Bryan T. Adey: Catalogue data in Autumn Semester 2021 |
| Name | Prof. Dr. Bryan T. Adey |
| Field | Infrastructure Management |
| Address | Inst. Bau-&Infrastrukturmanagement ETH Zürich, HIL F 24.3 Stefano-Franscini-Platz 5 8093 Zürich SWITZERLAND |
| Telephone | +41 44 633 27 38 |
| adey@ibi.baug.ethz.ch | |
| Department | Civil, Environmental and Geomatic Engineering |
| Relationship | Full Professor |
| Number | Title | ECTS | Hours | Lecturers | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 101-0031-AAL | Systems Engineering Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement. Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit. | 4 credits | 9R | B. T. Adey | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | • Systems Engineering is a way of thinking that helps engineer sustainable systems, i.e. ones that meet the needs of stakeholders in the short, medium and long terms. • This course provides an overview of the main principles of Systems Engineering, and includes an introduction to the use of operations research methods in the determination of optimal systems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The world’s growing population, changing demographics, and changing climate pose formidable challenges to humanity’s ability to live sustainably. Ensuring that humanity can live sustainably requires accommodating Earth’s growing and changing population through the provision and operation of a sustainable and resilient built environment. This requires ensuring excellent decision-making as to how the built environment is constructed and modified. The objective of this course is to ensure the best possible decision making when engineering sustainable systems, i.e. ones that meet the needs of stakeholders in the short, medium and long term. In this course, you will learn the main principles of Systems Engineering that can help you from the first idea that a system may not meet expectations, to the quantitative and qualitative evaluation of possible system modifications. Additionally, the course includes an introduction to the use of operations research methods in the determination of optimal solutions in complex systems. More specifically upon completion of the course, you will have gained insight into: • how to structure the large amount of information that is often associated with attempting to modify complex systems • how to set goals and define constraints in the engineering of complex systems • how to generate possible solutions to complex problems in ways that limit exceedingly narrow thinking • how to compare multiple possible solutions over time with differences in the temporal distribution of costs and benefits and uncertainty as to what might happen in the future • how to assess values of benefits to stakeholders that are not in monetary units • how to assess whether it is worth obtaining more information in determining optimal solution • how to take a step back from the numbers and qualitatively evaluate the possible solutions in light of the bigger picture • the basics of operations research and how it can be used to determine optimal solutions to complex problems, including linear, integer and network programming, dealing with multiple objectives and conducting sensitivity analyses. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The weekly content is structured as follows: 1 Introduction – An introduction to System Engineering, a way of thinking that helps to engineer sustainable systems, i.e. ones that meet the needs of stakeholders in the short, medium and long terms. A high-level overview of the main principles of System Engineering. An introduction to the example that we will be working with through most of the course. The expectations of your efforts throughout the semester. 2 Situation analysis – How to structure the large amount of information that is often associated with attempting to modify complex systems. 3 Goals and constraints – How to set goals and constraints to identify the best solutions as clearly as possible. 4 Generation of possible solutions – How to generate possible solutions to problems, considering multiple stakeholders. 5 Analysis – 1/5 – The principles of net-benefit maximization and a series of methods that range from qualitative and approximate to quantitative and exact, including pairwise comparison, elimination, display, weighting, and expected value. 6 Analysis – 2/5 – The idea behind the supply and demand curves and revealed preference methods. 7 Analysis – 3/5 – The concept of equivalence, including the time value of money, interest, life times and terminal values. 8 Analysis – 4/5 – The relationship between net-benefit and the benefit-cost ratio. How incremental cost benefit analysis can be used to determine the maximum net benefit. Marginal rates of return and internal rates of return. 9 Analysis – 5/5 – How to consider multiple possible futures and use simple rules to help pick optimal solutions and to determine the value of more information. 10 Evaluation of solutions – Regardless how sophisticated an analysis is, it requires that decision makers stand back and critically evaluate the results. This week we discuss the aspects of evaluating the results of an analysis. 11 Operations research – 1/4 – Once quantitative analysis is used it becomes possible to use operations research methods to analyse large numbers of possible solutions. This week we discuss linear programming and the simplex method. 12 Operations research – 2/4 – How sensitivity analysis is conducted using linear programming. 13 Operations research – 3/4 – How to use operations research to solve problems that consist of discrete values, as well as how to exploit the structure of networks to find optimal solutions to network problems. 