Authored and published by Aspiring Minds research and development team, these white papers touch a variety of topics in helping understand assessment, human capital quality and mapping.

National Employability Report - Engineers Annual Report 2014

The National Employability Report - Engineers, 2014 is an analytical study of the employability quotient of Indian engineers. It has over the years become an authoritative source for employability statistics for engineers and an auditory mechanism for higher education. The present report aims to delve further into the employability situation and also focuses on job aspirations of engineers. It also aims to understand what factors apart from merit influence employability outcomes.

 

National Employability Report - Hotel Management Graduates, 2014

The National Employability Report-Hotel Management Graduates 2014 is based on objective assessment (AMCAT-Hospitality) data of more than 4000 Hotel Management students from 140+ Hotel Management colleges across India. The report aims to analyze the employability variances across various groups to gain understanding of the needs and the gaps in the field and suggest required targeted intervention to bridge the same. The report also tries to understand the aspirations of the youth today when it comes to hospitality jobs.

 

A system to grade computer programming skills using machine learning

The automatic evaluation of computer programs is a nascent area of research with a potential for large-scale impact. Extant program assessment systems score mostly based on the number of test-cases passed, providing no insight into the competency of the programmer. In this paper, we present a machine learning framework to automatically grade computer programs. To get full report click here.

 
 

Principles for using Machine Learning in the Assessment of Open Response Items: Programming Assessment as a Case Study

Principles for using Machine Learning in the Assessment of Open Response Items: Programming Assessment as a case study, questions demanding subjective (open) responses have been considered to be the most desirable assessment format in order to gauge candidate learning. Such questions allow candidates to express creatively and help evaluators to understand a candidate's thought process. The evaluation of such subjective responses, however, has traditionally required human expertise and is challenging to automate. On the other hand, automated assessments provide scalability, standardization and efficiency.

Presented at NIPS Workshop on Data Driven Education, Reno, USA, 2013

 

Women in Engineering: A comparative study of barriers across nations

The Aspiring Minds report titled "Women in Engineering: A comparative study of barriers across nations" is an analytical study of trends for women in engineering in India. It aims to understand by way of comparison with the United States, that in what ways does engineering represent a space for progress for women in India and what and where do the barriers lie in terms of environmental factors and male-female ratio in India's engineering colleges.