Guarding Code Originality and Motivating Student Engagement: In-class Simulated Microcontroller Assignments in a Stage 1 Robotics Module

Creator(s)

Anshu Mukherjee, Jiajing Li, Paul Cuffe

Organisation(s)

University College Dublin

Discipline(s)

Engineering, Information and Communication Technologies, Manufacturing and Construction

Topic(s)

Assessment and Feedback, Curriculum Design, Digital Learning

License

CC BY-SA

Media Format

PDF, PDF document

Date Submitted

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Description

During the Spring trimester of 2024, in the UCD ‘Robotics Design Project’ (EEEN10020) module with 54 first-year undergraduate engineering students, we deliberately revised the assessment strategy. We evolved a take-home assignment into a pair of supervised in-class exercises.

Benefit of this resource and how to make the best use of it

Even before the emergence of Gen AI tools, there was ample reason to structure engineering coursework assignments in a more timetabled and actively-delivered fashion. Lightly-supported homework assignments with long timelines loom over a student’s trimester, more often a source of distraction and guilt than an opportunity for deep work and quality learning. University teachers play a powerful social role, and have the power to set timetables and impose expectations. Let’s use that for good. It has always a good idea to proactively and deliberately create assessments that get the best out of students. The emergence of powerful Gen AI tools is just another motivator: now at-home assessments can easily be plagiarized in an undetectable way, so it is very timely to reconsider how we support students in their continual assessment.

Creative Commons Attribution-ShareAlike (CC BY-SA)

This work is licensed under a CC BY-SA license, allowing adaptation and sharing with proper attribution, provided derivative works use the same license.

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Mukherjee, A., Li, J., & Cuffe, P. (2025). Guarding code originality and motivating student engagement: in-class simulated microcontroller assignments in a stage 1 robotics module. National Resource Hub (Ireland). Retrieved from: https://hub.teachingandlearning.ie/resource/guarding-code-originality-and-motivating-student-engagement-in-class-simulated-microcontroller-assignments-in-a-stage-1-robotics-module/ License: Creative Commons Attribution-ShareAlike (CC BY-SA).

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This Toolkit was created by students at University College Dublin, for students, to break down sustainability in a way that’s simple and easy to understand. Climate change is something that affects all of us—no matter what you’re studying, where you’re from, or what you do. It’s here, and it’s impacting our world—but many of us aren’t sure what we can do about it.

The purpose of this toolkit is a starting point for what students need to learn about living more sustainably on and off campus. We hope it’ll inspire students to take small steps that make a big impact, and they can do it all at their own pace. You can access the Moodle page to view the Toolkit. There are also Zip files of the SCORM packages used to create the Toolkit (Part 1 and Part 2) that can be downloaded and imported into a Virtual Learning Environment.

• Part 1: Climate Change → Watch short Youtube videos followed by a little quiz to brush up on your sustainability knowledge.
• Part 2: What Can You Do? → Find tips and tricks to incorporate sustainability into your day-to-day life, this is a resource tool to help you get started!

This open course is designed to facilitate the development of your Artificial Intelligence (AI) literacy so that you can explore and innovate using Generative AI (GenAI) within your teaching, learning, and assessment practices.

In light of the potential opportunities and challenges of these technologies, this course will facilitate you in exploring the fundamentals of GenAI and AI Literacy, whilst focusing on an ethical practice. You will consider innovative ways in which you can respond to the challenges arising from the impact of these technologies in Higher Education.

Completion of this course will support you in developing a GenAI teaching strategy to apply to your own practice.

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