Ensuring that patients adhere to prescribed medication remains an important challenge in global health. While technology has been utilized to monitor and improve adherence, solutions to date have been too costly for large-scale deployment in developing regions. This paper describes 99DOTS, a low-cost approach for tracking adherence using a combination of paper packaging and low-end mobile phones. Every day, patients reveal an unpredictable phone number behind the pills and send a free call to that number to indicate that drugs were dispensed and taken. Within five years of its inception, 99DOTS has become a standard of care for tuberculosis in India and has enrolled over 200,000 patients. We provide a holistic account of the project's evolution, including its iterative design, scaled implementation, and lessons learned along the way. We hope this account will serve as a useful case study for anyone seeking to establish and scale new low-cost technologies for a global audience.

With the wide penetration of mobile internet, social networking (SN) systems are becoming increasingly popular in the developing world. However, most SN sites are text heavy, and are therefore unusable by low-literate populations. Here we ask what would an SN application for low-literate users look like and how would it be used? We designed and deployed KrishiPustak, an audio-visual SN mobile application for low-literate farming populations in rural India. Over a four month deployment, 306 farmers registered through the phones of eight agricultural mediators making 514 posts and 180 replies. We conducted interviews with farmers and mediators and analyzed the content to understand system usage and to drive iterative design. The context of mediated use and agricultural framing had a powerful impact on system understanding (what it was for) and usage. Overall, KrishiPustak was useful and usable, but none-the-less we identify a number of design recommendations for similar SN systems.

We measure the effectiveness of a traditional honor code at deterring cheating in an online examination, and we compare it to that of a stern warning. Through experimental evaluation in a 409-student online course, we find that a pre-task warning leads to a significant decrease in the rate of cheating while an honor code has a smaller (non-significant) effect. Unlike much prior work, we measure the rate of cheating directly and we do not rely on potentially inaccurate post-examination surveys. Our findings demonstrate that replacing traditional honor codes with warnings could be a simple and effective way to deter cheating in online courses.

Students in the developing world are frequently cited as being among the most important beneficiaries of online education initiatives such as massive open online courses (MOOCs). While some predict that online classrooms will replace physical classrooms, our experience suggests that blending online and in-person instruction is more likely to succeed in developing regions. However, very little research has actually been done on the effects of online education or blended learning in these environments. In this paper we describe a blended learning initiative that combines videos from a large online course with peer-led sessions for undergraduate technical education in India. We performed a randomized controlled trial (RCT) that indicates our intervention was associated with a small but significant improvement in performance on a summative exam. We discuss the results of the RCT and an ethnographic study of the intervention to make recommendations for future, scalable blended learning initiatives for places such as India.

While most MOOCs rely on world-famous experts to teach the masses, in many circumstances students may learn more from people who share their context such as local teachers or peers. Here, we describe an experiment to explore how the "source" of video content, the teacher, affects online learning, specifically in the context of higher education in Indian colleges. The proposed experiment will compare three content sources -- a local lecturer (teacher from an Indian engineering college), a local peer (both male and female students similar to the targeted audience), and an internationally recognized expert (a Stanford lecturer). Students will watch videos by the various source authors, after which we will measure differences in their preference, engagement, and learning. In addition, we discuss our experiences with helping students prepare video lectures and describe the support and processes we used to curate interesting and clear peer-generated content.

Many Internet services depend on the integrity of their users, even when these users have strong incentives to behave dishonestly. Drawing on experiments in two different online contexts, this study measures the prevalence of cheating and evaluates two different methods for deterring it. Our first experiment investigates cheating behavior in a pair of online exams spanning 632 students in India. Our second experiment examines dishonest behavior on Mechanical Turk through an online task with 2,378 total participants. Using direct measurements that are not dependent on self-reports, we detect significant rates of cheating in both environments. We confirm that honor codes--despite frequent use in massive open online courses (MOOCs)--lead to only a small and insignificant reduction in online cheating behaviors. To overcome these challenges, we propose a new intervention: a stern warning that spells out the potential consequences of cheating. We show that the warning leads to a significant (about twofold) reduction in cheating, consistent across experiments. We also characterize the demographic correlates of cheating on Mechanical Turk. Our findings advance the understanding of cheating in online environments, and suggest that replacing traditional honor codes with warnings could be a simple and effective way to deter cheating in online courses and online labor marketplaces.