Integrating Active Learning in an Undergraduate Corrosion Science and Engineering Course—KFUPM’s Active Learning Initiative

Abstract

Material degradation in the form of corrosion is an important industrial problem that affects asset integrity, reliability, and sustainability in various industries. To equip engineering professionals with the knowledge required for appropriate material selection and corrosion-mitigation design, this subject forms an essential part of the engineering curriculum at both undergraduate and graduate levels across multiple disciplines. This paper presents the design, implementation, and evaluation of an active learning (AL)-based course framework to teach a corrosion science and engineering course at the mechanical engineering department, KFUPM. A combination of AL strategies, including project-based learning (PBL), case-based inquiries, peer instruction, and think–pair–share activities, etc., was systematically integrated into the course to promote collaborative learning, conceptual enrichment, and critical thinking. Positive student feedback (>90% for most of the survey questions) with a response rate of 89% indicated increased motivation, improved understanding of complex corrosion mechanisms, and increased confidence in applying knowledge to solve engineering problems. A Cronbach’s alpha coefficient of 0.75 was obtained, reflecting strong internal reliability of the instrument. These findings suggest that integrating AL pedagogies in the corrosion course contributed towards enhanced learning outcomes and student preparation to support sustainable industrial practices using informed materials selection and corrosion management.

1. Introduction

Engineering education has continued to evolve over the years to satisfy industry demands by graduating engineers capable of handling a wide range of industrial problems and providing a suitable solution to mitigate these challenges. Since its inception, efforts have been made to ensure that engineering education is “content-focused, design-oriented, with plenty of hands-on experience” in order to help students develop their critical thinking and problem-solving abilities [1]. Universities around the world seek accreditation from international bodies such as ABET (Accreditation Board for Engineering and Technology) and from national or regional accreditation agencies for recognition of their engineering programs. This ensures education quality and standard across the board, so that students from different universities can have equal chances to compete in the open job market.

Engineering education, slowly but steadily, is being transformed from “teacher-centered to student-centered”, by adopting innovative engagement/active learning (AL) strategies [2], such as flipped classrooms, project- or problem-based learning (PBL), and inquiry-based learning [3,4,5], etc. Corrosion is defined as the deterioration of materials through electrochemical or chemical reactions, and it poses a significant challenge for industrial infrastructure [6,7]. The global economic impact, due to corrosion, is immense, with estimated costs reaching nearly 3.4% of the world’s GDP [8,9]. It has been reported [10,11] that human error is responsible for approximately 65% to 90% of corrosion-related failures. This data not only emphasizes the importance of corrosion science and engineering education at both undergraduate and graduate levels across various disciplines, but also suggests that we better prepare our graduates with practical and research exposure to address industrial challenges [12].

Active learning(AL) is considered to be any instructional approach that helps in improving student focus and creating higher-order thinking skills. It engages students in the learning process through in-class activities and discussions, as opposed to passive listening [13]. It is widely reported in the published literature that this pedagogical strategy has a positive impact on student performance [14]. Guimaraes et al. [15] reported that active learning classes helped improve the average exam scores by 6% and reduced failure rates by 1.5 times as compared to traditional lectures [15].

Since corrosion control is essential to lowering infrastructure deterioration and lifetime costs, incorporating sustainability into corrosion education will greatly support sustainable asset management. Through the use of active learning techniques, such as problem-based learning, scenario-based assignments, and group projects, students become more deeply involved with corrosion problems in the real world, developing both technical proficiency and systems-level thinking. Active learning has been reported to develop sustainability competencies, including creativity, teamwork, and systems thinking, so incorporating these active learning techniques into corrosion and materials-degradation courses enables students to comprehend how long-term maintenance choices, resource optimization, and prevention techniques support the sustainable management of assets [16,17]. These approaches are based on pedagogical frameworks that train engineers to prevent issues in a way that is consistent with social, economic, and environmental sustainability objectives.

By engaging students in problem-solving activities and case-based learning, active learning helps reinforce key concepts and enhances long-term knowledge retention [18] by emphasizing skills such as analysis, evaluation, creativity, collaboration, and leadership. Recent higher education research shows that maker-oriented, project-based designs can advance creativity, problem-solving, and student-directed learning when supported by adequate resources, mentor capacity, and enabling institutional systems. These designs provide a pathway to sustainability competencies and green digital skills in technical curricula [19,20]. From the instructor’s perspective, such a class environment can allow them to tailor course delivery as per student needs [21]. It also creates better interaction and engagement between the instructor and students [22]. Active learning implementation, in a physics course, improved student concept understanding considerably [23,24]. One of the key benefits (which usually does not get enough attention) of active learning implementation is its usefulness in tackling issues related to test anxiety [25], as compared to traditional lecturing, which is mainly based on summative assessments [26].

Active learning helps prepare students to be more adaptable in their careers, while also contributing to minimizing the performance gaps among the students. The idea of active learning originates from the fact that it is difficult for students/the common audience to stay attentive for a duration of 50~75 min. of a lecture. It is reported that a typical attention duration is roughly 10~15 min [27,28,29], so considering this fact, lecture duration can be segmented into 2~3 mini lectures by designing appropriate paper-based/online active learning activities with a duration of 15~20 min. for each activity.

