Learner-Centred Design and Evaluation of Web-Based E-Learning Environments

Designing E-learning is a combination of pedagogical design, usability and information architecture. E-learning environments should have intuitive interfaces and clear information design, allowing learners to focus on learning. However, there is often a mismatch between what an on-line educator thinks the learner would learn, and what a learner thinks he will, and then has learned from the course. In addition, there is sometimes a mismatch between how an educator wants to teach and what is represented on the interface by the instructional designers. Such mismatches affect the learner's experience and his motivation for E-learning. In this paper, we will first discuss the source and nature of these mismatches. Next, we will discuss whether usability techniques in the HCI literature are appropriate for evaluating E-learning environments for the learner experience. We will then propose a combination of requirements elicitation and usability techniques for learner-centred design and evaluation of Web-based E-learning environments. The proposed methodology is based on our experience of conducting empirical studies for evaluating user-system interactions in E-Commerce contexts

Reflecting on E-Recruiting Research Using Grounded Theory

This paper presents a systematic review of the e-Recruiting literature through a grounded theory lens. The large number of publications and the increasing diversity of publications on e-Recruiting research, as the most studied area within e-HRM (Electronic Human Resource Management), calls for a synthesis of e-Recruiting research. We show interconnections between achievements, research gaps and future research directions in order to advance both e-Recruiting research and practice. Moreover, we provide a definition of e-Recruiting. The use of grounded theory enabled us to reach across sub-disciplines, methods used, perspectives studied, themes discussed and stakeholders involved. We demonstrate that the Grounded Theory Approach led to a better understanding of the interconnections that lay buried in the disparate e-Recruiting literature

Towards guidelines for building a business case and gathering evidence of software reference architectures in industry

Background: Software reference architectures are becoming widely adopted by organizations that need to support the design and maintenance of software applications of a shared domain. For organizations that plan to adopt this architecture-centric approach, it becomes fundamental to know the return on investment and to understand how software reference architectures are designed, maintained, and used. Unfortunately, there is little evidence-based support to help organizations with these challenges. Methods: We have conducted action research in an industry-academia collaboration between the GESSI research group and everis, a multinational IT consulting firm based in Spain. Results: The results from such collaboration are being packaged in order to create guidelines that could be used in similar contexts as the one of everis. The main result of this paper is the construction of empirically-grounded guidelines that support organizations to decide on the adoption of software reference architectures and to gather evidence to improve RA-related practices. Conclusions: The created guidelines could be used by other organizations outside of our industry-academia collaboration. With this goal in mind, we describe the guidelines in detail for their use.Peer ReviewedPostprint (published version

The Dynamics of Transformation in the Development of Digital Services

Service providers are increasingly depending and using digital infrastructure and tools provided by digital platforms to transform their services and develop digital ones that meet the needs of heterogeneous end users. However, while there is an emerging literature of developing digital services, little is known about the dynamics of transformation. Using multiple cases of firms that develop digital services, the digital service taxonomy was synthesized to understand the dynamics of transformation in developing digital services. This study identifies five main dynamics: the services experience, the service process, the service capabilities, the service environment and the service delivery.  Each of those dynamics and their associated factors is explored under the objectives of business, interaction and technology. This enables us to extend the existing literature on digital service development in particular and contributes to the research of digital innovation in general

A Novel Approach to Ontology Management

The term ontology is defined as the explicit specification of a conceptualization. While much of the prior research has focused on technical aspects of ontology management, little attention has been paid to the investigation of issues that limit the widespread use of ontologies and the evaluation of the effectiveness of ontologies in improving task performance. This dissertation addresses this void through the development of approaches to ontology creation, refinement, and evaluation. This study follows a multi-paper model focusing on ontology creation, refinement, and its evaluation. The first study develops and evaluates a method for ontology creation using knowledge available on the Web. The second study develops a methodology for ontology refinement through pruning and empirically evaluates the effectiveness of this method. The third study investigates the impact of an ontology in use case modeling, which is a complex, knowledge intensive organizational task in the context of IS development. The three studies follow the design science research approach, and each builds and evaluates IT artifacts. These studies contribute to knowledge by developing solutions to three important issues in the effective development and use of ontologies

