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Towards Outcomes-Based Education of Computer-Aided Chemical Engineering
Zdravko Kravanja, Miloš Bogataj (Editors), Proceedings of the 26th European Symposium on Computer Aided Process Engineering – ESCAPE 26 June 12th -15th, 2016, Portorož, Slovenia © 2016 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/B978-0-444-63428-3.50399-4
Towards Outcomes-Based Education of ComputerAided Chemical Engineering Zorka Novak Pintarič*, Zdravko Kravanja University of Maribor, Faculty of Chemistry and Chemical Engineering, Smetanova 17 2000 Maribor, Slovenia
Abstract Chemical engineering education is nowadays increasingly supported by the use of various computational tools as the employers’ requirements for computing skills of graduates are growing too. However, students often acquire computational skills in an unsystematic manner due to a lack of defining and applying computer-based outcomes within the syllabuses suitable for the particular level of the Bologna three-cycle system. This paper bridges this gap by providing the review of the essential learning outcomes in the computer-aided chemical engineering education during all three cycles. The identified outcomes gradually progress from application-based competencies up to more advanced process modeling ones based on knowledge synthesis and creation. Accordingly, the educational strategies and curricula can be redesigned in order to integrate courses more efficiently both horizontally and vertically, and upgrade the use of computational tools. Keywords: Computer-Aided; Chemical Engineering; Education; Bologna process; Learning Outcomes
1. Introduction The Bologna reform process has reached some of its basic goals so far, such as the organization of the studies into three main cycles, and the establishment of the European Credit Transfer System (ECTS) in a great majority of European higher education institutions (Yerevan Communique, 2015). However, an open question remains as to what extent a shift from formal reorganization of study programs towards their restructuring into high quality student- and outcomes-oriented education has been achieved. When considering that the chemical industry is one of the more important sectors within a modern economy, quality education for chemical engineers should provide students with specific parts of fundamental natural sciences, chemical engineering and non-technical subjects (EFCE, 2010). Modern chemical engineers may also need many non-traditional topics because the scopes of their activities has broadened significantly during recent decades (Kravanja, 2014). Besides, the complexities of those problems faced by chemical engineers have increased from isolated analytical to integrated multi-scale synthesis problems. Teaching chemical engineering students in using computer methods and tools has become of paramount importance for raising their abilities to generate complex and integrated process solutions (Kravanja and Klemeš, 2011). There exist several specific competencies in computer-aided chemical engineering education, for example, using spreadsheets (Ferreira et al., 2004) and process simulation (Ng and Chong, 2013). This presented contribution, however, aims at defining those general major learning outcomes associated with using computer methods, tools and concepts at all three Bologna levels of computer-aided chemical engineering education. According to Bloom’s taxonomy of learning objectives (Anderson et al., 2013), several essential computer skills are identified that support the efficient implementation of a
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chemical engineering curriculum, and stimulate students’ abilities to progress from obtaining and applying the basic knowledge during the first cycle, deepening knowledge during the second cycle, up to creating new knowledge during doctoral and postdoctoral studies. The identified outcomes could help to improve the syllabuses by leading to student- and outcomes-oriented courses.
