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Volume 22, Number 1, 2020 © WIETE 2020

Global Journal of Engineering Education

Measurable performance indicators of student learning outcomes: a case study

Tahar Ayadat, Danish Ahmed, Saidur Chowdhury & Andi Asiz
Prince Mohammad Bin Fahd University
Al Khobar, Kingdom of Saudi Arabia

ABSTRACT: Determining student learning outcomes is a crucial step in maintaining and improving teaching and
learning quality in education. Accrediting bodies require educational institutions to develop assessment systems to
analyse students learning outcomes. The main objective of this article is to discuss learning outcomes using performance
indicators within rubric-based assessment systems. This article complements various studies about assessment and was
intended for newly established engineering programmes seeking international accreditation. In this study, an example
was given of a grading scale mapped to performance indicators. The student learning outcomes at the programme level
were determined by combining and averaging the performance indicators of programme courses. Comparative analysis
was conducted between the direct assessment results and those of indirect assessments based on surveys distributed to
programme constituents including students, alumni and employers.

Keywords: Learning outcomes, teaching assessment, accreditation, continuous improvement, engineering education

INTRODUCTION

Student learning outcomes can be defined as a student’s ability to demonstrate a set of skills after completing
a course. Educational experts distinguish between student learning outcomes at the course, programme and institutional
levels [1]. They are interlinked and can be assessed qualitatively or quantitatively using measurable performance
indicators for each outcome [2-4].

Student learning outcomes at the course levels must cover the learning hierarchy as proposed by Bloom’s taxonomy,
starting from attainment of knowledge, comprehension or understanding, application, analysis, synthesis and
evaluation [5][6].

At the programme level, interpersonal (behavioural or attitude) skills including written and oral communications, ethics
and professionalism, teamwork and leadership must be incorporated to ensure students also possess the skills to succeed
in a professional setting. Student learning outcomes at the programme level can be derived from the learning outcomes
at the course level, and the learning outcomes at the institutional level can be derived from the learning outcomes at
the programme level.

In engineering education, students are expected to achieve these technical outcomes: to design engineering components
or systems; to apply knowledge of science and mathematics in engineering; and to conduct and interpret engineering
experiments. Other outcomes include interpersonal skills, such as written and oral communication, teamwork and
leadership, and lifelong learning [7][8].

At the Prince Mohammad Bin Fahd University (PMU), student learning outcomes for the civil engineering programme
follow the Accreditation Board for Engineering and Technology (ABET) student outcomes, which cover technical and
soft skills. The ABET is an international accreditation body with headquarters in the United States, and most of ABET-
accredited engineering programmes use ABET-prescribed student outcomes. However, ABET suggests that programmes
seeking accreditation can develop their own student learning outcomes at the programme level, provided they are in line
with the outcomes below:

(a) an ability to apply knowledge of mathematics, science, and engineering

(b) an ability to design and conduct experiments, as well as to analyse and interpret data

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(c) an ability to design a system, component, or process to meet desired needs within realistic constraints such as
economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
(d) an ability to function on multidisciplinary teams
(e) an ability to identify, formulate, and solve engineering problems
(f) an understanding of professional and ethical responsibility
(g) an ability to communicate effectively
(h) the broad education necessary to understand the impact of engineering solutions in a global, economic,
environmental, and societal context
(i) a recognition of the need for, and an ability to engage in life-long learning
(j) a knowledge of contemporary issues
(k) an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice [9].

Out of 11 outcomes, six of them are related to interpersonal skills, such as communication, leadership, teamwork, ethics,
professionalism and lifelong learning. The remaining five learning outcomes ((a), (b), (c), (e) and (k)) are focused on
engineering design and analysis. At the higher level (i.e. institutional or university), student learning outcomes arguably
can be called graduate competencies or attributes [10].

As at the programme level, student learning outcomes at the institutional level must cover basic learning skills, such as
knowledge, cognitive and interpersonal (behavioural) skills. At PMU, student learning outcomes at the institutional level
have six learning competencies:

I. Communication competency: ability to communicate effectively in English and Arabic in professional and social
situations.
II. Technological competency: ability to use modern technologies to acquire information, communicate, solve
problems, and produce the intended results.
III. Critical thinking and problem solving: ability to reason logically and creatively to make informed and responsible
decisions and achieve intended goals.
IV. Professional competency: ability to perform professional responsibilities effectively in both local and international
contexts.
V. Teamwork: ability to work effectively with others to accomplish tasks and achieve group goals.
VI. Leadership: ability to be informed, effective and responsible leaders in the family, the community and the Kingdom [11].

