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- 1. Original Article An automated continuous quality improvement framework for failing student outcomes based on mathematics weaknesses HA Wajid1 , Hassan Tariq Chattha1 , Bilal A Khawaja1 and Saleh Al Ahmadi1 Abstract In this paper, we present a detailed action plan under continuous quality improvement (CQI) exercise of outcomes based education framework related to Mathematics con- cerns highlighted by the Electrical Engineering (EE) Department. Failing and low per- formed student learning outcomes (SOs) and course learning outcomes (COs) in range of core EE courses were observed to be linked with weak Mathematics basis of students. This feedback was achieved through an automated CQI system in EvalTools under Faculty Class Assessment Report (FCAR) tab, where each instructor is required to make reflections about failing as well as low performed SOs and COs. Feedback was reviewed comprehensively, and mathematical concepts which significantly affect the performance of students in the core EE courses were derived. Moreover, a high level of Mathematics pre-requisite covering required mathematical concepts is identi- fied for the range of core EE courses. Consequently, well-defined tasks were assigned to continuously evaluate and monitor improvement in required Mathematics concepts to ensure SOs and COs achieved in core EE courses. Results are given to exhibit the effectiveness of continuous improvement management system (CIMS). 1 Department of Electrical Engineering, Faculty of Engineering, Islamic University of Madinah, Madinah, Saudi Arabia Corresponding author: Hafiz Abdul Wajid, Department of Electrical Engineering, Faculty of Engineering, Islamic University of Madinah, Al-Madinah Al-Munwarah, Medina 42351, Saudi Arabia. Email: hawajid@iu.edu.sa International Journal of Electrical Engineering & Education 0(0) 1–16 ! The Author(s) 2020 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/0020720920956563 journals.sagepub.com/home/ije
- 2. Keywords Outcome based education, continuous quality improvement framework, Engineering Education Introduction Quality standards are considered as a path of survival for any global organization because they provide detail of the requirements, specifications, the various guide- lines and characteristics which needs to be met by the product to meet the purpose of the product, process or the service. Some of the well-known industrial programs that set requirements for quality are Six Sigma,1 Total Quality Management,2,3 ISO 9000–9001 Quality Management System (QMS),2 the Baldrige National Quality Program (BNQP 2014) and European Foundation for Quality Model (EFQM).3,4 During the last decade,2–9 there has been a great interest in the application of quality standards in educational institutions all over the globe. This leads to global competitiveness among the educational institutions that are now seeking to employ quality programs that have the same basic principles to ensure the graduate stu- dents have the same knowledge level, skills and mutual recognition.5–7 Moreover, the expectation for better-quality graduates has been increasing which brings a gradual global shift from the content or curriculum-based education (CBE)6 to outcome based education (OBE).7–13 CBE was found lagging in terms of not meet- ing the requirements of both a) industry because of industrial revolution especially third and fourth revolution and b) academia, as it was mainly teacher-centric and identification of weaknesses in a range of activities related to teaching and learn- ing, was not possible. Furthermore, the CBE system was not defined (i.e., clear measurable statements) to address the achievements of graduate students at the completion of the academic degree. Consequently, students enrolled in renowned academic institutions across the globe often found struggling in understanding basic concepts in fundamen- tal, core, and advanced level courses of the degree plan. OBE is a relatively new system which is student’s centered and focuses more on the attainment of desired and defined knowledge and skillsets for the students which they must possess for both future knowledge creation and meeting industry requirements of skill sets.10,11 In OBE, the entire process consisting of curriculum, assess- ments, instructional strategies and performance standards7,10–12 is developed and implemented to meet desired outcomes. However, this poses a significant challenge for educationists as in OBE all assessments produce a) huge pool of information related to course and program outcome which can be used as feedback to revise and improve teaching and learning activities7,8 ; and b) this information cannot be adequately utilized to make decisions due to impractical manual processes that are either too exhaustive to complete for 2 International Journal of Electrical Engineering & Education 0(0)