Despite above above-discussed advantages of active learning, there are obvious challenges of its implementation (Figure 1), related to pedagogical (activities preparation fulfilling Bloom’s taxonomy’s higher-order thinking skills requirements) and practical aspects (workload, availability of resources, etc.) [30,31]. It requires more time and cognitive effort from the instructors, in contrast to traditional lecturing. The courses have a fixed syllabus to be covered, and so, during active learning, it is a challenge to complete the content on time. This is particularly true for coordinated courses and even for elective courses, which require careful planning. The student sample matters a lot both in terms of prior knowledge of the subject (along with its prerequisite), cognitive abilities, and their willingness to actively participate in an AL class environment. Students are usually enrolled in 4~5 courses (up to 15 credit hours), so spending time on pre-class activities can be challenging. Another major challenge is to design assessment rubrics for active learning activities to be used during different stages of the course throughout the semester.

The flipped classroom is a well-known active learning model in which students are familiarized with the lecture material before class, and the class time is used for active learning activities. Instead of homework assignments (which still can be assigned as per needs), class time is used in engaging activities to solve problems and practice concepts. The flipped classroom is an effective strategy for enhancing student engagement [32,33]. However, a key challenge is to ensure that students complete the necessary pre-class preparation, which can be hindered by time constraints, low motivation, or the quality of the recorded materials [34]. In this regard, the famous “fail, flip, fix, and feed” model reported by Alten [35] is a good approach, as it suggests first trying the unknown concepts, regardless of success/failure, and later learn it formally for in-depth learning. The issues, like lack of student motivation for pre-class preparation, can be addressed by assigning bonus online quizzes/surveys for pre-class material, using advanced educational technologies and learning management systems (such as Blackboard, being used at KFUPM) [36]. It is reported in the literature that online engagement tools like Kahoot, Socrative, etc., have helped in improving overall conceptual understanding and academic performance of the students [37].

Transforming Engineering Education at KFUPM-University Initiative

There is a well-established agreement on the positive impact of active learning in improving student performance; however, integrating such methodologies in the courses requires a lot of time and effort from the faculty (Figure 1). Often, such efforts are not recognized or valued in faculty performance evaluation metrics, leading many faculty members to avoid these time-consuming approaches. The issue of student resistance is another factor, as in such an AL environment, they also have to play an active role, inside/outside the class. Considering these issues, it will be ideal to have an institutional-level effort to transform engineering education. So, therefore, KFUPM took a commendable initiative nearly three years ago to officially promote active and student-centered learning across its engineering programs. The university provided extensive support to faculty via in-person and online professional development programs led by internationally recognized experts. The faculty is also supported with required tools such as software (Kahoot, Socrative, along with many others) and classroom infrastructure for active learning implementation. So, these continued efforts of the Deanship of Academic Development at KFUPM have resulted in a steady increase in the number of AL-integrated courses across multiple departments. This initiative fostered the growth of an active learning community at KFUPM, dedicated to enhancing undergraduate and graduate teaching practices. The faculty involved in such initiatives is often acknowledged and appreciated by engaging in university-level experience-sharing sessions/workshops organized under the Deanship of Academic Development. KFUPM has further institutionalized this initiative by announcing the courses to be taught using active learning on its official registrar’s portal (Figure 2). This practice contributed positively to preparing students in advance for the participatory nature of an active learning classroom environment.

This sustained implementation of active learning at KFUPM has been enabled by a combination of institutional investments and pedagogical support mechanisms consistent with international evidence on educational innovation. Prior studies [38,39] emphasize that a dedicated active learning environment is required to encourage collaboration and engagement. Similarly, digital infrastructure, including access to learning management systems, simulation tools, online AL engagement tools, and assessment platforms, has been shown to enhance the scalability of student-centered approaches. In addition, continued faculty mentoring and professional development are critical for a sustained instructional change as reported elsewhere [40]. At KFUPM, the availability of active learning classroom infrastructure, robust technological tools, and ongoing mentor-supported faculty training has been instrumental in achieving consistent adoption and measurable learning gains. This alignment with established evidence on education innovation reinforces the KFUPM model’s potential for scalability and long-term institutional impact.

This paper presents a comprehensive approach to applying active learning in an undergraduate corrosion science and engineering course at KFUPM. It discusses course redesign for active learning, its implementation, assessment, and student feedback on different aspects of the course. This study has adopted a sustainable and optimized AL framework to offer the course, with authentic outcomes, and, if implemented, can benefit other instructors teaching this or similar courses at undergraduate and graduate levels. Student feedback and performance evaluation results demonstrated improved student performance in terms of course average scores and higher-order thinking skills, as reflected by students in their respective course projects.

2. Materials and Methods

This section presents a detailed description of the methodology adopted for redesigning the course to incorporate active learning without any changes in the approved course contents. It outlines the course structure, implementation approach, and strategies for assessment and student feedback. The student feedback data used in this study was collected across two semesters, involving a total of 32 students for various feedback, with an overall response rate of 89%. There were 12 and 20 students enrolled in the respective semesters. The survey instrument was designed to capture student perceptions not only about overall course delivery but also about the integration of active learning strategies within the corrosion engineering course. The same instrument was used for the midterm and end-of-semester evaluation, where the latter was more focused on project-based learning. The first section of the questionnaire focused on general aspects of the course, such as course progress, teaching effectiveness, and their overall learning experience. The second section targeted the active learning component, with items assessing students’ perceptions of various online and paper-based learning activities and the extent to which these activities enhanced their engagement, critical thinking, engineering skills, and soft skills. The survey items were reviewed for clarity and alignment with the intended learning outcomes prior to administration. Some of the survey responses were collected using a three-point Likert scale (3 = Strongly Agree, 2 = Agree, 1 = Disagree), which were later used for statistical analysis. To evaluate the quality of the instrument, internal consistency was examined using Cronbach’s alpha calculation based on feedback. The analysis yielded a reliability coefficient value of 0.75 for alpha, indicating a good internal reliability.

