Automated Framework for Evaluating Sustainability and Resilience in Higher Education Curriculum

With the growing focus on sustainability and resilience, it is imperative and important to evaluate the readiness of higher education institutions (HEIs) in this field. The curriculums are the foundation of academic learning and practical experiences in higher education. It is required to include sustainability and resiliency related courses as part of curriculum for a future ready academic framework. In order to develop and design new courses, the reconnaissance of existing curriculum system has to be carried out to understand the current state of course offerings in context of sustainability and resiliency. With increasing number of universities, institutions and courses across the globe, manual review of the existing system is not feasible. Considering the advances in data analytics technology, this study proposes an automated framework for evaluating the curriculums of HEIs. An automated web crawler-based tool was developed using open-source python as coding language and google colab as the developing and testing platform. The automation framework was developed using four step approach—(a) Preparation of the training dataset using course catalogue websites of the selected universities, (b) Identification of the patterns of course information arrangement across different websites and developing algorithms for scraping the course related data from catalogue web page (c) Normalization of web response from catalogue web pages of different universities to list down the set of common information available across most of the catalogue information. This information formed the base for the schema designed for the extraction of course related data. (d) Automated framework was developed and validated. This tool can read the contents of course catalogue from the website of universities and further perform data collection and analysis of the courses. The system was developed for a subset of universities in United States. The data so collected from the automated system can be further analysed using computational method of text analytics and keyword ontology. As a final outcome, this tool lists the courses in the area of sustainability and resilience and provides insight into the type of the courses. This outcome can be effectively used to identify the gap and thus preparing the list of courses to be developed and designed for an efficient and future ready curriculum.