The six competencies practised at PMU are unique among Saudi Arabia’s universities. They were commended as one of
the key institutional strengths by ABET team evaluators. Student learning outcomes at the programme level must be
compatible with those at the university level [12].

It can be shown that the learning outcomes at the programme level can be fully correlated to the learning outcomes
(competency) at the university level (Table 1). Furthermore, assessment of student competency at the university level
can also be determined quantitatively. Presenting students’ rating with respect to the university competency or graduate
attributes would enhance a student’s ability to work at a professional level. Because of this, PMU has started issuing
a competency rating to each graduated student in addition to an academic transcript. Arguably, the graduate attributes
can be extracted directly from some of the key courses that focus mostly on the development of student interpersonal
skills, such as internship and senior design project courses.

A separate rubric with key performance indicators can be developed for each university competency [13]. However, in
this article, quantification of graduate attributes was generated based on student learning outcomes at the programme
level, with the intention of showing outcome consistency between the university and programme level.

Table 1: relationship between PMU learning outcomes (competency) and CE student learning outcomes.

CE student learning outcomes

PMU competency
a b c d e f g h i j k
I X
II X X X
III X X X X
IV X X X
V X
VI X X X

Learning outcomes should be distinguished from learning objectives. The objective refers to the teacher or programme
perspective rather than the student. Student learning outcomes and learning objectives can be stated at various levels.
At the programme level, they is called programme educational objectives (PEOs) and are one of the important
accreditation criteria that need to be assessed and evaluated. The PEO is intended to be achieved by engineering
graduates within five years of their graduations, which is different from the learning outcomes that are intended to be
achieved at the end of a course (e.g. after four years). However, PEOs must be supported by the student learning

41
outcomes or in other words they must be mapped congruently to each student learning outcome. The Department of
Civil Engineering (CE) at PMU has the following PEOs:

• PEO1: graduates have successful and professional careers in civil engineering and related industries, and meet the
expectations of the prospective employers.
• PEO2: graduates demonstrate leadership and effectively undertake services within their profession and contribute
to sustainable development in their communities.
• PEO3: graduates pursue their professional development through continuous lifelong learning, advanced studies and
membership in professional societies.

At present, the PMU Department of Civil Engineering has enrolled about 160 students supported by five teaching
professors, two laboratory instructors and one laboratory technician. The Department has four modern engineering
laboratories (materials, geotechnical, surveying and hydraulic) to support teaching and learning. Civil engineering
students are required to complete 139 credit hours to earn a Bachelor’s degree. This 139-credit-hour accomplishment
comprises 17 hours mathematics, 17 hours sciences, 57 hours engineering topics and 48 hours general social science.

The curriculum was designed in accordance with ABET specifications, with respect to math, science and engineering
course requirements [9][14]. The PMU CE Department has been accredited by ABET Engineering Accreditation
Commission and the next cycle of visits will be conducted in the next two academic years.

In this article, student learning outcomes at the programme level and competency at the institutional level will be
assessed and analysed. It is obvious that students can be assessed straightforwardly at the course level by a standardised
numerical scale measurement (e.g. 0-100) or letter grading (e.g. A to F). At the programme and institutional levels,
the assessment requires different indexing to indicate learning outcomes. The assessment of 1 to 100 is too refined to
indicate outcome achievement, and in this article four-scale rating is used to assess learning outcomes [15].

ASSESSMENT STRATEGY

Key performance indicators (KPIs) and rubrics for each programme outcomes were developed based on the applicability
and practicality of assessing courses against the outcomes. The rubrics considered basic criteria, weight for each
criterion and level [16]. Table 2 shows an example of outcome (a), its KPIs and rubric. The remaining programme
outcomes, KPIs and rubric can be seen in a document issued by the Department [17]. Most of the KPIs are limited to
four (e.g. outcome (c) and some have only one indicator (e.g. outcomes (i) and (j), which are interpersonal skills
related). Outcome (c) is designed to have the most indicators because of its design-oriented outcome.