2.1. Corrosion Course Details

The data presented in this manuscript is related to an undergraduate corrosion engineering course (ME 472) at the mechanical engineering department, KFUPM, a senior elective course (3 credit hours). It is also an important course of the “Corrosion and Material Degradation” undergraduate concentration (CX), hosted by the “Material Science and Engineering” department at KFUPM, which is open to five other departments, i.e., MSE, CHEM, ME, CE, and ISE, respectively. The instructor has been teaching this course since 2014 (on and off) and has updated the course material regularly. The course covers various aspects from the fundamentals of corrosion to failure modes and protection methods. The following are the course objectives.

(a)

Introduce the fundamentals of electrochemistry and thermodynamics of electrochemical reactions to predict corrosion tendency.

(b)

Familiarize students with the basic concepts of electrochemical kinetics to predict corrosion rates.

(c)

Describe the major industrial corrosion forms, their main degradation features, and primary prevention methods.

(d)

Introduce industrial measures for uniform corrosion prevention, including coatings, anodic and cathodic protection, inhibitors, and corrosion-resistant alloys.

Table 1. The detailed course learning outcomes undergraduate corrosion engineering course (ME472).

CLO No.	Course Learning Outcome	ABET Outcome(s)	Justification
CLO 1	Describe the characteristic features of different corrosion forms and their causes in engineering alloys and environments.	1	Aligns with outcome #1 (problem identification and formulation), as students can identify and explain corrosion problems using principles of materials science
CLO 2	Describe the primary corrosion protection techniques and their application and limitations.	1, 4	Aligns with outcomes #1 and #4 (ethical and societal context), as this CLO involves understanding and evaluating protection system
CLO 3	Apply electrochemistry, thermodynamics, and kinetic principles to predict corrosion tendencies and rates.	1, 6	Aligns with outcomes #1 and #6 (experimentation and data analysis), as it covers analysis and application of scientific principles)
CLO 4	Design cathodic protection systems (sacrificial or impressed current) for basic submerged/buried steel structures.	2	Aligns with outcome #2 (engineering design) as it includes applying engineering design to develop a protection system
CLO 5	Prepare a corrosion-related presentation and present it to the class.	3, 5	Aligns with outcome #3 (communication) and #5 (teamwork), as it involves communication skills and effective teamwork
CLO 6	Recognize the significance of corrosion cost and the technical measures available to control it.	4	Aligns with outcome #4 (ethics and responsibility) as it covers understanding societal/economic impacts

shows the course learning outcomes, which are categorized into three main areas: i.e., (a) knowledge and understanding, (b) skills, and (c) values, autonomy, and responsibility, respectively.

2.2. Active Learning Implementation Details

Considering the course objectives and CLOs, the course was redesigned, focusing on “content preparation, delivery, and subsequent assessments” for AL implementation. Different active learning techniques targeting the “conceptual enrichment” and “practical training/enhancing skills/competence” were integrated into the course. The techniques such as “inquiry-based learning (IBL), just-in-time teaching (JiTT), think–pair–share (TPS), active review sessions (ARS), project-based learning (PBL), and case-based inquiries (CBIs)”, etc., were systematically planned and incorporated. It is important to highlight that active learning integration in the course should not be just for the sake of its usage; rather, each active learning activity has to be well thought out (for individual/group activity) for specific outcomes. The activities, like JiTT, TPS, and ARS, were used for “conceptual enrichment”, while CBIs and PBL were used for higher-order thinking skills.

Table 2. The details of active learning strategies adopted for different course components.

Topic#	Topics	Integration of Active Learning Strategies
1	Basics of corrosion/introduction (what, why, cost) of corrosion	- Flipped class will contain audio/video of PowerPoint slides - Animated videos about fundamental aspects of corrosion - Active learning guided activity focusing on material/environmental interactions, anodic/cathodic reactions, corrosion cell types, etc. - Online self-evaluation activity (Blackboard/Kahoot/Socrative)
2	Thermodynamics of corrosion [electrode potentials; types of corrosion cells; Nernst equation; Pourbaix diagrams]	- Class discussion along with online audio/video of thermodynamic concepts - Active learning activities in class focusing on the “Pourbaix diagram for specific metal/H2O reaction utilizing Nernst equation calculations” - Active learning activities (in class) focusing on the “electrode potential and electrical double layer concepts” - Design problem activity to understand the role of potential and pH on Pourbaix diagram stability - Online self-evaluation activity (Blackboard/Kahoot/Socrative)
Active Learning Activity [Active Review Session (ARS)]
3	Corrosion kinetics [Faraday’s law; corrosion rate calculation; polarization; electrochemical corrosion measurement]	- Class discussion along with online audio/video of corrosion kinetics concepts - Design problem activity to calculate corrosion rate of different materials in given environment based on Faraday’s law - Active learning activities (in class) focusing on conceptual understanding of “polarization and factor affecting corrosion process, mixed potential theory concepts, and corrosion measurement techniques” - Lab session focusing on electrochemical corrosion measurement, specimen preparation, potentiostat hardware/software introduction - Online self-evaluation activity (Blackboard/Kahoot/Socrative)
4	Fundamentals of passivity	- Flipped class will contain audio/video lecture - Animated about fundamental aspects of corrosion - Active learning activities focusing on phenomenon of passivity, role of alloying elements, role of oxidizers - Online self-evaluation activity (Blackboard/Kahoot/Socrative)
5	Corrosion types	- Flipped class will contain audio/video lecture covering different types of corrosion - Active learning activities (in class) focusing on conceptual understanding of corrosion types (what, why, and how) - Case-based inquiries targeting each corrosion type (based on real reported cases in the literature) - Online self-evaluation activity (Blackboard/Kahoot/Socrative)
6	Corrosion prevention (coatings)	- Class discussion along with online audio/video of coating related concepts - Lab session focusing on coating deposition (electrodeposition method), failure testing (salt spray test), and electrochemical corrosion measurement) - Case-based inquiries on coating failure modes - Invited lecture from industry/academia
7	Corrosion prevention (cathodic protection)	- Class discussion along with online audio/video of cathodic protection concepts - Lab session focusing on coating failure testing (salt spray test) and electrochemical corrosion measurement) - Cathodic protection design - Case-based inquiries on CP design - Invited lecture from industry/academia
8	Corrosion prevention (inhibitors)	- Class discussion along with online audio/video of inhibitor related concepts - Lab session to evaluate performance of selected inhibitors

