Navigating the Challenges of Industry-based Capstone Projects

Shalinda Adikari
Dept Information Systems & Analytics
School of Computing (SOC)

The author draws on the Business Analytics Capstone Project course to show how structured planning, systematic intake, and instructional scaffolding can turn logistical hurdles into meaningful learning experiences.

Shalinda-Adikari-anchor-pic — *Image by brgfx on Freepik*

Adikari, S. (2025, December 16). Navigating the challenges of industry-based capstone projects. CTLT Teaching Connections. https://blog.nus.edu.sg/teachingconnections/2025/12/16/2025-shalinda-adikari/

Introduction

Capstone projects represent a pivotal component of undergraduate education, offering students a structured opportunity to bridge academic theory with practical, real-world applications. They often require working with industry partners, giving students real, data-driven challenges. An analysis of course listings on NUSMods reveals that approximately 30% of capstone projects are business-oriented, with students engaging directly with industry partners to address authentic, data-driven challenges (as illustrated by the word cloud in Figure 1). While these industry-linked experiences significantly enrich student learning, they also present distinctive challenges, particularly in single-semester formats, where compressed timelines demand early preparation and clear alignment between academic expectations and project scope.

Shalinda-Adikari-Fig1 — *Figure 1.* Word cloud generated from course descriptions in NUSMods.

This article argues that the success of industry-based capstones depends less on the projects and more on the systems that support them. Using the course BT4011 “Business Analytics Capstone Project” as a reference, it shows how structured planning, systematic intake, and instructional scaffolding can turn logistical hurdles into meaningful learning experiences. When these systems are put into action thoughtfully, they do more than solve administrative issues; they create an environment for deeper learning, better teamwork, and stronger student outcomes.

Key Challenges in Industry-based Capstones

Several recurring challenges emerge in industry-based capstone projects.

First, sourcing suitable projects is complex. Many companies submit proposals that are vague, overly ambitious, or misaligned with students’ skill sets or academic calendars. These mismatches often delay onboarding and compromise outcomes.
Second, even approved projects may suffer from unclear requirements. Sponsors might shift expectations midway, causing scope instability. In a single-semester format, such disruptions are particularly harmful, as time lost is hard to recover.
Third, most projects are data-driven, yet companies are often reluctant to share real data due to privacy or compliance concerns. Even with non-disclosure agreements (NDAs) in place, data may arrive late or be overly sanitised, reducing authenticity and learning value.

These issues are magnified in single-semester courses. Delays in data access, scoping, or sponsor engagement can derail progress. This makes early alignment and structured planning critical (Biggs et al., 2022).

Project Lifecycle: From Intake to Execution

To mitigate these issues, BT4011 “Business Analytics Capstone Project” uses a structured, end-to-end capstone lifecycle via a dedicated portal.

Pre-Semester Project Intake

The process starts before the semester, with industry partners being invited to submit proposals early. This allows time for vetting and adjustment. Companies register by submitting key details like name, business description, and Unique Entity Number (UEN). Once approved, they submit proposals comprising two sections: Project Information and Project Commitment.

The Project Information section includes the project title, problem description, expected workload, data sources, tools, deliverables, and the sponsor’s contact details.
The Project Commitment section outlines commitments: data availability by Week 2, biweekly meetings, attendance at final presentations, and confirmation of scope stability and data access approvals.

Submitted proposals undergo a thorough review by course instructors and are either approved, returned for revision, or rejected based on their scope, feasibility, and alignment with course objectives. To enhance transparency and ensure consistency with what is documented, each project sponsor is also required to upload a brief recorded video presentation summarising the project’s goals and expectations.

Student Bidding and Onboarding

Approved projects are published on the system for student bidding. After allocation, student teams are expected to initiate contact and hold a kickoff meeting with their assigned sponsor within the first two weeks of the semester. During this meeting, the sponsor is expected to provide the necessary project data as previously committed in the proposal submission.

Project Execution

Execution begins with a Project Charter, co-developed and signed by students and sponsors, outlining goals, deliverables, and roles. Instructors provide continuous support through regular consultations to monitor progress and resolve challenges. The project concludes with a Sign-off Form submitted by the sponsor, confirming successful delivery.

