Research

TELTSA: Technology Enhanced Learning: Theories, Systems, and Applications Special Track

Chairs and Coordinators:

Rawad Hammad, Senior Education Solutions Analyst, Research & Learning Solutions, King's College London, UK

Rawad.Hammad@kcl.ac.uk

Dr. Kamran Munir, Senior Lecturer – Information Science and Big Data, University of the West of England, Bristol, UK

Kamran2.Munir@uwe.ac.uk

within

BUSTECH 2018, The Eighth International Conference on Business Intelligence and Technology

http://www.iaria.org/conferences2018/BUSTECH18.html

Technology Enhanced Learning (TEL) comprises a variety of innovative ICT solutions to deal with numerous evolving educational challenges. These challenges include improving the experience of learners, academics, and institutions; providing an adaptive, effective, and personalized learning to every learner, managing and meeting the users’ requirements, to mention but a few. Overcoming these challenges can empower learners and consequently the overall society, and contribute to improving the community quality of life. Utilizing ICT in education, or in another word TEL, can facilitate efficient e-learning models where technology helps learners to build their own advanced critical thinking capabilities. It also facilitates new ways of learning such as connectivism, community of practice, and social based learning. Moreover, technology provides a solid ground, where learning communities can test their conceptualization of pedagogy and extend this conceptualization to accommodate new learners’ requirements/feedback. Furthermore, TEL offers significant benefits to disadvantaged learners such as disabled or those who suffer from cognitive disorder.

Despite the great potential shown above and the recent innovations in TEL domain, much development is needed to ensure better learning experience for everyone and to bridge the gap in the TEL state of the art. Effective TEL models, tools, and framework conceive learning as a complex process that includes various activities and interactions between different roles to achieve certain goals in a continuously evolving environment. This requires capturing the context and using advanced knowledge representation and management techniques. Also, due to the dynamic nature of learning process, TEL models should possess a high level of agility, where different abstraction levels are used thorough the Model Driven Engineering approaches. From technology perspective, the possibility of realization of TEL is being enabled by various Artificial Intelligence technologies, theories, and techniques (e.g., Machine Learning, Data Mining, Semantic Web, Big Data, and Learning Analytics), which can be used to customize the learner’s e-learning process, predict her performance, recommend learning activities, and so on. Other distributed computing models such as Cloud Computing and Service Orientation allow further flexibility so that e-learning scenarios/processes can be enacted/orchestrated using a series of web services. Finally, the substantive rise of adopting TEL software systems in real life scenarios (e.g., academic organizations, lifelong learning, formal/informal learning, etc.) necessitates these TEL software systems to be properly architected using various Enterprise Architecture concepts, standards, and framework such as TOGAF.

Publications

- TELTSA - Technology Enhanced Learning: Theories, Systems, and Applications

Rawad Hammad and Kamran Munir

Abstract: Due to the rapid evolving theories and technologies supporting Technology Enhanced Learning (TEL), further investigation for this domain is needed. Therefore, a brief review for TEL past and current state-of-the-art has been performed to predict the future of TEL technologies. This has been supported by design science research paradigm as a research framework, which supports development of an automated analysis technique based on text-mining patients’ feedback. At the end, a service-oriented architecture for TEL software system is presented in order to support end user(s) requirements; and more specifically, non-functional requirements [Full Text].


- Automated Analysis of Patient Experience Text Mining using a Design Science Research (DSR) Approach

Mohammed Bahja and Manzoor Razaak

Abstract: Online forums of hospitals are a common method of collecting patient feedback on the healthcare received. The feedback data obtained are often free text and large which may make a manual analysis of the data difficult and time-consuming. An approach to automatically analyse patient experience data would be beneficial for the hospital staff in several ways. In this paper, a Design Science Research (DSR) paradigm based framework is proposed that is used for our ongoing research in developing solutions with an aim for an automated approach to analyse patient experience data using natural languages processing techniques such as Sentiment Analysis, Topic Modelling, and Dependency Parsing. The framework design proposed provides a three-stage iterative process wherein at each iteration the patient feedback is deeply analysed based on the outcomes obtained from the preceding ones. This iterative approach facilitates the development of a strong, effective patient feedback analysis system [Full Text].


-Requirement-Driven Architecture for Service-Oriented e-Learning Systems

Rawad Hammad

keywords: Technology Enhanced Learning; e-learning; architecture; Non-Functional Requirements; Software architecture; SOA; Web Services

Abstract: The continuous evolving of Technology Enhanced Learning (TEL) requirements, more specifically Functional Requirements, increases the complexity of TEL software system since such requirements cannot be met by one TEL/e-learning solution. In addition to the traditional Virtual Learning Environments/Learning Management Systems capabilities, such Functional Requirements include: video streaming, plagiarism checker for students’ submissions, e-portfolio, etc. Therefore, combining various e-learning software systems, solutions, or tools seems more realistic. However, a limited effort has been done to investigate and control the impact of combining different solutions on the quality, i.e., Non-Functional Requirements (NFRs), of the overall e-learning software system. This paper proposes a new approach to elicit, precisely specify, and manage NFRs for TEL software systems. To meet these capabilities (i.e., Functional Requirements and Non-Functional Requirements), this paper also proposes a flexible service-oriented architecture for e-learning systems. The proposed list of NFRs is comprehensive and can be customized to various e-learning systems to meet stakeholders’ requirements. Moreover, the proposed architecture needs to be further developed to test its impact on TEL software systems in real scenarios [Full Text].

For more information please contact:

Special Track Chair: Rawad Hammad, Rawad.Hammad@kcl.ac.uk