Table 2: Rubric for outcome (a).

Outcome (a): ability to apply knowledge of mathematics, science and engineering

Criteria Low (1) Needs improvement (2) Good (3) Excellent (4)
Fails to understand Shows limited and less Demonstrates Understands and
and apply proper than adequate satisfactory applies proper and
a1: Apply linear algebra and application of linear application of linear accurate linear
mathematics to differential calculus algebra and differential algebra and algebra and
solve engineering in solving calculus in solving differential calculus in differential
problems. engineering engineering problems solving engineering calculus in solving
problems problems engineering
problems
Fails to apply Shows limited and less Demonstrates Understands and
fundamental than adequate satisfactory applies proper and
a2: Apply
concepts and understanding of theory application of proper accurate concepts
concepts and
theories in solving and concepts in solving concepts and theory in and theories in
theories of science
science and engineering problems solving engineering solving engineering
and engineering.
engineering problems problems
problems
Fails to transform Shows limited and less Demonstrates Understands and
science and than adequate satisfactory applies proper and
a3: Convert
engineering transformation of transformation of accurate
science and
problems into science and engineering science and transformation of
engineering
solvable problems into solvable engineering problems science and
problems to
mathematical models mathematical models into solvable engineering
solvable
mathematical models problems into
mathematical
solvable
models.
mathematical
models

42
The assessment tools included quizzes, examinations, term projects, laboratory experiments, internship training reports
and senior design project exercises. The Faculty maintains a numerical value for each course, a course assessment report
and a teaching improvement strategy. It should be noted that not all KPIs are applicable to each course.

For example, courses without laboratory experimentation will not mention outcome assessments about conducting
experiment and experimental data analysis, which is one of the performance indicators for outcome (b). Normally, in
one semester three measurements are taken for each course covering one mid-term examination, one final examination
and a group term project. The examination and project questions reflect the KPI in the assessment. No homework
assessments are required since they are only intended for student practice.

Table 3 shows an example of a student assessment for an engineering course, for outcomes (a) and (e). Each question
was devised in accordance with the KPIs including the maximum grade students can attain. The rubric was developed
based on a four-scale assessment and so the student grade needs to be converted. Each student will have a unique set of
performance value, and averaging outcomes values for all students will result in the overall performance for that specific
course.

Table 3: Sample of rubric assessment for a civil engineering course.

ABET Maximum Student ABET KPI Student

Question Maximum
KPI grade grade (1-4 scale) grade
a1 20 10 2
1 a2 5 4 3 35 24
a3 10 10 4
e1 20 16 3
2 e2 35 30 3 65 46
e3 10 0 1
Total 100 70
Note: KPI = key performance indicator

The teaching faculty checks whether the outcome is below a threshold value (e.g. 2.5) and identifies the teaching
improvements if they are required. If the outcome values for one course are averaged with the other courses with
the same outcome assessments, this will result in the overall student learning outcomes at the programme level. This is
the focus of this article.

Table 4 shows 10 courses used as indicators for outcomes assessment at the programme level. The main justification for
not including all engineering courses is that the measure must reflect the ability of civil engineering students to master
key design courses. If all engineering courses are included in the assessment, this would under-represent performance
because students at the early engineering level do not have ability in design and analysis.

Table 4: Selected 10 courses for student learning outcomes assessment at the programme level.

No. Course name Code no. a b c d e f g h i j k

1 Materials in Civil Engineering CVEN 3322
2 Reinforced Concrete Design CVEN 3312
3 Engineering Measurements CVEN 3341
4 Environmental Engineering Fundamentals CVEN 3331
5 Hydraulic Engineering CVEN 4432
6 Intro to Geotechnical Engineering CVEN 4423
7 Design of Steel Structures CVEN 4313
8 Construction Management CVEN 4314
9 Water and Waste Water Treatment CVEN 4333
10 Learning Outcome Assessment III ASSE 4311

The Civil Engineering Department Council decided that the 10 courses selected must cover major civil engineering
disciplines, including structures, environment, geotechnical and construction management. Apart from the
transportation engineering course, courses were selected at the junior and senior level that are design and/or laboratory-
based.

