Teaching knowledge engineering: Experiences

1998 ◽  
pp. 424-427
Author(s):  
Tom Andersen ◽  
Susanne C. Hartvig
Keyword(s):  
Knowledge Engineering ◽  
Teaching Knowledge

KEATS: A System to Support Knowledge Engineering and Training for Decision-Making Skills

1989 ◽  
Author(s):  
Fritz H. Brecke ◽  
Patrick Hays ◽  
Donald Johnston ◽  
Gail Slemon ◽  
Jane McGarvey ◽  
...  
Keyword(s):  
Decision Making ◽  
Knowledge Engineering ◽  
And Training

Engineering knowledge: philosophy and ponstructive meanig

2018 ◽  
pp. 10-16
Author(s):  
V. I. Onoprienko
Keyword(s):  
Information Technologies ◽  
Knowledge Engineering ◽  
Practical Rationality ◽  
Engineering Knowledge ◽  
World Today ◽  
The World ◽  
Technological Area

An expansion of information technologies in the world today is caused by progress of instrumental knowledge. It has been arisen a special technological area of knowledge engineering, which is related to practical rationality and experts’ knowledge for solving urgent problems of science and practice.

Knowledge Engineering

1998 ◽  
Author(s):  
John Debenham
Keyword(s):  
Knowledge Engineering

Application of Expert Systems Technology in Water Quality Modeling

1989 ◽  
Vol 21 (8-9) ◽  
pp. 1045-1056 ◽  
Author(s):  
Thomas O. Barnwell ◽  
Linfield C. Brown ◽  
Wiktor Marek
Keyword(s):  
Water Quality ◽  
Expert Systems ◽  
Knowledge Engineering ◽  
Stream Water ◽  
Environmental Modeling ◽  
Water Quality Modeling ◽  
Stream Water Quality ◽  
Quality Model ◽  
Knowledge Based ◽  
Available Technology

Computerized modeling is becoming an integral part of decision making in water pollution control. Expert systems is an innovative methodology that can assist in building, using, and interpreting the output of these models. This paper reviews the use and evaluates the potential of expert systems technology in environmental modeling and describes elements of an expert advisor for the stream water quality model QUAL2E. Some general conclusions are presented about the tools available to develop this system, the level of available technology in knowledge-based engineering, and the value of approaching problems from a knowledge engineering perspective.

Missed Opportunity: How Induction Policy Fails to Explicitly Address English Learner-Classified Students

2021 ◽  
pp. 002248712110000
Author(s):  
Lucrecia Santibañez ◽  
Christine Snyder ◽  
Danielle Centeno
Keyword(s):  
Teacher Induction ◽  
Language Proficiency ◽  
Teaching Skills ◽  
English Learner ◽  
Knowledge And Skills ◽  
Teaching Knowledge ◽  
Classified Students ◽  
Specific Teaching ◽  
Missed Opportunity

English Learner-classified (ELC) students are one of the nation’s most marginalized student populations. One promising but understudied strategy to strengthen teaching of ELC students is teacher induction. This article examines the role of teacher induction in strengthening novice teachers’ EL-specific teaching knowledge and skills. Through a detailed analysis of induction in California, we find that the state has little external assurance that teachers who have undergone induction can meet ELC students’ unique and diverse needs. California’s decentralized, flexible, teacher-led induction may support teachers’ development of general teaching skills, but misses an opportunity to support teachers in an area where many of them struggle. The study raises other problematic issues around mentoring for equity such as monolithic views of ELC students, lack of timely and actionable information about language proficiency, and lack of guidance as to what constitutes acceptable evidence of competency teaching ELC students.

Synthesising Privacy by Design Knowledge Toward Explainable Internet of Things Application Designing in Healthcare

2021 ◽  
Vol 17 (2s) ◽  
pp. 1-29
Author(s):  
Lamya Alkhariji ◽  
Nada Alhirabi ◽  
Mansour Naser Alraja ◽  
Mahmoud Barhamgi ◽  
Omer Rana ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Conceptual Understanding ◽  
Knowledge Engineering ◽  
Privacy Preserving ◽  
Design Knowledge ◽  
Privacy By Design ◽  
Healthcare Applications ◽  
Software Developers ◽  
Healthcare Application ◽  
Application Design

Privacy by Design (PbD) is the most common approach followed by software developers who aim to reduce risks within their application designs, yet it remains commonplace for developers to retain little conceptual understanding of what is meant by privacy. A vision is to develop an intelligent privacy assistant to whom developers can easily ask questions to learn how to incorporate different privacy-preserving ideas into their IoT application designs. This article lays the foundations toward developing such a privacy assistant by synthesising existing PbD knowledge to elicit requirements. It is believed that such a privacy assistant should not just prescribe a list of privacy-preserving ideas that developers should incorporate into their design. Instead, it should explain how each prescribed idea helps to protect privacy in a given application design context—this approach is defined as “Explainable Privacy.” A total of 74 privacy patterns were analysed and reviewed using ten different PbD schemes to understand how each privacy pattern is built and how each helps to ensure privacy. Due to page limitations, we have presented a detailed analysis in Reference [3]. In addition, different real-world Internet of Things (IoT) use-cases, including a healthcare application, were used to demonstrate how each privacy pattern could be applied to a given application design. By doing so, several knowledge engineering requirements were identified that need to be considered when developing a privacy assistant. It was also found that, when compared to other IoT application domains, privacy patterns can significantly benefit healthcare applications. In conclusion, this article identifies the research challenges that must be addressed if one wishes to construct an intelligent privacy assistant that can truly augment software developers’ capabilities at the design phase.

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