How to motivate students

Motivating students is a common problem in econometrics. Often this would have happened in lectures, now these are online. You need to focus on setting interesting problems at the outset. In addition to this it is worthwhile to point out to students how valuable these skills are in the job market (if this message can be conveyed by employers or alumni it will carry more credibility than if it comes from the lecturer).

Below are some examples of posing students interesting challenges.

Go to the Discussion Board on Piazza - (Access Code: C19 in case you log in for the first time) and share any good ways of motivating your students to put in the hours required to earn a serious coding batch.

Student-Generated Data

Guglielmo Volpe, City, University of London

In our quantitative modules we engage students with data to support their understanding of theory, appreciate applied work and develop important analytical skills. In this video I suggest that, perhaps, one effective way of engaging students while learning online is to ‘delegate’ to them the generation of at least some of the data used in your teaching and assessment. There are advantages and disadvantages of opting for such an approach. A major advantage is that students are actively involved in the generation of the dataset and they come to learn and appreciate the challenges that this involves. A drawback is that students need to be regularly reminded to collect and add the data to the shared dataset. Inconsistencies in the recording of the data is often a topic for discussion when the time for analysing the dataset comes. However, handing the ‘ownership’ of the data generation process to students empowers them and is an effective way of making them appreciate the challenges of putting together reliable and accurate data.

The video has been shot by using a screen-recorder software called Camtasia. After recording the video, I used some of the software’s editing functions to include some annotations and to zoom in and out of some sections of the screen.

Use big problems

Here is an example how the first lecture in a first econometrics course starts with the Card and Krueger examination of the minimum wage effect on employment.

Replication Studies

Steve Cook, Swansea University

This section considers the use of replication in the teaching of quantitative modules. The delivery and assessment of econometrics and forecasting modules are considered to illustrate the benefits of replication.  

Replication is considered in two forms. First, the replication of published research is explored to introduce research-led teaching in a 'full sense' by placing students in the position of authors rather than simply requesting they read published work. Second, the use of case studies on the Economics Network Ideas Bank is discussed.  Replication is presented as means of: addressing published concerns in relation to student anxiety with quantitative methods; answering the calls for the development of quantitative skills in UK social science graduates; promoting research-led teaching; developing self-efficacy; and introducing flipping in a 'non-restricted' form. The use of software, data sources/archives, Economics Network resources and published research are all discussed and demonstrated.

The three videos discuss the benefits of replication, the replication of research and replication using the EN Ideas Bank, respectively.

Benefits of Replication studies

Replication of Research

Replication using the Economics Network Ideas Bank

Up to: Theme 2: Teaching with data online

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