It is seen from Table 4 that outcome (e) is measured the most (six times). This is because outcome (e) is related to basic
engineering skills for students to identify, formulate and solve engineering problems. This is followed by outcomes (a),
(c) and (k), which relate to the design and analysis of engineering problems. With respect to outcome measurement
frequency, course Learning Outcome Assessment III (No. 10), also known as the senior design project, has the greatest
frequency (nine) from outcomes (c) through (k). This is because the senior design project demonstrates the mastery of all
the important skills that students are expected to acquire by the end of their undergraduate studies [18-20].

43
Outcomes (d), (g), (h) and (j) were taken twice; this is due to the nature of interpersonal skills assessment that can only
be measured through non-conventional ways; for example, by using self-evaluation in teamwork exercises, peer review
and evaluation of lifelong learning.

ANALYSIS RESULTS

Assessment of the programme outcomes has been conducted for six semesters within three academic years (2016 to
2019). Student learning outcomes (a) to (k) can be quantified by averaging the KPIs for each outcome. Summarised in
Figure 1 is the result for the 11 outcomes since the academic year 2016 to 2017. A line indicating threshold value (2.5)
is also shown in the graph.

Unlike the assessment conducted for each course, the numerical values for the programme outcomes are presented up to
one decimal point to indicate a refined level of attainment. This seems to contradict developing a rubric with a rounded
value of 1 to 4. However, the refined outcome values will be useful later to support justification for continuous teaching
improvement. It would be difficult to observe trends for outcome improvement if they are presented only in rounded
numerical values.

Figure 1: Student learning outcomes at the programme level.

In general, it can be observed that the target outcomes were achieved, all values are above the threshold value (2.5).
Looking closely at the average values, outcome (a) has the lowest value relative to the other outcomes. Although it is
higher than the target value, this could indicate that teaching staff should pay more attention to students’ abilities in
applying knowledge of mathematics and science in engineering. Except for outcomes (a) and (e), the other outcomes
showed improvement in the past three academic years.

Figure 2: University competency (graduate attributes).

44
The lowest outcome (a) has led to students’ low performance in outcome (e), i.e. student ability to identify, formulate
and solve engineering problems. The highest outcome value was (d), which is about teamwork. This was followed by
outcome (b), student ability to conduct laboratory experimentation. It can be deduced that students are excited to learn
as a team as most laboratory-based learning is team-based. It is strongly encouraged that teaching involves teamwork
exercises and uses factual and self-learning discovery (i.e. experimentation).

Graduate attributes (competency) can be quantified (Figure 2) using Table 1. As at the programme level, the highest
performance was obtained in teamwork (competency V). This is expected because of the one-to-one correlation between
the programme and university learning outcomes. The lowest performance was for competency III, which is critical
thinking and problem-solving. This is consistent with the programme level where ability to apply mathematics and
science (outcome (a)) and ability to identify, formulate and solve problems (outcome (e)) had the lowest values.
The graduate attributes are rarely used as important criteria in the programme accreditation process. This exercise has
been undertaken to demonstrate compatibility between the university and programme student outcomes.

DISCUSSION

The student learning outcomes at the programme level can be determined using learning outcomes at each course level
(CLO). To do this, mapping must be provided between course and programme outcomes. Then the rubric assessment for
each CLO needs to be developed as the KPI for the direct programme assessment.

Table 5 shows an example of the relationship between course learning outcomes and programme outcomes for
the Design of Steel Structures course. The rubric is developed for each CLO using a four-scale rating. The weight
distribution between programme outcomes mapped to one CLO must be determined. For example, CLO3 is mapped to
programme outcomes (a) and (c), and the weight distribution needs to be defined, such as 30% for outcome (a) and 70%
for outcome (c).

Table 5: Student learning outcomes mapping for the course, Design of Steel Structures.

Student learning outcomes at

Student learning outcomes at the course level (CLO)
the programme level
CLO1: Perform appropriate structural analyses based on the loads assigned for design (a)
CLO2: Determine various loading conditions and select critical load for use in (e)
structural design
CLO3: Perform design and analysis of structural members, connections and systems (a), (c)
CLO4: Produce design sketches or a drawing necessary for cost estimation (c), (k)
CLO5: Apply local building codes and engineering standards in structural design (c)
CLO6: Use modern computer software for steel structural analysis and design (k)

As is in the direct programme outcome assessment measure, finding the overall student learning outcomes at
the programme level is done by averaging all outcomes for selected courses (Figure 3). The main difference here is that
this technique requires assessment tools (examinations, projects) that are CLO-specific. There are pros and cons about
using this method. The major concern about the direct programme outcomes assessment is that the assessment is
determined and calculated indirectly via the CLOs.

