Measurement and Metrics
Research gap analysis derived from 2 engineering papers in our local library.
The gap
The papers collectively call for more precise measurement methods, including objective metrics (Paper 1), specific behavioral metrics (Paper 3), detailed performance indicators (Papers 2, 5, 8), and outcome-based KPIs (Papers 9, 10).
Consensus across the literature
The papers leave open the need for more rigorous and specific measurement tools to validate their findings.
Research trend
Emerging — attention growing, methods still coalescing.
Supporting evidence — 2 representative gaps
- Artificial intelligence system reliability and knowledge identity: A model for knowledge workers in knowledge management environments (2026) · doi
Future research could balance perception-based work with objective metrics (i.e., system log data, number and rates of errors, or response time) to enhance the precision of measurement.
Keywords: future balance perception based objective metrics system number rates errors response time enhance precision measurement - Speech-Driven AI Assistant Using Hidden Markov Model (2026) · doi
The system's accuracy rates, precision, recall, and other quantitative performance metrics are not explicitly reported.
Keywords: system accuracy rates precision recall quantitative performance metrics explicitly reported
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