Capacity building training through virtual model in India – challenges and opportunities

By: Barun Deb Pal

December 2021

In India, the economy-wide modelling was popular for macro-economic policy analysis as well as planning for economic development during the 1990s. However, currently the application of this analytical framework is very rare.  The erosion in capacity among scholars, policy makers and other stakeholders has contributed to the rare application of economy-wide modelling for policy analysis. On the other hand, IFPRI is a global leader in economy-wide modelling and is committed to strengthening capacity in its application for economic policy analysis. As a part of that commitment, I have been conducting capacity building training in collaboration with Indian Council for Agricultural Research (ICAR), Jawaharlal Nehru University (JNU) and several other autonomous research institutions in India since last five years without interruptions even during the recent pandemic time. In this blogpost I intend to share my practical experiences to conduct capacity building training on economy wide modelling for policy analysis in India.

The training on economywide modelling framework requires graphical presentations of theoretical background of the economic models, mathematical derivations and computer programming for data compilation and empirical solution of the models making it a rather complex topic. In-person classroom teaching using white board with marker pens is the best way to conduct training on such modelling techniques. However, with the onset of COVID-19 led pandemic, federal governments in India have laid down physical distancing protocols to stop spread of corona virus among the masses. As a result, a virtual academic world has been emerged where both teachers and students are adapted with virtual mode of learning process. The capacity building training for the research scholars is not exception to this phenomenon. During last eighteen months between May 2020 and October 2021, I have conducted five virtual capacity building trainings for 40-80 individuals, of which 30-40% of which were female.

The economy wide modelling training includes materials on input-output analysis, construction of social accounting matrix and its multiplier, and computable general equilibrium modelling for policy analysis which are difficult to instruct virtually. In particular, the following were challenges to conducting the virtual training on economy wide modelling:

1. Participants joined the training programs from a variety of locations and, due to poor internet in some places, participants, and sometimes trainers, were frequently interrupted by lost connections. As a result, participants lost their focus during the proceedings.
2. An effective learning process requires informal discussions among the participants as well and between the trainer and trainees. This elicits real-life economic policy examples which can be linked with economywide modelling analysis. However, this discussion was limited during virtual training given its top-down approach to learning.
3. During in-person training, a trainer can closely monitor the participants’ learning by looking at their faces during theoretical sessions and one-to-one interactions during practical sessions. However, monitoring the learning process of the participants is challenging during short virtual training courses.
4. Due to a lack of peer-to-peer interaction during virtual training, participants lose interest after an hour of the training even if the topic is of her/his research interests. In contrast, during in-person meetings, participants remain active for at least 4 hours in the morning session.

Despite these key challenges observed during virtual training, there are still several opportunities and the most significant are as follows.

1. In-person meetings require logistical arrangements and financial resources and, as a result, can only accommodate a limited number of participants. Virtual trainings can accommodate a larger number of participants from different geographical regions and time zones with little financial implication for the organizers.
2. Virtual training sessions can easily be recorded and can be used by participants to continue their learning beyond the official training hours. Moreover, the video recorded sessions can be published for wider dissemination and the trainer gets additional exposure on his/her areas of expertise.
3. Since virtual training does not involve travel, a trainer can deliver two training sessions to two different groups of participants within a day at different times.

However, virtual training during the last eighteen months has led me to innovate an effective way of delivering lectures. Here are a few recommended best practices that I have followed and that have been appreciated by the participants.

1. Write all important statements in the slides so that participants are better able to understand key messages both during the session and during later review.
2. Organize yourself before the training. Arrange your slides according to the time allocated for your training with a focus on only one topic with significant time available for practical examples.
3. Mathematical derivations should be explained using animation sequentially as if you are deriving it in the classroom on a whiteboard.
4. Prepare practical examples in a small dataset in MS Excel and circulate them among the participants during your session so that participants can follow the practical session on model simulations.
5. Ask participants about questions every 15 minutes so that they remain attentive in your session.
6. Since most of virtual training sessions are video recorded, speak slowly and clearly while conducting your sessions.
7. The lack of informal discussion among participants makes the learning process incomplete. Therefore, keep a slot for informal discussion among the participants so that new ides emerge and so that the trainer can understand any gaps in his/her teaching.

 

Barun Deb Pal is a Research Fellow with IFPRI’s South Asia Region