Are we looking at the metrics that measure Quality education all wrong?

Education system is highly complex. Small data can fix gaps. But is that enough? 

Last year I got a fantastic opportunity to visit the United Nations Headquarters in NYC.  As I visited the different chambers where many resolutions have been passed over the years, the budding policy wonk in me was hungry to learn more. UNICEF’s “School-in-a-box” kit which is used as a back-to-school operation around the world got me thinking about the education system and about the different variables used to quantify quality education in developing countries.

Big Data in educational reform and its impact

In an article in The Washington Post, “’Big Data’ was supposed to fix education. It didn’t. It’s time for ‘small data’”, the author talks about how Big Data has only helped reveal correlations between the various factors and not causality. Thus systemic improvements in the education system by using this information is not as useful as we may want it to be. Since education system is complex by nature, small data that captures the essence of learning and teaching in the classroom is what would eventually assist in making more effective policies.

Sustainable development goals (SDG) and Quality education

The 2030 Agenda created by UN has 17 goals. The 4^th goal being Quality Education has set most developing countries on the right path to incrementally achieve this goal. Various programs undertaken by Global Partnership for Education has resulted in an increase of youth literacy from 71% in 2000-05 to 75% in 2008-13. World Bank’s SABER ( Systems Approach to Better Education Results) program helps identify where individual countries need most interventions by collecting data on educational institutions and policies. Knowledge integration of data collected by these programs will be challenging, but will prove to be powerful in gauging the extent of improvement of these systems over the years. It would also help in identifying the crucial indicators for building a robust educational system.

SDG Target: “Equitable and quality primary and secondary education leading to effective learning outcomes”

In order to reach one of the targets set by the UN, it is vital to have quality data in order to make effective decisions to enforce the best practices thus improving the system. But how does one decide the metrics for this data? Various studies carried out by US Department of Education suggest that Teacher Assignment, Teacher Experience, Teacher Academic Skills, Class size, Technology, Academic Development, Goals, School Leadership among many others are used as quality measures. Another paper published by National Center for Education Statistics explains about using measures like Graduation rates, Proportion of students graduated without delay, drop-out rates, % of unemployed and so on. While using all these parameters may be one way to measure the quality, are we missing out on data points that may be unique to communities? Is there a danger of way too much generalization through the above mentioned metrics that cloud our abilities to understand the true underlying ground realities? We all do agree that we cannot compare the education systems of developing countries with those of the developed countries. Then is there more we can do in terms of quality data collection and additional metrics we can use specifically for developing countries?

Pulse of Education system in Developing countries

“Learning Unleashed” an Economist article mentions that the number of private schools have increased substantially over the years in developing nations. A large section of the society has preferred private schools over public schools due to poor infrastructure, quality of education in public schools. Lack of competition have left these public schools high and dry with no incentive for improvement. So it may be meaningful to identify metrics that measure competition in our data collection that contributes in an indirect yet significant way to quality education.

Along with variables that intend to capture the qualitative information about the internal school environment, we must also pay attention to the external environment. One can measure competition by geo-spatially mapping different schools in the surroundings, identifying if they’re private or public, funding for the schools and cost incurred per student.

Studies have shown that there is a strong correlation between quality education and diversity in schools. In most developing countries, public schools are mostly attended by children that belong to low-income groups and private schools by the higher income groups. Although, most schools now try to include children from all strata of the society, the students do not feel socially included leading to below average performance. Thus “socially-inclusive” variable is an important one in better understanding the quality of education.

Data about the surrounding physical condition of the school is a crucial factor too. Cleanliness and safety must be captured with the rest of the data points.

Changing reforms with changing times

While quality data collection has an undeniable role in making a positive impact in this field, suitable policies and reforms must be enforced making use of the inferences obtained from the collected data. Since private schools are preferred, it may be a good move to incentivize the private sector to invest in public schools. Developing countries like India have created a barrier to market entry by making land ownership a pre-requisite for building a school. Thus entrepreneurs with low capital with a drive to build schools lose opportunities.

It may also be a good move to allocate precise and limited number of responsibilities to primary school teachers with specific targets. For example, by ensuring a primary school teacher concentrates on improving only the reading skills of the students, it will be easy to keep track of the progress.

