Embedding artificial intelligence (AI) in chemical engineering curricula is often constrained by software deployment barriers and limited evidence about how students engage with AI-enabled workflows. This preliminary implementation and feasibility study integrated a neural processing unit (NPU)-powered cloud AI Notebook into two chemical engineering courses using fixed-bed reactor design as the central case. The instructor provided a functional multilayer perceptron (MLP) workflow, while students modified model architecture and hyperparameters, compared catalyst geometries, and interpreted predictions against computational fluid dynamics (CFD)-derived reference data. The teaching and survey cohort comprised 72students (22 undergraduates and 50 postgraduates), all of whom provided matched pre-intervention and post-intervention questionnaire data. A 28-student course-assessment subset (22 undergraduates and six first-year master students) completed a final-examination item and presentation assignment. The cloud NPU reduced single-epoch training time from 114.2 s on a local CPU to 5.8s and enabled repeated model exploration within a 45-minute session. Questionnaire scores increased descriptively across the four self-reported dimensions, while the final-examination item yielded a mean score of 8.36 out of 10 (SD 1.54). These findings support the technical feasibility and short-term educational relevance of the module. However, the absence of an objective pre-test, control group, and longitudinal follow-up precludes causal claims about learning gains.
Chemical engineering curricula must respond to digitalisation, sustainability, artificial intelligence and changing professional expectations while retaining the disciplinary core of the field. This study examines future curriculum priorities through a topic-level comparison of stakeholder views, curriculum design proposals, current international syllabus content and accreditation expectations. Topic priorities were identified through a survey and a structured workshop involving academic and industrial participants. Current provision was mapped using publicly available syllabus information from 40 leading international chemical engineering programmes, with topics coded by year, compulsory or optional status and frequency of appearance. The findings show strong agreement that mathematics, engineering fundamentals, unit operations and process design remain central to chemical engineering education. However, applied process design and safety topics were less consistently explicit in current syllabuses than their perceived importance would suggest, while broader digital, sustainability and sector-specific capabilities remain unevenly represented. These findings indicate that the future chemical engineering curriculum should evolve by making applied design, safety, digital and sustainability capabilities more visible, coherent and assessable across the programme, while allowing specialisation in emerging sectors. Curriculum renewal should therefore augment rather than replace the established chemical engineering core. Whilst transferable skills are noted, they are outside the scope of this paper.
This study evaluated Kahoot!-supported collaborative learning in a first-year chemical engineering fluid mechanics module delivered within an outcome-based education framework aligned to the Malaysian Qualifications Framework (MQF 2nd Edition) and current Malaysian engineering accreditation standards. A quasi-experimental design compared three cohorts: January 2025 (mixed implementation within one class), May 2025 (no Kahoot!), and September 2025 (full implementation). Performance was analyzed using Course Learning Outcome (CLO)-aligned indicators: Test 1 as a CLO1, Test 2 as a CLO2, and the normalized final examination. Cross-cohort one-way ANOVA showed no statistically significant differences for CLO1 or final-exam performance, but a significant cohort effect for CLO2 that was attributable to assessment variation in September 2025 rather than to the intervention. The strongest internally controlled comparison, within January 2025, showed negligible differences between Kahoot! and non-Kahoot! sections on CLO1, CLO2, and final-exam outcomes. The findings show that Kahoot! did not improve summative attainment in this module. Its defensible value lies instead in formative engagement, immediate feedback, and curriculum-compatible classroom interaction. For OBE and quality-assurance practice, the study shows that a digital response tool can be integrated without compromising attainment of assessed CLOs.
This study establishes a systematic instructional model to integrate value-oriented education, professional ethics, digital competence, and sustainability into the core chemical engineering course Pharmaceutical Reaction and Separation Engineering. A four-dimensional holistic framework is proposed, centering on disciplinary knowledge while embedding ethical literacy, digital skills, and sustainable development concepts. A mixed-methods evaluation was applied across 98 undergraduate students, including questionnaires, interviews, classroom observation, and academic performance assessment. Results demonstrate that embedded case teaching, scenario simulation, and discussion-based learning significantly improve students’ professional ethics, social responsibility, digital literacy, sustainability awareness, and academic achievement. The integrated design strengthens the connection between curriculum delivery and industrial competency requirements for pharmaceutical process engineers. The design aligns with international engineering accreditation standards and the UN Sustainable Development Goals. This work provides a replicable curriculum integration paradigm for chemical and pharmaceutical engineering education. It offers actionable insights for curriculum designers and instructors aiming to enhance ethical and sustainable practice in chemical engineering education. It supports the cultivation of ethically aware, digitally skilled, and sustainability-minded graduates to meet global industry demands.
