In this experience paper, we present ALAN, a framework to automate the generation of authentic assessment tasks in networking courses (NC). Using ALAN, all students in a cohort complete a set of assessment tasks generated from the same skeleton, with each student having their own parameters as input. The way we run ALAN assessments fosters students' self-regulation and peer learning and activates students' engagement in learning through assessment. We present three different ALAN assessments. We finally report on student perceptions and satisfaction and reflect on our experience.

In this experience paper, we introduce the concept of 'diverging assessments', process-based assessments designed so that they become unique for each student while all students see a common skeleton. We present experiences with diverging assessments in the contexts of computer networks, operating systems, ethical hacking, and software development. All the given examples allow the use of generative-AI-based tools, are authentic, and are designed to generate learning opportunities that foster students' meta-cognition. Finally, we reflect upon these experiences in five different courses across four universities, showing how diverging assessments enhance students' learning while respecting academic integrity.

In this experience paper, we present an automated assessment and marking generation framework to create capture-the-flag (CTF) questions in the context of Information Technology (IT) Forensics. This allows educators to generate many randomised Virtual Hard Disk (VHD) and packet capture (PCAP) files with different forensic artefacts for each student suitable for assessment tasks in disk-based and network-based forensic courses, respectively. These files are then inscribed inside quizzes, which are constructively aligned to what students have learned in their lecture and tutorial classes. We replaced our invigilated closed-book end-of-semester exams with these open-book multiple-attempt non-invigilated in-semester quizzes. We also conducted a survey asking students about, how the designed quizzes (1) were aligned with (and covering) the promised course learning outcomes, (2) were run to address academic integrity concerns, and (3) helped students manage their stress once their final exams are replaced by the presented quizzes.