2. Using computers within the chemical engineering curriculum Within a typical chemical engineering curriculum, the main goal of the first cycle is to provide students with the necessary knowledge and understanding of basic natural phenomena and chemical engineering mechanisms. In this way, students acquire competencies for the analytical approach, i.e. the ability to solve individual and isolated problems. During the second cycle, the topics of Chemical Engineering science become deeper and wider, also adding Process Systems Engineering (PSE) courses, as well as the specific courses for further specialization. The main goal of the second cycle is to provide students with a systems approach in order to gain abilities for designing chemical and other processes while taking into account the economics, environmental influences and social responsibilities. During the third cycle, students completely specialize in their selected research topics, while on the other hand seeking the wider relevance of their research. The main goal of the third cycle is to provide students with competencies for independent work in research and development, developing new methods and approaches, and thus creating new knowledge and innovations. According to the increased requirements of the chemical engineering curriculum, the abilities of students for using computing and computers in solving engineering problems need to increase as well. Based on the experiences gained during the development of Chemical Engineering curriculum at the University of Maribor, this section describes the distribution of computer-based outcomes across the three-cycle study system. 2.1. First cycle During the first cycle students acquire various laboratory skills in practical courses of inorganic, organic, analytical, physical and other chemistries. Other equally important skills for chemical engineering students are the computer skills. It is important to train the students as early as possible in the basics of computing, programing environments, and spreadsheets. Besides, students need to acquire or strengthen their writing and presentation skills. At the very beginning of the first cycle, they should be encouraged to use the reliable open computer software or free demo versions at their personal desktop computers or laptops. Web-based learning environments. Students of Chemical Engineering at the University of Maribor are introduced to the open-source learning platform Moodle very early. Within this platform they obtain access to teaching and learning materials, time schedules of all activities including practical courses, tests and exams, as well as their weekly home assignments. They can choose and register for practical courses and tests, and submit the assignment reports. Short e-tests are also performed. Lecturers record students’ grades within the Moodle’s grade-book, which is accessible to students confidentially via their home computers and mobile devices. Basic spreadsheets. During the first cycle laboratory work, students prepare extensive reports that include various calculations, data processing and visualization. Therefore, they need to be trained in working with spreadsheets including data input, calculations by applying relative and absolute cell references, sorting, classifying and aggregating data, using frequently used functions, visualizing through various graphic presentations, fitting models by using linear and nonlinear regressions, creating rules and constraints
Towards Outcomes-Based Education of Computer-Aided Chemical Engineering
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by conditional formatting and conditional statements. Another important feature is the ability to write Excel Macros (VBA), which are widely used in industry. Basic programing. Most black-box software allows for writing the user’s own routines in various programming languages, e.g. Fortran or C++. Students should therefore be acquainted with the basic principles of programing starting from problem definition, its analysis with deep understanding of mathematical expressions together with analyzing measurement units, drawing a flowchart, and writing a computer code. A curriculum should include a particular programing language with data input, using the intrinsic functions, loops, conditional statements, arrays, subprograms, and displaying the results. Working with arithmetic expressions. Regardless of which computing environment is used within the curriculum, an ability to convert the mathematical expressions into programming code is of paramount importance. Students need to acquire an overview of the arithmetic operators and operands, precedencies of operators, as well as the relational and logical operators. Numerical methods. During the first cycle, students need several skills for solving different problems through computing. In thermodynamics, chemical reaction engineering, heat and mass transfer etc. the numerical methods are needed for determining the polynomial roots and the roots of nonlinear functions, solving a system of linear equations, system of nonlinear equations, determining the minimums/maximums of functions, numerical integration etc. It is therefore necessary that students become familiar with specific mathematical software, e.g. Matlab, Mathcad, Scilab, especially the open source software or free student license programs. Mathematical programming. During the initial course of process optimization students become acquainted with linear and nonlinear programing (LP and NLP) for specific applications in chemical engineering, for example, production planning, designing small processes, data analysis, mixtures blending, transportation problems etc. Students needs to be trained in observing and understanding the technical problems, and translating them from a descriptive language into abstract mathematical expressions. Some modeling systems, like GAMS, offer free demo systems with limited numbers of constraints and variables, which are usually sufficient for first cycle students. Writing and presentation skills. Students bring basic skills for using word processors and presentation programs from previous education, however, the majority of them would need additional training in using more specific features, such as the styles, sections, numbered lists, cross-referencing, literature citing and similar. The knowledge of software, such as Word or Power Point, needs to be promoted through workshops, project- and seminar works. The use of free tools for citing the literature is also promoted among students. 