A hybrid e-learning framework: Process-based, semantically-enriched and service-oriented

Despite the recent innovations in e-Learning, much development is needed to ensure better learning experience for everyone and bridge the research gap in the current state of the art e-Learning artefacts. Contemporary e-learning artefacts possess various limitations as follows. First, they offer inadequate variations of adaptivity, since their recommendations are limited to e-learning resources, peers or communities. Second, they are often overwhelmed with technology at the expense of proper pedagogy and learning theories underpinning e-learning practices. Third, they do not comprehensively capture the e-learning experiences as their focus shifts to e-learning activities instead of e-learning processes. In reality, learning is a complex process that includes various activities and interactions between different roles to achieve certain gaols in a continuously evolving environment. Fourth, they tend more towards legacy systems and lack the agility and flexibility in their structure and design. To respond to the above limitations, this research aims at investigating the effectiveness of combining three advanced technologies (i.e., Business Process Modelling and Enactment, Semantics and Service Oriented Computing – SOC–) with learning pedagogy in order to enhance the e-learner experience. The key design artefact of this research is the development of the HeLPS e-Learning Framework – Hybrid e-Learning Framework that is Process-based, Semantically-enriched and Service Oriented-enabled. In this framework, a generic e-learning process has been developed bottom-up based on surveying a wide range of e-learning models (i.e., practical artefacts) and their underpinning pedagogies/concepts (i.e., theories); and then forming a generic e-learning process. Furthermore, an e-Learning Meta-Model has been developed in order to capture the semantics of e-learning domain and its processes. Such processes have been formally modelled and dynamically enacted using a service-oriented enabled architecture. This framework has been evaluated using a concern-based evaluation employing both static and dynamic approaches. The HeLPS e-Learning Framework along with its components have been evaluated by applying a data-driven approach and artificially-constructed case study to check its effectiveness in capturing the semantics, enriching e-learning processes and deriving services that can enhance the e-learner experience. Results revealed the effectiveness of combining the above-mentioned technologies in order to enhance the e-learner experience. Also, further research directions have been suggested.This research contributes to enhancing the e-learner experience by making the e-learning artefacts driven by pedagogy and informed by the latest technologies. One major novel contribution of this research is the introduction of a layered architectural framework (i.e., HeLPS) that combines business process modelling and enactment, semantics and SOC together. Another novel contribution is adopting the process-based approach in e-learning domain through: identifying these processes and developing a generic business process model from a set of related e-learning business process models that have the same goals and associated objectives. A third key contribution is the development of the e-Learning Meta-Model, which captures a high-abstract view of learning domain and encapsulates various domain rules using the Semantic Web Rule Language. Additional contribution is promoting the utilisation of Service-Orientation in e-learning through developing a semantically-enriched approach to identify and discover web services from e-learning business process models. Fifth, e-Learner Experience Model (eLEM) and e-Learning Capability Maturity Model (eLCMM) have been developed, where the former aims at identifying and quantifying the e-learner experience and the latter represents a well-defined evolutionary plateau towards achieving a mature e-learning process from a technological perspective. Both models have been combined with a new developed data-driven Validation and Verification Model to develop a Concern-based Evaluation Approach for e-Learning artefacts, which is considered as another contribution

eLEM: A novel e-Learner Experience Model

Many e-learning artefacts have been developed and promoted based on their ability to enhance learning and e-learner experience. However, there is a lack of precise definition of what the e-learner experience implies and associated models to inform this experience. This paper introduces a novel e-Learner Experience Model (eLEM) along with its roots in: (i) e-learning domain research, and (ii) user experience/usability. It also proposes a definition for the e-learner experience model based on the particularities of e-learning. eLEM has been derived based on a state of the art literature review and consists of a number of constructs along with measures of their effectiveness in evaluating the e-learner experience in an e-learning environment. eLEM has been comprehensively evaluated using a set of sufficient and representative case studies. It has also demonstrated modelling the e-learner’s experience in various contexts and identified four key challenges for further research. Finally, the eLEM has been integrated with the HeLPS e-learning framework and contributed to validating its process-centric models

Towards a generalised e-learning business process model

Modelling learning scenarios is central for e-learning domain. This has been manifested in the proliferation of the different Educational Modelling Languages, as well as in developed e-learning models. However, the existing modelled scenarios are deficient as they lack flexibility and the agility to respond to the dynamic nature of an e-learning process that is suitable to answer learners’ needs. This paper proposes a novel approach to develop a generalised business process model from a set of related business processes sharing the same goals and associated objectives. The proposed approach has been applied in the e-learning domain, which demonstrated its ability to develop a generalised e-learning business process model that is derived from the existing pedagogical models and technology-enhanced learning artefacts. Moreover, the proposed approach has been evaluated to test its effectiveness in generalising a set of business processes, which paves the ground to apply it in different contexts. The generalised e-learning business process model has been modelled using the industrial standard Business Process Modelling Notations (BPMN 2.0) so that processes can be dynamically enacted in service-oriented environments and, at the same time, adapting to answering e-learners’ learning requirements

Capturing Public Concerns about Coronavirus Using Arabic Tweets: An NLP-Driven Approach

