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  • Advanced Diagnostics Based On Program & Student Outcome Evaluations

    At Faculty of Engineering, IU both program and students performance evaluations are based on considering their respective measured ABET SOs and associated PIs as a relevant indicator scheme. Figures below show results of EE Program ABET SOs collected for terms 351 and 352. The performance indicator related to ABET_SO_1: An ability to apply the knowledge of mathematics, science and engineering; is PI_1_27: Apply basic laws and formulas of circuit theory, such as Ohm’s and Kirchoff’s laws as well as circuit theorems to analyze/simplify circuits (Thevenin and Norton, superposition principle, max power transfer theorem, transformation etc.). PI_1_27 shows a pattern of underperformance for the two terms 351, 352 in courses such as Circuit Theory-I, Circuit Theory-II and Fundamentals of Electrical Engineering. 

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    This is also observed in figurebelow where individual student evaluations confirm the failing pattern for PI_1_27. In this figure are highlighted certain areas of comparatively better patterns of learning in a typical underperforming EE student.

    Study of student failing patterns in these individual student evaluations will confirm any major weakness observed through the collectively averaged outcome data in program evaluations and further investigations of the respective course FCARs will help determine specific areas such as course content (breadth and/or depth), teaching materials, and/or pedagogical/ assessment methodology for realistic program and student improvement.

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    As a sample case if we investigate PI_1_27 failures from the FCAR for Circuit Theory-I we find as shown in figure below a pattern of failures indicated by multiple unique assessments utilized for measuring the skill relating to the application of basic electrical engineering laws to circuits. 

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    This is further substantiated by examining the objective evidence Final Exam Part-III Q45 as illustrated in figure below.

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    All documentation whether faculty submittals to students or graded student work are scanned and available in a digital database for instant access (refer to figures below). 

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    In Figure below the course reflections and action items suggest weakness in fundamental math skills as an underlying cause of underperformance. 

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    By examination of academically weak or strong students’ evaluations it is also possible to identify areas of strength in learning which are based on the students’ natural affinity to and interest in certain topics. Figure below illustrates a list of ABET SOs calculated from PIs measurements for a typical student evaluation. 

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    From figures above we observe that PI_1_12: Employ basic electrical power formulations and quantities, such as complex vectors, delta star transformation, network flow matrices (network topology and incidence matrices) and symmetrical components; PI_1_41: Convert a given number from one system to an equivalent number in another system; and PI_1_45: Explain basic semiconductors theory concepts such as applied electrical field, junction capacitance, drift/diffusion currents, semiconductor conductivity, doping, electron, hole concentrations, N-type, P-type semiconductors; show better performance and are at a stark contrast versus majority of the other PIs measured for these two terms. One significant observation is that these three PIs measure elementary math skills and concepts and also cover relatively easier topics such as Boolean algebra. The other PIs dealing with topics such as operating principles of various kinds of electronic devices and components, Application of Gauss’s Law, Maxwell’s equations etc. require slightly advanced learning of several engineering concepts and understanding of differential, integral calculus. 

    This information strongly suggests that students have initiated learning with the required level of interest but at later stages of the course they may need other mechanisms of course delivery such as active learning for retention of focus and enhanced learning. Student advising based on this information helps faculty to identify potential areas of strength or weakness in student performance through the observation of patterns of relatively high or low scores for certain ABET SO, CO related PIs. 

    Most academic or career related failures result from an improper selection of the field of study or industrial career due to delay or lack of availability of the necessary decision making student learning outcome information in a deficient education system. With the availability of such analytical tools and comprehensive diagnostics early identification of weakness and prompt remediation efforts are quite possible. On the other hand early recognition of strong skills in specific subjects based on well observed patterns followed by professional academic guidance leading to proper selection of an area of specialization in education, research for enhanced learning or in future industry related prospects will produce outstanding performers in their respective fields who will shape the future of the world.  

    Program, student evaluations, assessments and advising based on measurable ABET SOs, COs and PIs facilitate an outcome based education system and help the students to focus not just  on improvement of academic scores but learning outcomes since the academic scores to a good extent reflect performance relative to learning outcomes.