- 3. timely measurement and reporting, or too minimal for basic fulfilment of accreditation requirements.9 This entirely demands an automated digital technology-based system, which can be used effectively and efficiently for qual- ity improvement of teaching and learning activities on a continuous basis. In this regard,14 outlined technology-based outcomes assessment methodology, which is capable of establishing a useful automated continuous quality improve- ment framework with a unique feature of FCAR available in EvalTools. In FCAR, each instructor is required to make reflections about the underperformed and failing COs, performance indicators (PIs), their relevant SOs concerning the assess- ments. In addition to that, they also need to suggest corrective action items (AIs) which can be implemented in the next offering of that specific course. In this work, a CQI framework is proposed based on the detailed identification of weaknesses in mathematical concepts and their connection with the core EE courses as well as other engineering modules under the EE degree. Moreover, scores of assessments play a key role in improving the COs, course contents, contents delivery methods, moderation of assessments, revising curriculum and improving educational pro- cesses to achieve desired outcomes. The implementation of the CQI framework for failings COs linked with Mathematics weaknesses is the main theme of this work. The paper is structured as follows. The next section describes the identification of Mathematics weaknesses detailed analyses of these weaknesses and their role in the overall performance of students in their degree, and the Action plan for improvement section is devoted to the improvement strategy of these failures and shortcomings. Finally, conclusive remarks are given. Framework of continuous quality enhancement The proposed methodology comprises of two phases given in flow chart: • Identification Phase: Identification and connection of Mathematics weaknesses affecting the performance of students in the core EE courses are conducted in this phase. Also, the link of these concerns with failing SOs, PIs and COs are identified; • Improvement Phase: After identifying the gaps, a framework for improvement has been proposed under the continuous quality enhancement cycle. In order to shed light on technical aspects of the current study, we give the most relevant phases for identification and improvement and recommend readers to go through the flow chart for all administrative phases. Faculty course assessment report (FCAR) Assessment of outcomes is highly desired in the setting of OBE. In this regard, an efficient tool, which can facilitate in extracting curricular grades and can make data collection process automated is highly desired. EvalTools15 is found highly Wajid et al. 3
- 4. suitable as it employs the unique features of FCAR16 and performance vector methodology EAMU (Excellent, Adequate, Minimal, or Unsatisfactory).17 Flow Chart: Detailed flow chart describing identification and improvement phases Identification Phase Improvement Phase Faculty of Engineering (Mathematics Review Committee) • Identification of weaknesses • Detailed analysis • Proposed actions Faculty of Engineering (Curriculum Committee) • Revision of course contents as per requirement Faculty of Science (Mathematics Department) • Responsible for delivery and comprehension of desired topics of Mathematics EE Departmental Academic Review Council Quality Office: End-term review Program Coordinator: Responsible for monitoring, review and assign actions to relevant committees for enhanced academic achievements Coordinator: Compilation of detailed report based on FCAR EE Instructor: Reflections and actions proposed by EE instructor as per performance of students based on COs and SOs The FCAR consists of both reflections of failing COs and required action items related to the poor performance of students in course outcomes. Furthermore, EvalTools FCAR module provides summative/formative options and consists of the following components: course description, COs indirect assessment, grade distribution, COs direct assessment, assignment list, course reflections, old action items, new action items, student outcomes assessment and performance indicators assessment.16 This means the feature of FCAR in EvalTools makes identification of weak areas of students based on their curric- ular grades in specific course outcomes so easy and automated and proposed action items by instructor automatically drives exercise of CQI. Therefore, at first, in Table 1, to present an example of reflections and action items presented in FCAR, we consider only 4 core EE courses. In second column of Table 1, a) reflections: made by faculty members teaching core EE courses to identify stu- dent’s weakness in Mathematics based on their assessment results in final exam (FE), mid-term exam (MTE), quizzes (QZ) of core EE courses; b) action items: proposed explicit solutions to improve basic mathematical concepts for a specific 4 International Journal of Electrical Engineering & Education 0(0)