14 Operations research – 4/4 – How to set up and solve problems when there are multiple objectives. The course uses a combination of qualitative and quantitative approaches. The quantitative analyses requires the use of Excel. An introduction to Excel will be provided in one of the help sessions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The script for the original course is in German. The English material that can be used for the virtual course is: 1 ) Adey, B.T., Hackl, J., Lam, J.C., van Gelder, P., van Erp, N., Prak, P., Heitzler, M., Iosifescu, I., Hurni, L., (2016), Ensuring acceptable levels of infrastructure related risks due to natural hazards with emphasis on stress tests, International Symposium on Infrastructure Asset Management (SIAM), Kyoto, Japan, January 21-22. 2) Blanchard, B.S., and Fabrycky W.J., (2008), Systems Engineering and Analysis, 5th International Edition, Prentice Hall. 3) Revelle, C.S., Whitlach, E.E., and Wright, J.R., (2003), Civil and Environmental Systems Engineering, 2nd Edition, Prentice Hall. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | The literature will be made available at the beginning of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competencies |
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| 101-0031-01L | Systems Engineering | 4 credits | 4G | B. T. Adey | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | • Systems Engineering is a way of thinking that helps engineer sustainable systems, i.e. ones that meet the needs of stakeholders in the short, medium and long terms. • This course provides an overview of the main principles of Systems Engineering, and includes an introduction to the use of operations research methods in the determination of optimal systems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The world’s growing population, changing demographics, and changing climate pose formidable challenges to humanity’s ability to live sustainably. Ensuring that humanity can live sustainably requires accommodating Earth’s growing and changing population through the provision and operation of a sustainable and resilient built environment. This requires ensuring excellent decision-making as to how the built environment is constructed and modified. The objective of this course is to ensure the best possible decision making when engineering sustainable systems, i.e. ones that meet the needs of stakeholders in the short, medium and long term. In this course, you will learn the main principles of Systems Engineering that can help you from the first idea that a system may not meet expectations, to the quantitative and qualitative evaluation of possible system modifications. Additionally, the course includes an introduction to the use of operations research methods in the determination of optimal solutions in complex systems. More specifically upon completion of the course, you will have gained insight into: • how to structure the large amount of information that is often associated with attempting to modify complex systems • how to set goals and define constraints in the engineering of complex systems • how to generate possible solutions to complex problems in ways that limit exceedingly narrow thinking • how to compare multiple possible solutions over time with differences in the temporal distribution of costs and benefits and uncertainty as to what might happen in the future • how to assess values of benefits to stakeholders that are not in monetary units • how to assess whether it is worth obtaining more information in determining optimal solution • how to take a step back from the numbers and qualitatively evaluate the possible solutions in light of the bigger picture • the basics of operations research and how it can be used to determine optimal solutions to complex problems, including linear, integer and network programming, dealing with multiple objectives and conducting sensitivity analyses. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The weekly lectures are structured as follows: 1 Introduction – An introduction to System Engineering, a way of thinking that helps to engineer sustainable systems, i.e. ones that meet the needs of stakeholders in the short, medium and long terms. A high-level overview of the main principles of System Engineering. An introduction to the example that we will be working with through most of the course. The expectations of your efforts throughout the semester. 2 Situation analysis – How to structure the large amount of information that is often associated with attempting to modify complex systems. 3 Goals and constraints – How to set goals and constraints to identify the best solutions as clearly as possible. 4 Generation of possible solutions – How to generate possible solutions to problems, considering multiple stakeholders. 5 Analysis – 1/5 – The principles of net-benefit maximization and a series of methods that range from qualitative and approximate to quantitative and exact, including pairwise comparison, elimination, display, weighting, and expected value. 6 Analysis – 2/5 – The idea behind the supply and demand curves and revealed preference methods. 7 Analysis – 3/5 – The concept of equivalence, including the time value of money, interest, life times and terminal values. 8 Analysis – 4/5 – The relationship between net-benefit and the benefit-cost ratio. How incremental cost benefit analysis can be used to determine the maximum net benefit. Marginal rates of return and internal rates of return. 9 Analysis – 5/5 – How to consider multiple possible futures and use simple rules to help pick optimal solutions and to determine the value of more information. 10 Evaluation of solutions – Regardless how sophisticated an analysis is, it requires that decision makers stand back and critically evaluate the results. This week we discuss the aspects of evaluating the results of an analysis. 