2.2. Second cycle A two-year second cycle represents an upgrade from analytical to synthesis approach. A main goal is to qualify students for linking and integrating the acquired knowledge of natural sciences, unit operations and chemical engineering into a holistic approach for chemical process design and synthesis while considering operational, economic and environmental efficiencies of process solutions. Students perform simulations with available software, however, they also need to be able to write their own mathematical models and computer programs. Process Simulation. Students use process simulators, like Aspen and Hysys, during several courses for stationary and dynamic simulations of processes flow sheets, separation processes, heat integration and Heat Exchangers Network (HEN) design,
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economic evaluation, parametric optimization etc. They need to apply their knowledge and understanding for selecting an appropriate thermodynamic model, selecting and defining the models for reaction and separation, placing the recycle and purge streams appropriately, and writing their own routines if required. Mathematical programming. At this level, the knowledge of LP and NLP from the first cycle is upgraded by mixed integer linear and nonlinear programming (MILP and MINLP), and used for specific applications in chemical process engineering, like the superstructural approach to process synthesis and design, heat integration and HEN synthesis, computer-aided molecular design, capital budgeting etc. It is important to stimulate the students to independent modeling in order to acquire the abilities for generating their own mathematical optimization models. Spreadsheets’ specifics. At this stage, the students are well skilled in using spreadsheets, and it is easy to familiarize them with the specific functions and applications, for example statistical functions for hypothesis testing, economic functions for detailed economic evaluations, sensitivity analyses etc. Specific software. Students need the knowledge and skills to install and run various software packages for specific applications. They should be able to apply the software to their own problems arising either from the laboratory experiments, engineering feasibility studies or industrial problems. The use of free and academic licensed software is encouraged, for example, statistical programs (SPSS, Teach/Me Data Analysis), hazards and accident modeling programs (ALOHA), life cycle assessment programs (SimaPRO, openLCA), software for creative problem solving (TriSolver), heat integration (SuperTarget) etc. In addition, several computer codes have been developed at the Faculty of Chemistry and Chemical Engineering Maribor for waste management, water networks, piping systems design etc., that are used for education. 2.3. Third cycle The third cycle is specific for each student, and is completely research-oriented. PSEoriented students, in particular, combine all computer-aided knowledge and skills acquired during the preceding cycles in order to develop their own program codes and models for generating the solutions of specific problems. They also develop the methods and algorithms for solving the models. Highly advanced software is often used as well as multi-core architectures that require highly qualified students. The third cycle represents a leap towards creating new knowledge, and using it for advanced applications within the chemical engineering area.
3. Learning education
outcomes
for
Computer-Aided
Chemical
Engineering
When summarizing those specific computer-based activities identified in the previous section, the students’ outcomes can be defined, which at the first cycle are concentrated on knowledge, application, and analysis (Table 1), at the second cycle the focus is on the synthesis (Table 2), while at the third cycle creation and evaluation should be the main activities (Table 3). Through the three Bologna cycles, the types and structures of the computing models vary from well-defined models, usually with zero degrees of freedom, to more and more abstract and sophisticated models with many degrees of freedom. The type of modeling changes from a sequential-modular approach where each unit is calculated in a sequence, to the equation-oriented approach where all equations are solved simultaneously. The applied computational methods and algorithms become more and more demanding. This process requires shifts in students’ thinking from the analytical
Towards Outcomes-Based Education of Computer-Aided Chemical Engineering
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approach for solving limited isolated problems to the synthesis approach where process units are combined into flow-sheets and optimized subject to the overall process performances. This systems approach is characterized by multi-scale modeling including various time and spatial dimensions of the chemical supply-chains, simultaneous continuous and discrete decisions, handling uncertain parameters for generating flexible processes etc. Table 1: First cycle learning outcomes for computer-aided chemical engineering education
First cycle Knowledge Comprehension Application
Analysis
Students would be able to: Recall major arithmetic operators and operands, precedence of operators, as well as the relational and logical operators. Recognize major structures in the computer programs: loops, if statements, sets etc., and predict the output. Sketch a flow chart for designing a program, and develop a source code. Use spreadsheets for data storage, manipulation, sorting, filtering, visualization. Compute minimums and maximums of functions, zeros of polynoms, zeros of nonlinear equations, system of linear equations, system of nonlinear equations, in order to solve the problems within unit operations and chemical engineering problems. Develop computer programs for specific applications: numerical integration and differentiation, ordinary differential equations. Develop linear and nonlinear mathematical optimization process models. Identify degrees of freedom and optimal values of variables. Compare various solutions obtained.
