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Teaching Portfolio

What have I been teaching in recent years?

Regularly taught courses

Aya Kachi's teaching portfolio at the University of Basel.

Course evaluation

Of courses regularly taught at the University of Basel.


Evaluation criteria:

  1. Overall, the course was [Very bad (1) - Very good (6)]

  2. I would recommend this course to other students. [Totally disagree (1)  - Agree completely (6)]

  3. The lecturer structures the course well and identifies the objectives clearly.

  4. I think that the lecturer is committed.

  5. The material that is provided  is helpful.

  6. The tutorials promote comprehension of the subject matter.

  7. The course has promoted my ability to structure and present a topic.

  8. The course has promoted my ability to discuss.

The graph is a summary of pooled data (all courses, Fall 2015 - Spring 2021, N = 489).

Course description

International Political Economy of Energy and Climate Policy



Survey Research Methodology



Bachelor's Thesis Seminar: Energy and Climate Policy



Public Opinion and Science Communication



Science Communication in Action



Other courses taught

Irregular courses and workshops

International Political Economy of Energy and Climate Policy

Based on studies in International Political Economy, this course first identifies and provides an overview of relevant policy issues, actors, and institutions in the context of global governance of energy and climate policy issues. In particular, the course aims to gather a better understanding of political and economic dilemmas associated with domestic and international cooperation on energy and climate policy. Along the course, we also learn what constitutes ``good" or ``legitimate" transnational and international governance in terms of participation, rule-making, monitoring, and enforcement. The course should be of interest, particularly - but not limited - to students interested in international energy and climate policy-making and academic research involving international cooperation. Active class participation is essential for completing the course successfully. It is not a strict requirement, but I assume students have a basic understanding of econometrics (regressions) and game theory.

Learning activity

  1. Active participation and a self-assessment report on participation.

  2. One group case study submission in Session 2.

  3. Quizzes (3 or 4 comprehension tests) during the semester.

  4. Final assignment involving data. (You are allowed to use R, Python, STATA, or Excel.)

Bachelor's Thesis Seminar: Energy and Climate Policy

The primary purpose of this seminar is to guide you through the process of planning and completing your bachelor's thesis. Students in this seminar will work on topics that are related to energy and climate policy. Topics related to broader sustainability issues can be acceptable. Successful theses will engage in quantitative analyses – either empirical (data analysis) or formal theoretical (game theoretic) analyses. Those who want to conduct qualitative analyses should find a supervisor who is trained in qualitative methods, which is not us.


At the beginning of the seminar, students will first identify relevant literatures and develop a research question by themselves. During the first two kick-of meetings, we go over potential topics (but not research questions) in the area of energy and climate policy as well as an ideal thesis structure. This is why your attendance at these meetings are mandatory. Identifying an important and interesting research question requires a great amount of effort, but it is also a creative and exciting process. I welcome students who are motivated to engage in this process and those who are strongly interested in these topics.


As a formal requirement of this seminar, we accept theses that attempt to answer research questions only by quantitative analyses. By quantitative analyses, we mean either (i) formal theory (game theory, social choice theory) or (ii) quantitative data analyses (such as regressions). Generally speaking, it is not easy to learn a new analytical tool (e.g., game theory models or regression models) at the same time as you work on your thesis during the semester. (There have been a few impressive exceptions in the past!) Therefore, you are expected to join the seminar already with at least one quantitative analytical method at hand.

During your study at the university, you can learn many things. However, there are not a plenty of opportunities where you can gain deep and thorough knowledge about a single topic. I hope that this thesis seminar offers you such an opportunity and, at the end of the semester, you can boast with confidence (and evidence) that you have developed good knowledge on certain issues related to energy and climate policy.

Science Communication in Action

In short

In this colloquium, first, we are going to discuss why science communication really matters and what main challenges are. We are then going to discuss why we tend to face various challenges in communicating scientific findings. In doing so, we will look into the various incentives (interests) of many involved actors, such as professional researchers, media, policymakers, industry, research funding agencies, etc. (Don’t worry if you don’t understand why they are relevant yet.) We will also shed light on the fact that the practice of science always involves some uncertainty and that related technologies are advancing faster and faster, which make the communication even more difficult. And yet, scientific community is expected more and more to engage with society and share their findings in an accessible manner.

Through our discussions, we will try to understand why all these factors combined pose great chal- lenges in communicating (sending, receiving, and interpreting) science. In short, understanding such mechanisms through class discussion is the main point of this colloquium. Eventually, it has something to do with our mindset, too.

