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In this chapter, the discussion threads of six MOOCs courses offered from August 2013 to April 2014 via the Coursera forums were analysed. The purpose of this study is to identify important features that may have an impact on supervised classification analysis in predicting discussion threads that require instructors’ intervention. This study worked on data from the anonymised Coursera MOOC forums with 45,303 threads to gain an insight into the forums. The important features related to thread structures, social network, and popularity are identified using Univariate Feature Selection. Classification analyses using neural networks, decision trees, and naive Bayes algorithms were applied to generate the predictive models. The results show that the developed predictive model is performing well, and the decision trees algorithm outperformed other algorithms with excellent performance measures based on the level of accuracy, precision, recall, and f-measure.

Virtual collaborative learning has been gaining in popularity in open and distance learning (ODL) over the last decade. In collaborative learning environments, the instructors facilitate and initiate discussion on particularissues of concern. Students are given the chance to share their knowledge in a way theyhave not been used to and the possibility of participating in a coordinated effort to solve problems together. A preliminary study showed that collaborative learning activities enhancedstudent satisfaction, achievedthe course learning outcomes and encouragedgroup participation. Peer-to-peer interaction has been shown to be successful and can be engaged in during collaborative learning activities. Wiki is widely promoted as a virtual collaborative tool and has been integrated into several learning management systems. However, there are only limited studies on the effectiveness of moodle-wiki for virtual collaborative learning. Therefore, the aim of this study is to evaluate the effectiveness of moodle-wiki in terms of students' perceptions and performance. The data collected were analysed and evaluated, and the statistical results demonstrate that the students hadpositive perceptions of moodle-wiki and the collaborative tool enhanced their learning performance. This study will be useful for instructors and course designers as a guide to investigating students' perceptions and evaluating the effectiveness of a collaborative tool. The findings of this research are also useful for stakeholders to maximize students' academic learning achievement.

The paper aims to describe dynamic presentation generator that presents the same content in different ways through different media object and presentation layouts. The different media presentation will then display to student via Learning Management Systems (LMS). The paper also presents SCORM Compliant Learning Objects and Conceptual Model Instance (CMI). The prototype is then evaluated to demonstrate the performance of the students where the CMI data are collected for each student. The data collected include media preference, test score and time spent to study the Computer Programming subjects. The results show that with more media object used, students spent more time on the Webpages. However, the results also showed that using more media object may not produce better results in the assessment.

This paper presents the initiative of OER course development for the undergraduate course, Software Scalability and Reengineering using Wikibooks which was recently completed in Semester II, July 2014 in Wawasan Open University (WOU), Malaysia. The initiative presents the phases involved for the development of OER-based course materials namely the OER course integration using Wikibooks, evaluation of Quality Assurance (QA) in OER learning content and the design of OER course material. The learning design for the computing courses with engagement of learning experiences and feedbacks from different stakeholders in Open Distance Learning (ODL) environment are taken into consideration as one of the major components in the OER-based course development phases. The OER-based course comprises of course units, self-tests, unit practice exercises and activities focused on supporting distance learners to fulfill self-directed learning. Evaluations and studies are being carried out at end of the semester by the course team members on the primary aspects focusing on assessments and course learning outcomes. The OER course development has successfully carried out with the integration of four Wikibooks as major resources mainly "Introduction to Software Engineering", "A-Level Computing", "Embedded Systems" and "Embedded Control Systems Design" to promote the use and understanding of Wikibooks and building a learning community in ODL environment.

This paper presents the implementation and development of Mobile-Learning Initiatives in Wawasan Open University in Open Distance Learning (ODL) environment. The Mobile-Learning Initiative was introduced by Mobile Learning Research Group (MLRG) of WOU aiming to promote interactive mobile-learning experiences as an alternative learning for distance learners and carry out studies on mobile-learning applications and developments in the context of distance learning from ODL institutions. The components in this study intend to help educators in the implementation of mobile-learning and stimulate further research on mobile applications. This initiative is also hope to assist open and distance learning practitioners to better understand the concepts of m-Learning and how to more effectively incorporate mobile technologies into the teaching and learning environment.

This paper presents an empirical study aiming on investigating ODL students’ perception and adoption of SCORM Compliant Learning Object (SCLO). With the increasing use of SCLO in recent years, a better understanding and implementation of effective instructional resources is necessary to meet the diverse needs of ODL students and enhance their learning performance. The eventual usage of relevant stakeholders determines the success of a system. The system is useless if it is not used in the expected way by the potential users even though it is a good system. Therefore, the aim of this research is to examine if ODL students will eventually use SCLO for their learning. The study used TAM as a basis to investigate the relationship of external and internal variables. A survey instrument eliciting responses on a series of Likert-type questions was given to selected ODL undergraduate students. The results of this study confirm that users’ perception has significant effect on the acceptance and adoption of SCLO. The study provides a better understanding of students’ behavior on SCLO and the acceptance model.

Magnetic Resonance Imaging (MRI) images have been widely used for liver disease diagnosis. Designing and developing computer-assisted image processing techniques to help doctors improve their diagnosis has received considerable interest over the past years. In this paper, a computer-aided diagnostic (CAD) system for the characterization of hepatic lesions, specifically cyst and tumor as well as healthy liver, from MRI images using texture features and implementation of grid computing (Globus approach) and neural networks (NN) is presented. Texture analysis is used to determine the changes in functional characteristics of organs at the onset of a liver disease, Region of interest (ROI) extracted from MRI images are used as the input to characterize different tissue, namely liver cyst and healthy liver using first-order statistics. The results for first-order statistics are given and their potential applicability in grid computing is discussed. The measurements extracted from First-order statistic include entropy and correlation achieved obvious classification range in detecting different tissues in this work.

This paper presents a 3D face reconstruction face model by using PCA-based reconstruction model in synthesizing faces of individual. A 3D face reconstruction model is derived by transforming the shape and texture of the training sets into a vector space representation. In this paper, a reconstruction of face model is adapted from 3 Dimensional Face Space (3DFS) with the knowledge of the shape and texture of faces. Faces statistics produced by sampling from Face Space is computed by Principle Component Analysis (PCA) of 100 exemplar 3D faces. 3D face space is formed by two distinctive subspaces: the 3D shape space and 3D texture space which consist of 79- dimensional (79 shape and texture coefficient). The first shape space shows the impact of the shape and texture dimensions and the second texture space shows the influence of the shape and texture dimensions. A vertex is a point where two edges of a 2D polygon or two or more vertices of a 3D polyhedron meet. Face Space Coefficient (FSC) is computed as the input for training in generating novel 3D faces as Wavefront Object files (OBJ). The output 3D face space is computed with the aid of material file (.mtl) and texture file (.jpg, .rgb) and viewed by OBJ viewer to achieve good 3D representation using this approach.