Joint entity–relation knowledge embedding via cost-sensitive learning

As a joint-optimization problem which simultaneously fulfills two different but correlated embedding tasks (i.e., entity embedding and relation embedding), knowledge embedding problem is solved in a joint embedding scheme. In this embedding scheme, we design a joint compatibility scoring function to quantitatively evaluate the relational facts with respect to entities and relations, and further incorporate the scoring function into the max-margin structure learning process that explicitly learns the embedding vectors of entities and relations using the context information of the knowledge base. By optimizing the joint problem, our design is capable of effectively capturing the intrinsic topological structures in the learned embedding spaces. Experimental results demonstrate the effectiveness of our embedding scheme in characterizing the semantic correlations among different relation units, and in relation prediction for knowledge inference.     

Leveraging business-IT alignment through enterprise architecture—an empirical study to estimate the extents

Achieving business-IT alignment (BITA) as a long-term and appraising management issue can be accomplished in a few ways, enterprise architecture (EA) being one of them. This paper attempts to give a critical understanding of the effects of performing EA on different aspects of BITA maturity through a global survey. A total of 236 respondents from 60 countries, a relatively large response for a survey, were selected. The main purpose of the research is to examine these impacts and to identify directions for innovative practices in the future, the unique contributions of this work. A questionnaire designed on the Luftman’s maturity model as well as various other statistical methods, including PLS path modeling, Wilcoxon matched-pairs signed-ranks test and Mann–Whitney U test, are applied to understand how the EA can deliver benefits. The implications of our findings in this study as well as its limitations are discussed from different viewpoints to enable both academics and practitioners to detect the flaws in the existing EA frameworks and propose improvements.     

Student teachers’ satisfaction for blended learning via Edmodo learning management system

In a digitally driven world, behaviours of future teachers for blended learning (both face-to-face and on-line classes) need to be examined. This study serves three purposes. The first is to examine student teachers’ preferences for Community-of-Inquiry model-driven blended learning via Edmodo. Second, predicting student satisfaction on b-learning from a combination of four variables (gender, having internet access, using the internet for information access, and previous experience in on-line learning) was questioned. And third, b-learning orientations of participants were investigated. One of the mixed methods, the concurrent triangulation design was employed in which both qualitative and quantitative methods were applied. The study group included 135 freshmen and junior students (29 males and 106 females) from a western Turkish educational faculty. The findings for the first question indicated that 70.4% of student teachers prefer b-learning. For the second, 15% of the variance in satisfaction on b-learning was explained by the proposed model with a medium effect. And for the third, the qualitative findings were discussed under Perceived Usefulness (PU) and Perceived Uselessness and Unease-of-Use (PU-UU) themes. Although less than a quarter of participants found b-learning useless, most held positive notions for b-learning practices via Edmodo.     

Transferring auditors’ internal control evaluation knowledge to management

Due to both regulatory and competitive forces, attention to an organization's internal controls has increased significantly in the 1990s. Although management is ultimately responsible for ensuring internal controls are adequate, managers often lack knowledge of internal control concepts. This study reports on an experiment testing an expert system developed to facilitate the transfer of internal control knowledge to management. Experimental results indicate that expert systems are viable aids for transferring internal control knowledge to managers whose work experience is outside of accounting and control systems.     

Applying online externally-facilitated regulated learning and computational thinking to improve students’ learning

This study aims to explore, via quasi-experiments, the effects of online externally-facilitated regulated learning (ERL) and computational thinking (CT) on improving students’ computing skills in a blended learning environment. Four classes in a one-semester course entitled ‘Applied Information Technology: Data Processing’ were the samples for this research. The first class (C1, ERL&CT group) simultaneously received the interventions regarding online ERL and CT, the second class (C2, CT group) received the intervention regarding online CT, and the third class (C3, ERL group) received the intervention regarding online CT, while the last group (C4, control group) received a traditional teaching method, although teaching was also conducted in a blended computing class. Students in ERL&CT group and CT group came from the Department of Finance, while the ERL group and control group came from the Department of Law at a comprehensive university. According to the posttest analysis, the results indicate that students who received the intervention of online ERL had statistically better development of computing skills for using Excel by semester-end than those without. In addition, this study also reveals that the application of online CT alone could be helpful in students’ development of computing skills. Furthermore, the results indicate that students’ computing skills could be improved under the condition of simultaneously applying ERL and CT. Based on the findings of this study, the authors present implications for online teachers and educators, particularly for those teaching computing courses.     

