AI Article Synopsis

  • Accreditation agencies require engineering programs to assess learning outcomes, but many are resorting to quick fixes that compromise the rigor needed for effective Continuous Quality Improvement (CQI).
  • The COVID-19 pandemic has complicated these processes, leading to cancelled onsite visits and a shift to virtual audits, increasing the need for reliable evaluation methods.
  • This study introduces a digital Integrated Quality Management System meta-framework designed to automate the collection and reporting of CQI data, facilitating successful virtual accreditation audits for engineering programs.

Article Abstract

Engineering accreditation agencies and governmental educational bodies worldwide require programs to evaluate specific learning outcomes information for attainment of student learning and establish accountability. Ranking and accreditation have resulted in programs adopting shortcut approaches to collate cohort information with minimally acceptable rigor for Continuous Quality Improvement (CQI). With tens of thousands of engineering programs seeking accreditation, qualifying program evaluations that are based on reliable and accurate cohort outcomes is becoming increasingly complex and is high stakes. Manual data collection processes and vague performance criteria assimilate inaccurate or insufficient learning outcomes information that cannot be used for effective CQI. Additionally, due to the COVID19 global pandemic, many accreditation bodies have cancelled onsite visits and either deferred or announced virtual audit visits for upcoming accreditation cycles. In this study, we examine a novel meta-framework to qualify state of the art digital Integrated Quality Management Systems for three engineering programs seeking accreditation. The digital quality systems utilize authentic OBE frameworks and assessment methodology to automate collection, evaluation and reporting of precision CQI data. A novel that enables successful virtual ABET accreditation audits is presented. A theory based mixed methods approach is applied for evaluations. Detailed results and discussions show how various phases of the meta-framework help to qualify the context, construct, causal links, processes, technology, data collection and outcomes of comprehensive CQI efforts. Key stakeholders such as accreditation agencies and universities can adopt this multi-dimensional approach for employing a holistic meta-framework to achieve accurate and credible remote accreditation of engineering programs.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675559PMC
http://dx.doi.org/10.1109/ACCESS.2020.3041736DOI Listing

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