The main concern for the direct measure is that developing assessment tools (tests, projects) related to the KPIs at
the programme level - which by nature are very general - is challenging. There is a detailed method that can relate CLOs
for each course directly to each KPI at the programme level [4]. By using this refined method, weight factors need to be
applied to simulate the contribution of each CLO into the KPI. Regardless of various methods of assessment, major
accrediting bodies such as ABET have no big concern with simple or detailed methods provided the results can support
teaching improvement.

The ABET has introduced new student outcomes compacting the previous 11 outcomes (a) to (k)) into seven (1) to (7)
outcomes [14].These new outcomes became applicable in the 2019 to 2020 cycle of accreditation, and a programme can
retain the 11 outcomes or transform them into the new ones. The mapping between ABET new outcomes and (a) to (k)
outcomes can be seen in Table 6. For programmes that will undergo an accreditation cycle within the next two to three
years and plan to use (1) to (7) outcomes, while at the same time would like to utilise the old (a) to (k) data, conversion
can be done according to the mapping in Table 5, with few adjustments on how to incorporate several outcomes into one
new outcome.

For example, as shown in Table 5, outcome (k) can be proportionately added to outcomes (1), (2) and (6). Incorporating
(a) to (k) outcomes shows outcome performance trends vis-à-vis the old (a) to (k) data. Key performance indicators need
to be redeveloped similar to the previous KPIs for the (a) to (k) outcomes.

Table 6 shows the conversion of (a) to (k) to (1) to (7) outcomes. Again, except for the outcome (1) (identify, formulate
and solve engineering problems by the application of mathematics and science), all other outcomes showed improved

45
definitions, particularly outcome (5) (teamwork). Looking at the average value for the three academic years, outcome 4
(ethics and professionalism) shows the lowest value. This is through combining outcomes (f), (h) and (j) that already had
low scores (Figure 1); this is not crucial since the performance has improved year-by-year.

Table 6: Mapping of ABET (1) to (7) to (a) to (k) student outcomes.

ABET new student outcomes (versus (a) to (k) outcomes)

an ability to identify, formulate, and solve complex engineering problems by applying principles of
1
engineering, science, and mathematics ((a), (e) and (k))
an ability to apply engineering design to produce solutions that meet specified needs with consideration of
2 public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors
((c) and (k))
3 an ability to communicate effectively with a range of audiences (g)
an ability to recognise ethical and professional responsibilities in engineering situations and make
4 informed judgments, which must consider the impact of engineering solutions in global, economic,
environmental, and societal contexts ((f), (h) and (j))
an ability to function effectively on a team whose members together provide leadership, create
5
a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives (d)
an ability to develop and conduct appropriate experimentation, analyse and interpret data, and use
6
engineering judgment to draw conclusions ((b) and (k))
7 an ability to acquire and apply new knowledge as needed, using appropriate learning strategies (i)

Figure 3: Student learning outcomes ((1) to (7)) since the academic year 2016-17.

INDIRECT ASSESSMENT

A survey was conducted of senior graduating students to rate their abilities with respect to the student learning outcomes
of the PMU civil engineering programme. Provided by this survey is a programme comparative performance relative to
the direct assessment method presented earlier in this article. It should be noted that surveys for assessing learning
outcomes are called indirect assessments, and this term should not be confused with the programme outcomes assessed
via course or programme learning outcomes as described in the previous paragraph.

Feedback was sought on how far the Department has been successful in preparing graduates with the required
knowledge and skills to meet the programme outcomes and programme educational objectives. A 100% response rate
for graduating students was obtained at the end of spring. To be consistent with the direct assessment, the survey used
a four-rating scale, with four indicating excellent and one, low or unsatisfactory.

Summarised in Figure 4 is the survey result conducted during the past three academic years, including the average
values. Student learning outcomes (a) to (k) were used in this survey. Clearly students have rated highly their abilities to
meet the outcomes (3.5 or above). The survey is subjective relative to the direct measure that uses measurable indicators
for the assessment (examinations, project exercises, laboratory reports, and so on). That explains why the value (3.5) is

46
higher than the direct measure (2.5). However, it should be noted that this survey is only one of several inputs
considered for programme improvement. In general the students are satisfied with their achievement on all outcomes.