- 5. core EE course. These reflections and actions items were proposed by faculty members teaching core EE courses in EvalTools under FCAR tab. Identification and comprehensive analysis of mathematics weaknesses related to EE courses It is evident from Table 1, that identification of Mathematics courses covering required Mathematics basic concepts are of utmost importance to address con- cerns highlighted by EE faculty members. We found only five Mathematics courses (Calculus I, Calculus II, Calculus III, Ordinary Differential Equations and Table 1. Reflections and proposed action items report for spring semester 2017. Feedback of faculty members teaching core EE courses related to weaknesses in basic mathe- matical concepts through FCAR Course Title a). Reflections b). Action Items Electrical Machinery CO_6, PI_11_20; SO_11; FE-Q3: The comprehension of students in the topics related to induction motors is poor due to poor mathematical skills and poor background of Electro-Magnetic Theory (EMT). Improvement of basic math skills such as basics of vectors, integral and differential vector calculus, fundamental coordinate systems and complex numbers is required. Circuit Theory II CO_1; PI_5_34; SO_5; MTE-1-Q1: Students were unable to solve 2 equations with 2 unknown variables. There should be extra tutorials to cover the shortcomings of the mathematical skills of students during the summer. Electrical Power Transmission and Distribution CO_4; PI_11_58; SO_11; QZ2, MTE-1-Q2: The students did not comprehend the topic related to evaluating different types of overhead line supports and their insulators due to weak mathe- matical skills. The numerical problems are lengthy and highly mathematical which need a sound base in mathematics. Additional solved examples in class, quiz or assignments should be administered related to design or analysis of overhead transmission line conductor. Signals and Systems CO_8; PI_11_54; SO_11; QZ-4, MTE-2-Q3: Students are unable to find the Fourier Transform and Inverse Fourier Transform math- ematically related to the continu- ous-time signals. Department of Mathematics needs to be notified for review of the basic math skills such as integration. Wajid et al. 5
- 7. Table 3. Accreditation Board for Engineering and Technology (ABET) SOs coverage by core EE courses and connection with relevant Mathematics courses. Mathematics course and brief description ABET SOs Required by EE courses Engineering Mathematics: Matrix algebra and applica- tions of matrics to solve linear system of equations, vector calculus with appli- cations like arc length and wrokdone, functions of complex variables, differ- entiation and integration of functions of complex vari- ables and introduction to partial differential equa- tions and solutions of PDEs using separation of variables SO_1: Applying: Explain the fundamen- tals of controls theory and types of control systems Controls Theory SO_1: Applying: Recognize and explain schematic diagrams for various con- trol system equipment and systems such as block diagrams and signal flow graphs SO_1: Understanding: Design state- feedback controller based on modern control theory, Discuss its applications and Explain the funda- mentals of digital control theory SO_5: Analysing: Solve unit commit- ment problems using various meth- ods and describe unit commitment constraints and understand related formulae such as the objective func- tion, the unit limits and loading constraints Power Systems Operation and Control Ordinary Differential Equations: Basic concepts differential equation, differ- ent types of differential equations and their solu- tions. Laplace transform and its applications SO_1: Analysing: State the definitions of fundamental concepts and parame- ters used in modelling electric cir- cuits, such as charge, current, voltage, power, energy, ideal sources and passive sign convention Circuit Theory I SO_1: Understanding: Represent con- tinuous-time (CT) and discrete-time (DT) signals in complex exponential and sinusoidal forms Signals and Systems SO_11: Analysing: Determine linear time-invariant (LTI) system response by applying the convolution sum and convolution integral techniques SO_11: Evaluating: Use Continuous- Time Fourier transform to analyze the frequency spectrum of aperiodic signals, employing tables of Fourier transform pairs and properties SO_11: Evaluating: Use Discrete-Time Fourier transform to analyze the (continued) Wajid et al. 7
