the relevant region using visual cue. Experiment results show that our wrapper outperforms state-of-the-art wrapper WISH in data extraction.

The Effectiveness of MOOC Among Learners Based on Kirkpatrick’s Model

Massive open online course (MOOCs) are transforming the era of distance learning education in a groundbreaking way that it has attracted a huge amount of attention from the media, education institutions, and education professionals. The purpose of this study is to measure the effectiveness of courses delivered using MOOCs in Taylor’s University. The Kirkpatrick’s four levels of evaluation learning model were adapted to measure the effectiveness of MOOCs. A descriptive survey of 250 learners was conducted. The study indicated that comprehensive study materials in MOOCs are useful for the learners as future reference. MOOCs are effective in the sense that it helps learners to understand a certain topic and apply it in real life. The program has met the learners’ expectations, and they will strongly recommend the course to other people. Nevertheless, learners think that the study materials are sufficient for beginners, but advanced course is needed to meet their future job expectation. This study focuses on MOOCs in OpenLearning platform only. In the future, research can be expanded to focus on different MOOC platforms besides OpenLearning. Lastly, with the result obtained in this research, it will be able to contribute to the community of MOOC and institutions that plan to introduce MOOCs.

A Comparative Analysis Between Teacher Assessment and Peer Assessment in Online Assessment Environment for Foundation Students

This study explores the comparative analysis of teacher assessment and peer assessment in the context of online-based assessment. The comparative study will help to improve grading accuracy in our assessment system. Therefore, this research is about the feasibility of implementation of online assessment by integration with learning activity management system (LAMS) for students by conducting a qualitative survey. In this survey, 18 students from foundation in computing course were asked on problems and disadvantages of paper-based assessment, feasibility study of acceptance for implementation of online assessment in tutorial and examination, suggestions, and recommendations. This paper will present the literature review on types and modes of assessment for students in higher learning institution. The qualitative survey on the comparison of these two modes of assessment is conducted and its findings are presented. From there, a conceptual model that integrated online assessment with learning activity management system (LAMS) into Taylor’s Integrated Moodle e-Learning System (TIMeS) is proposed in this paper.

Assessing Factors Affecting Students’ Acceptance and Usage of X-Space Based on UTAUT2 Model

Collaborative classroom has started to replace traditional classroom in education. Flexible learning space promotes an engaging, active and learner friendly learning environment. There are many discussions about their design, architecture, effectiveness and acceptance to the students and lecturers. It is undeniable that collaborative learning space is able to support various types of learning styles of students. The purpose of this study is to examine the factors that affect students’ acceptance and usage of X-Space based on the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model. Data were collected from 370 students from five schools of the Foundation Programme. An exploratory factor analysis (EFA) was employed to analyse the data. This study focused on Foundation students, and the result should not be used for generalization. In the future, research can be expanded to focus on degree and postgraduate students. Lastly, with the result obtained in this research, it contributes to universities and institutions that plan to introduce and implement similar collaborative classroom facilities. This research can be used as a guide for them to design and implement technologies-rich collaborative classroom.

An evaluation on current ontological tools and their applications

Currently there are a number of ontological tools available in handling heterogeneous data presented in the computing domain. However, there are no surveys available in evaluating the performance of these tools. In this paper, we provide an in-depth discussion on the state-of-the-art ontological tools and their application to the real world domain. First, we describe the operation of these tools, their strength and differences in handling computing problems. Second, we discuss the limitations of these tools, and their support provided and compatibility across various systems. We also present the current trends in the development of these ontological tools and provide a case study of applying ontological tools to one area of interest-data extraction.