GenAI-Empowered Group-Based Authentic Assessment for Network Engineering Courses

The emergence of generative artificial intelligence (GenAI) has brought both challenges and opportunities for education. In this paper, we propose a GenAI-empowered, group-based authentic assessment for a Network Engineering course. This group assignment promotes challenge-based learning (CBL) and leverages GenAI to enhance students' creativity, critical thinking, collaboration, and technical problem-solving skills, while also improving students' GenAI literacy through fostering their ability to effectively engage with GenAI tools. The authenticity of this assignment is reflected in two folds: 1) students engage in a real-world engineering challenge, roleplaying as network engineers, and 2) they develop essential skills for co-creating solutions using GenAI tools, a key competency for future engineers. The group assignment is structured into five stages, each aligned with Bloom's Taxonomy to progressively develop cognitive skills from understanding foundational knowledge to synthesis, evaluation, and creation. To mitigate challenges such as overreliance on GenAI tools and varying levels of digital literacy, we provide guidance on the responsible and ethical use of GenAI, design reflective assessment tasks with constructive feedback, and establish clear marking criteria that emphasise both the learning process and the final outputs of the assignment. Initial evaluation and feedback from trials have highlighted the effectiveness of using GenAI tools in addressing complex engineering challenges and the value of collaborating in a real-world engineering context. This innovative approach demonstrates the potential of GenAIempowered authentic assessments to enhance learning experiences in technical fields like Network Engineering.