2022 Guest speakers 

  • Dr. Emma Hodcroft (Institute of Social and Preventive Medicine, University of Bern)

  • Dr. Jens Engelhardt (Bain & Company)

  • Prof. Rolf Weder, Prof. Kurt Schmidheiny, Prof. Pascal Gantenbein (Deans of the WWZ)

Learning activity

  1. Attendance and active participation (discussion)

  2. Participation in online surveys

  3. Group work in class

  4. Final essay

A longer story

“Science communication”?

When we say science communication, we often imagine a situation where scientists attempt to deliver technical information to the public and policymakers. In this course, we will use a broader definition of science communication; we will also consider many other situations where we need to communicate technical information such as research findings and policy designs in various contexts.


For example, when professors (scientists) teach technical topics to students, that is already a type of science communication. Scientists also need to discuss their research findings among each other, both within and between different disciplines. It is also scientists’ responsibility to inform the public, policymakers, and media about their findings. Citizens, too, debate on technologies, policies, and products citing scientific evidence they have seen somewhere (!). Political parties and individual politicians might try to talk citizens into their preferred policies using evidence they got from scientists. Similarly, even product marketing is an effort by companies to lure consumers into buying their products. Here too, companies use various research findings to illuminate the products’ advantages. Similar communications happen also within firms and governments when the staff reports their analyses to CEOs and managers.


Science communication as such is not only a task for professional researchers. In fact, nearly every phase of our life involves different types of science communication.

Good communication and information improve our decision-making

Now, why is it important for us to think about science communication? It’s because successful communication gives us relevant and accurate information about complex topics. Accurate infor- mation in turn helps us make better decisions in life. In other words, good information should help us choose behaviors, products, and policies that are better aligned with our goals and preferences! (Shouldn’t they?)

For example, imagine we have a clear preference for achieving good health, which is obviously a meaningful goal. However, if health experts do not communicate possible treatments effectively, or if we don’t have the necessary skills for understanding the evidence provided by the health experts, we can end up choosing a treatment that does not improve our health even though we wanted to.

If you are a policymaker trying to achieve a certain policy goal (e.g., reduce poverty), again, you need to understand the scientific findings that tend to connect your policy goal to the right policy designs.

Same goes for any decisions about personal finance, career, products, lifestyle, and so on. This is why a good communication -both as a sender and receiver of the information- has a significant influence on our life and happiness.

Bad communication and information can harm, and they are everywhere

But we all know that things are not that simple. We are constantly surrounded by both accu- rate and inaccurate information. You might have heard of the expressions, “misinformation,” “disinformation,” and sometimes “malinformaion.”

The crucial point here is that even with our best intention to bring technical and useful information as accurately as possible, there are still many reasons we end up providing wrong information or interpret the information inaccurately. Is there something we can do about it?

This colloquium

In this colloquium, we are going to discuss why we tend to face these various challenges in commu- nicating scientific findings. In doing so, we will look into the heterogeneous incentives (interests) of various involved actors, such as professional researchers, media, policymakers, industry, re- search funding agencies, etc. (Don’t worry if you don’t understand why they are relevant yet.) We will also shed light on the fact that the practice of science always involves some uncertainty and that related technologies are advancing faster and faster, which make the communication even more difficult. And yet, scientific community is expected more and more to engage with society and share their findings in an accessible manner.

Through our discussions, we will try to understand why all these factors combined pose great chal- lenges in communicating (sending, receiving, and interpreting) science. In short, understanding such mechanisms through class discussion is the main point of this colloquium. Eventually, it has something to do with our mindset, too.

Survey Research Methodology

In the current academic year, Prof. Daniel Auer is replacing me with his fantastic course module. The following is a course description of my version of the course.

The course is an applied methods colloquium taught at a master’s degree level. The main goal is to prepare us for conducting simple research and writing a short version of an academic report using a survey or survey- experiment method. The course covers four major areas: (1) the nature of the survey response, including the typical psychology of attitude expressions, issues of question wording and context, and social desirability pressures; (2) general topics in quantitative research, including random and systematic measurement errors, and the logic of causal analysis; (3) implementing online surveys with convenience and population-based samples, and (4) analyzing and interpreting treatment effects (for survey experiments) and learn how/what to report.

