This article presents and discusses student assignments reflecting on the documentary film If a Tree Falls, written as part of the Business Ethics and Sustainability course at The Hague University of Applied Sciences. This article follows two lines of inquiry. First, it challenges mainstream environmental education, supporting critical pedagogy and ecopedagogy. These pedagogies, which advocate pedagogy for radical change, offer a distinct and valuable contribution to sustainability education, enabling students to critically examine normative assumptions, and learn about ethical relativity, and citizenship engagement from environmentalists. The discussion of “lessons of radical environmentalism” is pertinent to the question of what types of actions are likely to achieve the widely acceptable long-term societal change. While this article focuses on student reflection on a film about radical environmentalism, this article also discusses many forms of activism and raises the question of what can be considered effective activism and active citizenship in the context of the philosophy of (environmental or sustainability) education in connection didactics and curriculum studies. Second, this article argues for the need for reformed democracy and inclusive pluralism that recognizes the needs of nonhuman species, ecocentrism, and deep ecology. The connection between these two purposes is expressed in the design of the student assignment: It is described as a case study, which employs critical pedagogy and ecopedagogy. https://doi.org/10.3390/educsci9040284 LinkedIn: https://www.linkedin.com/in/helenkopnina/
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Author supplied Business rules play a critical role in an organization’s daily activities. With the increased use of business rules (solutions) the interest in modelling guidelines that address the manageability of business rules has increased as well. However, current research on modelling guidelines is mainly based on a theoretical view of modifications that can occur to a business rule set. Research on actual modifications that occur in practice is limited. The goal of this study is to identify modifications that can occur to a business rule set and underlying business rules. To accomplish this goal we conducted a grounded theory study on 229 rules set, as applied from March 2006 till June 2014, by the National Health Service. In total 3495 modifications have been analysed from which we defined eleven modification categories that can occur to a business rule set. The classification provides a framework for the analysis and design of business rules management architectures.
In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