shows in detail the activities employed for each component of the course.

One of the challenges in active learning implementation is the lack of a unified assessment methodology, so, therefore, from the beginning, students were provided with grading rubrics related to active learning activities, which were mainly based on diagnostic and formative assessments.

Table 3. (a–c) shows in detail the grading rubrics adopted for in-class active learning activities during three different phases of the course.

(a) Guided Phase [Ch. 2~6]
#	A (Full Marks)	B (80%)	C (60%)	F
Completeness	All questions must be solved.	80% of the worksheet is attempted.	Half of the worksheet is completed.	<40% is attempted.
Effort	- Conceptual questions are discussed in detail as advised. - All steps and calculations are shown for numerical questions.	- There is a good discussion of concepts, but some information is missing (10~20%). - Most of the questions are solved in detail, except few (15~20%).	- Almost 50% of the worksheet questions (both conceptual and numerical are not discussed in detail).	- No detailed discussions of concepts and numerical.
Correctness	All paper-based activities must be correct, as it is a guided phase; however, in online activities, correctness does not matter, as they are not guided at this stage.
Submission	On time	On time	On time	On time
(b) Second Phase [Ch. 7~9] → combination of guided and non-guided activities
#	A (full marks)	B (80%)	C (60%)	F
Completeness	All questions must be solved.	80% of the worksheet is attempted.	Half of the worksheet is completed.	<40% is attempted.
Effort	- Conceptual questions are discussed in detail as advised. - All steps and calculations are shown for numerical questions.	- There is a good discussion of concepts, but some information is missing (10~20%). - Most of the questions are solved in detail, except few (15~20%).	- Almost 50% of the worksheet questions (both conceptual and numerical are not discussed in detail).	- No detailed discussions of concepts and numerical.
Correctness	All paper-based activities (guided) must be correct; however, correctness does not matter in independent/non-guided (paper-based) and online activities.
Submission	On time	On time	On time	On time
(c) Third Phase [Ch. 11~13] → 80~90% of the activities will be independent/non-guided
#	A (full marks)	B (80%)	C (60%)	F
Completeness	All questions are attempted.	80% of the worksheet is attempted.	Half of the worksheet is completed.	<40% is attempted.
Effort	- Conceptual questions are discussed in detail as advised. - All steps and calculations are shown for numerical questions.	- There is a good discussion of concepts, but some information is missing (10~20%). - Most of the questions are solved in detail, except few (15~20%).	- Almost 50% of the worksheet questions (both conceptual and numerical are not discussed in detail).	- No detailed discussions of concepts and numerical.
Correctness	In all paper-based and online activities, correctness matters along with other criteria such as completeness, effort, and on-time submission.
Submission	On time	On time	On time	On time

presents the detailed assessment rubrics for in-class active learning activities, which are organized across three phases of the course. During phases 1 and 2, most of the activities are guided activities, and so, the grading is mainly based on “student participation, effort, collaboration with peers, participation in class review sessions, and timely online submissions”. However, during the third phase, the activities are “open-ended/not guided, open-book/open-notes/open online resources”, so, therefore, here in this phase, the quality of the work in terms of its correctness is considered for grading. This guided-to-open-ended sequence reflects a learning-by-making orientation in which students iteratively design, test, and reflect on solutions to authentic problems, consistent with contemporary maker education frameworks in higher education.

3. Results and Discussion

3.1. In-Class Active Learning Activities Implementation Strategy

A well-thought-out design and implementation strategy has to be adopted for the best learning outcomes. Considering this, an active learning design framework was developed, as shown in Figure 3. Based on this framework, active-learning intervention strategies were carefully incorporated to accomplish the different outcomes of the course. A balance was established between flipped classes and in-class discussions to complete the course material in an engaging and enriching class environment. The use of audio/video lectures, online/paper-based/case-based activities, and self-learning/active review sessions is systematically used throughout the course.

The following section will present few examples to highlight the design and implementation of different activities used in the course.

3.1.1. Teaching Fundamentals/Basics of Corrosion

Traditionally, this topic is taught using slides or whiteboard explanations, which can be further strengthened by asking some questions, such as (a) What is corrosion? and (b) Why and how does corrosion take place? This will be definitely helpful rather than simply explaining from the slides; however, the instructor has prepared multiple variants of active learning activities (both paper-based and online) to teach the fundamental aspects of the subject, as shown in Figure 4.

