It is a challenge for mathematics teachers to provide activities for their students at a high level of cognitive demand. In this article, we explore the possibilities that history of mathematics has to offer to meet this challenge. History of mathematics can be applied in mathematics education in different ways. We offer a framework for describing the appearances of history of mathematics in curriculum materials. This framework consists of four formats that are entitled speck, stamp, snippet, and story. Characteristic properties are named for each format, in terms of size, content, location, and function. The formats are related to four ascending levels of cognitive demand. We describe how these formats, together with design principles that are also derived from the history of mathematics, can be used to raise the cognitive level of existing tasks and design new tasks. The combination of formats, cognitive demand levels, and design principles is called the 4S-model. Finally, we advocate that this 4S-model can play a role in mathematics teacher training to enable prospective teachers to reach higher cognitive levels in their mathematics classrooms.
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From the article: Abstract Over the last decades, philosophers and cognitive scientists have argued that the brain constitutes only one of several contributing factors to cognition, the other factors being the body and the world. This position we refer to as Embodied Embedded Cognition (EEC). The main purpose of this paper is to consider what EEC implies for the task interpretation of the control system. We argue that the traditional view of the control system as involved in planning and decision making based on beliefs about the world runs into the problem of computational intractability. EEC views the control system as relying heavily on the naturally evolved fit between organism and environment. A ‘lazy’ control structure could be ‘ignorantly successful’ in a ‘user friendly’ world, by facilitating the transitory creation of a flexible and integrated set of behavioral layers that are constitutive of ongoing behavior. We close by discussing the types of questions this could imply for empirical research in cognitive neuroscience and robotics.
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Accurate modeling of end-users’ decision-making behavior is crucial for validating demand response (DR) policies. However, existing models usually represent the decision-making behavior as an optimization problem, neglecting the impact of human psychology on decisions. In this paper, we propose a Belief-Desire-Intention (BDI) agent model to model end-users’ decision-making under DR. This model has the ability to perceive environmental information, generate different power scheduling plans, and make decisions that align with its own interests. The key modeling capabilities of the proposed model have been validated in a household end-user with flexible loads
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More and more aged people are joining the traffic, either using a passenger car or through a special low speed two-seater for in-city use. For elderly people, self-management in staying mobile is an essential part of their quality of life. However, with increased involvement of elderly in traffic, the risk of serious accidents increases, especially in cities. Fortunately, a rapid development of innovative technology is shown in vehicle design, with focus on advanced driver support, herewith referred to as ‘ambient intelligence’. This holds a promise to improve the safety situation, under the condition that adaption to the elderly driver’s need is accounted for. And that is not a straightforward issue, since ‘no size fits all’. With increasing age, we see an increased variety in driving skills with emphasis on cognitive, perceptual and physical limitations. In addition, people may suffer from diseases with a neurological background or other (cardiopulmonary disease, obesity or diabetes). The partners in this project have expressed the need to survey the feasibility of ‘ambient intelligence’ technology for low-speed vehicles also addressing E-Health functions to bring people safely home or involve medical help in case of health-critical situations. The MAX Mobiel make their vehicle available for that, and will help to guard the elder customer demand. The HAN Automotive Research team carries out the research, in cooperation with the HAN professorship on E-Health. Hence, both the automotive technology part of the HAN University of Applied Sciences as well as expertise from the Health oriented part of the HAN are included, being essential to successfully extend the relevant technologies to a fully integrated elderly driver support system, in the future. Noldus Information Technology is involved on the basis of their knowledge in human monitoring (drive lab) and data synchronization. The St. Maartenskliniek (Nijmegen) brings in their experience with people being restricted in physical or neurological sense.