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The pertinent literature is reviewed and a paradigm or a framework is presented to guide conceptualisation and implementation for the programme development process in educational administration in an African country, Rwanda. The framework components include four dimensions and related systematic conceptual levels and procedural stages. It is argued that improvement of education requires the definition of the goals of educational administration, the upgrading of the instruction for on‐the‐job practitioners, and the development of a pre‐service programme for prospective school administrators responsible for efficient and effective management of the centralised educational system. The framework claims to be a disciplinary matrix for developing a pre‐service programme in the field of educational administration.

The purpose of the current study was to examine the role of distance learning in enhancing introverted students’ lack of communication and social interaction to improve their performance in translation class. Cain (2013) and Kuzeljevich (2017) agreed that identifying “introverted” and “extroverted” students is important for meeting their learning needs. While extroverted students have strong social skills that allow them to interact comfortably in different learning environments, introverted students tend to be more shy, quiet, and silent, thus, requiring more careful planning in classroom settings. Therefore, educators need to support introverted students in reaching their full academic and social potential.

The present case study adopted a qualitative research method to explore the role of online/distance learning during the COVID-19 pandemic in enhancing introverted students’ performance and communication abilities in translation classes. The researcher of the current study spent a considerable time observing and set herself as part of the group (i.e. translation students of level 6 class) to understand the phenomenon, events and the new situation of having translation students interact in online settings. Data collection was based on this observation, interviews with the participants and archival documents. To enhance the validity and credibility of this research, the researcher employed the method of triangulation.

The results (see Appendixes A, B and C) revealed the level of students interactions in translation classes and their attitudes toward online learning. Based on the observations made by the instructor, the researcher found that the involvement of the introverted students during online translation learning was remarkable, as they provided their translation outputs in the chat window of Microsoft Teams with no hesitation. Consequently, 65% of the students were providing their translation output through the chat window, which indicates that they are more introverted and preferred not to speak. Comparing this result to face-to-face translation class, the researcher found that 25% of the students provided their translation outputs through oral participation.

This study contributes to the field of translation and education. Previous studies have not sufficiently examined the role of distance learning in enhancing the performance and communication of introverted students in translation classes. The current study is also expected to provide insight into the field of technical translation in remote teaching and learning settings.

The increasingly rapid pace of scientific and technological change, combined with unprecedented development of means of communications, poses both challenges and opportunities for the adapting of learning to economic development. On the one hand, this change can increase economic and educational inequalities both within and among countries. On the other hand, the means for faster diffusion of knowledge vastly increases opportunities for specific learning needs, thus enhancing economic development. The need for access, flexibility and quality learning is an essential function of a complex and economically advanced society. The assumptions that people can acquire all the necessary learning in some form from a terminal degree or from compulsory education grade limits are no longer adequate considering the continuous need for social and economic development.

The future of online business education seems quite bright. Three‐fifths of the 1,700 US institutions of higher learning that are engaged in distance education – 55 percent of which offer credit‐bearing business courses – already use some form of Internet‐based technology. Nonetheless, there have been no large‐scale studies of potential online business students in terms of their traits and desires. In this article, the background of distance education is presented. Then, the results of a major survey, involving NPD’s Online Research Panel, are discussed. In all, 2,651 adults participated in the survey, 1,945 of whom indicated some interest in online business education. Eight propositions are tested, relating to demographics, courses versus programs, reasons for enrolling or not enrolling, desired features, customer service expectations, tuition, prestige and value, and institutional attributes.

This study investigated what should be the major research and development areas regarding the logistics of electronic business. The method of study consisted of five elements: the creation of a preliminary e‐logistics vision; focus interviews of e‐business and logistics experts, identification and categorisation of the key R&D topics, a panel workshop to critically analyse the preliminary findings and prioritise the R&D topics, and formulation of a research agenda to guide future research work in the field of e‐business logistics. The two‐phased process, where the interviews were followed by the workshop, enabled the evaluation and prioritisation of the preliminary findings. The requirements of e‐business on the national logistics infrastructure were found to be one of the focus research areas. According to the study, integrated supply network structure with suitable visibility and usage of real‐time data transfer is another area of great importance. Research and development of new logistics service concepts should also be promoted as well as research on the effects and possibilities of using new product data management and product identification methods.