- 8. Table 3. Continued Mathematics course and brief description ABET SOs Required by EE courses frequency spectrum of aperiodic sig- nals, employing tables of Fourier transform pairs and properties SO_1: Understanding: Classify a system as linear or non-linear, time-varying or time-invariant, causal or non- causal Communication Theory SO_5: Evaluating: Derive impulse response and the transfer function of a linear time-invariant (LTI) system Calculus III: Sequences and series, analytical geometry in 3D and 3D coordinate system, vectors and its basics, multivariable calcu- lus (differntiation and inte- gartion of functions of more than one variables) SO_1: Applying: Develop admittance model of a power transmission network Electrical Power Transmission and Distribution SO_11: Analysing: Calculate the real, reactive power flows and losses on a transmission network using power flow algorithms SO_1: Understanding: Describe the construction and operation of syn- chronous motor/generator and verify in the lab Electrical Machinery SO_5: Creating: Analyze the steady- state performance of basic (single- phase) transformers SO_5: Creating: Analyze the steady- state operation of the synchronous motor/generator by deriving their equivalent circuit and verify in the lab SO_11: Analysing: Derive the equiva- lent circuit and characteristics of the induction motor and verify in the lab SO_5: Analysing: Calculate the high- frequency response of basic transis- tor circuit configurations Electronics II SO_5: Evaluating: Examine the perfor- mance of the given thyristor rectifier circuits both theoretically and in practical settings Power Electronics SO_5: Analysing: Analyze a balanced, three-phase wye-wye and wye-delta connected Circuit Theory II (continued) 8 International Journal of Electrical Engineering & Education 0(0)
- 9. Engineering Mathematics) taken by EE students are relevant in this regard as given in Table 2. Moreover, a high level of Mathematics pre-requisite is identified, so we can address these concerns and present a CQI framework in order to ensure students achieve desired COs which leads to attaining required skill and knowledge sets at the program level. Also, failing in any Mathematics course means the stu- dent can not register for core EE course, and he/she is required to retake Mathematics course and must pass. In this study, we focus on core EE courses (see Table 3) and analyse the role of Mathematics concepts that must have mastered by students to achieve learning objectives of core EE courses (i.e. good performance or grades in course outcomes). Table 3. Continued Mathematics course and brief description ABET SOs Required by EE courses SO_5: Analysing: Calculate power (average, reactive and complex) in a three-phase circuit and verify in the lab experiment SO_5: Evaluating: Calculate average power in an electric circuit excited by a periodic voltage or current signal Calculus II: Integration of single variable fuctions and applications of integrals specifically area under the curve SO_11: Evaluating: Determine the Laplace transform of a function Circuit Theory I & Circuit Theory II SO_11: Evaluating: Calculate the inverse Laplace transform using par- tial fraction expansion SO_11: Analysing: Determine the trig- onometric and exponential Fourier series for a periodic signal SO_11: Evaluating: Apply the Laplace transform to analyze the circuits in s- domain Calculus I: Basics of single variable functions, limits, continuity and differentiation SO_1: Analysing: Compute the number of channels per cell and maximum channel capacity for different fre- quency re-use systems Wireless and Mobile Communications SO_5: Analysing: Define and apply Gauss’s law, divergence and Maxwell’s first equation Electromagnetic Field Theory Fourier series (Not covered by any MATHS course) Signal and Systems Wajid et al. 9
- 11. The assessment of outcomes plays a vital role in an OBE system, and two methods known as direct assessment and indirect assessments are used for the measurement of outcomes. Course completion survey, exit survey, alumni survey and employer survey are part of indirect assessment, whereas COs and SOs are covered in direct assessment.18,19 Therefore, the identification of COs, PIs, SOs, Bloom’s learning domains, types of assessments used, and percentage weightage of assessments in core EE courses affected by poor basics of Mathematics is considered. Assessments are graded using four different types of formats given in Table 4.14 Corresponding to each type of assessment method, the percentage and multiplica- tion factors are given in Table 4. Multiplication factors are needed when a single SO is linked with multiple Cos.14 The course instructor must assess the performance of students covering both skill and knowledge sets in order to measure COs. Usually, exams, quizzes, home- works, projects etc. are used which are part of direct assessment methods. In our case, we found that only three SOs (see Table 5) out of 11 ABET SOs are found linked related to assessment methods such as homeworks, quizzes and exams used by core EE courses. This is consistent as only these SOs (1, 5 and 11) are related to Mathematics. A threshold is always chosen to determine the achievement level of the COs. A threshold value of 60% is