11 Operations research – 1/4 – Once quantitative analysis is used it becomes possible to use operations research methods to analyse large numbers of possible solutions. This week we discuss linear programming and the simplex method. 12 Operations research – 2/4 – How sensitivity analysis is conducted using linear programming. 13 Operations research – 3/4 – How to use operations research to solve problems that consist of discrete values, as well as how to exploit the structure of networks to find optimal solutions to network problems. 14 Operations research – 4/4 – How to set up and solve problems when there are multiple objectives. The course uses a combination of qualitative and quantitative approaches. The quantitative analyses requires the use of Excel. An introduction to Excel will be provided in one of the help sessions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | • The lecture materials consist of a script, the slides and example calculations in Excel. • The lecture materials will be distributed via Moodle two days before each lecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Appropriate literature in addition to the lecture materials will be handed out when required via Moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This course has no prerequisites. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 101-0507-00L | Infrastructure Management 3: Optimisation Tools Does not take place this semester. | 6 credits | 2G | B. T. Adey | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course will provide an introduction to the methods and tools that can be used to determine optimal inspection and intervention strategies and work programs for infrastructure. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Upon successful completion of this course students will be able: - to use preventive maintenance models, such as block replacement, periodic preventive maintenance with minimal repair, and preventive maintenance based on parameter control, to determine when, where and what should be done to maintain infrastructure - to take into consideration future uncertainties in appropriate ways when devising and evaluating monitoring and management strategies for physical infrastructure - to use operation research methods to find optimal solutions to infastructure management problems | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Part 1: Explanation of the principal models of preventative maintenance, including block replacement, periodic group repair, periodic maintenance with minimal repair and age replacement, and when they can be used to determine optimal intervention strategies Part 2: Explanation of preventive maintenance models that are based on parameter control, including Markovian models and opportunistic replacement models Part 3: Explanation of the methods that can be used to take into consideration the future uncertainties in the evaluation of monitoring strategies Part 4: Explanation of how operations research methods can be used to solve typical infrastructure management problems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | A script will be given out at the beginning of the course. Class relevant materials will be distributed electronically before the start of class. A copy of the slides will be handed out at the beginning of each class. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Successful completion of IM1: 101-0579-00 Evaluation tools is a prerequisite for this course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 101-0509-00L | Infrastructure Management 1: Process | 6 credits | 3G | B. T. Adey | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Infrastructure asset management is the process used to ensure that infrastructure provides adequate levels of service for specified periods of time. This course provides an overview of the process, from setting goals to developing intervention programs to analyzing the process itself. It consists of weekly lectures and a group project. Additionally, there is a weekly help session. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | There are a large number of efforts around the world to obtain more net benefits from infrastructure assets. This can be seen through the proliferation of codes and guidelines and the increasing amount of research in road infrastructure asset management. Many of these codes and guidelines and much of the research, however, are focused on only part of the large complex problem of infrastructure asset management. The objective of this course is to provide an overview of the entire infrastructure management process. The high-level process described can be used as a starting point to ensure that infrastructure management is done professionally, efficiently and effectively. It also enables a clear understanding of where computer systems can be used to help automate parts of the process. Students can use this process to help improve the specific infrastructure management processes in the organisations in which they work in the future. More specifically upon completion of the course, students will • understand the main tasks of an infrastructure manager and the complexity of these tasks, • understand the importance of setting goals and constraints in the management of infrastructure, • be able to predict the deterioration of individual assets using discrete states that are often associated with visual inspections, • be able to develop and evaluate simple management strategies for individual infrastructure assets, • be able to develop and evaluate intervention programs that are aligned with their strategies, • understand the principles of guiding projects and evaluating the success of projects, • be able to formally model infrastructure management processes, and • understand the importance of evaluating the infrastructure management process and have a general idea of how to do so. