[September, 2024]

1. For a while now, I have been enjoying the content that Kat Pattillo puts together on EdWell. As someone who appreciates history, I found the post on 16 educationists from the Global South very informative, and indeed, I learned a lot about the amazing work by some of these individuals (source) 

2. Not technically a resource I “found,” but rather a write-up that my team and I worked on — I also wanted to share a brief on an RCT that I found very interesting. Although it might be exploring a question that is a bit too in-the-weeds and specific for those in the education/measurement space, it focuses on administration practices for reading comprehension assessments and how those might affect the learning levels recorded in the data. Since I don't know when/if this will ever be published as a formal paper, I thought it'd post it here, in the spirit quasi-scientific dissemination of information that might be potentially useful for other folks (source) 

3. The issue of “Enumerator effects” is a significant yet often underrated problem in empirical data collection. These effects can bias results significantly, particularly since we may not know the counterfactual unless we undertake costly re-testing. I found this paper by Walter and Moneke on how enumerators select their samples to be an interesting and worrying new take on this issue (source) 

4. A bit more theoretical, but I recently read for the first time (what I hear is) the classic “A Theory of Misgovernance” by Abhijit Banerjee. The takeaway seems to be that even if governments have the best intentions, they can experience inefficiency and corruption, partly due to those very intentions (source)  

5. Although I would not recommend fully outsourcing literature reviews to this tool, I have found the AI tool Consensus to be very helpful for quick literature searches and syntheses. I have been using only the free version though, so I cannot speak to the value of the paid version (source) 

6. I’m not yet finished reading this resource, partly due to how rich its content is, but I have found this quasi-handbook on data collection by Stantcheva to be very useful. I think that this is particularly beneficial for those of us who were trained in graduate school on data analysis and interpretation but not necessarily on data collection or the entire “data generating process” (e.g., I had courses on “how to Stata” but not on “how to use Survey CTO” or “how to manage enumerators”). Worth a read, for sure! (source) 

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[January, 2024]

1. I really enjoyed Ale Ganimian and Sharnic Djaker’s review on within-class learning heterogeneity in LMICs — what we know about it and the interventions that have been tried to minimize its negative effects on classroom instruction and learning outcomes (source) 

2. The recent World Bank report on 'Making Teacher Policy Work' comes as a very welcome resource on the most effective policies, best practices, and ways to make the teaching labor force more aligned with delivering learning outcomes in LMICs (source) 

3. This paper explores some potential reasons why the estimated impact of preschool programs appears to be diminishing over time. Although it focuses on a U.S.-centered context, it still provides interesting lessons for LMICs that are currently increasing access to early childhood education for when (likely soon) they reach the level of maturity of the educational system in the U.S. in terms of enrollment and household counterfactuals for children (source) 

4. I recently stumbled upon a book called 'Better Data Visualizations' by Jonathan Schwabish at a bookstore. I haven't finished the whole book yet, but so far, it’s been a great no-code resource to think about data presentation and visualization more critically and effectively (source) 

5. Looking to support a new analyst who was only familiar with R but needed to transition to Stata, I found this basic yet helpful guide on how to clean data in Stata — I think it is very helpful for experienced coders (just not in Stata) to pick it up pretty quickly (source) 

6. Along the same lines of a CGD paper that came out about a year or two ago, this is a fascinating paper by Yarrow, Cahu, Breeding, and Afkar on policymakers' beliefs about learning outcomes and policy goals in the East Asia Pacific. I love this type of research — policymakers at different levels drive reform (although perhaps not as fast and directly as many imagine), and better understanding their beliefs, biases, and motivations is a valuable first step towards enacting effective policy reforms (source) 

7. Finally, Luis Crouch and Deborah Spindelman wrote a great paper on the historical trajectory of the Japanese and South Korean education systems to get to where they are. Often, we analyze the impact of specific policies or even analyze a whole educational system at a given point in time (à la most RISE-an work), but this is a very interesting way to understand how two countries with enormous economic and educational progress in the past 50-100 years got to where they are (source) 

 

[August, 2023]

1. First, Dave Evans and Amina Mendez-Acosta have put out a great paper addressing the issue of student absenteeism and how to measure it in the absence of real-time data on student attendance. This is an extremely important issue, especially considering a) the high enrollment rates worldwide, but also b) the fact that the actual educational dosage that children receive can vary significantly based on their attendance (source) 

2. Andy de Barros and Ale Ganimian's blog (based on their paper) explore the extent to which customization drives improvements in certain interventions like TaRL, as opposed to other factors such as additional instructional time (source) 

3. While designing an RCT at work, I found myself rereading a valuable resource by Dave McKenzie on the perils of pairwise randomization. "Reason 4" is particularly interesting for those of us in the education sector (source) 

4. Another outstanding visualization, similar to the "immersive story" in my November 2022 update, delves into the global education landscape. The World Bank team has truly excelled in making complex data more accessible for interpretation and discussion (source) 

