Antonette Shibani is a Senior Lecturer at TransDisciplinary (TD) School, University of Technology Sydney.

Antonette led the design of Innovation Lab (iLab), a core work-integrated learning subject for the Master of Data Science and Innovation at TD School, University of Technology Sydney (UTS) from 2019-2023. Here she championed the use of innovative teaching methods and reimagined sustained partnerships with industry.

iLab prepares students to navigate the challenges faced by data science professionals in the real world, including working with messy and large data sets, programming complexities, and evolving artificial intelligence technologies. Beyond technical skills, data science professionals require a diverse set of interconnected skills and mindsets to thrive in their careers. However, many students find these requirements daunting. As a data science educator, Antonette’s goal is to develop these key competencies among students, enabling them to not just survive, but thrive in their professional lives.

Antonette designed iLab to empower students exploring their interests while gaining practical experience in real-world data challenges. Multiple student teams work on complex problems set by partners, producing innovative solutions for targeted sub-problems, while learning from each other. This approach facilitates diverse perspectives for transdisciplinary learning and offers unique learning journeys based on students’ interests and skills they want to develop. Partners value the fresh ideas generated by students, often resulting in the development of data pipelines or AI tool prototypes within 2-3 months, prompting them to seek future partnerships with the University. Many students go on to find future career opportunities through their partnership with industry, and co-create outputs such as reports, publications, and presentations that build their professional profiles.

iLab is offered as a capstone for all students enrolled in the Master of Data Science and Innovation, providing them with a safe-to-fail learning environment to put their learned knowledge into practice. Antonette’s approach focuses on transdisciplinary, problem-based learning, where students collaboratively tackle real-world challenges presented by industry and academic partners. This shift from traditional client employee dynamics (often seen in internship experiences) to a mutual learning framework has markedly improved student learning experiences and partner engagement. The intervention focuses on well-rounded development, supporting intellectual, emotional, and social growth of students in addition to technical skill development. The practice-oriented learning experience helps students become job-ready by applying theoretical knowledge to practical challenges.

Projects in iLab are team-based to nurture teamwork, with teams allocated based on common interests and preferences. Peer surveys ensure accountability, and a final peer assessment provides weightage to grades based on individual contributions. The use of progress tracking templates, partner interactions, oral presentations, and professional portfolios contribute to project and time management, professionalism, and communication skills. Feedback from stakeholders has been continuously incorporated to drive improvement in the programme. Antonette’s role in the transformation of the subject and its successful outcomes has earned a top recognition for teaching at UTS in 2023 (a Teaching and Learning Citation).


Read more about the Data Science and Innovation Course here.

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Edited by Tasha Day (UIIN)