This work presents a pedagogical approach to improve the quality, consistency, and effectiveness of feedback on continuous assessments through a graduate teaching assistant (GTA) workflow training. Student satisfaction with feedback in UK higher education has historically been lower than for other teaching elements, often due to unclear, inconsistent, or non-actionable comments. In response, a structured workflow was developed and implemented within a final-year Chemical Engineering course at the University of Manchester to improve feedback and marking practices on coursework marked by GTAs. The workflow, based on a “Prepare–Train–Test–Ready” cycle, aimed to ensure marking consistency, detailed justification of marks, and feedback focussed on critical discussion and student improvement. The approach was informed by established feedback principles, including timely, specific, goal-oriented, and actionable feedback, as well as tailored feedback categories. Implementation took place in the past two academic years and resulted in improved student satisfaction, way fewer complaints about marking, and measurable increases in feedback evaluation scores. In addition, the enhanced quality of feedback boosted students’ academic performance in the final exam and their overall attitude towards the course. The study thus demonstrates that a structured GTA workflow training can significantly improve student learning experience and feedback effectiveness across STEM disciplines.
The Haber–Bosch process remains one of the most significant industrial chemical processes in terms of global impact, energy use, and engineering complexity. This communication describes a scaffolded and transferable teaching module employing ChemCAD™ to simulate the industrial Haber-Bosch ammonia synthesis process, aimed at fourth-year undergraduate chemical engineering students enrolled in an Industrial Processes course with prior knowledge of thermodynamics, reaction engineering, and process simulation. A complete set of ready-to-use learning materials, including step-by-step exercises, environmental reflection prompts, simulation activities, instructor guidance, complete ChemCAD™ simulation files, and supplementary resources, was developed to support learning in mass and energy balances, reactor modeling, phase separation, recirculation loops, compression, thermodynamics equilibrium analysis, and process evaluation and energy analysis. The module was designed to promote technical analysis, systems thinking, and critical reflection on sustainability, while progressively introducing students to industrial process flowsheets, recycle strategies, energy requirements, and engineering decision-making. The module has been implemented in multiple iterations of the Industrial Processes course at the Universidad Autónoma de Guadalajara (Mexico), including a COIL (Collaborative Online International Learning) experience developed in collaboration with Universidad de Lima (Peru). The proposed module provides instructors with a transferable framework for integrating simulation-based learning, sustainability-oriented reflection, and international collaborative activities into undergraduate chemical engineering education, while offering a flexible platform that can be extended toward kinetic reactor models, industrial recycle configurations, and advanced sustainability analyses. Supplementary implementation materials, including editable workbooks and ChemCAD™ simulation files, are provided to support adoption and adaptation by other educators.
Everyday situations can provide powerful contexts for chemical engineering education when they require both calculation and engineering judgement. This paper presents an Example of Good Practice based on indoor exposure during domestic gas cooking. A 30 m3 student studio with a 3 kW gas burner is used to teach a wellmixed transient species balance, ventilation effects, carbon monoxide toxicity and methane flammability risk. The same first-order accumulation framework is deliberately reused for three contrasting interpretations: carbon dioxide as a confinement and ventilation indicator, carbon monoxide as an acute toxic hazard, and methane as a flammable gas whose risk depends on the lower and upper flammability limits. The activity was implemented with chemical engineering students; anonymous cohort-level questionnaire data were available before instruction (n = 92) and after a process-safety teaching sequence (n = 89). The results show substantial descriptive improvements across the targeted concepts, including source-to-volume effects, ventilation time constant, the distinction between CO2 and CO, and interpretation of methane flammability limits. The paper provides the technical basis, learning objectives, implementation sequence, assessment rubric, questionnaire and instructor notes needed to reuse or adapt the case in undergraduate or master-level chemical engineering courses. Social media post abstract: A gas-cooking case helps students connect transient mass balances to CO2, CO and CH4 safety decisions.