Table 2: Second cycle learning outcomes for computer-aided chemical engineering education
Second cycle Application Analysis
Synthesis
Evaluation
Students would be able to: Apply simulation software for stationary and dynamic simulations. Analyze data and test hypotheses by using spreadsheets or other programs for statistics, economic analyses, LCA. Distinguish between sequential-modular and equation-oriented approaches to process flow sheeting. Distinguish between hierarchical and superstructural approaches to process design and synthesis. Test various programs, compare their characteristics, evaluate their performances, propose the more appropriate ones for problem solving. Prepare the guidelines for using software. Generate algorithms for solving problems by combining various software for achieving specific goals. Create mixed integer linear and nonlinear programming models for discrete-continuous decision making during process design and synthesis. Compare the solutions obtained by evaluating their efficiencies and sustainability by using software. Recommend optimal solutions under specific circumstances.
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Table 3: Third cycle learning outcomes for computer-aided chemical engineering education
Third cycle
Students would be able to:
Synthesis/ Creating
Develop specific types of optimization problems, e.g. multicriteria, multi-period, multi-scale models, including risk and uncertainty. Develop innovative computing solution methods, algorithms and strategies. Perform global optimizations. Evaluate developed programs, models and algorithms, and compare the results with other approaches. Verify and validate computer programs and optimization models.
Evaluation
4. Conclusions This contribution defined the major learning outcomes relating to the use of computers during chemical engineering education in a Bologna three cycle degree system. The outcomes develop gradually from the capabilities for solving individual zero-degreesof-freedom numerical problems, through positive-degrees-of-freedom optimization problems including discrete-continuous decisions, and to creating the advanced models with specific characteristics, e.g. multi-period, multi-objective and multi-scale optimization models. Computer-based learning outcomes at the first cycle are mainly focused on knowledge of programing and the applications of various software for problem analyses. The second cycle focuses on modeling for process design, analysis and synthesis, while the third cycle is oriented towards syntheses of process systems, supply chains and networks, models and programs’ creation and evaluation. In this way, graduates would be qualified to confidently apply those computational methods and computer tools appropriate to their degree-level for supporting their work during the professional career, or even develop their own computer tools for specific applications.
References L. W. Anderson, D. R. Krathwohl, P. W. Airasian, K. A. Cruikshank, 2013, A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives, Harlow: Pearson Education Limited. EFCE, 2010, EFCE Bologna Recommendations for Chemical Engineering Education in a Bologna three cycle Degree System, http://www.efce.info/Bologna_Recommendation.html (accessed 10/02/2016). E. C. Ferreria, R. Lima, R. Salcedo, 2004, Spreadsheets in Chemical Engineering Education – A Tool in Process Design and process Integration. International Journal of Engineering Education, 20 (6), 928-938. Z. Kravanja, 2015, Chemical engineering education in European higher education, QScience Proceedings (Engineering Leaders Conference 2014) 2015:30, https://dx.doi.org/10.5339/qproc.2015.elc2014.30 (accessed 10/02/2016). Z. Kravanja, K. J. Klemeš, 2011, The Role of Computer-Aided Chemical Engineering Education within the European Bologna Three-Cycle Study System. IEEE, 4th International Conference on Modelling, Simulation and Applied Optimization (ICMSAO), 2011, DOI: 10.1109/ICMSAO.2011.5775643. D. K. S. Ng, M. F. Chong, 2013, An Undergraduate Teaching Strategy for Process Simulation in Chemical Engineering, Proceedings of the 6th International Conference on Process Systems Engineering (PSE ASIA) 25-27 June 2013, Kuala Lumpur. Yerevan Communique, EHEA Ministerial Conference, 2015, http://bolognayerevan2015.ehea.info/files/YerevanCommuniqueFinal.pdf (accessed 10/02/2016).