Enhancing students’ knowledge building through utilising social interactions in an online learning environment

ABSTRACT

In the new “open world” of information, educational systems should involve students in constructing new knowledge of value to a community out of fragmentary information. The already proposed Knowledge Building (KB) approaches typically support only a few general-purpose activities due to the constraints of the utilised web-based environments. To organise and facilitate students’ KB during course activities, this study incorporated services provided by DoosMooc social learning environment into a knowledge transformation model. This approach is completely adapted to an educational context and allows time for iterations, helping students to both contribute to social KB processes and take collective responsibility for improving their understanding of authentic problems. The features provided by the introduced environment support and assess students’ KB activities and facilitate processes of creating, representing, organising, and reviewing different types of knowledge artefacts. The results of a semester-long experiment indicate that the approach and the corresponding instructional design thereof could successfully organise students’ KB activities and facilitate the required interactions. This study reports the impacts of parameters such as learner expertise and quality of shared knowledge on the planned KB processes, and investigates the relationships between students' KB activities and learning achievements.     

Determinants of employees’ intention to exert pressure on firms to engage in web accessibility

Web accessibility can help reduce the digital divide between persons with disabilities and the web by providing easy access to information on the Internet. Providing web accessibility can be an important element that manifests a firm's corporate social responsibility (CSR) and employees can play a vital role in this process. This paper examines how employees can impact a firm's decision to fulfil their CSR regarding web accessibility. We propose that employees’ intention to exert pressure on a firm is primarily influenced by three psychological needs, namely need for control, need for belonging, and need for meaningful existence. Additionally, perceived importance of CSR moderates the relationship between need for meaningful existence and intention. We empirically test the research model using data collected from 106 Chinese employees. The results suggest that for employees to pressure their firms to improve the accessibility of their websites, it is imperative to enhance their perceived importance of web accessibility, and their need for belonging and for a meaningful existence. We present the theoretical and managerial implications arising from our findings.     

Using ‘tangibles’ to promote novel forms of playful learning

Tangibles, in the form of physical artefacts that are electronically augmented and enhanced to trigger various digital events to happen, have the potential for providing innovative ways for children to play and learn, through novel forms of interacting and discovering. They offer, in addition, the scope for bringing playfulness back into learning. To this end, we designed an adventure game, where pairs of children have to discover as much as they can about a virtual imaginary creature called the Snark, through collaboratively interacting with a suite of tangibles. Underlying the design of the tangibles is a variety of transforms, which the children have to understand and reflect upon in order to make the Snark come alive and show itself in a variety of morphological and synaesthesic forms. The paper also reports on the findings of a study of the Snark game and discusses what it means to be engrossed in playful learning.     

Using social networks to distort users’ profiles generated by web search engines

The Internet is one of the most important sources of knowledge in the present time. It offers a huge volume of information which grows dramatically every day. Web search engines (e.g. Google, Yahoo…) are widely used to find specific data among that information. However, these useful tools also represent a privacy threat for the users: the web search engines profile them by storing and analyzing all the searches that they have previously submitted. To address this privacy threat, current solutions propose new mechanisms that introduce a high cost in terms of computation and communication. In this paper, we propose a new scheme designed to protect the privacy of the users from a web search engine that tries to profile them. Our system uses social networks to provide a distorted user profile to the web search engine. The proposed protocol submits standard queries to the web search engine; thus it does not require any change in the server side. In addition to that, this scheme does not require the server to collaborate with the users. Our protocol improves the existing solutions in terms of query delay. Besides, the distorted profiles still allow the users to get a proper service from the web search engines.     

From rankings’ collinearity to counting SDR's via chromatic list expression

The problem of counting rankings satisfying the collinearity condition with respect to two rankings over the metric spaces of rank distance is treated in this paper by transforming it into finding the number of systems of distinct representatives (abbreviated as SDR's) with respect to associated set systems. A formula for the chromatic list expression of graphs is then given in terms of the inclusion and exclusion principle, followed by a formula for the number of SDR's of set systems when the graphs are complete.     