Generative artificial intelligence (genAI) has entered chemistry and chemical engineering education with unusual speed and unusually high epistemic stakes. Because chemistry learning depends on verbal explanation, symbolic notation, quantitative reasoning, visual representation, and safety-constrained practice, while chemical engineering adds process-scale models, flowsheets, piping and instrumentation diagrams, control logic, scale-up assumptions, and professional safety decisions, the educational consequences of large language models are more complex than a generic question of efficiency. This PRISMA-guided scoping review synthesizes a bounded corpus of 25 chemistry and chemical engineering studies and interprets it alongside broader higher-education scholarship on assessment, trust, policy, and responsible AI use. Across the included literature, adoption is unfolding along two linked paths: unsanctioned student use that destabilizes conventional assessment, and deliberate pedagogical integration that asks students to test, critique, verify, and sometimes redesign machine output. The review also foregrounds less positive impacts, including over-reliance, hallucinated evidence, unequal AI literacy, erosion of assessment validity, and unsafe transfer of AI-generated advice into laboratory or process contexts. Five themes recur: assessment disruption, prompting and AI literacy, chemistry- and chemical-engineering-specific capability limits, laboratory and teacher-facing integration, and governance. The review argues that genAI in chemistry and chemical engineering education should not be framed as a simple tutoring technology. Instead, it should be understood as a socio-technical infrastructure whose educational value depends on disciplinary verification practices, representational competence, professional judgment, and institutional design.
Virtual laboratories (VLs) provide a promising solution for overcoming the resource and safety constraints of traditional laboratory teaching. However, many VLs lack the necessary pedagogical support to facilitate deep learning and inquiry. To address this, this study developed a Structured Inquiry-Based Virtual Laboratory (SIBVL), which integrates the key stages of inquiry-based learning (IBL) into a virtual environment. It was then implemented in a flipped chemical engineering classroom. A quasi-experimental design involving pre- and posttests was employed with 90 s-year chemical engineering students from a university in central China. Participants were assigned to one of three groups: an SIBVL group, a general virtual lab (GVL) group, or a traditional flipped classroom (TFC) group. All students engaged in a silicic acid preparation experiment as the core learning task. Data were collected using a knowledge achievement test (SAPKAT), a laboratory skills rubric (LSPR), and an adapted version of the Instructional Materials Motivation Survey (IMMS). The results showed that students in the SIBVL group performed significantly better than those in the GVL and TFC groups in terms of learning achievement, laboratory skills, and perceived motivation. These results show the benefit of incorporating IBL into VLs and provide empirical evidence for integrating such environments into flipped chemical engineering classrooms.
We present the design and evaluation of a simulation-based learning approach implemented in a second-year chemical engineering module, integrating Aspen HYSYS with a methanol production case study to embed sustainability and develop student awareness of the United Nations Sustainable Development Goals (SDGs). Through process simulation, we enable students to model complete flowsheets, explore scenario-based analyses, and evaluate sustainability-driven process modifications. Within a structured mini-design project involving reaction and separation systems, we require students to analyse mass and energy balances, optimise process performance, and evaluate trade-offs between efficiency and sustainability. We also ask students to identify and justify relevant SDGs within their designs. Our analysis of student outputs shows improved ability to link engineering decisions with sustainability objectives, enhanced energy-focused reasoning, and stronger systems-level thinking. Overall, the results highlight the effectiveness of simulation-based learning in integrating technical competence with sustainability literacy in undergraduate chemical engineering education.
Heat transfer is a core course in majors such as chemical engineering and power engineering, characterized by its strong theoretical foundations and complex analytical methods. Incorporating numerical simulation into heat transfer teaching can significantly enhance students' conceptual understanding and foster their interest. This paper presents improvements in heat transfer pedagogy based on Energy2D simulation software. Using fin heat conduction and fluid cross-flow over tube bundles as representative teaching cases, the instructional design incorporates Energy2D simulations to concretize abstract concepts and enhance understanding of challenging lecture content. A feedback survey utilizing a 5-point Likert scale was conducted among 57 students to evaluate the intervention's effectiveness in terms of learning outcomes, software usability, teaching support, and overall satisfaction. Results indicate an overall satisfaction rate exceeding 90% with the Energy2D-assisted instruction, along with significant improvements in student engagement and understanding of heat transfer principles. Beyond validating theoretical knowledge through practical simulation, this approach effectively cultivates students' software application skills. This study demonstrates the potential of simulation-aided instruction to enhance engineering intuition and problem-solving abilities, offering valuable insights for improving pedagogical strategies in engineering courses.
