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J-PAL is recruiting a Senior Training Associate and a Research and Training Associate based at the J-PAL Global office at the Massachusetts Institute of Technology in Cambridge, MA. 

The Global Training group creates resources and teaching materials and delivers courses to develop internal staff capacity and cultivate a network of like-minded stakeholders, in order to promote the production and use of rigorous evidence as part of J-PAL’s mission of fostering evidence-informed policy.

Research and Training Associate

In this position, you will have the opportunity to work with some of the top researchers at MIT and around the world while publishing research data, assisting with data analysis for research projects, and designing, organizing, and conducting courses for policy partners.  You will build out data analysis tools and new reference and teaching materials, and you will help train researchers, research staff, and policymakers in staff trainings, executive education programs, and online courses. We interact with high-level policy makers from governments, foundations, and NGOs, and we work closely with staff from our regional offices in Chile, France, India, Indonesia, and South Africa--and travel frequently to those locations--as well as staff from J-PAL’s partner organizations, like Innovations for Poverty Action and the Center for Effective Global Action.

For more information, please visit:   

https://www.povertyactionlab.org/careers/research-and-training-associate-j-pal-global-102462

Senior Training Associate

Your primary tasks as a Senior Training Associate will be to create lectures, case studies, and other teaching materials, organize courses and liaise with J-PAL’s regional offices and training partners, and develop new, creative ways to disseminate knowledge about impact evaluations, including through innovative online learning platforms. Your work contributes to creating greater capacity for J-PAL’s efforts to reduce poverty by ensuring that policy is based on scientific evidence.

For more information, please visit: 

New Research Answers Whether Technology Is Good Or Bad For Learning

For years educators and scholars have debated whether technology aids learning or inhibits it.

In the most recent issue of Education Next, for example, Susan Payne Carter, Kyle Greenberg, and Michael S. Walker write about their research finding that allowing any computer usage in the classroom “reduces students’ average final-exam performance by roughly one-fifth of a standard deviation.” Other studies have shown similarly dismal numbers for student learning when technology is introduced in the classroom.

Yet there are also bright shining stars of technology use—both in proof points and in studies, such as this Ithaka study or this U.S. Department of Education 2010 meta-analysis.

So what gives? Since 2008 I’ve, perhaps conveniently, argued that scholars and advocates on both sides of this debate are correct. As we wrote in Disrupting Class in 2008, computers had been around for two decades. Even 10 years ago, we had already spent over $60 billion on them in K–12 schools in the United States to little effect. The reason quite simply was that when we crammed computers into existing learning models, they produced begrudging or negative results. To take a higher education example, when I was a student at the Harvard Business School, far fewer of us paid attention to the case discussion on the couple days at the end of the term when laptops were allowed, as we chose to instead chat online and coordinate evening plans. In that context, I would ban laptops, too.

When the learning model is fundamentally redesigned to incorporate intentionally the benefits of technology, say, in a blended-learning model, however, you can get very different results. To use another personal example, I fervently hope that the public school district where my daughters will go to school will comprehensively redesign its learning environments to personalize learning for each student through the use of technology. As we disruptive innovation acolytes like to say, it’s almost always about the model, not the technology.

This finding isn’t unique to the technology of computers in classrooms. It was true with chalkboards as well.

As Harvard’s David Dockterman recounts, the blackboard was reportedly invented in the early 19th century. The technology was adopted quickly throughout higher education in a lecture model to convey information to all the students at once. The first recorded use in North America was in 1801 at the United States Military Academy in West Point—ironically the location of the study that Carter, Greenberg, and Walker conducted—and it spread quickly.

Having observed the success of the blackboard in college, schoolhouses began installing the technology, but the teaching and learning changed minimally. The blackboards were largely unused because teachers had difficulty figuring out how to use them. Why? At the time, the prevalent model of education in public schools was the one-room schoolhouse in which all students, regardless of age or level, met in a single room and were taught by a single teacher. Rather than teaching all the students the same subjects, in the same way, at the same pace—like in today’s schools—the teacher rotated around the room and worked individually with small groups of students. As a result, the blackboard didn’t make much sense in the context of the one-room schoolhouse because the teacher rarely, if ever, stood in front of the class to lecture.

It wasn’t until the early 1900s when the public education system changed its instructional model—to today’s factory model—that the blackboard became a staple of American education. Lesson? The model matters.

Fast forward to today, and we see the same dynamic. A new—and very helpful—analysis of the research helps tease this out and perhaps can at last break the infuriating log-jam between those who argue technology is a distraction at best and those who argue it is an extremely positive force.

At J-PAL—MIT’s Poverty Action Lab—Maya Escueta (Columbia), Vincent Quan (J-PAL North America), Andre Joshua Nickow (Northwestern), and Phil Oreopoulos (University of Toronto; Co-Chair, J-PAL's Education sector) released a review of more than 100 experimental studies (RCTs and RDDs) in education technology to examine the evidence across four key areas of education technology: access to technology, computer-assisted learning, technology-based behavioral interventions in education, and online learning.

Among the findings, according to the summary J-PAL provided:

Computer-assisted learning, in which educational software helps students develop particular skills, is particularly promising, especially in math. This is likely because of the software’s ability to personalize by adapting to a student’s learning level and letting the student learn at the right pace for her, as well as the ability to provide teachers immediate feedback on student performance that is actionable. This is of course no surprise to those of us who have been excited about blended-learning models that personalize learning for students.

Technology-based behavioral interventions—like nudging a student to register for a course—produce consistently improved learning outcomes.

Initiatives that provide computers to every student in a classroom do not improve learning outcomes. That is very predictable given our research on the perils of cramming technology. I’ll repeat myself again here: You have to focus on the learning model first followed by the technology in service of that learning model. Initiatives that start with the technology almost always fail in my experience.

Research on online courses is still early, but it appears that “blended” courses produce similar outcomes as in-person courses, which could drive down costs. In-person classes outperform fully online ones—a reason to still keep fully online courses focused on areas of nonconsumption, where the alternative is nothing at all and therefore not competing against an in-person course.

In my view, this is what I’d expect a review to find, as it points to the tremendous promise of technology to personalize learning (note: the outcomes here are still reliant on good learning design) and the peril of merely cramming technology in to existing, analog learning models.

The group of Johannes Haushofer in the Department of Psychology and the Woodrow Wilson School of Public and International Affairs at Princeton University is seeking applications for a research specialist. They are interested in understanding the psychological and neurobiological consequences of poverty, and their implications for economic choice. They conduct lab and field experiments in both developing and developed countries, using approaches from neurobiology, psychology, and economics.

The successful applicant will assist with many aspects of research, particularly planning, implementing, and analyzing lab experiments and randomized controlled trials, conducting literature reviews, developing interventions, and contributing miscellaneous research support. Some travel to the field (especially Kenya) is envisaged.

This particular position includes management and econometric analysis of experimental data from lab and field experiments. Knowledge of econometrics/statistics and familiarity with Stata, R, or related software is desired. The position is particularly appropriate for candidates with backgrounds in in economics, statistics, political science, sociology, public policy, psychology, or related fields.

The Abdul Latif Jameel Poverty Action Lab (J-PAL) is the world leader in conducting evidence-based research in developing countries.

Work directly on J-PAL research programs, which are used by Givewell and other organizations to determine the most effective global poverty interventions (a top cause ).