The learning outcome of question #1 (Figure 4a) is that students should be able to understand different types of material/environmental interactions. They have to figure out the material properties (such as material type, microstructure, stresses, heat treatment, etc.), which can affect the rate and nature of its interaction with different environments (soil, aqueous, urban, rural, etc.) in varying environmental parameters such as T, P, flow rate, electrolyte nature, pH, etc. This will help them to brainstorm comprehensively on all related aspects, which are the basis of this course. The learning outcome of question #2 is to help them understand the role of oxidizers (number of oxidizers, their types, concentration, etc.) on the corrosion rate of zinc in a given environment. The students, while working in groups, need to elaborate on which beaker will have the highest corrosion rate (why and how). Though the electrolyte is the same in all cases, the number of oxidizers is changing, which will ultimately affect the corrosion rate. Question #3 is designed to convey an important concept related to the fundamentals of corrosion, that why some part of a metal surface starts corroding or corrodes more as compared to the rest of the surface. This will provide them with important concepts related to the formation of local anodes/cathodes on metal surfaces and the reasoning behind it, such as “material composition/microstructure, defects, electrolyte concentration variation along with surface deposits”, etc.

3.1.2. Teaching Thermodynamics of Corrosion/Pourbaix Diagram

Question #1 in this active learning activity (Figure 4b) was designed for numerical practice of the Nernst equation and its applications to understand the effect of T, P, and electrolyte concentration (key environmental parameters affecting the corrosion rate of materials) on electrode potential. An understanding of the Nernst equation is important, as it will be used later for constructing Pourbaix diagrams (PB) of different metals. Question #2 is carefully designed to help students understand the applications of PBs in determining different corrosion protection strategies, i.e., water treatment, anodic protection/passivation, and cathodic protection, respectively. This question will also enrich the fundamental concept that PB diagrams do not provide any information regarding corrosion rates or the quality of oxide films (a key consideration in the utilization of PBs). In another activity, students compared the Pourbaix diagrams of iron and chromium to explore why stainless steel is regarded as a key alloy for corrosion protection. This allowed them to analyze the shifts in stability regions, particularly those related to oxide films and their types, in the two diagrams. Question #3 will help the students to understand the concept of the electrical double layer (EDL), which is the basis for the development of a key thermodynamic parameter, called electrode potential. They will also understand different models explaining the formation of EDL at the metal/solution interface.

3.1.3. Teaching Material Failure Modes/Corrosion Types

Figure 4c,d shows the activities related to the second half of the course, where students learn different types of corrosion failures and their respective mechanisms. The activities in this section are mainly case-based inquiries, in which students are presented with actual case studies from different industries. They need to analyze the case and report the type of corrosion, its causes (related to material, environment, fabrication, etc.), and what could have been done to avoid such a problem. Question #1 in this example (Figure 4c) presents a failure of 304 stainless steel (SS) used for drinking water transportation and should not have failed, as there was no issue in terms of material selection. While brainstorming this case, they need to consider material type, its history (welding, heat treatment, etc.), along with pipeline commissioning details (hydrotesting, etc.) and actual working environment (T, flow rate, condensation, water quality, etc.). This will foster higher-order thinking skills among the students, as they need to analyze all the details, identify the reasons, and suggest a solution. By doing so, they will be able to apply the knowledge learned so far in the course, starting from the basics, thermodynamics, kinetic aspects, and passivity. Question #2 highlights the importance of controlling fabrication conditions to avoid material corrosion issues. The student groups need to think critically why the stainless steel block is showing signs of corrosion in an open-air fabrication shop. Question #3 is designed to convey concepts related to galvanic corrosion, local anodes/cathodes, coating failures, and material selection and design. Figure 4d shows an online Socrative self-evaluation/self-learning activity enriching students′ conceptualization of corrosion types. Students can discuss the questions with each other, and after submission, can have correct answers with key conceptual details as feedback. The instructor, after analyzing student performance, can identify the conceptual gaps for further enrichment. Figure 5 shows student engagement in different class activities such as TPS, ARS, large group discussions, and online Socrative/Kahoot self-learning sessions.

The examples discussed above are instrumental in fostering higher-order thinking skills among students, as outlined in Bloom’s taxonomy. By engaging in active learning activities that require analysis, evaluation, and creation, students move beyond mere memorization or understanding of content. These activities challenge learners to break down complex concepts, identify patterns, and make informed judgments, thereby enhancing their critical thinking and problem-solving abilities. For instance, when students are asked to evaluate a research study or compare different solutions to a problem, they are not only recalling information but actively applying it in meaningful contexts, which strengthens their cognitive abilities at a higher level. The instructor has designed different active learning activities to guide students through these upper levels of Bloom’s taxonomy. By encouraging tasks such as designing a project, constructing a model, or debating multiple perspectives, students are prompted to synthesize knowledge and generate original ideas. This hands-on engagement ensures that learning is dynamic and participatory, rather than passive. As a result, students develop the ability to think critically, assess information rigorously, and create innovative solutions, equipping them with the essential skills needed for lifelong learning and real-world problem-solving.