considered for data given in Table 6, respectively, to define the success of students. Moreover, for the success of course delivery 60% of students registered in a course must achieve these COs and SOs.16,17 Students achievements are measured using the following percentage levels17 (90–100%: fully achieved, 80–90%: excellently achieved, 70–80%: achieved, 60–70%: satisfac- torily achieved, below 60%: failed). In order to analyse the role of basics of Mathematics requires to achieve course outcomes of core EE courses, we present data for spring semester 2017 in the form of groups based on three ABET SOs. Marks weightage out of 100 is considered for each EE course based on assessment grading formats given in Table 4. Moreover, it is highly essential to measure the percentage of assessments used corresponding to the failing COs by all EE courses for concerned SOs. Percentage of the marks given in Table 6 is an aggregation of all core EE courses mentioned in Table 3. As an example, we consider the course of Circuit Theory I, and the assessment was Mid-Term I Exam (Question No. 01, 20 marks out of 100). First, we identify the Table 5. ABET SOs assessed by the EE Department linked with mathematical concepts. SO_No. ABET SOs for EE courses SO_1 An ability to apply knowledge of mathematics, science, and engineering SO_5 An ability to identify, formulate, and solve engineering problems SO_11 An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice Wajid et al. 11
- 13. assessment format used for weightage of MTE-I, which is assessment format number 3 (see Table 4) and it has 15% weightage out of 100 marks. So, 20 marks out of 100 are just 3% of total 100 marks for Circuit Theory I course. Likewise, each assessment percentages were measured corresponding to each core EE course. Finally, we calculate percentage participation of ABET SO_1, SO_5 and SO_11 for COs of a range of EE courses (given in Table 3) offered throughout the degree plan affected by weak Mathematics basics and found 7.21%, 6.38% and 10.56% involvement of ABET SO_1, SO_5 and SO_11, respectively. These figures indeed signify the importance of a framework for continuous improvement, when it comes to teaching Mathematics courses. Moreover, course contents, curriculum and edu- cational processes for Mathematics, as a whole need to be reconsidered to achieve targeted outcomes of core engineering disciplines. Interestingly, more than 95% of Mathematics courses are taught by the Faculty of Science, which is another sig- nificant constraint when it comes to improving the required Mathematics basics. This indeed poses a significant challenge, when it comes to dealing with concerns of the EE Department. Table 7. Mathematics concerns action plan for EE courses. CALCULUS I: Instructors from the Faculty of Engineering and Science (specifically instructor for PHYSICS 1 course) must reinforce fundamental principles of differentiating rules with a primary focus on applications. CALCULUS II: Mathematics instructor from the Faculty of Science is requested to arrange one- hour mandatory tutorial session per week and share list of basic integration formulae and an example of the partial fraction at the beginning of the semester. Moreover, cover the appli- cation of integration which is the area under the curve by devoting 10 minutes in any topic relevant they find. However, instructor of course Probability and Statistics is specifically requested to cover this in Normal Distribution topic. CALCULUS III: Mathematics instructor from the Faculty of Science is requested to give extra practice sheets related to triple integration and basics of vectors, mainly focusing more on applications. Moreover, the instructor for Engineering Mathematics is requested to cover the basics of vectors as well. ORDINARY DIFFERENTIAL EQUATIONS: Department of Mathematics, Faculty of Science is requested to arrange at least one tutorial session for Laplace transforms and also share a list of basic Laplace transforms. ENGINEERING MATHEMATICS: Faculty of Engineering, Curriculum Committee is asked to consider revision of contents of course Engineering Mathematics. Moreover, instructor for this course is requested to arrange a tutorial session as per need to develop sound base related to desired Mathematics topics along with all lecturers of Faculty of Engineering. Moreover, Engineering Mathematics instructor is requested to give extra practice sheets related to desired topics. Finally, for the Fourier series topic, curriculum committee is requested to ensure inclusion of Fourier series as it is not covered by any other Mathematics courses taken by EE students. Wajid et al. 13