In the latter half of the colloquium (for full-module students – see Section 4), we, the whole class collectively, draft a survey (or a survey experiment depending on the year’s topic) and field it with an appropriate sample of respondents. The class survey project’s topic will likely be within the realm of current energy-, environment-, sustainability-, or AI-related issues. (I will explain this in the first session.) After all, if we want to learn a method in the most practical way, which is to learn by doing, we need to agree on a single topic relevant to many of us. However, this should not prevent you from learning survey research methods even when your research interests lie outside of these topics. For instance, you might be interested in studying opinion or attitude formation in the context of marketing or international trade. I strongly encourage you to reflect on the methodology and the topics we cover in class with your favorite research context. If you have questions and thoughts about survey issues in your research area, please do not hesitate to share or ask in- and outside the class. The chances are that some others in the class would also be interested in such issues.

Survey-based data collection enables various interesting empirical studies. For example, public opinion stud- ies investigate simple but fundamental puzzles around us. Why did (or did not) somebody vote/think/behave in a certain way? Why did this person choose a particular product among hundreds of options? Why do we hold different perceptions on the same topic/product/policy? Another example of increasing salience is an empirical study that analyzes sources of varying perceptions by experts, e.g., politicians, interest groups, and industry actors. Here, the respondents would answer your questions not as individual voters but as ac- tors with specific expert knowledge. Survey research turns all these casual but essential questions into more elegant and scientific statements that we can test empirically. It allows us to test these mechanisms behind opinion and attitude formation. As people’s minds are complex, we have to be very careful in designing and wording surveys to ensure that what we ask is measuring what we intend to measure. We will learn “how to” by doing it. Welcome to this exciting field.

Next, I will mention some technical aspects. For learning about and conducting surveys and survey experi- ments, we will use Qualtrics as a survey software and R for computing simple statistics (e.g., for estimating experimental treatment effects). The course “Energy and Climate Policy–Citizens’ Perspectives” (VV-Nr: 43030, offered in HS) is not a strict requirement but is highly recommended before taking this course. Basic knowledge of sampling, statistics, and regressions (e.g., OLS and logit) would be beneficial. If you have concerns about these prerequisites, do not hesitate to talk to me at the beginning of the semester.

Finally, I hope that you enjoy this creative process of survey research. The collective work in class naturally requires some coordination effort and hard work also outside of the course, but cooperation and sometimes compromises are also the very reality of our research life. They are all part of our learning in this colloquium.

Public Opinion and Science Communication

In this course, we learn essential topics and empirical methods in the (sub)fields of public opinion and science communication. Formerly, we called this course "Energy and Climate Policy: Citizens' Perceptions."


So-called public opinion scholars have been intrigued by questions like why individuals hold different perceptions about policies, technologies, or products and how these perceptions might influence their support (acceptance) for these objects. The field of science communication (or the science of science communication) has zoomed in to one of the trickiest determinants of people's perceptions and decision-making: people's knowledge, information-seeking behavior, and their "interactions" with scientific evidence. As you can easily imagine, to understand the nature of such communication, we must also consider how scientific findings are "chosen," understood, interpreted, and reported by some other actors as well, such as policy proposers, industry, and the media. As much as we can within a limited amount of time, we will touch upon these issues, too.

Learning activity

  1. Active participation and a self-assessment report on participation

  2. An article summary (giving a presentation and leading class discussions in group)

  3. Business case solving (in group, using Harvard Business Case)


Course structure

(1) In the first part, we draw on the public opinion literature, specifically in the energy and environmental policy domain. Based on the literature, we will learn what influences people's beliefs and attitudes. This segment will pay significant attention to the empirical methodologies used in the literature, mainly survey and survey experiment methods. 


(2) In the second (and a shorter) segment, we will move to the topic of the science of science communication. Like the first segment, we rely on the literature to learn what tends to prevent people from using scientific evidence to make well-informed decisions. In this segment, our substantive focus goes beyond energy and environment (simply due to the diverse focus of the subfield). 


(3) During the last few weeks, we will shift our gear and work on business cases (group work). This activity also serves as your final assignment (project) for the course. Each group will choose a business case to work on (from a selection of established cases published by Harvard Business Publishing: Contrary to our earlier focus on policies, now the relevant decision-making of our emphasis is business-related decisions. However, the way we will use Harvard Business Cases will be slightly "exotic." Instead of evaluating a person's or firm's financial and strategic motives, we will evaluate whether their (the protagonists') decisions could have been improved if they used different strategies to understand their stakeholders' reactions (opinions/perceptions) or communication with them. Our purpose is to apply what we learned from the literature to various decision-making cases in the real world.  ​

Other courses

  • Spatial and Spatio-temporal Quantitative Analysis (June 22, 2021), Host: University of Geneva, Switzerland

Thesis seminar
Other teaching
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