Experimental instruction of instrumental analysis is crucial for developing and enhancing students' proficiency in instrument operation. However, due to the high cost of sophisticated instruments and limited availability of equipment, it is challenging for each student to have ample opportunities for independent practice and repeated operation. This study targets the prominent shortcomings in university instrumental analysis laboratory teaching, namely the scarcity of large-scale precision instrument resources and inadequate hands-on operation opportunities for individual students. We applied virtual simulation platforms for multiple large instruments, designed diverse teaching models, and carried out a controlled teaching experiment with 120 undergraduates from two different chemistry-related majors. The teaching efficacy was comprehensively evaluated via theoretical examinations, operational skill assessments, and learning interest questionnaires. Results reveal that virtual simulation experiments boast distinct advantages including risk-free operation and repeatable practice, however could not replace physical experiments in cultivating students’ hands-on operational experience and practical problem-solving capabilities. The virtual-physical hybrid teaching model proves to be the most effective approach. It enables students to efficiently grasp instrument operating principles, standard operational procedures and safety protocols via virtual simulation. It also facilitates the transformation of theoretical knowledge into hands-on practical skills through physical laboratory experiments. This virtual-physical hybrid teaching model represents the most efficient and economical solution for teaching scenarios with limited resources.
The incorporation of virtual tools has been shown to enhance comprehension and engagement in chemical engineering education. To support practical learning in photocatalytic reactor design, the LEDsModel Lab simulator was developed in MATLAB (R) R2024b and fully compatible with GNU Octave (version 9.2.0), focusing on the determination of the Local Superficial Rate of Photon Absorption (LSRPA) and the influence of reactor configuration on light distribution. Through four case studies, students apply theoretical models to practical scenarios, bridging the gap between theory and practice. Fully integrated into the Advanced Analysis and Design of Chemical Reactors course (6 ECTS, Master's in Chemical Engineering, University of Granada), preliminary classroom observations indicate a positive trend in student performance, accompanied by increased engagement with photocatalytic reactor modelling. This is reflected in higher grades and lower failure rates, alongside a clear strengthening of key competencies in problem-solving, quantitative analysis, and computational modelling. Its implementation has further allowed an expansion of course content to include intrinsic photocatalytic kinetics, demonstrating the potential of interactive simulation tools to enrich curriculum content, improve learning outcomes, and prepare students for the analytical and practical challenges of modern chemical engineering.
Graduate attributes (GAs) are a required component for accreditation of undergraduate engineering programs in Canada. Similar to ABET student outcomes in the United States, they attempt to quantify a broad range of technical and non-technical skills that engineers are expected to possess upon graduation. However, the heterogenous nature of the data makes it difficult to draw meaningful conclusions using basic statistics, necessitating the use of more advanced analysis. This work presents and applies a mixed-effects model to six years of GA data from the final two years of a four-year chemical engineering program as a means of providing a clearer measure of overall student performance on specific outcomes by separating heterogenous factors such as assessment method and course offering from overall student performance. Through a mixed-effects modeling approach, assessment method was found to have a strong effect on observed performance, with test questions showing highly reduced scores relative to all observations, while presentations and oral examinations demonstrated inflated scores. Course offering was applied as a second effect to account for the specific impact of instructor, course level, and cohort on baseline performance. Although knowledge base was found to be weakest attribute using basic statistics, the mixed-effects model identified that this was largely attributable to the predominant use of more challenging assessments such as exam questions and that communication may be a weaker attribute once assessment difficulty is accounted for. Monitoring GAs using a mixed-effects approach provides a more reliable evaluation of student performance than basic statistics, thereby strengthening continual program improvement.
Despite the central role of reactor design in chemical engineering education, students often struggle to grasp the complex interplay between kinetics, thermodynamics, and transport phenomena. To address this issue, this paper introduces ReactorApp, a MATLAB-based educational toolbox capable of simulating and optimizing ideal chemical reactors and their associations. To achieve this, the application exploits Object-Oriented Programming principles and creates a user-friendly environment where students can explore reactor dynamics, energy balances, the effects of process parameters, and retrieve thermophysical properties from Aspen HYSYS. This paper covers the theoretical background, implementation structure, and pedagogical benefits of ReactorApp, together with a series of benchmark problems to demonstrate the app’s effectiveness.In practice, ReactorApp is offered as an optional self-study aid for students of Reactor Design I module of the University of Alicante. While no formal evaluation study is reported, classroom use suggests that it enhances students’ understanding of the subject by enabling easy access to visual representations of reactor performance and a straightforward way to run their own experiments. Consequently, the app supports self-assessment on course assignments, leading to a more efficient engagement during practical sessions, and encourages the development of computational skills. Versatility was a key design criterion, making it a flexible resource for other chemical engineering subjects and project work. Overall, this work presents an interactive and open-source simulation tool to bridge theoretical concepts with practical competences in chemical engineering education.
