{'fraction_non_alphanumeric': 0.019455252918287938, 'fraction_numerical': 0.0, 'mean_word_length': 5.67965367965368, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Criterion Weights for Knowledge Management Integrated Quality Accreditation System for Indian Engineering Education Using Analytical Hierarchy Process

The engineering education system of India is becoming more and more complex due to various reasons like unmanageable number of colleges affiliated to universities, wide spectrum of student quality, multi-boss system in management and conflicting interests of stakeholders. Ever since the Accreditation board of engineering and technology (ABET) of US, Malcolm Baldrige National Quality Award (MBNQA) of US and European Foundation for Quality Management (EFQM) of UK have been established, many other countries have developed their own version of national quality award (NQA) and accreditation systems. These NQAs and accreditation systems tend to follow the general framework of the MBNQA or ABET or EFQM with different emphases on criterion. Since MBNQA has a prominent knowledge management (KM) component in it and EFQM has a strong mechanism of measuring outcomes/results, it is attempted to develop a robust framework for Knowledge Quality Management (KQM) by integrating KM and outcome components into it using systems theory. Towards this, all possible attributes and indicators to study the interaction and interrelationship of various enablers and results have been identified. In order to assign weights to the identified system variables (Enablers and Results), responses were taken electronically on a pre-defined Excel template and weights are calculated by applying AHP method.