Quantifying the Comprehensiveness of an Academic Computing Program’s Continuous Improvement Plan

Abstract

This Research to Practice Full Paper presents the findings of our research about the comprehensiveness of continuous improvement plans and initiatives at academic computing programs. Continuous improvement (CI) plans consist of 8 components: (1) Administration, (2) Curriculum, (3) Course, (4) Faculty, (5) Research, (6) Academic Advising, (7) Facilities, and (8) Support Staff. To implement a truly comprehensive CI plan, an academic computing program must address all 8 CI components by identifying the types of data used for improving each one. For each component, this data can be produced internally (by the CI component itself) or externally (by other CI components). The degree to which two components exchange CI data determines the quality of their CI integration.In this paper, we detail a comprehensive list of data types used for each component’s continuous improvement. We also propose a quantifiable model (360-CI) to "measure" the comprehensiveness of an academic computing program’s continuous improvement plan or initiative. This model is represented by the Academic Computing Continuous Improvement Scoring Survey (ACCISS). ACCISS uses the list of continuous improvement data types to reveal the ones produced and utilized within an academic computing program. ACCISS also aims at identifying potential new data types that can be added to the comprehensive list. The results of the questionnaire can then be mapped to the 360-CI model to generate a comprehensiveness score out of 360.The questionnaire tool was administered at a large electrical engineering and computer science program. A high response rate provided us with confidence in the results of the generated score. The paper details the process of the questionnaire implementation, the results (including the comprehensiveness score), and the lessons to be learned when the questionnaire is administered in the future. The results also help this specific program identify areas for improvement in their continuous improvement process.