ABC, 123: Can you text me now? The Impact of a Mobile Phone Literacy Program on Educational Outcomes.

We report the short-term results from a randomized evaluation of a mobile phone literacy and numeracy program (Project ABC) in Niger, in which adult literacy students learned how to use mobile phones as part of a literacy and numeracy class. Students in ABC villages showed substantial gains in numeracy exam scores. There is also evidence of heterogeneity in program effects across regions, suggesting the impact is context dependent. These results were stronger in one region, for women and for participants younger than 45. There was also evidence of persistent impacts: six months after the end of the first year of classes, students in ABC villages retained what they had learned better than the non-ABC students. These effects do not appear to be driven by differences in teacher quality and motivation, nor student attendance.Education; literacy; information technology; program evaluation; Nigeria

ABC, 123: The Impact of a Mobile Phone Literacy Program on Educational Outcomes

CGD non-resident fellow Jenny Aker and co-authors report on the results from a randomized evaluation of a mobile phone education program (Project ABC) in Niger, in which adult students learned how to use mobile phones as part of a literacy and numeracy class. Overall, students demonstrated substantial improvements in literacy and numeracy test scores. There is also evidence of persistent impacts: six months after the end of the first year of classes, students in the program retained what they had learned better than others. The effects do not appear to be driven by differences in teacher quality or in teacher and student attendance. The results suggest that simple and relatively cheap information and communication technology can serve as an effective and sustainable learning tool for rural populations.Education

Mobiles and mobility: The Effect of Mobile Phones on Migration in Niger

Labor markets in developing countries are subject to a high degree of frictions. We report the results from a randomized evaluation of an adult education program (Project ABC) in Niger, in which students learned how to use simple mobile phones as part of a literacy and numeracy class. Overall, our preliminary results suggest that access to this technology substantially influenced seasonal migration in Niger, increasing the likelihood of migration by at least one household member by 7 percentage points and the number of households' members engaging in seasonal migration. Evidence suggests that there are some heterogeneous impacts of the program, with a higher probability of a household member migrating in one region. These effects do not appear to be driven by differences in observable characteristics of households or differential effects of drought during the survey period. Rather we posit that they are largely explained by the effectiveness of mobile phones as a search technology: Students in ABC villages used mobile phones in more active ways and communicated more with migrants within Niger. These initial results suggest that simple and cheap information technology can be harnessed to affect labor mobility among rural populations. --

Can ABC lead to sustained 123? The medium-term effects of a technology-enhanced adult education program

Can information technology preserve the short-term learning gains associated with adult education programs? This study estimates the medium-term impacts of a mobile phone module (Project ABC) that was added to a standard adult education curriculum and for which there were significant short-term impacts on educational outcomes. Two years after the end of the program, students in ABC villages had reading scores that were significantly higher than those in standard adult education classes, and women and younger students were better able to decode numbers. This can be partially attributed to more active mobile phone usage in ABC villages. Households in ABC villages also were more likely to own certain durable assets, had higher levels of food security, and were more likely to save. Overall, these results suggest that short-term learning gains associated with technology can persist, especially if students have the opportunity to practice using that technology after the end of classes

Can mobile phones improve agricultural outcomes? Evidence from a randomized experiment in Niger

The widespread growth of mobile phone coverage worldwide has offered new potential for increasing rural households’ access to information and public and private transfers. Yet despite the proliferation of mobile phone-based interventions in the agricultural sector, there is mixed evidence on their impact. We report the results of a randomized evaluation in Niger, in which rural households increased their access to information technology and their capacity to use it. We find that households in treated villages planted a more diverse basket of crops, particularly marginal cash crops grown by women. This did not increase the likelihood of selling these crops or the farm-gate price received, suggesting that other market failures need to be addressed to improve farmers’ welfare

Noise-Net: Determining physical properties of HII regions reflecting observational uncertainties

Stellar feedback, the energetic interaction between young stars and their birthplace, plays an important role in the star formation history of the universe and the evolution of the interstellar medium (ISM). Correctly interpreting the observations of star-forming regions is essential to understand stellar feedback, but it is a non-trivial task due to the complexity of the feedback processes and degeneracy in observations. In our recent paper, we introduced a conditional invertible neural network (cINN) that predicts seven physical properties of star-forming regions from the luminosity of 12 optical emission lines as a novel method to analyze degenerate observations. We demonstrated that our network, trained on synthetic star-forming region models produced by the WARPFIELD-Emission predictor (WARPFIELD-EMP), could predict physical properties accurately and precisely. In this paper, we present a new updated version of the cINN that takes into account the observational uncertainties during network training. Our new network named Noise-Net reflects the influence of the uncertainty on the parameter prediction by using both emission-line luminosity and corresponding uncertainties as the necessary input information of the network. We examine the performance of the Noise-Net as a function of the uncertainty and compare it with the previous version of the cINN, which does not learn uncertainties during the training. We confirm that the Noise-Net outperforms the previous network for the typical observational uncertainty range and maintains high accuracy even when subject to large uncertainties.Comment: 22 pages, 14 figures, Accepted for publication by MNRAS on 04. Januar

Measuring Young Stars in Space and Time -- II. The Pre-Main-Sequence Stellar Content of N44

