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Published:
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Teaching portfolio
Here I make public a teaching portfolio that summarises a coherent set of materials representing my view of teaching as a scholarly activity, my professional experience and pedagogical training as well as some examples of course design.
Teaching resources
This section contains a variety of materials that I have used, developed and adapted for my seminars on research methods, agent based models and data collection and processing.
Module 1: Research methods using R
Lab 1: T-test and Simple linear regression. Download ipynb file
Lab 2: One-way ANOVA. Download ipynb file
Lab 3: Multiple regression. Download ipynb file
Module 2: Twitter data collection and analysis using R
Lab 4: Data collection and co-ocurrence analysis.
Module 3: Agent based models
Lab 5: Building a simple agent based model
Lab 6: Generating data using a cultral evolutionary model. In this lab we will use a version of the model published in Cognitive Science:
Other external resources:
Research methods
Linear models and linear mixed effects models in R
Agent-based modelling
A Short Tutorial on Agent Based Modeling in Python
Data collection and analysis
Digital Methods Initiative Twitter Capture and Analysis Toolset