Girls’ higher education in India on the road to inclusiveness: on track but heading where?

The scope of this paper spans from macro-level national and inter-state comparisons to more micro-level intra-state scrutiny of systemic fault-lines shaping the contours of girls’ education in India. Post independence, national level indicators have been suggestive of greater gender parity. Yet, there is more to inclusiveness of girls in Indian higher education than increasing absolute numbers or improving gender ratios. Rising female participation has coincided with a massive ‘systemic expansion’ of delivery systems and therefore, would have to be a function of this expanded availability. As a corollary, systemic skews and limitations, both qualitative and quantitative, are bound to influence how girls get incorporated into the system. This would matter not just in terms of how many access it, but also what courses do they access and where. In the course of this paper, we scan through several geographic layers of delivery systems to surface how critical systemic traits are shaping access to higher education in India, and how girls remain particularly vulnerable to them. It reveals how the progress achieved so far has spawned its own hierarchies, which do not get reflected adequately in the national level indicators. As we scale down to states, the first set of skews begins to surface in the form of inter-state disparities of access and uneven faculty-wise distributions. Moving to the next level of geographic dis-aggregation, further skews are revealed based on availability of medium of instruction; as also the guidelines of gender based affirmative action meant for improving girls’ participation that ironically end up creating their own distortions. Through a study of these multi-layered hurdles, this paper brings forth the systemic side of impediments that have remained less explored in comparison with the cultural-attitudinal biases that have plagued girls’ participation to higher education in India.     

Decoding Reed-Solomon codes using Euclid’s algorithm

Reed-Solomon codes are indeed an elegant illustration of a very practical application of abstract algebra. An interesting discovery was the fact that Euclid’s algorithm for finding greatest common divisors of polynomials, could be used for decoding these codes. In this article we explain this connection. Priti Shankar is with the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore. Her interests are in theoretical computer science and error correcting codes.     

Profiles of Childhood Maltreatment: Associations with Sexual Risk Behavior during Adolescence in a Sample of Racial/Ethnic Minority Girls

This study examines associations between childhood maltreatment and developmental trajectories of sexual risk behaviors (SRBs) in a sample of 882 sexually active adolescent girls, predominantly Hispanic or Black, assessed every 6 months between 13 and 23 years. Latent profile analyses revealed four distinct maltreatment profiles: Low Maltreatment (76%), Moderate Emotional Neglect Only (15%), Severe Physical/Emotional Abuse (3%), and Severe Sexual Abuse (6%). Multilevel growth analyses showed the Moderate Emotional Neglect Only and Severe Sexual Abuse profiles exhibited more SRBs starting in late adolescence, and the Severe Sexual Abuse profile also exhibited a faster increase than the Low Maltreatment profile. Understanding heterogeneity within maltreated populations may have important implications for healthy sexual development.     

Web caching

The World Wide Web has been growing in leaps and bounds. Studies have indicated that this massive distributed system can benefit greatly by making use of appropriate caching methods. Intelligent Web caching can lessen the burden on Web servers, improves its performance and at the same time reduces the network traffic.     

Student satisfaction with R vs. Excel in Data Mining and Business Analytics: A Herzberg's motivation-hygiene theory perspective

Applying Herzberg's motivation-hygiene theory, we studied the determinants of student satisfaction in using R in a Decision Support Systems course that previously used Excel to teach Data Mining and Business Analytics (DMBA). The course is a degree requirement, and prior programming experience is not a prerequisite. We hypothesized that motivators for student satisfaction with R would include: (i) an intrinsic interest in DMBA, (ii) a perception that R is a better tool than Excel for DMBA, and (iii) a favorable view of R as a facilitator of career advancement. We postulated that the hygiene factor was the compulsory course requirement to learn R, a new and challenging language to students in this study. Data from 120 students, analyzed using Principal Component Analysis (PCA) and Generalized Additive Modeling (GAM), showed that motivators were positively related to satisfaction while hygiene factors were neutral. Students showed willingness to take on a harder challenge in exchange for intrinsic and future career benefits. The model can be useful in curriculum design or career advisement to increase student satisfaction in learning new software skills while meeting market demands.