There’s a long way to go before the education system gets fixed for good. Good quality data, data analysis married to timely policy reforms can accelerate this process. Data alone is no silver bullet!

References:

https://nces.ed.gov/pubs2001/2001030.pdf

http://www.globalgoals.org/global-goals/quality-education/

http://wbgfiles.worldbank.org/documents/hdn/ed/saber/supporting_doc/in_actions/SABER_in_Action_Nigeria.pdf

http://www.globalpartnership.org/focus-areas/learning-outcomes

https://www.washingtonpost.com/news/answer-sheet/wp/2016/05/09/big-data-was-supposed-to-fix-education-it-didnt-its-time-for-small-data/?utm_term=.e5304f541b29

http://www.economist.com/news/briefing/21660063-where-governments-are-failing-provide-youngsters-decent-education-private-sector

In the middle

Being a 25 year old, around 90% of the people I meet, range between 22-35 years of age. Though the sample size is inadequate to extrapolate and make general statements, I am drawing my observations in this post, gathered over a bunch of such interactions over the past 6-7 years.  

About 80% of the people I meet, read about, follow on social media are either very strongly opinionated or have no opinions at all. People either care too much or too little. People either complain constantly or are complacent. People are either too optimistic or have lost all hope. People call themselves liberals or conservatives. So, the questions I keep asking myself is, “Why aren’t we in the middle?”, “Is it alright to have such extremities?” and “Is it possible to be a little bit of both?”

These interactions about a myriad of topics ranging from geo-politics to childhood cartoons and deep learning algorithms to Roman civilization has taught me a little bit about people’s personalities and how people draw their satisfaction from being proven right. Now this is something we all know and I’m no pundit on human behavior or psychology. But it’s something that deeply fascinates me. And learning what makes each of us tick could help us find the answer to why we aren’t in the middle. So, I went through the following phases to analyze this.

Phase 1: Self analysis:

I try quite hard to be in the middle. Not have extreme opinions on anything. When I hear a story, read an article or absorb any piece of information, I try to take it with a pinch of salt and skepticism. I try to consume the same information from various sources. But during this process of self analysis, I inferred something quite significant. I realized how I had made no attempt to express my thoughts, opinions out in the open. And no other better way than to pen them down. Now you know why you’re reading about this, don’t you?

Phase 2: Learn about the source:

I started out an experiment where I started asking people where they consumed their news and other information from. While it helped me learn a good deal about their preferences, I also understood why they believed what they believed in. In this era of fake news and alternative facts, I tried to ask them how much they believed in what they read. Though most people didn’t entirely rely on what they read or watched, they seemed to be influenced by it in some way or the other.  

Phase 3: Learn why they think it’s right:

Certain life experiences drive people to have certain biases towards/against a certain process, race, gender and so on. What I learned is that - something new that follows intuition and supports the biases overrules logic most times. Regardless of how hard one tries to disassociate oneself and their preconceived notion with the newly learned piece of information, they generally tend to formulate their opinion based on this information that transitions into a fact in the head. And once a fact, it becomes quite hard (not impossible) to unlearn it.

Phase 4: What’s next after the fact is established? :

Humans have an incessant need to be proven right at all times. We all try our level best trying to show our friends, relatives, colleagues how our opinions (which we consider facts) are almost always right. While the streak of modesty in us tries to remind us of all the possible ways our logic could be failing us, we still don’t take a step back and think. And every time we desperately try to prove to someone why what we think is correct, we also try to prove the other person wrong. We stop listening and we impose. This is where I believe the nature of extremity crawls in. At the time of information consumption, we are all in the middle. We are learning something we do not know, it’s all new. Once it transitions as a fact and we want to convince someone else why we think we’re right, we push ourselves into believing that it’s the only single truth ever known to mankind and how every one else who thinks otherwise, is an idiot.

These 4 phases didn’t entirely help me arrive at any specific conclusions about the questions I had. I’m still in the process of understanding why being in the middle is important to me. Whatever we learn, we learn from nature. While extreme ecosystems does support life, what we know from science is moderate ecosystem is what lets life grow and expand. From the fear of getting too philosophical and preachy, I’d like to stop my first post with the question I’d posed somewhere in the middle (Haha, you see that?) of my post – “Why aren’t we in the middle?”