5. Good compilation of ed stats for different countries worldwide. As someone who finds the other UNESCO stats portals not-too-user-friendly, I really appreciate that they are also compiled here in a way that is easy to download but also to visualize online (source) 

6. This podcast with Yue-Yi — always with her thoughtful takes and questions — and Jennifer Opare-Kumi, is intriguing. The potential connection between FLN and children's mental health outcomes is a topic that I hadn't really thought much about before. While more research is definitely needed in this area, this is potentially yet another reason to support the promotion of FLN  (source) 

7. Finally, I was recently on the market for an early childhood development (ECD) tool. I needed (1) a tool that was not impossibly long, (2) that incorporates learning outcomes, or at the very least, "pre-skills", and (3) is supported by a robust validation process, preferably conducted in LMICs. I came across the AIM-ECD tool from the World Bank, which was great — especially the Direct Assessment component. Highly recommended for other fellow researcher-practitioners  (source) 

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[November, 2022]

1. First, I've been really enjoying the power of "immersive stories", which leverage data and multimedia to tell a compelling story (The Economist has done a few). The World Bank Education Group did a great job with this one (source) 

2. They've done it again! Here's a great compilation of all the research presented at the development conference NEUCD — for those of us who couldn't make it  (source) 

3. As I'm trying to learn more about socio-emotional skills —what they are, how they develop, and what options we have as practitioners to measure them— I stumbled upon this gem, put together by the Global Center for the Development of the Whole Child, with actually practical recommendations on how to think about this issue, and tackle it in a rigorous way (source)  

4. I came across this just today (so, of course I haven't read all the links in this resource), but Christine Cai put together a very handy resource on "Advances in applied micro" which can be a game changer for those of us hoping to stay sharp post-grad school! (source) 

5. Fascinating paper that a) quantifies foundational learning gaps around the world, but most importantly (and uniquely), b) estimates the economic costs of these gaps. This seems like a key paper that will be cited every time one needs to justify investments in FLN (source) 

6. Beautiful plotting package in Stata by Jan Kabatek. I've only played with it a little bit, but it's very promising for gorgeous plots (I especially like the shares plot)  (source)  

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[June, 2022]

1. It's finally out! The RCT testing the effectiveness of Bridge Kenya (full disclosure: a program run by my current employer) is out. Besides the (1) amazing line up of researchers, (2) the —quite-literally— off-the-charts effects on learning outcomes at such scale, the paper has a ton of cool methodological nuggets, and I do think it's pretty much state-of-the-art in terms of an evaluation in education. Check it out! (source) 

2. Our World in Data has a cool overview of the state of the international education landscape. I wouldn't say it presents new information per se, but it does a very nice job at pulling it all together (source) 

3. The CGD folks put together a great report here on education interventions that have worked at scale. Mostly focused on enrollment, I really like the call to keep paying attention to this outcome —not just learning. Learning is the ultimate goal, but there is still a lot of work to do around the margin of enrollment as well (source) 

4. Helpful manual by Paul Glewwe and Petra Todd for M&E practitioners and researchers on impact eval, including some of the most common quantitative, and to a lesser extent, qualitative approaches used). (source) 

5. I'm still making my way through this one, but I stumbled upon this great overview for non-psychologists like myself on the science of learning. Very readable and I've learned a lot so far! (source) 

6. The previous report reminded me of another similar report by Helen Abadzi on the science of learning — particularly as it relates to the improvement of foundational literacy and numeracy through the "automation" of these tasks (source) 

7. Finally, David McKenzie at the World Bank put together an updated list of all the methodological posts and resources from their blog. Very valuable public good — both the posts and the curated list. (source) 

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[September, 2021]

1. The Global Education Policy Dashboard is an initiative to benchmark the performance of education systems around the world more holistically, and in a more standardized manner.  Here is an example for Jordan, and I hope that this tool is expanded for as many countries as possible (source) 

2. Great journalistic description on the importance of properly tailoring reading materials (and instruction more broadly) to the local contexts (source) 

3. Helpful set of tips to work with large data sets in Stata (source) 

4. Communicating the intricacies of RCTs, especially what "breaks" an impact eval and what doesn't, can be a tough task, regardless of the audience. That's why I loved this informal, but rigorous, "FAQ" by Macartan Humphreys on how to interpret different challenges that come up in studies involving RCTs (source) 

5. In light of International Literacy Day (September 8), this was a great post by the WB Ed practice on three concrete steps countries can take to increase literacy in LMIC (source) 

6. I recently had a chance to read (and really enjoy!) “Failing in the Field” by Dean Karlan and Jacob Appel. I love the idea of crowdsourcing lessons from failures - we don't all have to make the same mistakes to learn something from them (source) 

