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Proposing a Feedback System to Enhance Learning Based on Key Performance Indicators

Proposing a Feedback System to Enhance Learning Based on Key Performance Indicators

Anders Berglund, Johannes Blackne, Niklas Jansson
Copyright: © 2014 |Volume: 3 |Issue: 1 |Pages: 14
ISSN: 2155-496X|EISSN: 2155-4978|EISBN13: 9781466656215|DOI: 10.4018/ijqaete.2014010101
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MLA

Berglund, Anders, et al. "Proposing a Feedback System to Enhance Learning Based on Key Performance Indicators." IJQAETE vol.3, no.1 2014: pp.1-14. http://doi.org/10.4018/ijqaete.2014010101

APA

Berglund, A., Blackne, J., & Jansson, N. (2014). Proposing a Feedback System to Enhance Learning Based on Key Performance Indicators. International Journal of Quality Assurance in Engineering and Technology Education (IJQAETE), 3(1), 1-14. http://doi.org/10.4018/ijqaete.2014010101

Chicago

Berglund, Anders, Johannes Blackne, and Niklas Jansson. "Proposing a Feedback System to Enhance Learning Based on Key Performance Indicators," International Journal of Quality Assurance in Engineering and Technology Education (IJQAETE) 3, no.1: 1-14. http://doi.org/10.4018/ijqaete.2014010101

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Abstract

This paper proposes a feedback system that is based on the self-evaluation of perceived productivity as a mechanism for detecting deviations in an engineering design student project. By monitoring key performance indicators, project members used feedback loops to recognize alarming patterns and act accordingly. The study is based on descriptive survey data that addressed three factors of influence: perceived productivity, perception of stage completion, and work-activity distribution. The productivity data was analysed by detecting patterns in the form of peaks and lows and by combining the patterns with qualitative data from observations and documented work activities. Measurements were taken every time the project team got together; 33 occasions during the course of the project, resulting in a total of 280 student responses for productivity (P) and completion (C) and 115 student replies for work activity distribution. The findings provide an extraction of peak values and low values that enables tracking of critical incidents. Through an in-depth activity log, each value was enriched with lessons learned about what took place and the consequences for the project, thus enhancing learning from past activities through systematic feedback sessions. The accumulated set of data provided distinguishable patterns for the project team to interpret. Over time this made student actions more proactive, activity execution more distinct and purposeful, and resource allocation in combination with feedback reflections more refined.

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