The future of technology enhanced active learning – a roadmap

The notion of active learning refers to the active involvement of learner in the learning process, capturing ideas of learning-by-doing and the fact that active participation and knowledge construction leads to deeper and more sustained learning. Interactivity, in particular learnercontent interaction, is a central aspect of technology-enhanced active learning. In this roadmap, the pedagogical background is discussed, the essential dimensions of technology-enhanced active learning systems are outlined and the factors that are expected to influence these systems currently and in the future are identified. A central aim is to address this promising field from a best practices perspective, clarifying central issues and formulating an agenda for future developments in the form of a roadmap

The Matter of Entrepreneurial Learning: A Literature Review

This paper is a comprehensive review of the entrepreneurial learning literature and its engagement with the material aspects of entrepreneurship, as part of the “material turn” in the social sciences. Drawing on actor-network theory, we construct a classificatory scheme and an evaluative matrix to find that this field is dominated by an anthropocentric bias and cognitivist approaches which largely ignore issues of materiality in entrepreneurship. However we also identify some heterogeneous network-based conceptualisations of entrepreneurial learning which could provide the foundations for more materially aware approaches. We conclude by calling for a material turn in entrepreneurial learning and outline some possible avenues for it

What drives contract design in strategic alliances? Taking stock and how to proceed

We collect and assess prior empirical evidence on contract design in alliances that has been published since Parkhe’s (1993) seminal study on inter-firm contracts. We elaborate on the effects of transaction-related factors, experience gained from prior relationships, and deliberate learning efforts on contracts. Our paper offers three contributions. First, we systematically review the existing literature on alliance contracts and summarize our findings. Second, while prior research has traditionally focused on contractual complexity, we place the content of contracts center stage and identify three contractual functions. While existing studies on contractual functions predominantly refer to safeguarding as a response to appropriation concerns, we also consider coordination and contingency adaptability as outcomes of adaptation concerns. Third, we disentangle the differential influences of previous experiences on distinct contractual functions and show that experience gained from prior relationships has different effects on safeguarding and contingency adaptability than on coordination. Overall, we add to the systematization of the current debate on alliance contract design and trace promising avenues for future research on the impact of transaction- and experience-related factors on the complexity and content of alliance contracts

The Effectiveness of Customer Education: evaluating synchronous and asynchronous e-learning technologies

This paper considers the role played by customer education in enhancing their engagement by enriching the customer experience. Enrichment may be seen in terms of enhanced customer communication or service co-creation. This is often mediated by the effectiveness of customer education. Consequently, organisations are evolving new ways of educating their customers to carry out their roles as co-producers. Increasingly this process depends on the latest synchronous and asynchronous e-learning technologies, requiring significant resource investments. Whilst it is easy for organisations to become absorbed with the latest technological trends, we suggest a refocussing on how customers actually engage in learning and skills acquisition. A conceptual framework is developed that combines key concepts from IT service delivery with well-established models of learning acquisitio

Developing Educational Software: a professional tool perspective

The selection, and use of educational software and its impact in schools are still controversial issues. In this paper we present an alternative conceptualisation of educational software based on considering the software as an instrument for teachers’ professional performance. We review previous work in the areas of the design, development and evaluation of educational software and of the process of educational innovation. The review of these four areas converges to demonstrate the need for knowing and considering the context of use of educational software and for understanding users' perspectives about its roles and possibilities and hence supports a consideration a perspective on educational software which sees it as a professional tool for teachers performance of their teaching role

Engineering Crowdsourced Stream Processing Systems

A crowdsourced stream processing system (CSP) is a system that incorporates crowdsourced tasks in the processing of a data stream. This can be seen as enabling crowdsourcing work to be applied on a sample of large-scale data at high speed, or equivalently, enabling stream processing to employ human intelligence. It also leads to a substantial expansion of the capabilities of data processing systems. Engineering a CSP system requires the combination of human and machine computation elements. From a general systems theory perspective, this means taking into account inherited as well as emerging properties from both these elements. In this paper, we position CSP systems within a broader taxonomy, outline a series of design principles and evaluation metrics, present an extensible framework for their design, and describe several design patterns. We showcase the capabilities of CSP systems by performing a case study that applies our proposed framework to the design and analysis of a real system (AIDR) that classifies social media messages during time-critical crisis events. Results show that compared to a pure stream processing system, AIDR can achieve a higher data classification accuracy, while compared to a pure crowdsourcing solution, the system makes better use of human workers by requiring much less manual work effort