A construction of knowledge rules for reactive planning of job-mix assignment to homogeneous serial batch machines

2014 ◽  
Vol 151 ◽  
pp. 56-66
Author(s):  
Yon-Chun Chou ◽  
Yue-Lan Lin ◽  
King-Fai Chun
2012 ◽  
Vol 7 (1) ◽  
Author(s):  
Robin Ward McCartney ◽  
Donna Dugger Wadsworth

A visual instructional tool that is theory-driven and supported by evidence-based research is used to support student learning and information-processing. The graphic organizer has enhanced learning in Science Education as well as Special Education, emphasizing the construction of knowledge with meaningful sequential relationships rather than memorizing isolated fragments of information. Students construct a visual schema that represents a system of interrelated concepts and icons created by the learner. This article provides a description of a qualitative application of how students with disabilities are able to represent their ideas by assimilating subject matter and their personal perceptions of content by drawing pictures connected to concepts within the visual graphic. Positive results were documented in this study.


Author(s):  
Richard Duschl ◽  
Lucy Avraamidou ◽  
Nathália Helena Azevedo

AbstractGrounded within current reform recommendations and built upon Giere’s views (1986, 1999) on model-based science, we propose an alternative approach to science education which we refer to as the Evidence-Explanation (EE) Continuum. The approach addresses conceptual, epistemological, and social domains of knowledge, and places emphasis on the epistemological conversations about data acquisitions and transformations in the sciences. The steps of data transformation, which we refer to as data-texts, we argue, unfold the processes of using evidence during knowledge building and reveal the dynamics of scientific practices. Data-texts involve (a) obtaining observations/measurements to become data; (b) selecting and interpreting data to become evidence; (c) using evidence to ascertain patterns and develop models; and (d) utilizing the patterns and models to propose and refine explanations. Throughout the transformations of the EE continuum, there are stages of transition that foster the engagement of learners in negotiations of meaning and collective construction of knowledge. A focus on the EE continuum facilitates the emergence of further insights, both by questioning the nature of the data and its multiple possibilities for change and representations and by reflecting on the nature of the explanations. The shift of emphasis to the epistemics of science holds implications for the design of learning environments that support learners in developing contemporary understandings of the nature and processes of scientific practices.


Author(s):  
Pauliina Mattila ◽  
Floris van der Marel ◽  
Maria Mikkonen

AbstractWhile the construction of knowledge hubs has gained recent traction, little is known on how networked actors perceive their collective culture. Authors looked at the topic through a single case study, the Design Factory Global Network, a network of 24 autonomous yet connected hubs for passion-based co- creation in an educational setting. Data was collected via questionnaires, asking 1) to describe their Design Factory in three distinct, words, 2) explicate these with exemplary stories, and 3) express future development wishes. 98 stories and future wishes were shared by representatives from 15 Design Factories. Excerpts reflecting cultural levels (attitudes, norms, manifestations) were identified and made sense of by looking at which level of stakeholder relationship (internal, host, network, wider environment) they targeted. 78 attitudes, 114 norms and 95 manifestations were mentioned, mostly targeting the internal community and the host levels. Authors draw some practical implications for each of the identified level or relationship, contributing to the knowledge of the creation and development of such innovation hubs. In addition, further research directions are proposed.


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