Towards Outcomes-Based Education of ComputerAided Chemical Engineering Zorka Novak Pintarič*, Zdravko Kravanja University of Maribor, Faculty of Chemistry and Chemical Engineering, Smetanova 17 2000 Maribor, Slovenia
Abstract Chemical engineering education is nowadays increasingly supported by the use of various computational tools as the employers’ requirements for computing skills of graduates are growing too. However, students often acquire computational skills in an unsystematic manner due to a lack of defining and applying computer-based outcomes within the syllabuses suitable for the particular level of the Bologna three-cycle system. This paper bridges this gap by providing the review of the essential learning outcomes in the computer-aided chemical engineering education during all three cycles. The identified outcomes gradually progress from application-based competencies up to more advanced process modeling ones based on knowledge synthesis and creation. Accordingly, the educational strategies and curricula can be redesigned in order to integrate courses more efficiently both horizontally and vertically, and upgrade the use of computational tools. Keywords: Computer-Aided; Chemical Engineering; Education; Bologna process; Learning Outcomes
1. Introduction The Bologna reform process has reached some of its basic goals so far, such as the organization of the studies into three main cycles, and the establishment of the European Credit Transfer System (ECTS) in a great majority of European higher education institutions (Yerevan Communique, 2015). However, an open question remains as to what extent a shift from formal reorganization of study programs towards their restructuring into high quality student- and outcomes-oriented education has been achieved. When considering that the chemical industry is one of the more important sectors within a modern economy, quality education for chemical engineers should provide students with specific parts of fundamental natural sciences, chemical engineering and non-technical subjects (EFCE, 2010). Modern chemical engineers may also need many non-traditional topics because the scopes of their activities has broadened significantly during recent decades (Kravanja, 2014). Besides, the complexities of those problems faced by chemical engineers have increased from isolated analytical to integrated multi-scale synthesis problems. Teaching chemical engineering students in using computer methods and tools has become of paramount importance for raising their abilities to generate complex and integrated process solutions (Kravanja and Klemeš, 2011). There exist several specific competencies in computer-aided chemical engineering education, for example, using spreadsheets (Ferreira et al., 2004) and process simulation (Ng and Chong, 2013). This presented contribution, however, aims at defining those general major learning outcomes associated with using computer methods, tools and concepts at all three Bologna levels of computer-aided chemical engineering education. According to Bloom’s taxonomy of learning objectives (Anderson et al., 2013), several essential computer skills are identified that support the efficient implementation of a
2368
Z.N. Pintarič and Z. Kravanja
chemical engineering curriculum, and stimulate students’ abilities to progress from obtaining and applying the basic knowledge during the first cycle, deepening knowledge during the second cycle, up to creating new knowledge during doctoral and postdoctoral studies. The identified outcomes could help to improve the syllabuses by leading to student- and outcomes-oriented courses.