Big Data Reference Architecture for e-Learning Analytical Systems

The recent advancements in technology have produced big data and become the necessity for researcher to analyze the data in order to make it meaningful. Massive amounts of data are collected across social media sites, mobile communications, business environments and institutions. In order to efficiently analyze this large quantity of raw data, the concept of big data was introduced. In this regard, big data analytic is needed in order to provide techniques to analyze the data. This new concept is expected to help education in the near future, by changing the way we approach the e-Learning process, by encouraging the interaction between learners and teachers, by allowing the fulfilment of the individual requirements and goals of learners. The learning environment generates massive knowledge by means of the various services provided in massive open online courses. Such knowledge is produced via learning actor interactions. Also, data analytics can be a valuable tool to help e-Learning organizations deliver better services to the public. It can provide important insights into consumer behavior and better predict demand for goods and services, thereby allowing for better resource management. This result motivates to put forward solutions for big data usage to the educational field. This research article unfolds a big data reference architecture for e-Learning analytical systems to make a unified analysis of the massive data generated by learning actors. This reference architecture makes the process of the massive data produced in big data e-learning system. Finally, the BiDRA for e-Learning analytical systems was evaluated based on the quality of maintainability, modularity, reusability, performance, and scalability

SERVICE-PROCESS CONFIGURATIONS IN ELECTRONIC RETAILING: A TAXONOMIC ANALYSIS OF ELECTRONIC FOOD RETAILERS

Service-processes of electronic retailers are founded on electronic technologies that provide flexibility to sense and respond online to the dynamic and complex needs of customers. In this paper, we develop a taxonomy of service-processes in electronic retailing and demonstrate their linkage to customer satisfaction and customer loyalty. The taxonomy is grounded in a conceptual classification scheme that differentiates service-process stages on a continuum of flexibility. Using data on electronic service-processes collected from 255 electronic food retailers, we identified eight configurations for the taxonomy. We also collected and analyzed publicly reported customer satisfaction survey data that were available for 52 electronic food retailers in the study sample. The results of this analysis indicate positive and significant correlation of the ordering of the taxonomy configurations with (i) customer satisfaction with product information, product selection, web site aesthetics, web site navigation, customer support, and ease of return, and (ii) customer loyalty. Taken together, the results of our empirical analyses demonstrate that the taxonomy captures information and variety within and across the electronic service-process configurations in ways that can be related to customer satisfaction and customer loyalty.Marketing, Research and Development/Tech Change/Emerging Technologies,

Landscape Design Dialogue. Bridging the gap between knowledge and action

Spatial planners and landscape architects do not excel in theory development. The authors, being a practicing landscape architect-planner and a planning scholar, explore new roads to a middle range theory of landscape design and planning. Building on theories-in-use in regional planning practice they develop an empirically grounded methodology for planning and design. The process of theory building is part of a process of methodical reflection on best and worst practices. It focuses on an analysis of planning and design efforts in the period 1970 – 2005 which have gradually transformed the landscape of the Rhine-Meuse Flood Plain in the Netherland

Deep Active Learning for Named Entity Recognition

Deep learning has yielded state-of-the-art performance on many natural language processing tasks including named entity recognition (NER). However, this typically requires large amounts of labeled data. In this work, we demonstrate that the amount of labeled training data can be drastically reduced when deep learning is combined with active learning. While active learning is sample-efficient, it can be computationally expensive since it requires iterative retraining. To speed this up, we introduce a lightweight architecture for NER, viz., the CNN-CNN-LSTM model consisting of convolutional character and word encoders and a long short term memory (LSTM) tag decoder. The model achieves nearly state-of-the-art performance on standard datasets for the task while being computationally much more efficient than best performing models. We carry out incremental active learning, during the training process, and are able to nearly match state-of-the-art performance with just 25\% of the original training data

Can 3D Virtual Worlds Address Healthcare Issues? Development, Delivery, Efficacy and Motivations to Use

The proposed work, which comprises of three essays, is aimed at developing and testing the efficacy of delivering healthcare services through virtual worlds (with focus on Second Life®). The first essay explores the unique aspects of system (presence) development in virtual worlds (VWs). In our study, multiple cases have been analyzed to investigate the process of systems development in SL projects and contrasted with existing information system development approaches. The second essay develops and empirically examines the efficacy of delivering healthcare services in the 3D virtual world (specifically in Second Life ®), and identify the factors (technological, process and user) that could contribute to the success or failure of such a delivery mechanism The third essay extends the proposed framework (in essay 2) by examining the role of hedonic motivations in adoption of healthcare services in the 3D VW s (specifically in Second Life ®). Contributions to education and research are discussed