This In order to analyze the people reactions and opinions about Coronavirus (COVID-19), there is a need for computational framework, which leverages machine learning (ML) and natural language processing (NLP) techniques to identify COVID tweets and further categorize these in to disease specific feelings to address societal concerns related to Safety, Worriedness, and Irony of COVID. This is an ongoing study, and the purpose of this paper is to demonstrate the initial results of determining the relevancy of the tweets and what Arabic speaking people were tweeting about the three disease related feelings/emotions about COVID: Safety, Worry, and Irony. A combination of ML and NLP techniques are used for determining what Arabic speaking people are tweeting about COVID. A two-stage classifier system was built to find relevant tweets about COVID, and then the tweets were categorized into three categories. Results indicated that the number of tweets by males and females were similar. The classification performance was high for relevancy (F=0.85), categorization (F=0.79). Our study has demonstrated how categories of discussion on Twitter about an epidemic can be discovered so that officials can understand specific societal concerns related to the emotions and feelings related to the epidemic

Bridging the Gap Between Informal Learning Pedagogy and Multimodal Learning Analytics

Multimodal Learning is happening in different contexts, where different technologies are utilized. In such contexts, different modalities are used by learners in very unstructured ways. These modalities include video, audio, motion, eye tracking, to mention but a few. However, effective applications of Multimodal Learning Analytics remain challenging. Enabling educational technologies are underpinned by various pedagogical models that are designed to provide educational values of technology. Nevertheless, the link between Multimodal Learning Analytics and informal learning pedagogy is not very well established in the literature. Hence, this chapter aims at bridging the gap between multimodal learning analytics research concepts and approaches from one side and key informal learning pedagogical approaches such as self-directed learning and learning theories such as behaviorism and cognitivism from the other side. Establishing this link is expected to pave the ground for insightful and pedagogically informed learning analytics across multiple contexts. In addition, further explanations on what Multimodal learning analytics techniques and challenges are discussed to highlight the key concerns of MMLA applications

Trends, applications, and challenges of chatbot technology

Chatbots offer exceptional services to end-users due to various factors, including the ability to respond to customer requests quickly according to their convenience. Given the magnitude of research and interest in chatbots, further study on several vital and evolving concerns including human-bot interaction, chatbot adoption, chatbot architecture, design considerations, and chatbot applications in various domains including education and customer support is necessary. Trends, Applications, and Challenges of Chatbot Technology provides novel research content and reviews of current chatbot technology and sheds light on challenges and open questions as well as possible research directions. Covering key topics such as human-computer interaction, education, customer support, and algorithms, this reference work is ideal for computer scientists, industry professionals, policymakers, researchers, academicians, practitioners, scholars, instructors, and students

Characterizing Visual Programming Approaches for End-User Developers: A Systematic Review

Recently many researches have explored the potential of visual programming in robotics, the Internet of Things (IoT), and education. However, there is a lack of studies that analyze the recent evidence-based visual programming approaches that are applied in several domains. This study presents a systematic review to understand, compare, and reflect on recent visual programming approaches using twelve dimensions: visual programming classification, interaction style, target users, domain, platform, empirical evaluation type, test participants\u27 type, number of test participants, test participants\u27 programming skills, evaluation methods, evaluation measures, and accessibility of visual programming tools. The results show that most of the selected articles discussed tools that target IoT and education, while other fields such as data science, robotics are emerging. Further, most tools use abstractions to hide implementation details and use similar interaction styles. The predominant platforms for the tools are web and mobile, while desktop-based tools are on the decline. Only a few tools were evaluated with a formal experiment, whilst the remaining ones were evaluated with evaluation studies or informal feedback. Most tools were evaluated with students with little to no programming skills. There is a lack of emphasis on usability principles in the design stage of the tools. Additionally, only one of the tools was evaluated for expressiveness. Other areas for exploration include supporting end users throughout the life cycle of applications created with the tools, studying the impact of tutorials on improving learnability, and exploring the potential of machine learning to improve debugging solutions developed with visual programming. © 2013 IEEE

Embracing Technological Change in Higher Education

Access to information has never been easier, thanks to the rapid development of the internet and communication technologies, and the ubiquity of smartphones and other internet-enabled devices. In traditional classroom learning, teachers provide students with various sources of information that are known to be reliable. Nowadays, especially in a post-pandemic era, students increasingly rely on a host of resources available on the internet. Exposure to vast amounts of scattered information could adversely affect students’ learning process. Meanwhile, pedagogical approaches, classroom learning practices, and student learning activities have evolved significantly to cope with contemporary challenges. This study reviews the current learning practices and the technological interventions in a rapidly evolving higher education landscape. In particular, the challenges when integrating technology into higher education are considered in detail and ways put forward for doing so in that context

E-learning at Islamic University of Gaza

E-learning is a new form of education and is a tool to reach students everywhere. In Gaza Strip it was used to solve the difficulty in movement problem. It was used as an enhancement tool in the educational process. IUG started experimenting with e-learning since 1999. IUG started a systematic approach in developing it e-learning teams. Joint partnership with Middlesex University help set up a system. Couple of courses were available to all university students and limited success was enjoye