Search result: Catalogue data in Autumn Semester 2021
Science, Technology, and Policy Master  | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 Social Sciences | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 860-0003-00L | Cornerstone Science, Technology, and Policy  Only for Science, Technology, and Policy MSc and PhD. ISTP-PhD students please register via the Study Administration. | O | 2 credits | 1S | T. Bernauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course introduces students to the MSc STP programme. It provides a general introduction to the study of STP. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This course introduces students to the MSc program in two ways. First, it provides a general introduction to the study of STP. Second, it exposes students to various complex policy problems and ways and means of coming up with proposals for and assessments of policy options. In a reading workshop, students will learn how to improve their skills in reading and understanding scientific papers in the English language. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | - Introduction to Science, Technology and Policy. - Reading Workshop: Reading and understanding scientific papers in English language. A detailled programme will be sent out to the participants in advance to the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Literature and references will be available on Moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 860-0004-00L | Bridging Science, Technology, and Policy Only for Science, Technology, and Policy MSc and PhD. ISTP-PhD students please register via the Study Administration. | O | 3 credits | 2S | T. Bernauer, T. Schmidt | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course focuses on technological innovations from the beginning of humanity through the industrial revolution up until today. It provides students with a deeper understanding of the factors that drive technological innovations, and the roles government policies, society, science, and industry play in this regard. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This course picks up on the ISTP Cornerstone Science, Technology and Policy course and goes into greater depth on issues covered in that course, as well as additional issues where science and technology are among the causes of societal challenges but can also help in finding solutions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Week 1: no class because of ISTP Cornerstone Science, Technology and Policy course Week 2: technology & society in historical perspective - technological innovations up to the industrial revolution Week 3: technology & society in historical perspective - technological innovations during the industrial revolution - engines & electricity Week 4: technology & society in historical perspective - from the industrial revolution to modernity - mobility and transport (railroads, ships, cars, airplanes, space) Week 5: food production: the green revolutions. Week 6: microelectronics, computing & the internet Week 7: life sciences: pharmaceuticals & diagnostic technology Week 8: energy: primary fuels, renewables, networks Week 9: automation: self-driving cars & trains, drones Week 10: communication & Big Data: semiconductors and software Week 11: military & security issues associated with technological innovation Week 12: possible futures (1): nuclear fusion, geoengineering Week 13: possible Future (2): information, communication, robotics, synthetic biology, nanotech, quantum computing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Skript: Course materials will be available on moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Literature: Literature and references will be available on Moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 860-0005-00L | Colloquium Science, Technology, and Policy (HS) Only for Science, Technology, and Policy MSc and PhD. | O | 1 credit | 2K | T. Schmidt, T. Bernauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Presentations by invited guest speakers from academia and practice/policy. Students are assigned to play a leading role in the discussion and write a report on the respective event. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Presentations by invited guest speakers from academia and practice/policy. Students are assigned to play a leading role in the discussion and write a report on the respective event. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | See the program on the ISTP website: http://www.istp.ethz.ch/events/colloquium.html The series is open to the public. Lectures last about 60 minutes followed by an open discussion. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | open to anyone from ETH | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 860-0031-00L | Policy Analysis Only for Science, Technology, and Policy MSc. | O | 4 credits | 2V | T. Schmidt, B. Steffen, F. M. Egli | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course Policy Analysis 1 will introduce important concepts and methods for ex-ante policy analysis. It will mostly focus on the policy content (vis-à-vis the policy process). We will primarily discuss quantitative methods. The course will contain several practical assignments in which students have to apply the concepts and methods studied. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students should gain the skill to perform policy analyses independently. To this end, students will be enabled to understand a policy problem and the rationale for policy intervention; to select appropriate impact categories and methods to address a policy problem through policy analysis; to assess policy alternatives, using various ex-ante policy analysis methods; and to communicate the results of the analysis. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course has four major topics: •Rationales for public policy in Science and Technology •Impact of policies on firms and investors •Impacts of policies on socio-technical systems •Impact of policies on society at large | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 363-0503-00L | Principles of Microeconomics GESS (Science in Perspective): This lecture is for MSc students only. BSc students register for 363-1109-00L Einführung in die Mikroökonomie. | O | 3 credits | 2G | M. Filippini | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course introduces basic principles, problems and approaches of microeconomics. This provides the students with reflective and contextual knowledge on how societies use scarce resources to produce goods and services and ensure a (fair) distribution. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The learning objectives of the course are: (1) Students must be able to discuss basic principles, problems and approaches in microeconomics. (2) Students can analyse and explain simple economic principles in a market using supply and demand graphs. (3) Students can contrast different market structures and describe firm and consumer behaviour. (4) Students can identify market failures such as externalities related to market activities and illustrate how these affect the economy as a whole. (5) Students can also recognize behavioural failures within a market and discuss basic concepts related to behavioural economics. (6) Students can apply simple mathematical concepts on economic problems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The resources on our planet are finite. The discipline of microeconomics therefore deals with the question of how society can use scarce resources to produce goods and services and ensure a (fair) distribution. In particular, microeconomics deals with the behaviour of consumers and firms in different market forms. Economic considerations and discussions are not part of classical engineering and science study programme. Thus, the goal of the lecture "Principles of Microeconomics" is to teach students how economic thinking and argumentation works. The course should help the students to look at the contents of their own studies from a different perspective and to be able to critically reflect on economic problems discussed in the society. Topics covered by the course are: - Supply and demand - Consumer demand: neoclassical and behavioural perspective - Cost of production: neoclassical and behavioural perspective - Welfare economics, deadweight losses - Governmental policies - Market failures, common resources and public goods - Public sector, tax system - Market forms (competitive, monopolistic, monopolistic competitive, oligopolistic) - International trade | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture notes, exercises and reference material can be downloaded from Moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | N. Gregory Mankiw and Mark P. Taylor (2020), "Economics", 5th edition, South-Western Cengage Learning. The book can also be used for the course 'Principles of Macroeconomics' (Sturm) For students taking only the course 'Principles of Microeconomics' there is a shorter version of the same book: N. Gregory Mankiw and Mark P. Taylor (2020), "Microeconomics", 5th edition, South-Western Cengage Learning. Complementary: R. Pindyck and D. Rubinfeld (2018), "Microeconomics", 9th edition, Pearson Education. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | GESS (Science in Perspective): This lecture is for MSc students only. BSc students register for 363-1109-00L Einführung in die Mikroökonomie. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 860-0041-00L | Statistics 1 Only for Science, Technology and Policy MSc. | O | 4 credits | 2V | E. K. Smith | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course covers the necessary fundamentals for the use of statistics to understand policy. Theoretically the course will provide a survey of foundational concepts and techniques statistics and mathematics. The applied part of the course will focus on implementing these techniques in R, as well as the practical skills required to develop their own data based research projects. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Gain a familiarity with foundational concepts and techniques in statistics, and be able to apply these to new problems. Be comfortable independently conducting a variety of tasks in R, such as data cleaning, visualisation and analysis. Produce summaries of statistical analyses that non-specialists can understand. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | This course introduces students to the necessary fundamentals of statistics, and its application, to understand policy. Theoretically the course will provide a survey of foundational concepts and techniques statistics and mathematics. The applied part of the course will focus on implementing these techniques in R, as well as developing the practical skills in the language required to be able to independently conduct data based research projects. By doing so, students will gain a familiarity with foundational concepts and techniques in statistics, and be able to apply these to new problems. Students will also develop the requisite skills to be able to independently conduct a variety of tasks in R, such as data cleaning, visualisation and analysis. Finally, students will be able to produce summaries of statistical analyses that non-specialists can understand. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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