The highest result was obtained for outcome (d) (teamwork), which is consistent with that obtained from the direct
measure. The lowest value was obtained for outcome (b) (laboratory experimentation) followed by outcome (k) (using
modern engineering design tools). The result seems contradictory, with those obtained from the direct assessment
showing high values for the laboratory experimentation and using modern engineering tools.

Students seemed less confident in these two areas that are intended to develop students’ ability in mastering
technological tools in engineering problem solving. Corrective actions, including introducing software-based learning in
design, such as engineering drawing and replicating laboratory equipment to stimulate factual-based learning, have been
taken to improve student confidence. Also, introducing two semester senior design project courses is to be implemented
to enrich student engineering design experience using up-to-date tools or computer software.

Figure 4: Graduating senior exit survey results since the 2016 to 2017 academic year.

Another survey was conducted to obtain feedback from employers. The response rate was low due to a low number of
civil engineering graduates within the past seven years. Unlike survey questions distributed to the senior graduating
students, the survey questions to employers were designed to reflect the actual assessments for employees who have
been working in an engineering company for up to five years.

Table 7 (see Appendix), has a summary of the survey questions and results. Unlike the direct assessment rubric and
survey to the senior exit students, a five-point scale was used, from five (strongly agree) to one (strongly disagree).
The associated student learning outcomes and programme education objectives (PEOs) are also presented along with
the survey questions.

The survey results show an overall satisfaction among the employers on the quality of education at the CE-PMU
programme. Again, to adjust for subjectivity the benchmark value was set at 3.75. While most of the scores are above
the benchmark of 3.75, the score for questions 1 and 3 are on the lower side indicating: 1) a need for improvement in
the students’ ability to possess basic principles and skill in the civil engineering areas; and 2) a need for improvement in
using instrument and measurement tools in civil engineering. It can be observed that lack of confidence in conducting
laboratory experimentation (outcome (b)) is the main source for these low scores. The results were consistent with those
obtained from the indirect assessment (survey) conducted of graduating students.

CONCLUSIONS

Based on direct and indirect assessment results conducted for three academic years, since 2016-17, graduates from
the PMU civil engineering programme appear to achieve all student learning outcomes at an acceptable level.
Despite this, improvements still are needed in several areas. This is facilitated through curriculum upgrades, including:
1) introducing an engineering drawing course to enhance student ability applying mathematics, particularly in
understanding complex geometry; and 2) splitting the senior design project (capstone) course into two semesters to
improve student learning through modern engineering design tools.

47
Corrective actions also have been taken to improve teaching and learning practices. These include: 1) upgrading
laboratories by replicating key laboratory equipment to improve student participation and motivation; and 2) updating
existing design software to bring students closer to up-to-date engineering practice.

ACKNOWLEDGEMENTS

The authors would like to extend appreciation to former PMU civil engineering faculty members Drs Alaa Salman and
Omar Ouda for assisting data collection of the student learning outcomes assessment.