The Hubble Space Telescope (HST) survey Measuring Young Stars in Space and Time (MYSST) entails some of the deepest photometric observations of extragalactic star formation, capturing even the lowest mass stars of the active star-forming complex N44 in the Large Magellanic Cloud. We employ the new MYSST stellar catalog to identify and characterize the content of young pre-main-sequence (PMS) stars across N44 and analyze the PMS clustering structure. To distinguish PMS stars from more evolved line of sight contaminants, a non-trivial task due to several effects that alter photometry, we utilize a machine learning classification approach. This consists of training a support vector machine (SVM) and a random forest (RF) on a carefully selected subset of the MYSST data and categorize all observed stars as PMS or non-PMS. Combining SVM and RF predictions to retrieve the most robust set of PMS sources, we find $\sim26,700$ candidates with a PMS probability above 95% across N44. Employing a clustering approach based on a nearest neighbor surface density estimate, we identify 18 prominent PMS structures at $1$ $\sigma$ significance above the mean density with sub-clusters persisting up to and beyond $3$ $\sigma$ significance. The most active star-forming center, located at the western edge of N44's bubble, is a subcluster with an effective radius of $\sim 5.6$ pc entailing more than 1,100 PMS candidates. Furthermore, we confirm that almost all identified clusters coincide with known H II regions and are close to or harbor massive young O stars or YSOs previously discovered by MUSE and Spitzer observations.Comment: 29 pages, 21 figures, accepted for publication in A

Measuring Young Stars in Space and Time -- I. The Photometric Catalog and Extinction Properties of N44

In order to better understand the role of high-mass stellar feedback in regulating star formation in giant molecular clouds, we carried out a Hubble Space Telescope (HST) Treasury Program "Measuring Young Stars in Space and Time" (MYSST) targeting the star-forming complex N44 in the Large Magellanic Cloud (LMC). Using the F555W and F814W broadband filters of both the ACS and WFC3/UVIS, we built a photometric catalog of 461,684 stars down to $m_\mathrm{F555W} \simeq 29$ mag and $m_\mathrm{F814W} \simeq 28$ mag, corresponding to the magnitude of an unreddened 1 Myr pre-main-sequence star of $\approx0.09$ $M_\odot$ at the LMC distance. In this first paper we describe the observing strategy of MYSST, the data reduction procedure, and present the photometric catalog. We identify multiple young stellar populations tracing the gaseous rim of N44's super bubble, together with various contaminants belonging to the LMC field population. We also determine the reddening properties from the slope of the elongated red clump feature by applying the machine learning algorithm RANSAC, and we select a set of Upper Main Sequence (UMS) stars as primary probes to build an extinction map, deriving a relatively modest median extinction $A_{\mathrm{F555W}}\simeq0.77$ mag. The same procedure applied to the red clump provides $A_{\mathrm{F555W}}\simeq 0.68$ mag.Comment: 29 pages, 15 figures, accepted for publication in A

Signals: I. Survey description

SIGNALS, the Star formation, Ionized Gas, and Nebular Abundances Legacy Survey, is a large observing programme designed to investigate massive star formation and H II regions in a sample of local extended galaxies. The programme will use the imaging Fourier transform spectrograph SITELLE at the Canada–France–Hawaii Telescope. Over 355 h (54.7 nights) have been allocated beginning in fall 2018 for eight consecutive semesters. Once completed, SIGNALS will provide a statistically reliable laboratory to investigate massive star formation, including over 50 000 resolved H II regions: the largest, most complete, and homogeneous data base of spectroscopically and spatially resolved extragalactic H II regions ever assembled. For each field observed, three datacubes covering the spectral bands of the filters SN1 (363–386 nm), SN2 (482–513 nm), and SN3 (647–685 nm) are gathered. The spectral resolution selected for each spectral band is 1000, 1000, and 5000, respectively. As defined, the project sample will facilitate the study of small-scale nebular physics and many other phenomena linked to star formation at a mean spatial resolution of ∼20 pc. This survey also has considerable legacy value for additional topics, including planetary nebulae, diffuse ionized gas, and supernova remnants. The purpose of this paper is to present a general outlook of the survey, notably the observing strategy, galaxy sample, and science requirements

Genetic Diversity and Antimicrobial Resistance of Escherichia coli from Human and Animal Sources Uncovers Multiple Resistances from Human Sources

Escherichia coli are widely used as indicators of fecal contamination, and in some cases to identify host sources of fecal contamination in surface water. Prevalence, genetic diversity and antimicrobial susceptibility were determined for 600 generic E. coli isolates obtained from surface water and sediment from creeks and channels along the middle Santa Ana River (MSAR) watershed of southern California, USA, after a 12 month study. Evaluation of E. coli populations along the creeks and channels showed that E. coli were more prevalent in sediment compared to surface water. E. coli populations were not significantly different (P = 0.05) between urban runoff sources and agricultural sources, however, E. coli genotypes determined by pulsed-field gel electrophoresis (PFGE) were less diverse in the agricultural sources than in urban runoff sources. PFGE also showed that E. coli populations in surface water were more diverse than in the sediment, suggesting isolates in sediment may be dominated by clonal populations.Twenty four percent (144 isolates) of the 600 isolates exhibited resistance to more than one antimicrobial agent. Most multiple resistances were associated with inputs from urban runoff and involved the antimicrobials rifampicin, tetracycline, and erythromycin. The occurrence of a greater number of E. coli with multiple antibiotic resistances from urban runoff sources than agricultural sources in this watershed provides useful evidence in planning strategies for water quality management and public health protection