2. Using computers within the chemical engineering curriculum Within a typical chemical engineering curriculum, the main goal of the first cycle is to provide students with the necessary knowledge and understanding of basic natural phenomena and chemical engineering mechanisms. In this way, students acquire competencies for the analytical approach, i.e. the ability to solve individual and isolated problems. During the second cycle, the topics of Chemical Engineering science become deeper and wider, also adding Process Systems Engineering (PSE) courses, as well as the specific courses for further specialization. The main goal of the second cycle is to provide students with a systems approach in order to gain abilities for designing chemical and other processes while taking into account the economics, environmental influences and social responsibilities. During the third cycle, students completely specialize in their selected research topics, while on the other hand seeking the wider relevance of their research. The main goal of the third cycle is to provide students with competencies for independent work in research and development, developing new methods and approaches, and thus creating new knowledge and innovations. According to the increased requirements of the chemical engineering curriculum, the abilities of students for using computing and computers in solving engineering problems need to increase as well. Based on the experiences gained during the development of Chemical Engineering curriculum at the University of Maribor, this section describes the distribution of computer-based outcomes across the three-cycle study system. 2.1. First cycle During the first cycle students acquire various laboratory skills in practical courses of inorganic, organic, analytical, physical and other chemistries. Other equally important skills for chemical engineering students are the computer skills. It is important to train the students as early as possible in the basics of computing, programing environments, and spreadsheets. Besides, students need to acquire or strengthen their writing and presentation skills. At the very beginning of the first cycle, they should be encouraged to use the reliable open computer software or free demo versions at their personal desktop computers or laptops. Web-based learning environments. Students of Chemical Engineering at the University of Maribor are introduced to the open-source learning platform Moodle very early. Within this platform they obtain access to teaching and learning materials, time schedules of all activities including practical courses, tests and exams, as well as their weekly home assignments. They can choose and register for practical courses and tests, and submit the assignment reports. Short e-tests are also performed. Lecturers record students’ grades within the Moodle’s grade-book, which is accessible to students confidentially via their home computers and mobile devices. Basic spreadsheets. During the first cycle laboratory work, students prepare extensive reports that include various calculations, data processing and visualization. Therefore, they need to be trained in working with spreadsheets including data input, calculations by applying relative and absolute cell references, sorting, classifying and aggregating data, using frequently used functions, visualizing through various graphic presentations, fitting models by using linear and nonlinear regressions, creating rules and constraints
Towards Outcomes-Based Education of Computer-Aided Chemical Engineering
2369
by conditional formatting and conditional statements. Another important feature is the ability to write Excel Macros (VBA), which are widely used in industry. Basic programing. Most black-box software allows for writing the user’s own routines in various programming languages, e.g. Fortran or C++. Students should therefore be acquainted with the basic principles of programing starting from problem definition, its analysis with deep understanding of mathematical expressions together with analyzing measurement units, drawing a flowchart, and writing a computer code. A curriculum should include a particular programing language with data input, using the intrinsic functions, loops, conditional statements, arrays, subprograms, and displaying the results. Working with arithmetic expressions. Regardless of which computing environment is used within the curriculum, an ability to convert the mathematical expressions into programming code is of paramount importance. Students need to acquire an overview of the arithmetic operators and operands, precedencies of operators, as well as the relational and logical operators. Numerical methods. During the first cycle, students need several skills for solving different problems through computing. In thermodynamics, chemical reaction engineering, heat and mass transfer etc. the numerical methods are needed for determining the polynomial roots and the roots of nonlinear functions, solving a system of linear equations, system of nonlinear equations, determining the minimums/maximums of functions, numerical integration etc. It is therefore necessary that students become familiar with specific mathematical software, e.g. Matlab, Mathcad, Scilab, especially the open source software or free student license programs. Mathematical programming. During the initial course of process optimization students become acquainted with linear and nonlinear programing (LP and NLP) for specific applications in chemical engineering, for example, production planning, designing small processes, data analysis, mixtures blending, transportation problems etc. Students needs to be trained in observing and understanding the technical problems, and translating them from a descriptive language into abstract mathematical expressions. Some modeling systems, like GAMS, offer free demo systems with limited numbers of constraints and variables, which are usually sufficient for first cycle students. Writing and presentation skills. Students bring basic skills for using word processors and presentation programs from previous education, however, the majority of them would need additional training in using more specific features, such as the styles, sections, numbered lists, cross-referencing, literature citing and similar. The knowledge of software, such as Word or Power Point, needs to be promoted through workshops, project- and seminar works. The use of free tools for citing the literature is also promoted among students. 