The sharp decline in enrollment in Chemical Engineering programs in Brazil highlights the need to examine whether current curricula reflect the scientific and technological transformations shaping the field. This study presents a comparative analysis of the top 80 ranked Chemical Engineering programs in Brazil and the United States, with a focus on the inclusion of emerging areas in the chemical industry—biotechnology, nanotechnology, data science, artificial intelligence, machine learning, and information technologies. A systematic review of course syllabi revealed that, while Brazilian programs maintain a solid foundation in biotechnology and process modeling, they demonstrate limited integration of digital and nanotechnological competencies. In contrast, U.S. programs show greater breadth and interdisciplinary integration in these areas. The findings point to strategic opportunities for curricular modernization, which are essential for aligning education with technological advances and for enhancing the appeal of the field to a new generation of students and the evolving demands of the industry.
This communication presents a structured example of good teaching practice implemented in the courses Industrial Processes, Heat Transfer, and Tequila Process Engineering, where a ChemCAD simulation of a steam generation plant for tequila production, derived from published real-world research, is integrated into a role-based active learning module. The practice closes the industry-research-classroom loop through a three-phase pedagogical sequence: a contextual industrial visit, critical validation of the simulation model, and role-based simulation scenarios involving conflicting professional perspectives (Utilities Manager, Sustainability Manager, and Energy Efficiency Manager). Rather than aiming to demonstrate causal learning gains, this paper documents the pedagogical design, implementation conditions, and reflective evaluation of the module as an example of good practice in process engineering education. The module was implemented with a cohort of eight chemical engineering students (full implementation) and adapted for courses with 14 and 18 students. Student performance data and perception results are presented as indicative and contextual evidence accompanying the pedagogical description. Quantitative results showed a trend toward improved academic performance (mean difference of +10.5 points, large effect size, Hedges' g = 0.90), although small cohort sizes and non-equivalent comparison groups limit statistical inference. Qualitative evidence was strong: 89% of the teams proposed technically viable solutions, and 78% successfully integrated technical, environmental, and economic criteria in their final recommendations. Student perception surveys (n = 26) revealed exceptionally high ratings (average 4.6/5.0), particularly regarding theory-practice integration and motivation driven by the industrial context. The main contribution lies in the detailed description of the instructional design, required resources, adaptation strategies for different teaching contexts, and practical lessons learned, offering a replicable and transferable pedagogical framework to enrich process engineering education through authentic, research-based learning experiences.
Ensuring safety in chemical processes is essential to engineering education, particularly for high-risk industrial scenarios. Traditional classroom instruction and on-site training are often inadequate for conveying the dynamic complexity of hazardous reactions and equipment failures. This study presents an immersive 3D simulation training module to strengthen chemical safety engineering education, centered on a critical case: feed valve leakage and subsequent fire in a catalytic cracking unit-a common yet potentially catastrophic refining incident. We detail the simulation's design and implementation, integrating real-time process dynamics with established safety protocols, and evaluate learning outcomes through controlled experiments with educators and students. Results show that the simulation significantly enhances understanding of fault diagnostics, risk mitigation, and emergency response; students who participated in the simulation exhibited a significant improvement in fault diagnosis accuracy, achieving a post-simulation mean score of 8.6 out of 10, distinctly higher than the score of 6.2 attained by the control group. We provide recommendations for integrating such modules into chemical safety curricula and outline future research directions for simulation-based learning in process safety management.
Generative artificial intelligence (GAI) is rapidly transforming higher education, raising pedagogical, ethical, and epistemological challenges. In chemical engineering, concerns have emerged that student over-reliance on GAI may undermine the development of key skills such as problem-solving, creativity, and critical thinking. This mixed-methods study explored staff and student perspectives on the integration of GAI into chemical engineering education. Data were gathered through questionnaires (students n =115; staff n =17), two student focus groups, and five semi-structured staff interviews. Quantitative data were statistically analysed, and qualitative data were examined using reflexive thematic analysis. Five themes were identified: ethics, reliability and accuracy, impact on learning, pedagogical disruption, and staff use. Applying the Technological Pedagogical Content Knowledge (TPACK) model highlighted distinct staff-student differences. Students viewed GAI as a beneficial learning support, with limited concern for bias or authorship. Staff raised critical issues around reliability, transparency, and pedagogical alignment, but acknowledged GAI's potential to streamline routine tasks such as feedback provision. Based on these insights, this study goes beyond reporting perspectives, to also propose curriculum interventions including early AI literacy and critique-based assessment. It also offers policy recommendations addressing equity, sustainability, and the responsible integration of GAI into chemical engineering education.