REFERENCES

1. European Commission. Using Learning Outcomes - European Qualification Framework Series: Note 4.
Luxembourg, 48 (2011).
2. Estes, A. and Ressler, S., Surviving ABET accreditation: satisfying the demand of criterion 3. Proc. 2007
American Society for Engng Educ. Annual Conf., Paper AC 2007-875 (2007),
3. Damaj, I., Zaher, A. and Yousafzai, J., Assessment and evaluation framework with successful application in ABET
accreditation. Inter. J. of Engng. Pedagogy, 7, 3, 73-91 (2017).
4. Alzubaidi, L., Program outcomes assessment using key performance indicators. Proc. 62nd ISERD Inter. Conf.,
Boston, USA (2017).
5. Bloom, B.S., Taxonomy of Educational Objectives, Handbook I: the Cognitive Domain. New York: David McKay
Co Inc. (1956).
6. Uziak, J., Oladiran, M.T. and Moalosi, R., Reviewing and developing course descriptions to comply with
accreditation requirement. Global J. of Engng. Educ., 12, 1, 30-37 (2010).
7. Alshehri, A.A., Augmenting engineering undergraduates’ generic competencies aligned with ABET outcomes 3
and 5. Global J. of Engng. Educ., 21, 3, 171-178 (2019).
8. Patil, A.S. and Pudlowski, Z.J., Important issues of the accreditation and quality assurance and a strategy in the
development of an accreditation framework for engineering courses. Global J. of Engng. Educ., 7, 1, 39-50 (2005).
9. ABET, Criteria for Accrediting Engineering Programs. Accreditation Board for Engineering and Technology:
Engineering Accreditation Commission (2018), 29 January 2020, http://www.abet.org
10. Spracklin-Reid, D. and Fisher, A., Course-based learning outcomes as the foundation for assessment of graduate
attributes - an update on the progress of Memorial University. Proc. 2013 Canadian Engng. Educ. Association,
Montreal, QC, 17-20 June, 4 (2013).
11. PMU, Prince Mohammad Bin Fahd University (2019), 29 January 2020, http://www.pmu.edu.sa
12. Boden, D.G. and Gray, P.J., Using rubrics to assess the development of CDIO syllabus personal and professional
skills and attributes at the 2.x.x level. Global J. of Engng. Educ., 11, 2, 117-122 (2007).
13. Knight, P.T. and Banks, W.M., The assessment of complex learning outcomes. Global J. of Engng. Educ., 7, 1, 39-
50 (2003).
14. Felder, R. and Brent, R., Designing and teaching courses to satisfy the ABET engineering criteria. J. of Engng.
Educ., 92, 1, 7-25 (2003).
15. Thompson, M.R., Clemmensen L.H. and Ahn, B., Effect of rubric rating scale on the evaluation of engineering
design project. Inter. J. of Engng. Educ., 29, 6, 1490-1502 (2013).
16. Lanziner, N. and Strong, D.S., Designing rubrics to assess engineering design, professional practice, and
communication over three years of study. Proc. 2016 Canadian Engng. Educ. Assoc. Conf., 19-22 June, Dalhousie
University, Halifax, Canada (2016).
17. PMU, Civil Engineering (2018), 29 January 2020, https://www.pmu.edu.sa/academics/civil_engineering_dept_coe_udp
18. Rover, D.T., Jacobson, D.W., Kamal, A.E. and Tyagi, A., Implementation and Results of a Revised ABET
Assessment Process. Proc. 120th ASEE Annual Conf. and Expo., 23-26 June, Atlanta, USA, ID#7964 (2013).
19. Al-Bahi, A.M., Taha, M.A. and Turkmen, N., Teaching and assessing engineering professional skills. Inter. J. of
Engng. Pedagogy, 3, special issue 3, 13-20 (2013).
20. Chong, A. and Romkey, L., Evolving a rubric for use in assessing engineering graduate attributes in a student
senior research thesis. Presented at 2012 ASEE Annual Conf. and Expo., San Antonio, Texas, June (2012).

BIOGRAPHIES

Dr Tahar Ayadat is an Associate Professor of Civil Engineering at Prince Mohammad Bin

Fahd University (PMU), Al Khobar, Kingdom of Saudi Arabia. He earned his PhD in civil
engineering from Sheffield University, England, in 1991. His major expertise is in
geotechnical and geo-environmental engineering. Dr Ayadat has about 30 years of academic
and practical experience in conducting design, analysis, inspection, expertise and management
of various projects, such as domestic, commercial and industrial constructions, bridges, roads
and railways, dams, site rehabilitation, and so on. He has published more than 100 papers and
technical reports in refereed journals, international conference proceedings and government
(public) domains. He supervised and co-supervised many MSc and PhD theses. Dr Ayadat is
at present a registered Professional Engineer (PEng) in the Province of Quebec, Canada.
He also has been a member of the Canadian Society of Civil Engineering since 2004.

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 Mr Danish Ahmed is at present a laboratory instructor in the Civil Engineering Department
at Prince Mohammad Bin Fahd University (PMU), Al Khobar, Kingdom of Saudi Arabia.
His major expertise is in seismic testing of reinforced concrete structural members,
retrofitting and finite element modelling. He completed his Master of Science in Civil
Engineering (Structures), in 2009-2012 in the Department of Civil Engineering at King Fahd
University of Petroleum and Minerals, Kingdom of Saudi Arabia, and in December 2005-
2008, he completed a Bachelor of Science in civil engineering in the Department of Civil
Engineering at Sir Syed University of Engineering and Technology, Pakistan. He received
a bronze medal and university scholarships for outstanding academic performance.

