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In this paper a conception of the model for learning scenario determination is presented. We define the learning scenario as a sequence of the hypermedia pages, representing particular knowledge units, and tests related to them. The scenario determination is a dynamic process that begins when a new student takes up a course. The opening scenario for this student is chosen as the consensus of the final scenarios of the students, who have already finished this course, and who belong to a class of the learners similar to the new one. We have elaborated the consensus‐based procedure for the scenario determination. Since this procedure operates on a set of similar learners, we have developed the conceptions of learner’s profile and students’ classification. The learner’s profile is proposed to include the attributes describing students’ personal data (as name, birthday etc.), their cognitive and learning styles as well as their usage data (represented by the learning scenarios). The students’ classification is based on a set of the basic attributes that seem to influence the learning effects. Their significance is verified during the learning process. We have also elaborated the procedure of reducing undistinguishable values of the attribute and removing useless attributes from the set of basic attributes. A learning procedure proposed, describes generally the situations when the scenario is modified, and the methods used for its modification.

This article intervenes in the debate, among US disability rights advocates, about physician-assisted suicide (PAS). Through an ethnographic study, I situate this debate in the context of the dominant form of end-of-life care in the US hospice. Based on this analysis, I argue that PAS should be an issue of secondary concern to disability rights advocates, and that their primary concern, at the end-of-life, should be the improvement of US hospice care. By thus “putting the ‘right to die’ in its place,” they can achieve consensus among themselves and leverage this consensus to achieve the most substantial advancement of disability rights.

The range of official business that can be handled online has grown in the recent decade. In many cases, e-services are a must. At the same time, the economic impact and social importance of mobile technology have increased. Mobile devices are becoming more and more popular, and their applications diversify. It comes as no surprise that mobile users expect e-services and official information to be available through this channel. The purpose of this paper is to identify problems (difficulties) occurring when browsing websites of local government units (LGU) on mobile devices.

The comfort of website browsing depends mostly on the development technique, and the way content is published. Responsive websites are much easier to view on mobile devices than “static” ones. The study involves 400 websites of LGU in Poland. The websites were subjected to quantitative and qualitative analyses with selected techniques and computer tools.

The set of 400 websites contained 119 (29.75%) that were not responsive. It exhibited a substantial potential for the optimisation of websites for mobile devices. The study revealed the most common usability failures such as distorted images, “scattered icons”, partial responsiveness and bothersome messages in pop-ups.

The research identified the most widespread problems with the tested websites. The study yielded recommendations for local governments, which may be useful when managing content, upgrading the website or replacing it with a new one.

Ship route prediction (SRP) is a quite complicated task, which enables the determination of the next position of a ship after a given period of time, given its current position. This paper aims to describe a study, which compares five families of multiclass classification algorithms to perform SRP.

Tested algorithm families include: Naive Bayes (NB), nearest neighbors, decision trees, linear algorithms and extension from binary. A common structure for all the algorithm families was implemented and adapted to the specific case, according to the test to be done. The tests were done on one month of real data extracted from automatic identification system messages, collected around the island of Malta.

Experiments show that K-nearest neighbors and decision trees algorithms outperform all the other algorithms. Experiments also demonstrate that linear algorithms and NB have a very poor performance.

This study is limited to the area surrounding Malta. Thus, findings cannot be generalized to every context. However, the methodology presented is general and can help other researchers in this area to choose appropriate methods for their problems.

The results of this study can be exploited by applications for maritime surveillance to build decision support systems to monitor and predict ship routes in a given area. For example, to protect the marine environment, the use of SRP techniques could be used to protect areas at risk such as marine protected areas, from illegal fishing.

The paper proposes a solid methodology to perform tests on SRP, based on a series of important machine learning algorithms for the prediction.

Workplace agility is emerging as the highest priority for the providers of workplace services and infrastructure. ‘Agility’ means continuously improving work and the infrastructure that enables it. An agile workplace is one that is constantly transforming, adjusting and responding to organisational learning. Agility requires a dynamic relationship between work and the workplace and the tools of work. In that relationship the workplace becomes an integral part of work itself ‐ enabling work, shaping it and being shaped by it. This paper focuses on defining workplace agility and discusses the triggers that prompt agile workplace making. Strategies for creating agile workplaces are discussed and the idea of ‘rehearsing’ change is introduced. This paper is excerpted from ‘The Agile Workplace’, which introduces the business and technology forces that drive and enable agile work. The report includes chapters about change management, organisational responsibilities and performance metrics.

This chapter presents empirical evidence on the effects of attributional retraining (AR), a motivation-enhancing treatment that can offset maladaptive explanatory mind-sets arising from adverse learning experiences. The evidence shows that AR is effective for assisting college students to adapt to competitive and challenging achievement settings.

This chapter describes the characteristics of AR protocols and details three primary advances in studying AR efficacy in terms of achievement performance, psychosocial outcomes, and processes that mediate AR-performance linkages. The psychological mechanisms that underpin AR effects on motivation and performance are outlined from the perspective of Weiner’s (1974, 1986, 2012) attribution theory.

Laboratory and field studies show that AR treatments are potent interventions that have short-term and long-lasting psychosocial, motivation, and performance benefits in achievement settings. Students who participate in AR programs are better off than their no-AR counterparts not just in their cognitive and affective prospects, but they also outperform their no-AR peers in class tests, course grades, and grade-point-averages, and are more persistent in terms of course credits and graduation rates.

This paper contributes to the emerging literature on treatment interventions in achievement settings by documenting key advances in the development of AR protocols and by identifying the next steps critical to moving the literature forward. Further progress in understanding AR efficacy will rest on examining the analysis of complex attributional thinking, the mediation of AR treatment effects, and the boundary conditions that moderate AR treatment efficacy.

A defining feature of international business is the necessity for people from diverse cultural backgrounds to interact and collaborate but intercultural interaction is difficult and may give rise to disagreement and conflict. I have been working on the dynamics that promote positive intercultural interaction in the international business context, and two streams of my research, one empirical and the other conceptual, are reviewed here. The first stream is concerned with fairness issues surrounding the pay disparity between locals and expatriates in multinational enterprises operating in China, which has implications for MNC operations in other emerging economies. My research has shown that the pay disparity is associated with negative reactions from local employees but some management practices associated with the relationship between locals and expatriates, attributions made by locals, and salient norms about the pay disparity can buffer such negative reactions. In this research program, the focus is not on the actual interaction between locals and expatriates. To address this gap, a conceptual framework is presented, which provides insight about the factors that contribute to positive interaction between locals and expatriates. This paper ends with implications for future research on intercultural interaction in the MNC context.