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The weekly lectures are structured as follows: 1 Introduction: An introduction to infrastructure management, with emphasis on the consideration of the benefits and costs of infrastructure to all members of society, and balancing the need for prediction accuracy with analysis effort. The expectations of your throughout the semester, including a description of the project. 2 Positioning infrastructure management in society: As infrastructure plays such an integral part in society, there is considerable need to ensure that infrastructure managers are managing it as best possible. A prominent network regulator explains the role and activities of a network regulator. 3 Setting goals and constraints – To manage infrastructure you need to know what you expect from it in terms of service and how much you are willing to pay for it. We discuss the measures of service for this purpose, as well as the ideas of quantifiable and non-quantifiable benefits, proxies of service, and valuing service. 4 Predicting the future – As infrastructure and our expectations of service from it change over time, these changes need to be included in the justification of management activities. This we discuss the connection between provided service and the physical state of the infrastructure and one way to predict their evolution over time. 5 Help session 1 6 Determining and justifying general interventions - It is advantageous to be able to explain why infrastructure assets need to be maintained, and not simply say that they need to be maintained. This requires explanation of the types of interventions that should be executed and how these interventions will achieve the goals. It also requires explaining which interventions are to be done if it is not possible to do everything due to for example budget constraints. This week we cover how to determine optimal intervention strategies for individual assets, and how to convert these strategies into network level intervention programs. 7 Determining and justifying monitoring - Once it is clear how infrastructure might change over time, and the optimal intervention strategies are determined, you need to explain how you are going to know that these states exist. This requires the construction of monitoring strategies for each of asset. This week we focus on how to develop monitoring strategies that ensure interventions are triggered at the right time. 8 Converting programs to projects / Analysing projects – Once programs are completed and approved, infrastructure managers must create, supervise and analyse projects. This week we focus on this conversion and the supervision and analysis of projects. 9 Help session 2 10 Ensuring good information – Infrastructure management requires consistent and correct information. This is enabled by the development of a good information model. This week we provide an introduction to information models and how they are used in infrastructure management. 11 Ensuring a well-run organization – How people work together affects how well the infrastructure is managed. This week we focus on the development of the human side of the infrastructure management organisation. 12 Describing the IM process – Infrastructure management is a process that is followed continually and improved over time. It should be written down clearly. This week we will concentrate on how this can be done using the formal modelling notation BPMN 2.0. 13 Evaluating the IM process – Infrastructure management processes can always be improved. Good managers acknowledge this, but also have a plan for continual improvement. This week we concentrate on how you can systematically evaluate the infrastructure management process. 14 Help session 3 and submission of project report. The course uses a combination of qualitative and quantitative approaches. The quantitative analysis required in the project requires at least the use of Excel. Some students, however, prefer to use Python or R. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | • The lecture materials consist of handouts, the slides, and example calculations in Excel. • The lecture materials will be distributed via Moodle two days before each lecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Appropriate literature will be handed out when required via Moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This course has no prerequisites. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 101-0509-10L | Network Infrastructure 1  Only for Spatial Development and Infrastructure Systems MSc. | 3 credits | 2G | B. T. Adey, C. Martani | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Spatial planners ensure our built environment optimally meets our future needs. This course explains how spatial planners can evaluate proposed modifications to network infrastructure when there is substantial future uncertainty with respect to requirements, and how to develop implementation plans taking into consideration asset life cycles. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Spatial planners ensure our built environment optimally meets our future needs. This is challenging, as the built environment is a large and complex system, which interacts extensively with the natural environment. Additionally, there is considerable uncertainty with respect to the expectations of the built environment in the future, due to the uncertain environment in which we live, e.g. changing technologies and the changing climate. It is in the face of this complexity and uncertainty that spatial planners need to propose potential improvements and defend them convincingly to a large and diverse set of stakeholders. The objective of this course is to provide spatial planners with an introduction to two essential tools in this regard. The first tool is a methodology to systematically take into consideration the future uncertainty in infrastructure requirements when proposing changes to the built environment. This involves the identification of key uncertainties, modelling their effect on infrastructure requirements and assessing how changes in future needs and the environment may affect future decisions. The second tool is a methodology to systematically estimate the life cycles of infrastructure assets. This methodology can be used together with the state of the existing infrastructure assets to develop optimal implementation plans. More specifically, upon completion of the course students will understand how: • to identify and quantify the service being provided by the built environment • to construct an objective function to be used in the evaluation of proposed modifications to estimate changing societal needs and their potential effect on required infrastructure • to develop concepts for flexible/robust infrastructure alongside traditional infrastructure • to simulate future scenarios to evaluate the costs and effects on the service provided over time by infrastructure • to estimate the service provided by existing infrastructure now and in the future • to determine optimal maintenance strategies for infrastructure • to convert them into optimal intervention programs, which can be used to build strong arguments as to when system modifications should be implemented. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course consists of 9 lectures, 2 projects and 5 help sections. The two hour weekly lecture period is used as follows: 1 Planning infrastructure interventions – This lecture provides an introduction to the course and why it is useful in helping spatial planners propose and evaluate modifications to the built environment. The requirements for successful completion of the course are discussed and the two projects are introduced. 2 Service – Arguments for modifying the built environment are built on meeting the future needs of stakeholders. This week we present how to identify, quantify and value the service provided by the built environment. The measures of service, along with intervention costs are used to construct an objective function to be used in the evaluation of proposed modifications. 3 Changing needs – Trying to modify the built environment to meet future needs, requires estimating them. This week we discuss how to estimate them and their potential effect on required infrastructure. 4 Robust and flexible infrastructure – In the face of large amounts of future uncertainty it is useful to have either robust infrastructure, i.e. infrastructure that meets a large range of possible future needs, or flexible infrastructure, i.e. infrastructure that can be easily modified to meet different possible future needs. This week we discuss the concepts of robustness and flexibility and demonstrate their roles in maximizing the net-benefit of infrastructure. 5 Evaluating robust and flexible infrastructure – Robust and flexible infrastructure sometimes comes with increased costs. Whether or not the costs are worth it depends on a myriad of factors. This week we present a methodology that helps you develop robust and flexible infrastructure and evaluate their costs and benefits over time. 6 Simulating the uncertain future – As a key aspect to evaluating robust and flexible infrastructure is simulating what might happen in the future, this week, we explain how use Monte Carlo simulations and conduct an in class exercise so that you have an enhanced understanding of how it is done. 7 Help sessions 7-9 – We use the lecture periods to answer any questions you might have on project 1. 10 Existing infrastructure – Deciding how to modify infrastructure does not only require thinking about how to meet future needs. It also requires thinking about how the existing infrastructure is likely to provide service in the future. This week, we discuss the connection between provided service and the state of the infrastructure and use a common methodology to predict their evolution over time. 11 Maintenance strategies – It is useful to know the optimal maintenance intervention strategies for infrastructure assets when considering how to modify infrastructure to accommodate future needs, as it is easier to justify expenditures when a maintenance intervention is planned than immediately afterwards, when it is in a like new state. This week we explain how optimal intervention strategies are estimated. 12 Maintenance programs – As planning periods approach, exact decisions need to be made as to which interventions will be executed, taking into consideration network level constraints, such as budgets. This week we demonstrate how the state of assets together with the optimal maintenance strategies and network level constraints can be combined to determine optimal maintenance programs. These programs are used to optimally integrate both maintenance and modification interventions into one intervention program. 13 Help sessions 13 and 14 – We use the lecture periods to answer any questions you might have on project 2. The course uses a combination of qualitative and quantitative approaches. The quantitative analysis required in the project requires at least the use of Excel. Some students, however, prefer to use Python or R. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | • The lecture materials consist of handouts, the slides, and example calculations in Excel. • The lecture materials will be distributed via Moodle two days before each lecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Appropriate literature will be handed out when required via Moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This course has no prerequisites. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 101-0515-AAL | Project Management Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement. Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit. | 2 credits | 4R | B. T. Adey | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | General introduction to the development, the life cycle and the characteristics of projects. Introduction to, and experience with, the methods and tools to help with the preparation, evaluation, organisation, planning, controlling and completion of projects. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | To introduce the methods and tools of project management. To impart knowledge in the areas of project organisation and structure, project planning, resource management, project controlling and on team leadership and team work. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | - From strategic planning to implementation (Project phases, goals, constraints, and feasibility) - Project leadership (Leadership, Teams) - Project organization (Structure) - Project planning (Schedule, cost and resource planning) - Project controlling - Risk and Quality Management - Project completion | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 103-0377-10L | Basics of RE&IS Only for Spatial Development and Infrastructure Systems MSc. | 3 credits | 2G | K. W. Axhausen, B. T. Adey, A. Grêt-Regamey, C. Sailer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course Basics of RE&IS provides essential basic knowledge for the Master's degree program in Spatial Development & Infrastructure Systems and is divided into the three main topics of technical-scientific working, writing & presenting. The students deepen and apply the learned knowledge in the context of three performance elements and one ungraded semester performance. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | - Students will be able to identify, name, and be able to define the content taught. - The students can assess, discuss and explain the necessity, significance and application of the standards in scientific work. - Students will be able to apply the content, implement it in different examples and use it to solve the exercises and the semester assignment. - With the techniques learned in the course, students will be able to analyze and differentiate scientific sources and apply them in their work in a structured way. - The knowledge learned will help students to be able to assess, decide, evaluate and critically evaluate in the context of the semester assignment. -Students are able to systematically compare and present their results in an argumentative manner. -Students are able to produce their results in collaboration with their group and are able to develop, formulate and design a scientific and technical report to complete the assignment. -The students are able to present their results in an engaging presentation together with their project group and use attractive and formally correct visualizations, maps or diagrams for this purpose. -The students thus develop a common understanding with regard to their methodological knowledge and can henceforth work scientifically at an appropriate level. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Students will learn the basics of scientific work and practice their skills within the framework of three performance elements as well as an ungraded semester work, which will be worked out in groups of two to three students. In the first half of the semester, students will learn the theoretical basics and apply and understand these in the context of the exercises (=performance elements) in groups of maximum of two. The final ungraded semester exercise in the second part of the course, students will work in groups of maximum two on an assignment, which they will document and communicate in the form of a written report and a final presentation at the end of the course. -Exercise 1: Citations & Referencing 20% -Exercise 2: Searching, Reading and Summarizing 20% -Exercise 3: Maps, Graphs & Visualizations 20% -Exercise 4: Review 20% -Presentation of review 20% Students will be supervised by at least three assistants and one professor throughout the course. The main course lead changes periodically between the following RE&IS chairs: Infrastructure Management (IM), Transportation Systems (TS), Traffic Engineering (SVT), Transport Planning (VPL), Spatial Development and Urban Policy (SPUR), Planning of Landscape and Urban Systems (PLUS) and Spatial Transformation Laboratories (STL). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | All documents relevant for the course (slides, literature, further links, etc.) are provided centrally via the moddle platform. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | American Psychological Association (APA) (2010) Publication Manual of the American Psychological Association, 6th edition, APA, Washington, D.C. Axhausen, K.W. (2016) Style Guide for Student Dissertations, IVT, ETH Zürich, Zürich (available as download under learning materials) Backhaus, N. and R. Tuor (2008): Leitfaden für wissenschaftliches Arbeiten, 7. überarbeitete und ergänzte Auflage. Schriftenreihe Humangeographie 18, Geographisches Institut der Universität Zürich, Zürich. ZürichChapman, M. and C. Wykes (1996) Plain Figures, HM Stationary Office, London. ETH (2017) Citation etiquette: How to handle the intellectual property of others, ETH, ETH Zürich, Zürich (last retrieved 29.11.2017) Modern Language Association of America (MLA) (2016) MLA Handbook, 8th edition, MLA, New York. Monmonier, M. (1991) How to lie with maps, University of Chicago Press, Chicago. Tufte, E. R. (2001) The Visual Display of Quantitative Information, Graphics Press USA Wilkinson, L. (1999) The Grammar of Graphics, Springer, Berlin. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||