Exploring the feasibility of web form adaptation to users’ cultural dimension scores

With many daily tasks now performed on the Internet, productivity and efficiency in working with web pages have become transversal necessities for all users. Many of these tasks involve the inputting of user information, obligating the user to interact with a webform. Research has demonstrated that productivity depends largely on users’ personal characteristics, implying that it will vary from user to user. The webform development process must therefore, include modeling of its intended users to ensure the interface design is appropriate. Taking all potential users into account is difficult, however, primarily because their identity is unknown, and some may be effectively excluded by the final design. Such discrimination can be avoided by incorporating rules that allow webforms to adapt automatically to the individual user’s characteristics, the principal one being the person’s culture. In this paper we report two studies that validate this option. We begin by determining the relationships between a user’s cultural dimension scores and their behavior when faced with a webform. We then validate the notion that rules based on these relationships can be established for the automatic adaptation of a webform in order to reduce the time taken to complete it. We conclude that the automatic webform adaptation to the cultural dimensions of users improves their performance.     

Reinforcement learning technique using agent state occurrence frequency with analysis of knowledge sharing on the agent’s learning process in multiagent environments

Reinforcement learning techniques like the Q-Learning one as well as the Multiple-Lookahead-Levels one that we introduced in our prior work require the agent to complete an initial exploratory path followed by as many hypothetical and physical paths as necessary to find the optimal path to the goal. This paper introduces a reinforcement learning technique that uses a distance measure to the goal as a primary gauge for an autonomous agent’s action selection. In this paper, we take advantage of the first random walk to acquire initial information about the goal. Once the agent’s goal is reached, the agent’s first perceived internal model of the environment is updated to reflect and include said goal. This is done by the agent tracing back its steps to its origin starting point. We show in this paper, no exploratory or hypothetical paths are required after the goal is initially reached or detected, and the agent requires a maximum of two physical paths to find the optimal path to the goal. The agent’s state occurrence frequency is introduced as well and used to support the proposed Distance-Only technique. A computation speed performance analysis is carried out, and the Distance-and-Frequency technique is shown to require less computation time than the Q-Learning one. Furthermore, we present and demonstrate how multiple agents using the Distance-and-Frequency technique can share knowledge of the environment and study the effect of that knowledge sharing on the agents’ learning process.     

Pre-service teachers’ skills and perceptions about the use of virtual learning environments to improve teaching and learning

This paper explores data retrieved from Educational Immersive Virtual Worlds to describe pre-service teachers’ skills and perceptions about the simulation tasks. This project had 10 participants who were immersed for 3 years in the Technology and Pedagogical Models in Immersive Worlds island, a multi-user virtual environment in Second Life and Open Simulator. In this project, we evaluated how three-dimensional virtual environments can facilitate the achievement of teaching and learning processes. Based on quantitative and qualitative methodologies, two data collection instruments were applied. Through observation grids and personal log books, professional performance of the 18 pedagogical challenges implemented was collected. The statistical analysis shows that the students improved their technology skills and educational aspects about good practices in classes, regardless of the type of platform used. The analysis through Constant Comparing Method reported a positive assessment of the use of virtual environments, especially about the use of teaching strategies. Main conclusions regarding the pedagogical context reflect the importance of peer assessment on teaching performance, as well as the complexity of role-plays as intellectual challenges to enhance pre-service teachers’ skills. The main difficulties identified during the development of the activities were technical in nature, reporting hardware and connectivity issues.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.     

UK public’s intention to engage with academia via online technologies

Online technologies have made it possible for practitioners and the public to reach academics directly and seek information and knowledge in areas of professional or personal interest. This paper uses the extended version of the Unified Theory of Acceptance and Use of Technology (UTAUT2) to examine the factors that affect the adoption of online technologies by practitioners and other members of the public in order to engage with the academic community. Understanding the driving factors of such online engagement is very important as it can inform academic practice and how institutional support is provided. The results of our online survey (N?=?241), derived by using Structural Equation Modelling, show that behavioural intention is mainly affected by the user's habit, performance expectancy and facilitating conditions. Also, educational level has a moderating effect in the cases of habit and social influence and gender in the cases of habit and hedonic motivation.     

Learning opponent’s beliefs via fuzzy constraint-directed approach to make effective agent negotiation

This work presents a general framework of agent negotiation with opponent learning via fuzzy constraint-directed approach. The fuzzy constraint-directed approach involves the fuzzy probability constraint and the fuzzy instance reasoning. The proposed approach via fuzzy probability constraint can not only cluster the opponent’s information in negotiation process as proximate regularities to improve the convergence of behavior patterns, but also eliminate the noisy hypotheses or beliefs to enhance the effectiveness on beliefs learning. By using fuzzy instance method, our approach can reuse the prior opponent knowledge to speed up the problem-solving, and reason the proximate regularities to acquire desirable results on predicting opponent behavior. In addition, the proposed interaction method enables the agent to make a concession dynamically based on expected objectives. Moreover, experimental results suggest that the proposed framework allows an agent to achieve a higher reward, a fairer deal, or a smaller cost of negotiation.     

