I have been teaching at the undergraduate and postgraduate levels since 2014; since 2018, my responsibilities have included curriculum design, course development, coordination and the supervision of multiple teaching teams.
Between 2019 and 2023, I have been coordinating three courses in the Bachelor of Communication (Digital and Social Media) offered by the School of Communication of the University of Technology Sydney, including Working with Data and Code and Digital Media Metrics. In 2022, I designed the postgraduate short course Application Implementation with Microsoft Dynamics.
In 2023, I moved to the School of Social and Political Sciences at the University of Sydney, where I have been designing, coordinating and delivering three courses: Data Analytics in the Social Sciences at the undergraduate level and Research Design and Data Analytics for Social Research at the post-graduate level.
My teaching experience in quantitative methods includes statistical and data analysis (with R), research methods, data visualisation (with R and Tableau), and coding (with R and Python) delivered to diverse audiences, including undergraduate, postgraduate and research students but also academics and professionals. I have designed and delivered quantitative research methods courses and workshops to postgraduate students and academic staff, including social media analysis, network analysis with R, and quantitative text analysis with R. In 2018, I designed a course on Topic models in R and delivered it during the Digital Humanities Downunder summer school to an audience of about 50 research students, postdoctoral researchers and academic staff. In 2022, I designed and delivered a one-day Text mining and analysis workshop during the ANZCA Digital Methods Winter School.
I have experience coordinating large courses (up to 300 students) and recruiting, training and supervising teaching assistants. My coordinating responsibilities have included managing teaching staff, marking, recruiting students, providing pastoral care for students, defending academic integrity against plagiarism and cheating, and supervising graduate and postgraduate research students (I am currently supervising one PhD student and one Honour student). In 2020 and 2021, I gained significant experience transitioning courses and materials to an online-only delivery mode using Canvas. I have used Canvas and other educational technologies (e.g. Padlet, Menti and the Student Relationship Engagement System) ever since.
My teaching experience, combined with my research experience, gives me the ability to teach quantitative methods, including computational methods and advanced research methods to a wide range of cohorts in various fields of study and with a range of numerical and computer skills. For example, my experience teaching statistical elements and computer programming to students in the Bachelor of Communication program at UTS and at the School of Social and Political at the University of Sydney helped me develop the capacity to simplify complex numerical concepts with the support of curated visualisations.
I have a genuine passion for developing digital partnerships in learning and teaching, particularly for introducing technology-enhanced pedagogy and innovative digital tools. In the design of my curricula, I also embrace the Active Learning principle so as to recurrently engage students with hands-on in-class activities to apply the information they just received.
My accomplishments in this area over the past two years include the following:
I developed a teaching program for Python using Jupyter Notebook, one of the most popular computational tools among data scientists. This allows students to access a Python interpreter easily from their browser to execute interactive notebooks without the need to install dedicated software on their computer, an error-prone process that can potentially discourage students.
To support the coupling of both statistical concepts and R in the learning experience, I designed a series of short, hands-on exercises for practising statistical concepts that students encounter in data analytics units and applying them to real-world problems. These exercises are created with the open-source R package “exams”, which allows for seamless portability across and incorporation with different Learning management systems (LMS), and are dynamically generated from a template, allowing for random variations of the numerical values and questions.
I designed and implemented a full-fledged social media application to create a realistic social media “sandpit” where students can not only complete tasks requiring a reactive digital audience but also gain access to complete social media datasets.
I designed a series of assessment tasks based on simulated data, allowing students to engage with realistic and large-scale demographics surveys, opinion surveys and social media records. These types of personal information is often unavailable for teaching purposes because of ethical considerations or cost. Based on actual census and survey records, I coded generative functions to create thousands (and potentially millions) of individuals with realistic interests, opinions, and demographic traits.
I am actively maintaining a website with learning resources to help researchers access the Twitter API using R.