- 14. Another important dimension for analysing the role of failing COs is to identify skills and learning level corresponding to assessment used in the core EE courses. It was found that assessments were addressing i) only Cognitive domain for learn- ing ii) involved all levels of skills set (elementary, intermediate and advanced) iii) 5 learning levels of Bloom’s taxonomy are covered. It is evident that 15% of ques- tions used for assessments were at the elementary level of skill set and understand- ing level of knowledge set. More interestingly, they were just mapped to SO_1. More than half of assessments 52.5% (consisting of 15% at the application level (covering SO_1 only) and 37.5% at analyzing level (covering SO_1, SO_5 and SO_11) are addressing the intermediate level of skill sets. Furthermore, almost one-third 32.5% of assessments are found related to Advanced Level skills cover- ing SO_5 and SO_11, whereas following is the distribution of Blooms learning levels, i.e., evaluation level 25% and 7.5% at creation level. These findings given in Table 6 signifies the importance of considering them and fixing them through the continuous quality framework. Action plan for improvement Based on the analysis presented in the previous section, we now consider key factors linked with improving the COs, course contents, contents delivery methods, moderation of assessments, revising curriculum and improving educational pro- cesses to achieve desired outcomes. In Table 7, a brief action plan for each Mathematics course is given considering the reflection and actions proposed by faculty members teaching core EE courses. The proposed changes are made with great care assigning task explicitly to the concerned faculty teaching the mentioned Mathematics courses and making sure applications of underlying basics of Mathematics are taught to EE students. Moreover, the addition of tutorial sessions is made mandatory so that EE students can comprehend the basics of Mathematics more rigorously. Moreover, few topics such as Fourier series is added in the con- tents of Engineering Mathematics course. Conclusions The global shift in engineering education from CBE to OBE imposed by the Washington Accord20 binds the engineering institutions to assess and evaluate the student learning outcomes. Therefore, ensuring that graduates have achieved the desired educational objectives, a continuous quality improvement and man- agement framework is a mandatory activity for the course improvement. This paper has presented a detailed action plan under the CQI exercise of the OBE framework related to Mathematics concerns highlighted by the faculty mem- bers at the Department of Electrical Engineering, Faculty of Engineering, IUM, KSA. The underperformed or failing COs, their relevant PIs and SOs for a range of core EE courses were observed to be linked with weak Mathematics basis of the students. This feedback was achieved by using an automated CQI system in place 14 International Journal of Electrical Engineering & Education 0(0)
- 15. EvalTools under FCAR. The achieved course-specific feedback was reviewed com- prehensively, and the Mathematics concepts significantly affecting the perfor- mance of students in the core EE courses were derived. Consequently, factors serving as a major impediment in achieving students learning outcomes were identified, and an action plan is proposed with the follow- ing strengths: a. Proper linkage of mathematical concerns and identification of the high level of Mathematics pre-requisite for each EE course; b. Estimation of percentage weightage of assessments for failing core EE course outcomes; c. Use of continuous quality improvement (CQI) processes. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, author- ship, and/or publication of this article. Funding The author(s) received no financial support for the research, authorship, and/or publication of this article. ORCID iDs HA Wajid https://orcid.org/0000-0003-1690-0823 Bilal A Khawaja https://orcid.org/0000-0003-1537-5502 References 1. Tetteh GA. Evaluating university leadership performance using lean six sigma frame- work. Int J Lean Six Sigma 2019; 10: 1018–1040. 2. Khan MN, Malik SA and Janjua SY. Total quality management practices and work- related outcomes: a case study of higher education institutions in Pakistan. Int J Qual Reliability Manage 2019; 36: 864–874. 3. Rodriguez J, Valenzuela M and Ayuyao N. TQM paradigm for higher education in the Philippines. Qual Assur Educ 2018; 26: 101–114. 4. Goetsch DL and Davis SB. Quality management for organizational excellence. 6th ed. New Jersey, NJ, USA: Pearson, 2010. 5. Al-Yahya SA and Abdel-Halim MA. A successful experience of ABET accreditation of an electrical engineering program. IEEE Trans Educ 2013; 56: 165–173. 6. Aldowaisan T and Allahverdi A. Continuous improvement in the industrial and man- agement systems engineering programme at Kuwait University. Eur J Eng Educ 2016; 41: 369–379. 7. Qadir J, Shafi A, Al-Fuqaha A, et al. Outcome-based engineering education: a global report of international OBE accreditation and assessment practices, edarxiv.org/rde62 (accessed 5 June 2020). Wajid et al. 15
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