3.2. In-Class Active Learning Activities Implementation Evaluation/Grading Strategy

It is important to design a proper active learning implementation grading strategy with proper rubrics (as shown in Table 3). Assessments, in their essence, are very important to ensure students have gained the required course skills; however, the way evaluations should be designed matters a lot. The overall objective of any course is to help our students grasp the required course skills, not to punish them. So, therefore, the common anxiety factors related to traditional summative assessments can be minimized with active learning implementation. Test-related anxiety is reported to seriously affect the performance of students at all levels, including higher education [41,42]. In order to address typical test-related anxiety factors such as poor preparation, low prior test performances in the past, and failure-related fear, active learning assessments should be diagnostic and formative in nature [43,44]. Therefore, as reported in the previous section, 20% of the course grade was dedicated to in-class active learning activities and 20% to higher-order thinking skills, achieved through PBL implementation in the course. The study has implemented the assessment of in-class activities in three phases, with careful integration of guided and open-ended activities. This has helped in the overall improvement of the academic progress of the students. They not only earned grades for their active participation in the class activities, but this also helped them prepare well for subsequent quizzes, midterm, and final exam, i.e., summative assessments [45,46]. Diagnostic assessment is used to discover what students already know, the skills they bring, and any misconceptions they may have before instruction begins. This can be completed through tools such as pre-tests and self-assessments, etc. By identifying strengths and weaknesses early, lesson plans and teaching strategies can be adjusted accordingly. Formative assessment, on the other hand, happens during the learning process and provides ongoing feedback for both students and instructors. It helps track progress, identify areas for improvement, and evaluate the effectiveness of teaching methods. Formative assessment (FA) enables teachers to understand how students grasp, retain, and connect scientific concepts and theories [47,48].

Table 4. Student grades as per grading rubrics shown in Table 2 for active earning activities.

Active Learning Implementation in Class [Phase#1]
Student ID#	#1—Basics (0.5)	#2—Basics (15)	#3—Thermo (1)	#4—Thermo (0.5)		#5—Kinetics (0.5)
1	0.5	11	1	0.5		0.5
2	0	10	0.7	0.4		0.5
3	0.5	8	0.7	0.5		0.5
4	0.5	12	0.8	0		0.5
5	0.5	12	0.9	0.5		0.5
6	0.5	7	0.7	0.4		0.5
7	0.5	0	0.7	0.5		0.5
8	0.5	9	0.8	0		0
9	0.5	7	0.9	0.5		0.5
10	0.5	11	0.8	0.5		0.5
11	0.5	0	0.8	0.4		0.5
12	0.5	12	0.9	0.5		0
Active Learning Implementation in Class [Phase#3]
Student ID#	#12—Coatings (1)	#13—Coatings (1)	#14—CP (1)	#15—CP (1)	#16—CP (2)	#17—Inhibitors (2)
1	0.4	0.5	0.5	1	2	1.6
2	0	0.45	0	1	1.3	0.5
3	0.5	0.4	0.2	0.5	1	1.2
4	0	1	0.5	0.2	1.5	1
5	0.5	0.5	0.5	0.7	2	1.6
6	0.4	0.5	0.5	0	0.5	1.5
7	0.3	1	0.3	1	0.7	0.5
8	0.3	0.4	0.5	1	1	1
9	0.4	1	0.5	0.5	2	1
10	0.4	0.2	0.2	0.5	0.5	0
11	0	0.7	0.5	1	2	0.8
12	0.4	0.5	0.5	1	1.1	1.2

gives an idea of student grades based on the above-mentioned assessments.

3.3. Pre-/Post-Assessment Sample of AL Implementation

Table 5. Quiz results of pre-/post-AL implementation of corrosion kinetics in the corrosion engineering course.

# of Students	Before (Out of 10)	After (Out of 10)
1	8	9
2	5	6
3	3	5
4	2	3
5	5	5
6	5	6
7	4	6
8	5	7
9	3	5
10	5	4
11	4	6
12	5	7
13	5	6
14	3	5
15	7	10

presents the quiz scores of students before and after implementing active learning in the class to quantify the conceptual understanding of core corrosion concepts. Fifteen students completed the quiz before and after the active-learning intervention and the analysis showed a significant improvement in the performance, with mean scores increasing from 4.60 (pre-test) to 6.00 (post-test), t(14) = 5.50, p < 0.001, with a large effect size (Cohen’s d = 1.42, 95% CI [0.85, 1.95]), indicates a positive impact. The average gain of 1.4 points demonstrates a substantial enhancement in conceptual understanding following the active-learning module, supporting the effectiveness of the instructional approach.

Figure 6a,b shows two final exam questions of the undergraduate corrosion engineering course, which are designed to test higher-order thinking skills of the students as per Bloom’s taxonomy staircase. Based on student performance analysis of these two questions, it was deduced that two-thirds of the students (10 out of 15) scored 3 or above (out of 5), suggesting a satisfactory to strong ability to interpret data, justify reasoning, and apply conceptual understanding. A smaller percentage of students (5 out of 15) found it difficult to extend their reasoning, which suggests further improvement to address open-ended, complex questions. This data suggests that the majority of students were able to engage successfully with higher-order learning tasks, consistent with Bloom’s “Analyze” and “Evaluate” levels. It also suggests that such aspects require further strengthening in future offerings of the course.

3.4. Project-Based Learning

Project-Based Learning (PBL) stands out as an effective approach for bridging theoretical knowledge with real-world application. It supports the development of essential practical skills like teamwork, problem-solving, and innovation that are crucial for 21st-century engineers. PBL naturally aligns with Bloom’s taxonomy, engaging students across all levels of cognitive development. Initially, learners focus on remembering and understanding core concepts needed for their projects. As they move forward, they apply this knowledge to real-life scenarios, tackling challenges that demand critical thinking. Through repeated cycles of action and reflection, PBL encourages students to analyze their results, assess approaches, and refine solutions. This process not only deepens their understanding but also leads to the creation of a final product or solution representing the highest tier in Bloom’s cognitive hierarchy. Such comprehensive engagement promotes both knowledge retention and the growth of advanced thinking skills necessary for lifelong learning and engineering careers. Moreover, when PBL is embedded within a holistic, experience-driven, and principle-based teaching model, it enhances students′ ability to reach and make sense of the higher levels of Bloom’s taxonomy. In engineering education, Bloom’s framework plays a vital role by guiding the development of advanced cognitive skills. It empowers students to go beyond just learning concepts; they learn to critically analyze, evaluate, and design innovative solutions for complex engineering challenges.

