Adina Rom: Katalogdaten im Herbstsemester 2022
|Frau Dr. Adina Rom
Professur für Entwicklungsökonomie
ETH Zürich, CLD B 6
|+41 44 633 85 65
|Geistes-, Sozial- und Staatswissenschaften
|ETH4D PhD Seminar: Research for Development
Number of participants limited to 15.
|I. Günther, A. Rom, E. Tilley
|Doctoral candidates from all ETH departments, whose research is related to global sustainable development issues, and conducting research in low- or middle-income countries are invited to give a presentation about their on-going work and discuss their doctoral project with a diverse group of researchers.
|Doctoral students are able to present their doctoral project to an interdisciplinary audience and to respond to questions within a wider global sustainable development context.
|Make Your Own Short Film about Global Development Research
|In this workshop, students will learn how to create a short film about their research related to global sustainable development using their smartphones They will also reflect on the power of films to reproduce or break prejudices and stereotypes in global development. Short theoretical inputs will be combined with practical work on students' own video projects.
|Students know how to tell an interesting story about their research and how to shoot and cut a short movie using conventional smartphones and laptops.
Students know strategies to ensure that the stories they tell do not reproduce stereotypes.
|In this hands-on workshop, students will create a short film about their research in three steps: First, they learn how to choose a topic and tell an interesting story about their research. There will be an opportunity for critical reflection about the danger of reproducing stereotypes and the opportunity of using images to empower people. Second, they will learn how to shoot a short film using a smartphone and what apps and tools can increase the quality of the film. Third, students learn how to cut videos. They receive an introduction to Premiere Pro. Finally, there will be a “Mini Film Festival” where students show their work and receive feedback. The course will be taught by the videographer Katharina Deuber.
|Voraussetzungen / Besonderes
|• To participate in the course, students have to bring their own smartphone and need access to a video editing software on their computers/phones (more detailed information will follow before the course)
• Preference is given to doctoral students working on issues related to global development.
|Technology and Policy Analysis
|T. Schmidt, E. Ash, F. M. Egli, R. Garrett, M. Leese, A. Rom, B. Steffen
|Technologies substantially affect the way we live and how our societies function. Technological change, i.e. the innovation and diffusion of new technologies, is a fundamental driver of economic growth but can also have detrimental side effects. This module introduces methods to assess technology-related policy alternatives and to analyse how policies affect technological changes and society.
Participants understand (1) what ex ante and ex post policy impact analysis is, (2) in what forms and with what methods they can be undertaken, (3) why they are important for evidence-based policy-making.
Analysis of Policy and Technology Options:
Participants understand (1) how to perform policy analyses related to technology; (2) a policy problem and the rationale for policy intervention; (3) how to select appropriate impact categories and methods to address a policy problem through policy analysis; (4) how to assess policy alternatives, using various ex ante policy analysis methods; (5) and how to communicate the results of the analysis.
Evaluation of Policy Outcomes:
Participants understand (1) when and why policy outcomes can be evaluated based on observational or experimental methods, (2) basic methods for evaluating policy outcomes (e.g. causal inference methods and field experiments), (3) how to apply concepts and methods of policy outcome evaluation to specific cases of interest.
Big Data Approaches to Policy Analysis:
Participants understand (1) why "big data" techniques for making policy-relevant assessments and predictions are useful, and under what conditions, (2) key techniques in this area, such as procuring big datasets; pre-processing and dimension reduction of massive datasets for tractable computation; machine learning for predicting outcomes; interpreting machine learning model predictions to understand what is going on inside the black box; data visualization including interactive web apps.
|Course materials can be found on Moodle.