Recommending suitable learning scenarios according to learners’ preferences: An improved swarm based approach

The paper presents a new approach for recommending suitable learning paths for different learners groups. Selection of the learning path is considered as recommendations to choosing and combining the sequences of learning objects (LOs) according to learners’ preferences. Learning path can be selected by applying artificial intelligence techniques, e.g. a swarm intelligence model. If we modify and/or change some LOs in the learning path, we should rearrange the alignment of new and old LOs and reallocate pheromones to achieve effective learning recommendations. To solve this problem, a new method based on the ant colony optimisation algorithm and adaptation of the solution to the changing optimum is proposed. A simulation process with a dynamic change of learning paths when new LOs are inserted was chosen to verify the method proposed. The paper contributes with the following new developments: (1) an approach of dynamic learning paths selection based on swarm intelligence, and (2) a modified ant colony optimisation algorithm for learning paths selection. The elaborated approach effectively assist learners by helping them to reach most suitable LOs according to their preferences, and tutors – by helping them to monitor, refine, and improve e-learning modules and courses according to the learners’ behaviour.     

An empirical investigation linking learners’ adoption of blended learning to their intention of full e-learning

Learning management system (LMS) is playing a major role in higher academic institutions worldwide. Even though full e-learning is becoming a feasible strategy for a number of institutions in the world, some institutions, especially those in developing countries, are resisting a full e-learning environment. Consequently, these academic institutions initially adopt LMS for blended learning to assess their readiness for full e-learning transformation. There are a number of studies that investigate the determinants of full e-learning, but very limited studies investigate the link between learners’ perception of blended learning and full e-learning. The objective of this study was to link learners’ adoption (perceived ease of use, perceived usefulness (PU) and satisfaction) of LMS in blended learning and their personal characteristics (self-efficacy, technology experience and personal innovativeness) to their intention to use full e-learning. Data were collected through a questionnaire from 512 learners in Oman. The study found that personal innovativeness, PU and satisfaction of LMS in blended learning are significant to learners’ intention to engage in full e-learning. Thus, learners’ adoption of LMS in blended learning boosts their intention to full e-learning. The results provide useful insights for practitioners and researchers on full e-learning planning and strategy.     

‘You talking to me?’ The influence of peer communication on adolescents’ persuasion knowledge and attitude towards social advertisements

This article examines how peer communication among adolescents (14–16 years) affects the evaluation of social advertising (i.e. targeted ad that adopts the social proof heuristic by using an individual’s social ties as endorsers for a brand) on social networking sites (SNSs). More precisely, the focus lies on how engaging in online peer chatting on these social platforms alters persuasion knowledge and attitude towards the ad. In order to test this, two between-subjects experiments were conducted in which adolescents chatted with peers on a mock SNS that contained a social ad. In Experiment 1, results reveal that a social ad generates a more positive attitude among adolescents when they have engaged in online peer communication, and at the same time, triggers less persuasion knowledge. In Experiment 2, the depth of the relationship between the chatters (tie strength) plays a significant moderating role as peer communication with strong ties yields greater effects, compared to communication with weak ties. These findings reveal important social influence dynamics that may alter the elaboration of persuasive communication, leading to valuable theoretical and practical implications.     

Harnessing the social web to enhance insights into people’s opinions in business,government and public administration

Transparency, participation, and collaboration are the core pillars of open government. For the systematic integration of citizens and other stakeholders into the policy and public value creation process, their opinions, wishes, and complaints first need to be received. In the future, including user-generated content from social media will become a main channel for the enrichment of this information base for public administrative bodies and commercial firms. However, the sheer speed of growth of this constantly updated data pool makes manual work infeasible. The automated gathering, combination, analysis, and visualization of user-generated content from various sources and multiple languages is therefore imperative.In this study, we present a design science research approach to develop a general framework (‘MarketMiner’) to handle large amounts of foreign-language user-generated content. As a first empirical application, we implement the framework in the automotive industry by analyzing Chinese automotive forums for the benefit of English-speaking users. At the same time, the ideas, methods, and insights are transferred to the public sector context, especially in light of the current challenges of a high number of political refugees from Arabic countries entering into the European Union.The results are promising in that MarketMiner can dramatically improve the utilization of multi-language, multi-source social media content. The modular set-up of the artifact allows an easy transfer to additional areas of application.