2.2. Second cycle A two-year second cycle represents an upgrade from analytical to synthesis approach. A main goal is to qualify students for linking and integrating the acquired knowledge of natural sciences, unit operations and chemical engineering into a holistic approach for chemical process design and synthesis while considering operational, economic and environmental efficiencies of process solutions. Students perform simulations with available software, however, they also need to be able to write their own mathematical models and computer programs. Process Simulation. Students use process simulators, like Aspen and Hysys, during several courses for stationary and dynamic simulations of processes flow sheets, separation processes, heat integration and Heat Exchangers Network (HEN) design,
2370
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economic evaluation, parametric optimization etc. They need to apply their knowledge and understanding for selecting an appropriate thermodynamic model, selecting and defining the models for reaction and separation, placing the recycle and purge streams appropriately, and writing their own routines if required. Mathematical programming. At this level, the knowledge of LP and NLP from the first cycle is upgraded by mixed integer linear and nonlinear programming (MILP and MINLP), and used for specific applications in chemical process engineering, like the superstructural approach to process synthesis and design, heat integration and HEN synthesis, computer-aided molecular design, capital budgeting etc. It is important to stimulate the students to independent modeling in order to acquire the abilities for generating their own mathematical optimization models. Spreadsheets’ specifics. At this stage, the students are well skilled in using spreadsheets, and it is easy to familiarize them with the specific functions and applications, for example statistical functions for hypothesis testing, economic functions for detailed economic evaluations, sensitivity analyses etc. Specific software. Students need the knowledge and skills to install and run various software packages for specific applications. They should be able to apply the software to their own problems arising either from the laboratory experiments, engineering feasibility studies or industrial problems. The use of free and academic licensed software is encouraged, for example, statistical programs (SPSS, Teach/Me Data Analysis), hazards and accident modeling programs (ALOHA), life cycle assessment programs (SimaPRO, openLCA), software for creative problem solving (TriSolver), heat integration (SuperTarget) etc. In addition, several computer codes have been developed at the Faculty of Chemistry and Chemical Engineering Maribor for waste management, water networks, piping systems design etc., that are used for education. 2.3. Third cycle The third cycle is specific for each student, and is completely research-oriented. PSEoriented students, in particular, combine all computer-aided knowledge and skills acquired during the preceding cycles in order to develop their own program codes and models for generating the solutions of specific problems. They also develop the methods and algorithms for solving the models. Highly advanced software is often used as well as multi-core architectures that require highly qualified students. The third cycle represents a leap towards creating new knowledge, and using it for advanced applications within the chemical engineering area.
3. Learning education
outcomes
for
Computer-Aided
Chemical
Engineering
When summarizing those specific computer-based activities identified in the previous section, the students’ outcomes can be defined, which at the first cycle are concentrated on knowledge, application, and analysis (Table 1), at the second cycle the focus is on the synthesis (Table 2), while at the third cycle creation and evaluation should be the main activities (Table 3). Through the three Bologna cycles, the types and structures of the computing models vary from well-defined models, usually with zero degrees of freedom, to more and more abstract and sophisticated models with many degrees of freedom. The type of modeling changes from a sequential-modular approach where each unit is calculated in a sequence, to the equation-oriented approach where all equations are solved simultaneously. The applied computational methods and algorithms become more and more demanding. This process requires shifts in students’ thinking from the analytical
Towards Outcomes-Based Education of Computer-Aided Chemical Engineering
2371
approach for solving limited isolated problems to the synthesis approach where process units are combined into flow-sheets and optimized subject to the overall process performances. This systems approach is characterized by multi-scale modeling including various time and spatial dimensions of the chemical supply-chains, simultaneous continuous and discrete decisions, handling uncertain parameters for generating flexible processes etc. Table 1: First cycle learning outcomes for computer-aided chemical engineering education
First cycle Knowledge Comprehension Application
Analysis
Students would be able to: Recall major arithmetic operators and operands, precedence of operators, as well as the relational and logical operators. Recognize major structures in the computer programs: loops, if statements, sets etc., and predict the output. Sketch a flow chart for designing a program, and develop a source code. Use spreadsheets for data storage, manipulation, sorting, filtering, visualization. Compute minimums and maximums of functions, zeros of polynoms, zeros of nonlinear equations, system of linear equations, system of nonlinear equations, in order to solve the problems within unit operations and chemical engineering problems. Develop computer programs for specific applications: numerical integration and differentiation, ordinary differential equations. Develop linear and nonlinear mathematical optimization process models. Identify degrees of freedom and optimal values of variables. Compare various solutions obtained.