It has been reported consistently in the literature that PBL significantly helps in improving overall student performance in terms of both technical (experimental, simulation/modeling, data analysis and interpretation, etc.) and soft skills (present preparation, delivery, etc.) [49,50,51]. Chen et al. [52] reviewed PBL implementation and its associated challenges in engineering education and reported four levels of implementation, i.e., course, cross-course, curriculum, project, etc. The review concludes that effective PBL requires structured curriculum design, faculty training, continuous student support, and stronger institutional backing to maximize its impact on engineering education. Guo et al. [53] reported empirical studies on PBL in higher education, focusing on student outcomes and associated assessments. They have reported that PBL can enhance knowledge, problem-solving, teamwork, motivation, and professional skills. It was also emphasized in their work that PBL is considered an authentic learning process. Guerra et al. [54] conducted a systematic review of the required skills of graduates, such as high-order thinking, interdisciplinary teamwork, and adaptability to societal and technological change. It highlights the importance of active learning environments, particularly PBL, in fostering these skills. Considering this, the instructor has summarized and adopted the PBL framework as shown in Figure 7 for PBL implementation and its subsequent outcomes.

Project-Based Learning Methodology

Project-based learning followed a detailed implementation and evaluation plan as presented in Figure 8. It started with a course project idea pitch by a team of students as per the provided layout, which includes a tentative title, project background, execution details (experimental/computations), and relevance of the topic with industry. After the idea pitch, one-on-one meetings were conducted with each team to fine-tune the project, considering its timeframe, equipment/software requirements, and materials/chemicals/accessories availability. This is followed by a detailed project execution plan preparation and finalization, in which each team member will be leading at least one or multiple project tasks. After this, students are asked to match their project tasks with student learning outcomes of the course, to have a clear idea of how their project will help them understand different components of the course.

The project is finalized within the 4th~6th week of the semester, and soon afterwards, students start their experimental/simulation work. Subsequently, two progress/intervention meetings are conducted to track the progress of each team and guide them in case of any confusion. During the second progress meeting, students are required to present data analysis/interpretation, which provides an opportunity for each team to improve their results and re-perform any experiments/simulation runs if required. Finally, at the end, students are required to prepare the poster presentations for external evaluation, as per the provided rubric shown in

Table 6. Final poster presentation evaluation rubrics for project-based learning component of the course.

Presentation/Poster Evaluation Guidelines for Project-Based Learning
#1	Background and Objectives: The term project background and objectives are clearly mentioned.
#2	Material Used and Preparation: The types of materials used and details about material preparation are well explained.
#3	Experimental and Simulation Plan: The experimental plan, as well as the simulation, is well-designed and organized to achieve the objectives.
#4	Presentation Quality and Conclusions: The poster was well-organized (concise but informative with no spelling or grammar mistakes) and presented logically. Conclusions are well-documented.
Project-Based Learning External Evaluation
Group and Project Title	Team Members	Project Background (5 point)	Project Objectives (5 point)	Experimental Plan (10 points)	Experimental Results (20 points)	Presentation Quality (5 points)	Team Total (45 points)	Individual Evaluation (10 points)	Progress Meetings (10 points)	Team Member Score (out of 20)
Project-Based Learning Peer Evaluation [Provide justification for your evaluation score]
Group and Project Title	Team Members	Peer Evaluation (Excellent)		Peer Evaluation (Very Good)		Peer Evaluation (Good)		Peer Evaluation (Poor)
#1	Excellent → As a task leader, not only accomplished their task, but also participated in all project-related activities.
#2	Very good → As a task leader, accomplished their task and, when asked, helped others as well in their tasks.
#3	Good → As a task leader, focused and accomplished their given task assignment.
#4	Poor → Did not complete their task and missed most of the project-related combined activities.

. Based on the poster presentation, term project grades are finalized, and three winning posters are selected for certificates/medals during the Mechanical Engineering Departmental Poster Expo. One important evaluation of project-based learning is peer review evaluation, as per Table 6. This peer review strategy is very helpful to keep each team member on track and contribute with the best of their abilities to make the project successful.

Table 7. Winning course project topics of previous two semesters (PBL implementation).

#	Implementation of Project-Based Learning (PBL) in Corrosion Engineering Course (List of Best Course Projects for the Previous Two Semesters)
1	Effect of surface roughness (#200, 600, 1000) on the corrosion behavior of Al vs. SS 304 in a chloride environment
2	Application of machine learning tools in corrosion prediction with a focus on galvanic corrosion design
3	Effect of processing parameters on the corrosion performance of additively manufactured alloys, mechanism and challenges
4	Modeling galvanic corrosion between iron and zinc in seawater
5	Internal corrosion mechanism and challenges of oil and gas pipeline material selection/design considerations
6	Comparative analysis of corrosion resistance in 304 SS and 305Si using electrochemical techniques in 3.5 wt.% NaCl solution

shows the list of winning projects of the last two semesters, and Figure 9 shows pictorial evidence of student projects related outcomes/activities. Throughout this PBL execution, student teams put their maximum effort, starting from project planning, execution, data analysis, and up to the poster presentations, reaching higher levels of Bloom’s taxonomy. They were able to acquire the skills presented in the planned PBL framework (Figure 6). Considering the dynamics of corrosion science and engineering subject and its industrial needs, it was quite satisfying to see the students acquire an in-depth understanding of the subject with hands-on experience while working on applied projects.

