151-8102-00L Research Beyond the Lab: Open Science and Research Methods for a Global Engineer
| Semester | Frühjahrssemester 2022 |
| Dozierende | E. Tilley, L. Schöbitz |
| Periodizität | jährlich wiederkehrende Veranstaltung |
| Lehrsprache | Englisch |
Lehrveranstaltungen
| Nummer | Titel | Umfang | Dozierende | ||||
|---|---|---|---|---|---|---|---|
| 151-8102-00 G | Research Beyond the Lab: Open Science and Research Methods for a Global Engineer | 3 Std. |
| E. Tilley, L. Schöbitz |
Katalogdaten
| Kurzbeschreibung | From the proverbial 'field' to the heart of Zurich, engineering research is guided by the same fundamental principles. With the goal to improve the human condition with technology, we designed this course to teach learners how to conduct a research project out of the lab, and apply open science principles to their data analysis projects. | |||||||||||||||
| Lernziel | By the end of the course, learners will be able to: • articulate a foundational understanding of 'research' • identify and implement an appropriate research paradigm for a given study • identify the importance of, and challenges related to research ethics • create a SMART research question • articulate appropriate research aims and objectives for specific questions • create survey questions using a variety of question types and understand the limitations and uses for each type of survey question • apply 12 principles for data organisation in spreadsheets in the layout of a collected dataset • clone a repository from GitHub into the RStudio Cloud and can use the RStudio IDE to commit and push changes to GitHub • create a repository on GitHub and start a new R Project using the RStudio IDE in the RStudio Cloud • can use three different ways of getting support in solving coding problems online • can apply 10 functions from the dplyr R Package to generate a subset of data for use in a table or plot • use GitHub to publish their Course project report as a website • can use exported references from Zotero in Better BibTex Format to generate an automated reference list • cross-reference figures and tables within an R Markdown file | |||||||||||||||
| Inhalt | Over the course of the semester, students will develop a research project and learn the necessary qualitative and quantitative methods required to collect data from people. We will use tidyverse R packages to work with data, and git and GitHub as tools for version control and collaboration. By the end of the course, students will have a complete overview of how a typical field-based research project is designed, implemented and communicated. Content will be delivered through lectures and tutorials. The success of the course will depend on the student's own willingness to engage with local challenges, stakeholders, citizens and agencies in order to develop a comprehensive body of work that answers a relevant, local problem. Topics covered include: • Theory and foundations of field-based Research • Research Ethics: your role as a researcher, data privacy, ethical approval processes • Qualitative and Quantitative research methods • Research Design and implications for analysis • Data Collection using digital tools • Version control and collaboration with git and GitHub • Exploratory analysis with tidyverse R packages for data visualisation and communication • Concept of tidy data and tidyverse R packages for data transformation | |||||||||||||||
| Skript | Distributed during the course. | |||||||||||||||
| Voraussetzungen / Besonderes | This course does not have any specific prerequisites. No prior experience of working with a programming language is required, nor do we expect statistical knowledge beyond basic summary statistics taught in high school environments. Note on accessibility: Although there are 2 weeks of data collection outside of the classroom, we do not want this, or any other component of the hybrid-style course to be a barrier to anyone who is interested in enrolling. If you have a specific concern about your ability to participate, please contact us, so we can discuss strategies to ensure that you are included. | |||||||||||||||
Kompetenzen |
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Leistungskontrolle
| Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird) | |
Leistungskontrolle als Semesterkurs | |
| ECTS Kreditpunkte | 4 KP |
| Prüfende | E. Tilley, L. Schöbitz |
| Form | Semesterendprüfung |
| Prüfungssprache | Englisch |
| Repetition | Es wird ein Repetitionstermin in den ersten zwei Wochen des unmittelbar nachfolgenden Semesters angeboten. |
| Prüfungsmodus | schriftlich 120 Minuten |
| Zusatzinformation zum Prüfungsmodus | There is a final written exam, which assesses the technical skills taught during the course. It contains programming exercises using the R programming language. The success of the exam depends on the effort put into the compulsory continuous performance assessment. The performance assessment consists of 10 weekly homework assignments worth 20% and a course project during the second half of the course (from Week 7) worth 30%. The course project is a hands-on research project that requires team work and concludes with the submission of a report one week after the end of of final lecture. The report is assessed for its technical parts and the intellectual framing of the results. Grading scheme in summary: Final written exam: 50% Compulsory continuous performance assessment: 50%, of which Homework: 20% (n = 10) Course project: 30%, of which Technical bits of submitted report: 20% Intellectual framing of results: 10% |
| Hilfsmittel schriftlich | Any online and hardcopy resources can be used during the final exam. |
Lernmaterialien
| Hauptlink | rbtl course website |
| Es werden nur die öffentlichen Lernmaterialien aufgeführt. | |
Gruppen
| Keine Informationen zu Gruppen vorhanden. |
Einschränkungen
| Plätze | Maximal 25 |
| Warteliste | Bis 21.02.2022 |