Improving Upon Best Practices:  FCAR 2.0

Estell, John K.; Yoder, John David S.; Morrison, Briana B.; Mak, Fong

doi:10.18260/1-2--21512

Cited by 11 publications

(23 citation statements)

References 0 publications

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“…The EAMU performance vector is the basis of the embedded assessment model in the FCAR [45,[68][69]. The EAMU performance vector [69][70] maintains a count of the number of students whose performance for a given outcome was rated with Excellent (E), Adequate (A), Minimal (M), or Unsatisfactory (U) levels.…”

Section: ) Embedded Assessments Methodology Using Fcarmentioning

confidence: 99%

“…Course delivery in a given term is modified based on recommendations incorporated from the carried over old actions. [45,[68][69].…”

Section: ) Embedded Assessments Methodology Using Fcarmentioning

confidence: 99%

“…Several engineering programs have utilized additional software applications such as True Outcomes® to compensate for comprehensive and accurate outcomes for assessment standards that are not features of Blackboard® [34]. The Faculty of Engineering chose EvalTools® 6 since it is the only current tool employing the embedded assessment model using the FCAR and EAMU performance vector methodology [36,40,45,47,68].…”

Section: Practical Framework -Digital Platform Evaltools ®mentioning

confidence: 99%

“…EvalTools® enables high levels of faculty involvement in CQI processes with full-scale automation achieved by integrating the Administrative Assistant (AAS), Learning Management (LMS), Outcomes Assessment (OAS) and Continuous Improvement Management (CIMS) Systems [36,40,45,47,68,76]. The CIMS electronically integrates multiple results of term review outcomes from programs with CQI imput from 20 standing administrative committees at the Faculty of Engineering.…”

Section: Practical Framework -Digital Platform Evaltools ®mentioning

confidence: 99%

“…In this study, we present essential elements of an authentic outcome based assessment model implemented using web-based software EvalTools® [45,47] and embedded assessment technology employing the Faculty Course Assessment Report (FCAR) and Performance Vector Table (PVT) methodology [40,45,68] to effectively collect and report accurate cohort outcomes data scientifically aggregated from all courses in a program for credible multi-term evaluations. A nonexperimental approach employing linear regression methods is used to perform SOs trend analyses for Electrical Engineering (EE), Mechanical Engineering (ME) and Civil Engineering (CE) programs' impact evaluations at the Islamic University of Madinah.…”

Section: Introductionmentioning

confidence: 99%

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Impact Evaluations of Engineering Programs Using ABET Student Outcomes

Hussain

Spady²,

Khan

et al. 2021

IEEE Access

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Engineering programs worldwide collect and report student learning outcomes data to conduct program evaluations for quality assurance and accreditation purposes. Accreditation agencies such as ABET typically mandate that at least two years of program evaluation data be provided and for institutions to show how this data has been used for continuous quality improvement. Engineering programs rarely evaluate interventions using multi-term student outcomes information over several years, since this quantitative data generally lacks accuracy and statistical power. The quality of outcomes data is affected by obsolete assessment methods and lack of digital access and technical analysis. In this study, we present essential elements of an authentic outcome based assessment model that used web-based software and embedded assessment technology to collect and report accurate cohort outcomes for credible multi-term evaluations. A non-experimental approach employing regression analyses were used to identify trends in student outcomes and evaluate the impact for three engineering programs. Detailed rubrics provide criteria to accurately classify multi-year student outcomes. The findings of this study present practical steps for engineering programs to effectively collect and report accurate cohort outcomes data and perform credible evaluations of program interventions based on multi-year outcomes data.

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Section: ) Embedded Assessments Methodology Using Fcarmentioning

confidence: 99%

“…Course delivery in a given term is modified based on recommendations incorporated from the carried over old actions. [45,[68][69].…”

Section: ) Embedded Assessments Methodology Using Fcarmentioning

confidence: 99%

Section: Practical Framework -Digital Platform Evaltools ®mentioning

confidence: 99%

Section: Practical Framework -Digital Platform Evaltools ®mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Impact Evaluations of Engineering Programs Using ABET Student Outcomes

Hussain

Spady²,

Khan

et al. 2021

IEEE Access

View full text Add to dashboard Cite

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ABET Accreditation During and After COVID19 - Navigating the Digital Age

Hussain

Spady²,

Naqash

et al. 2020

IEEE Access

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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 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 Remote Evaluator Module 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 metaframework to achieve accurate and credible remote accreditation of engineering programs.

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