Does collaborative learning work in chemical, process and energy engineering?
Yes. When collaboration is built into modules, supported logistically and assessed with individual accountability, it lifts learning in chemical, process and energy engineering. In the National Student Survey (NSS), the opportunities to work with other students theme tracks peer collaboration across UK providers and sits near neutral overall (index +4.4), while engineering and technology trends notably positive (+26.8). Within chemical, process and energy engineering, collaboration is unusually prominent in student comments (7.1% share) and positively viewed (+21.4), but gaps in assessment clarity still surface, with marking criteria attracting a strongly negative tone (−50.8). These sector signals shape what follows.
In the dynamic world of chemical, process, and energy engineering education, the opportunity for students to work collaboratively is increasingly seen as an integral part of their academic experience. This analysis draws on student perspectives of group work, assessments, and communication within their courses to provide staff with pragmatic routes to improve practice. Collaborative projects mirror teamwork in industry settings and help students develop discipline‑relevant skills, while acting as a professional practice ground. As we examine how students from various backgrounds engage in group tasks, we highlight how structured collaboration, predictability, and transparent assessment enable better outcomes.
What are the positive impacts of team-based projects?
Students benefit when projects are designed to require interdependence and when staff scaffold roles and milestones. Teams harness a range of viewpoints and skills and build confidence by solving complex problems together. This shared work fosters a sense of belonging and prepares cohorts for the team‑oriented realities of engineering workplaces. Studios, labs, and project sprints that make collaboration routine tend to produce stronger engagement and better attainment because expectations are explicit and time is protected for joint work.
What challenges and frustrations arise in group work?
Unequal participation undermines learning and fairness. Free‑riding, role ambiguity, and late engagement sap motivation and skew grading. Time constraints and timetable clashes especially affect mature and part‑time learners, making it harder to join in sustained peer work. These risks lessen when modules publish roles and working norms up front, provide asynchronous routes for time‑poor students, and include light‑touch peer contribution checks at milestones alongside a proportionate peer‑assessment component.
How should assessment work in collaborative projects?
Assessment needs to evidence both group outcomes and individual contribution. Programmes that publish checklist‑style rubrics mapped to learning outcomes, provide annotated exemplars that show “what good looks like,” and include self, peer, and tutor inputs achieve better perceived fairness. A short feed‑forward note alongside grades (“next time, do more of X, less of Y”) increases usefulness. Given persistent concerns about assessment clarity in the discipline, staff should treat the assessment brief, marking criteria, and weighting of individual versus group components as core teaching materials, not appendices.
How do communication dynamics within groups affect outcomes?
Communication drives progress, yet avoidable friction persists when information is fragmented. Students work more effectively when each group has a pre‑provisioned digital space (channels, folders, templates), when the module offers a single source of truth for deadlines and changes, and when staff hold predictable contact slots. These moves reduce coordination overhead, keep teams focused on engineering problems rather than logistics, and improve the fairness of contribution.
What should educators prioritise now?
- Make collaboration the default: build structured team activity into module timetables (kick‑off, mid‑point, showcase), with intentional group formation and published working norms.
- Design for time‑poor learners: offer asynchronous routes and scheduled “collaboration windows” online or in evenings; enable simple partner‑matching across cohorts based on availability.
- Reduce friction and increase accountability: pre‑create the digital workspace per group; require brief milestone check‑ins; include a fair peer‑assessment element to deter free‑riding.
- Stabilise operational rhythm: nominate a single owner for timetabling and course communications; issue a weekly update as the “one source of truth” and set escalation routes when plans shift.
- Make inclusion visible: provide accessible materials, hybrid‑ready rooms, and short teamwork micro‑skills resources (conflict resolution, delegation, decision‑making).
What does this mean for programmes now?
Collaborative learning delivers strongest gains in this discipline when programmes align design, timetabling, and assessment. Structured teamwork amplifies the discipline’s intrinsic strengths, while assessment transparency and predictable operations address the issues students raise most often. Staff who treat group projects as both learning and assessment environments—planned, resourced, and moderated as such—see better student engagement, more credible grading, and smoother delivery.
How Student Voice Analytics helps you
Student Voice Analytics shows how collaboration plays out in your context by tracking tone and volume for this category over time, with drill‑downs by school/department, cohort, campus/site and demographics. It benchmarks like‑for‑like across CAH subject groups and segments (e.g. age, mode), so you can target support for mature and part‑time learners where collaboration is harder to access. The platform produces concise, anonymised briefings for programme teams and export‑ready outputs for committees and quality reviews, supporting rapid, evidence‑led improvements to module design, timetabling and assessment.
Request a walkthrough
Book a Student Voice Analytics demo
See all-comment coverage, sector benchmarks, and governance packs designed for OfS quality and NSS requirements.
- All-comment coverage with HE-tuned taxonomy and sentiment.
- Versioned outputs with TEF-ready governance packs.
- Benchmarks and BI-ready exports for boards and Senate.
More posts on opportunities to work with other students:
- What do management students say about working with peers?
- Do sociology students get meaningful opportunities to work with peers?
- Do structured collaboration opportunities improve Computer Science students’ experience?
- Can collaborative learning work for medical students?
More posts on chemical, process and energy engineering student views:
- What did COVID-19 change for UK chemical, process and energy engineering students?
- What do chemical, process and energy engineering students need from feedback?
- What support do chemical, process and energy engineering students need most?
- What drives workload pressure in chemical, process, and energy engineering?