Evidence of Impact

Over several iterations of the course, industry partners have repeatedly returned to propose new projects, citing clear course objectives, well-structured processes, and high-quality student deliverables as reasons for their continued participation. Feedback from sponsors has been very positive. They highlight the professionalism and analytical skills demonstrated by student teams. On the student side, course evaluations have been strong. Learners often mention that the structured scaffolding enhanced their confidence in managing real-world projects, particularly in client communication and teamwork skills. Many students also achieve higher grades compared to other courses. They attribute their success to the course’s practical relevance, timely assistance, and well-designed project lifecycle.

Thus, this demonstrates that the project lifecycle upholds both academic integrity and professional rigour (Wiggins & McTighe, 2005).

Transforming Administrative Protocols into Learning Scaffolds

While these steps may appear administrative, they serve as learning scaffolds rooted in educational theory and practice.

Scaffolding for Professional Capability Development

The structure aligns with constructivist learning principles, such as Vygotsky’s Zone of Proximal Development, offering guidance that challenges students without overwhelming them (Vygotsky, 1978). Clear scopes, timelines, and stakeholder roles help students move from classroom tasks to solving real-world problems.

Students learn to analyse open-ended business challenges, manage ambiguity, and apply analytics tools. Handling real-world data, even when it is incomplete or sensitive, helps students build practical skills in ethical handling and data governance. Working to meet expectations defined through charters and deliverables prepares students for client-aligned solutioning. This mirrors backward instructional design, where learning tasks are aligned with defined real-world outcomes (Wiggins & McTighe, 2005).

Developing Personal Competencies Through Structured Autonomy

The administrative processes embedded in the course, such as project bidding, charter submission, milestone tracking, and scheduled consultations, are not just procedural but are designed to support the development of key personal competencies.

The bidding process allows students to evaluate project scopes independently and make informed choices, encouraging ownership and initiative.
Creating the Project Charter requires clear communication with sponsors, helping students translate project requirements into actionable plans and commit to timelines and deliverables, fostering professional responsibility.
Structured milestone tracking and regular instructor consultations serve as checkpoints that promote reflection and self-monitoring. These mechanisms encourage metacognition and self-regulated learning (Zimmerman, 2002) by guiding students to assess their progress and adapt their strategies.

Together, these practices mirror Kolb’s Experiential Learning Cycle (Kolb, 1984), where students engage with real challenges, reflect on their actions, conceptualise insights, and apply them in project settings. The system cultivates essential personal skills that extend well beyond academic success.

Conclusion

Delivering an industry-based capstone in a single semester is demanding. However, with early engagement, structured intake, and clear expectations, it becomes a transformative learning experience. The Business Analytics Capstone Project course shows how well-designed administrative processes can evolve into pedagogical scaffolds. Students leave not only with technical expertise but also the self-management, communication, and problem-solving skills vital for thriving in today’s data-driven workplace.

References

Biggs, J., Tang, C., & Kennedy, G. (2022). Teaching for Quality Learning at University (5th Ed.). McGraw-Hill Education (UK).

Kolb, D. A. (1984). Experiential Learning: Experience as the Source of Learning and Development. Prentice Hall.

Vygotsky, L. S. (1978). Mind in Society: Development of Higher Psychological Processes (M. Cole, V. Jolm-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4

Wiggins, G., & McTighe, J. (2005). Understanding by Design (2nd Ed.). Association for Supervision and Curriculum Development (ASCD).

Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2

Shalinda Adikari is a Lecturer at the Department of Information Systems and Analytics, in the School of Computing (SOC). His primary research interest lies within the field of data science, especially the design of data-driven applications. Currently, he works with the online advertising industry, where he is researching and developing new solutions to optimise the real-time bidding process in online advertising. His research has been published in the INFORMS Journal of Computing. He has also presented his research at leading academic conferences such as the International Conference on Information Systems (ICIS), the Workshop on Information Technology and Systems (WITS), and the Pacific-Asia Conference on Information Systems (PACIS). He was awarded the best paper award at WITS 2016.

Shalinda can be reached at dispsaa@nus.edu.sg.