Adaptable Navigation in a SCORM Compliant Learning Module

Advances in Web-Based Education ◽

10.4018/978-1-59140-690-7.ch009 ◽

2006 ◽

pp. 203-224

Author(s):

Boris Gauss ◽

Boris Urbas

Keyword(s):

Steady State ◽

Systems Engineering ◽

Future Research ◽

Process Systems Engineering ◽

Process Systems ◽

Learning Modules ◽

Learning Module ◽

Technological Standard ◽

The Subject

This chapter is about the use of metaphors and adaptable navigation in the context of the technological standard SCORM. Our theoretical focus is on hypertext navigation in SCORM compliant learning modules and the potential of adaptable navigation metaphors within this standard. In the empirical section, we present a case study about navigation design and usability evaluation of a learning module prototype. This learning module was developed for the subject matter of steady-state modelling in process systems engineering, and features an adaptable navigation with a novel process control metaphor. We conclude with a discussion on the didactical value of navigation metaphors and adaptability in SCORM, and provide some suggestions for future research in this area.

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Homogenous multi-agent optimization for process systems engineering problems with a case study of computer aided molecular design

Chemical Engineering Science ◽

10.1016/j.ces.2016.05.026 ◽

2017 ◽

Vol 159 ◽

pp. 194-206 ◽

Cited By ~ 10

Author(s):

Berhane H. Gebreslassie ◽

Urmila M. Diwekar

Keyword(s):

Systems Engineering ◽

Molecular Design ◽

Process Systems Engineering ◽

Process Systems ◽

Computer Aided ◽

Engineering Problems ◽

Multi Agent

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Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward

Frontiers in Chemical Engineering ◽

10.3389/fceng.2020.620168 ◽

2021 ◽

Vol 2 ◽

Author(s):

Iosif Pappas ◽

Dustin Kenefake ◽

Baris Burnak ◽

Styliani Avraamidou ◽

Hari S. Ganesh ◽

...

Keyword(s):

Systems Engineering ◽

Optimal Solution ◽

Parametric Uncertainty ◽

Optimal Decision ◽

Future Research ◽

Uncertain Parameters ◽

Process Systems Engineering ◽

Process Systems ◽

Multiparametric Programming ◽

The Impact

The inevitable presence of uncertain parameters in critical applications of process optimization can lead to undesirable or infeasible solutions. For this reason, optimization under parametric uncertainty was, and continues to be a core area of research within Process Systems Engineering. Multiparametric programming is a strategy that offers a holistic perspective for the solution of this class of mathematical programming problems. Specifically, multiparametric programming theory enables the derivation of the optimal solution as a function of the uncertain parameters, explicitly revealing the impact of uncertainty in optimal decision-making. By taking advantage of such a relationship, new breakthroughs in the solution of challenging formulations with uncertainty have been created. Apart from that, researchers have utilized multiparametric programming techniques to solve deterministic classes of problems, by treating specific elements of the optimization program as uncertain parameters. In the past years, there has been a significant number of publications in the literature involving multiparametric programming. The present review article covers recent theoretical, algorithmic, and application developments in multiparametric programming. Additionally, several areas for potential contributions in this field are discussed, highlighting the benefits of multiparametric programming in future research efforts.

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