Dr Saidur R. Chowdhury is an Assistant Professor in the Civil Engineering Department at

Prince Mohammad Bin Fahd University (PMU), Al Khobar, Kingdom of Saudi Arabia.
He completed his PhD in environmental and geo-environmental engineering at Western
University (UW) in Canada. Dr Chowdhury is a Professional Engineer (PEng) in
the province of Ontario in Canada. He has more than two years of postdoctoral experience at
both Western University and the Simpson Environmental Corporation in Burlington,
Ontario, as well as in the University of Saskatchewan. He has published scientific papers in
refereed journals and international conference proceedings, as well as technical reports for
different environmental consulting companies in Canada. Western University has
acknowledged his research contribution by honouring him with the prestigious R.M. Quigley
Award (2011) for Research Excellence. He is registered with the Ministry of Environment
and Climate Change to act as a Qualified Person (QP) for Environmental Site Assessment (ESA) and treatment under
Ontario Regulation 153 / 04.

Dr Andi Asiz is an Associate Professor and Chair of the Civil Engineering Department at
Prince Mohammad Bin Fahd University (PMU), Al Khobar, Kingdom of Saudi Arabia.
His major expertise is in structural engineering and mechanics. He has more than 15 years of
academic and practical experiences in conducting analysis, design, inspection and monitoring
of various engineered structures, from reinforced concrete and steel buildings, pre-stressed
concrete bridges to timber structures. He has published more than 50 papers and technical
reports in refereed journals, international conference proceedings and government (public)
domains. In collaboration with the University of New Brunswick in Canada, he is at present
co-supervising and advising doctoral students in structural engineering. He obtained his PhD
degree in civil engineering from the University of Colorado at Boulder, USA. Dr Asiz is at
present a registered Professional Engineer (PEng) in the Province of New Brunswick,
Canada. He also has been a member of the American Society of Civil Engineers (ASCE) since 1997.

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 APPENDIX

Table 7: Employer survey result.

Average
No. To what level do you agree with the following statements about CE graduates of PMU?
score
Possess a basic knowledge of the principles and skills related to civil engineering (outcomes (a),
1 3.3
(c)); (PEO1)
Can apply their knowledge and skills in finding engineering solutions to technical problems at
2 3.8
work (outcomes (c), (e)); (PEO1)
Possess an ability to use instruments and measurement tools as needed in the practice of the
3 2.8
engineering profession (outcomes (b), (k)); (PEO1)
Possess an ability to engage in advanced education, research, and development (outcome (i));
4 4.2
(PEO3)
5 Possess critical thinking and problem-solving skills (outcome (e)) 4.5
6 Can work independently without the need for supervision (outcomes (d), (i)); (PEO2) 4.2
7 Possess an ability to work within a team environment (outcome (d)); (PEO2) 4.7
8 Possess an ability to communicate effectively (outcome (g)); (PEO1) 4.5
9 Possess good technical writing skills (outcome (g)); (PEO1) 4.5
10 Possess sound project management and leadership skills (outcome (h)); (PEO2) 4.3
Possess the minimum requirements/competence for obtaining a job for an entry level position
11 4.4
(outcomes (h), (i)); (PEO1)
12 Possess the technical competence to advance in their career (outcome (i)); (PEO3) 3.8
13 Involved in the development of new and valuable ideas (outcomes (h), (j)); (PEO2) 4.2
14 Possess the ability to acquire new knowledge and skills on their own (outcome (i)); (PEO3) 4.3
15 Understand the need for continued professional development (outcome (i)); (PEO3) 4.3
16 Demonstrate an understanding of workplace procedures and practices (outcome (f)); (PEO2) 4.0
17 Demonstrate an understanding of professional and ethical responsibility (outcome (f)); (PEO2) 4.5
Overall, we are satisfied with the technical competence and professional attitude of PMU CE
18 4.5
graduates (outcomes not applicable); (PEOs 1, 2)
I would recommend the PMU civil engineering programme to a friend or relative (outcomes not
19 4.5
applicable)

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