The performance (as per the evaluation rubric shown in Table 6) of nine project-based learning (PBL) teams was quantitatively analyzed to have a clear idea of student/team performance in this important active learning component of the corrosion engineering course. The mean PBL score of nine teams was found to be (M = 35.6 ± 5.8) out of 45, which shows overall satisfactory achievement. Most of the teams performed well in all five components of the evaluation rubric, i.e., project background, objectives, experimental plan, results and discussion, and presentation quality, respectively. It was found that the highest average score was for presentation quality (M = 4.33 ± 0.87) and clarity of project objectives (M = 4.11 ± 0.78). These results suggest that teams effectively communicated their technical understanding of the project scope and objectives. The data related to the experimental plan (M = 7.44 ± 1.42) and results and discussion (M = 15.67 ± 2.50) exhibited overall good performance of the teams in terms of experimental methodology design and data analysis/interpretation. The project-based learning is expected to provide hands-on experience to the students, and by doing so, they should be able to acquire higher-order thinking skills of Bloom’s taxonomy, i.e., apply–analyze–evaluate, respectively. It is also clear from these results that the suggested PBL framework contributed significantly to enhancing the technical problem-solving and communication skills of the students. Embedding design-and-make cycles in corrosion projects aligns with emerging evidence that such tasks cultivate sustainability competencies and green digital skills alongside technical outcomes, particularly when teams engage with digital tools, materials choices, and lifecycle considerations.

3.5. Student Feedback Regarding Active Learning and Project-Based Learning

Figure 10a–d show the results of anonymous student feedback regarding active learning implementation and their impact on student understanding of fundamental concepts. It is basically the result of a mid-evaluation survey, to have an early student feedback regarding active learning integration in the course. Figure 10a shows some general questions regarding teaching/communication/class practice work, and the student response was satisfactory. However, Figure 10b–d show the results of more specific questions related to the outcome of “active learning strategies”, adopted until the mid-point of the course. It is clear from the results that students overwhelmingly appreciate that their understanding of different concepts was significantly improved after active learning activities were incorporated in the course to reinforce the concepts initially taught using a traditional approach.

Based on data presented in Figure 10, the normalized gain was calculated to quantify the improvement in students’ perceptions before and after the implementation of active learning activities, based on the methodology adopted by Hake et al. [55]. This methodology has been widely used in engineering and STEM education research to analyze data in Likert-scale responses. The normalized gain reflects the ratio of the observed improvement to the maximum possible improvement and is found to be 0.61, 0.58, and 0.48 for questions 1~3, respectively. This shows medium to high gain levels, highlighting a positive impact of active learning on student learning.

Figure 11 and Figure 12 show detailed student responses at the end of the course, related to active learning and problem-based learning implemented in the course. The survey questions targeted different student and course learning outcomes. It is clear from Figure 11a–c that the majority of the students agree that the integration of different active learning activities in the course (paper-based and online) improved their subject understanding and critical thinking skills. When asked about 5E’s related to student engagement, exploration, explanation, elaboration, and evaluations, the feedback remained quite positive.

Figure 12 provides student feedback on different aspects of the PBL. Students were asked how PBL has helped them in improving higher-order thinking skills, such as engineering skills, and the response was quite satisfying. Regarding soft skills and overall understanding of the subject, most of the students appreciate and acknowledge the positive impact of PBL. When asked about challenges faced while working on experimental projects, they reported the following: (a) time constraints; (b) demanding; (c) more lab support; and (d) availability of accessories and materials. Students also highlight the importance of continuous feedback and progress intervention meetings to keep the project progress on track.

3.6. Study Limitations

The results presented above highlight significant improvement in the overall performance of the students based on active learning implementation in the course; however, there are a number of limitations that need to be considered. Firstly, the study was conducted over two semesters, but the sample size was not very large, as not all 32 students were engaged in all surveys and quizzes. Another significant limitation was the lack of a control or comparison group for accurate quantitative comparison and identifying the separate impact of the active-learning intervention. It is also worth mentioning that instructor–student interaction can vary and so influence both engagement levels and self-reported perceptions of learning. In this study, a three-point Likert scale was used for various survey questions and limited in-depth capturing of student attitudes or perceptions. Self-assessment results may possibly have been impacted by potential response bias, especially considering the small cohort size and high instructor–student interaction in such elective courses. However, despite all these constraints, the presented data shows consistent improvement in student performance, which supports the overall validity of the observed learning effects. In the future offering, the sustainability aspects of the PBL framework will be further strengthened by incorporating an explicit sustainability criterion in the PBL evaluation rubric to encourage students to integrate environmental, social, and economic considerations into their project designs and decisions.

4. Conclusions

The paper discussed in detail the implementation of active learning and project-based learning in an undergraduate corrosion engineering course at the mechanical engineering department, KFUPM. The key takeaways can be summarized below:

• The paper presents a well-structured and sustainable active learning implementation methodology for each component of the course.
• The use of active and project-based learning in an undergraduate corrosion engineering course at KFUPM has considerably improved student engagement and conceptual understanding, as the overwhelming majority (up to 90%) responded positively.
• The redesigned course, to implement active learning activities such as TPS and CBIs, enhanced collaboration, critical thinking, and lifelong learning competencies among students, as more than 90% voted in favor.
• The adoption of formative and diagnostic assessments with continuous feedback was helpful to reduce anxiety among the students without compromising the quality of the evaluation process.
• The Cronbach’s alpha value for the questionnaire was found to be 0.75, indicating good internal reliability.
• The developed active learning–PBL framework provided a sustainable model for a student-centered and outcome-oriented learning environment.