The purpose of this multi-voiced paper is to propose a prosocial paradigm for the field of performance management and management control systems. This new paradigm suggests cultivating prosocial behaviour and prosocial groups in organizations to simultaneously achieve the objectives of economic performance and sustainability.

The authors share a common concern about the future of humanity and nature. They challenge the influential assumption of economic man from neoclassical economic theory and build on evolutionary science and the core design principles of prosocial groups to develop a prosocial paradigm.

Findings are based on the premise of the prosocial paradigm that self-interested behaviour may outperform prosocial behaviour within a group but that prosocial groups outperform groups dominated by self-interest. The authors explore various dimensions of performance management from the prosocial perspective in the private and public sectors.

The authors call for theoretical, conceptual and empirical research that explores the prosocial paradigm. They invite any approach, including positivist, interpretive and critical research, as well as those using qualitative, quantitative and interventionist methods.

This paper offers implications from the prosocial paradigm for practitioners, particularly for executives and managers, policymakers and educators.

Adoption of the prosocial paradigm in research and practice shapes what the authors call the prosocial market economy. This is an aspired cultural evolution that functions with market competition yet systematically strengthens prosociality as a cultural norm in organizations, markets and society at large.

Centrifugal compressors are integral components in oil industry, thus effective maintenance is required. Condition-based maintenance and prognostics and health management (CBM/PHM) have been gaining popularity. CBM/PHM can also be performed remotely leading to e-maintenance. Its success depends on the quality of the data used for analysis and decision making. A major issue associated with it is the missing data. Their presence may compromise the information within a set, causing bias or misleading results. Addressing this matter is crucial. The purpose of this paper is to review and compare the most widely used imputation techniques in a case study using condition monitoring measurements from an operational industrial centrifugal compressor.

Brief overview and comparison of most widely used imputation techniques using a complete set with artificial missing values. They were tested regarding the effects of the amount, the location within the set and the variable containing the missing values.

Univariate and multivariate imputation techniques were compared, with the latter offering the smallest error levels. They seemed unaffected by the amount or location of the missing data although they were affected by the variable containing them.

During the analysis, it was assumed that at any time only one variable contained missing data. Further research is still required to address this point.

This study can serve as a guide for selecting the appropriate imputation method for missing values in centrifugal compressor condition monitoring data.

Existing studies on human activity recognition using inertial sensors mainly discuss single activities. However, human activities are rather concurrent. A person could be walking while brushing their teeth or lying while making a call. The purpose of this paper is to explore an effective way to recognize concurrent activities.

Concurrent activities usually involve behaviors from different parts of the body, which are mainly dominated by the lower limbs and upper body. For this reason, a hierarchical method based on artificial neural networks (ANNs) is proposed to classify them. At the lower level, the state of the lower limbs to which a concurrent activity belongs is firstly recognized by means of one ANN using simple features. Then, the upper-level systems further distinguish between the upper limb movements and infer specific concurrent activity using features processed by the principle component analysis.

An experiment is conducted to collect realistic data from five sensor nodes placed on subjects’ wrist, arm, thigh, ankle and chest. Experimental results indicate that the proposed hierarchical method can distinguish between 14 concurrent activities with a high classification rate of 92.6 per cent, which significantly outperforms the single-level recognition method.

In the future, the research may play an important role in many ways such as daily behavior monitoring, smart assisted living, postoperative rehabilitation and eldercare support.

To provide more accurate information on people’s behaviors, human concurrent activities are discussed and effectively recognized by using a hierarchical method.