Table 2: Second cycle learning outcomes for computer-aided chemical engineering education
Second cycle Application Analysis
Synthesis
Evaluation
Students would be able to: Apply simulation software for stationary and dynamic simulations. Analyze data and test hypotheses by using spreadsheets or other programs for statistics, economic analyses, LCA. Distinguish between sequential-modular and equation-oriented approaches to process flow sheeting. Distinguish between hierarchical and superstructural approaches to process design and synthesis. Test various programs, compare their characteristics, evaluate their performances, propose the more appropriate ones for problem solving. Prepare the guidelines for using software. Generate algorithms for solving problems by combining various software for achieving specific goals. Create mixed integer linear and nonlinear programming models for discrete-continuous decision making during process design and synthesis. Compare the solutions obtained by evaluating their efficiencies and sustainability by using software. Recommend optimal solutions under specific circumstances.
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Table 3: Third cycle learning outcomes for computer-aided chemical engineering education
Third cycle
Students would be able to:
Synthesis/ Creating
Develop specific types of optimization problems, e.g. multicriteria, multi-period, multi-scale models, including risk and uncertainty. Develop innovative computing solution methods, algorithms and strategies. Perform global optimizations. Evaluate developed programs, models and algorithms, and compare the results with other approaches. Verify and validate computer programs and optimization models.
Evaluation
4. Conclusions This contribution defined the major learning outcomes relating to the use of computers during chemical engineering education in a Bologna three cycle degree system. The outcomes develop gradually from the capabilities for solving individual zero-degreesof-freedom numerical problems, through positive-degrees-of-freedom optimization problems including discrete-continuous decisions, and to creating the advanced models with specific characteristics, e.g. multi-period, multi-objective and multi-scale optimization models. Computer-based learning outcomes at the first cycle are mainly focused on knowledge of programing and the applications of various software for problem analyses. The second cycle focuses on modeling for process design, analysis and synthesis, while the third cycle is oriented towards syntheses of process systems, supply chains and networks, models and programs’ creation and evaluation. In this way, graduates would be qualified to confidently apply those computational methods and computer tools appropriate to their degree-level for supporting their work during the professional career, or even develop their own computer tools for specific applications.
References L. W. Anderson, D. R. Krathwohl, P. W. Airasian, K. A. Cruikshank, 2013, A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives, Harlow: Pearson Education Limited. EFCE, 2010, EFCE Bologna Recommendations for Chemical Engineering Education in a Bologna three cycle Degree System, http://www.efce.info/Bologna_Recommendation.html (accessed 10/02/2016). E. C. Ferreria, R. Lima, R. Salcedo, 2004, Spreadsheets in Chemical Engineering Education – A Tool in Process Design and process Integration. International Journal of Engineering Education, 20 (6), 928-938. Z. Kravanja, 2015, Chemical engineering education in European higher education, QScience Proceedings (Engineering Leaders Conference 2014) 2015:30, https://dx.doi.org/10.5339/qproc.2015.elc2014.30 (accessed 10/02/2016). Z. Kravanja, K. J. Klemeš, 2011, The Role of Computer-Aided Chemical Engineering Education within the European Bologna Three-Cycle Study System. IEEE, 4th International Conference on Modelling, Simulation and Applied Optimization (ICMSAO), 2011, DOI: 10.1109/ICMSAO.2011.5775643. D. K. S. Ng, M. F. Chong, 2013, An Undergraduate Teaching Strategy for Process Simulation in Chemical Engineering, Proceedings of the 6th International Conference on Process Systems Engineering (PSE ASIA) 25-27 June 2013, Kuala Lumpur. Yerevan Communique, EHEA Ministerial Conference, 2015, http://bolognayerevan2015.ehea.info/files/YerevanCommuniqueFinal.pdf (accessed 10/02/2016).