7. Good policy brief with an in-depth/360 view of the political economy, pedagogical considerations, and root causes of weak learning outcomes in LMIC around foundational literacy and numeracy  (source) 

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[July, 2021]

1. I really enjoyed reading this paper on the extent to which governments should prioritize (or not) “FLN” - foundational numeracy and literacy. As someone who works mostly around topics of FLN, my tendency is to heavily favor these skills, but I loved thinking harder about the other potential (and valuable!) uses of the “marginal dollar” in education (source) 

2. The World Bank has nice new website on learning poverty (source). They also released a working paper on both the methods behind the creation of this metric, and the policy relevance of measuring "learning poverty" as a target towards which countries can work (source)

3. I recently came across the Relative Wealth Index data from Facebook, which has fine-grain GIS data (i.e., grids of 2.4 km², or plots of 1.5 km each side) on community wealth for pretty much all low- and middle-income countries. Super helpful! For instance, I recently wanted to do some balance tests and sub-group analyses by wealth for some schools for which I had their latitudes and longitudes, but did not have access to individual-level wealth data or pretty much any community-level data. I simply did a spatial merge of the two layers and then had my community-level data for each school (source)

4. Along the same vein of cool maps, the Project Connect merges some of my favorite topics (maps, edtech, and educational systems in LMIC!) into one of the coolest websites I’ve seen recently. They show the extent of school-level connectivity to the internet for several countries – super interesting for cross-country comparisons, or to easily spot geographic disparities in internet access at school (source)

5. Finally, check out “Softie”, a documentary about the struggles of a brave, budding politician in Kenya (source)

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[June, 2021]

1. Paper studying actual learning trajectories in Indonesia! We have long discussed learning trajectories in the abstract, or through repeated cross-sections, but this type of panel-data analysis is very rare. I liked that it supported some previous observations (e.g., students at the very, very bottom learn very little), but it also challenged other assumptions (e.g., they find that learning does happen, at least on average, as a result of school). Definitely worth a read! (source)

2. The CGD compiled a great set of essays of different researchers, and academics on the frontiers of education in LMIC (source), as a response to Girin Beeharry's essay "The pathway to SDG 4" in the International Journal of Educational Development (source)

3. Awesome large-scale studying on improving child development services in India (source)

4. I might be late to the game here, but I recently stumbled upon the Angolan band "Cordas do Sol" and have been recently listening on repeat while working (source)

5. A few years ago, the XYZ Show did a bit on the Uwezo report for East Africa, and I recently "re-discovered" this on YouTube. Sadly (but in a very witty way), I think they hit the nail on the head with this one... still, it's interesting to see how deep into the mainstream a policy report like Uwezo went! (source)

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[September, 2020]

1. Cool paper on the quality of administrative data in India. Really creative way to merge admin data with RCT data to shed light on the quality of admin records in low- and middle-income countries (source)

2. Thorough review of the latest (Econ-y/policy) evidence on what we know about how to improve access and learning outcomes  in Africa (source). Great update to one of the authors' (Dave Evans) previous papers with a similar flavor (source)

3. This is an older, yet great NPR podcast on what being a journalist in Nicaragua is like, especially after the 2018 crisis. The podcast is originally in Spanish (source), but this is the English translation (source)

4. In light of my recent review of edtech interventions in low- and middle-income countries (source), this is an interesting blog on the system-wide EdTech landscape in Tanzania (source) 

5. Great journalistic work by the NYT on the effect of COVID on education around the world (source)

6. Another very informative review of the landscape (both state and interventions) of early literacy in low- and middle-income countries (source)

7. Lastly, next time you need to compare your effect size to the broader literature, check out this super handy paper by Dave Evans and Fei Yuan (source)

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[March, 2020]

1. Data collected by grassroots movement "Map Kibera" on location of schools within Kenya's largest slum, Kibera (source)

2. Great blog post on the power and limitations of scripting lessons for teachers in low- and middle-income countries (source). Along a similar line, blog post on the issue of scalability of education interventions in the developing world (source).

3. Very informative webinars on the awesome R package ggplot2, my go-to for visualizations (part 1) (part 2) (admittedly, it is an investment of 4.5 hours, but well-worth it, even if you need to watch it in parts or while doing house chores)

4. Interesting overview (with some ideological leanings here and there too, I think) on the history and development of education in recent colonies, particularly in Sub-Saharan Africa (source)

5. Helpful tips from Dave Evans on how to get more visibility on your research (source)

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[February, 2020]

1. Blog post on grade repetition policies in low- and middle-income countries (source)

2. Fascinating article on pre-colonial, West African history (source)

3. Awesome RCT shedding light on how "local education markets" shape how effective ed interventions can be (source)

4. Sweet and powerful book that touches upon many relevant themes to pre-independence Kenya, from the point of view of a child (source)

5. For my Spanish-speaking friends: not a read, but Residente's new song will move you with its touching throwbacks to what growing up in Latin America was like (source)