Project: Supporting Novice & Expert Strategies for Energy Model Assessment in an Energy Management Information System

Partner: FedDev ARC
Dates: 2012 - 2013
Participants: Jamieson, G., Hilliard, A.
Description: Drawing from participant observation and a field study of energy efficiency, this work addressed the information required to assess the quality of a decision aid. The standard energy management practice of Energy Monitoring & Targeting (M&T) uses empirical model-driven statistics to produce a summary decision-aiding CUSUM chart. This study determined that users could not reliably interpret CUSUM charts, in part because they could not assess what the empirical model 'behind' the chart represented. The result was a prototype energy model explanatory report developed through heuristic evaluation and user-centered design. It was designed to support both novice (associative and criteria-based) and expert (statistical reasoning) assessment strategies.

View PDF Hilliard, A. (2015). "Energy Monitoring and Targeting as diagnosis; Applying work analysis to adapt a statistical change detection strategy using representation aiding" (Ph.D.). University of Toronto (Canada), Ann Arbor. Retrieved from Dissertations & Theses @ University of Toronto; ProQuest Dissertations & Theses Global. (1759161412)

View PDF Hilliard, A., Jamieson, G. A., & Jorjani, D. (2014). "Communicating a Model-Based Energy Performance Indicator." Ergonomics in Design: The Quarterly of Human Factors Applications, 22(4), 21–29.

View PDF Hilliard, A., & Jamieson, G. A. (2014). "A Strategy-Based Ecological(?) Display for Time-Series Structural Change Diagnosis." In Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics (pp. 353–358). San Diego, CA: IEEE.

View PDF Hilliard, A., & Jamieson, G. A. (2014). "Monitoring & Targeting Energy in Practice: A Field Study." In Proceedings of the 2014 ECEEE Summer Study in Industry (pp. 591–601). Arnhem, NL: European Council for an Energy Efficient Economy. Retrieved from

View PDF Hilliard, A., & Jamieson, G. A. (2013). "Recursive Estimates as an Extension to CUSUM-based Energy Monitoring & Targeting". In Proceedings of the 2013 ACEEE Summer Study on Energy Efficiency in Industry (pp. 4–1..4–13). Niagara Falls, NY: ACEEE. Retrieved from

« View all projects