Dr Ghobadi's teaching integrates cutting-edge research, industry collaboration, and inclusive design to foster students’ capacity for "longitudinal thinking" and "creativity" in understanding and addressing issues at the intersection of digital technologies, businesses, and society.
She has designed and taught courses on project management, system thinking, and digital innovation across undergraduate, postgraduate, and executive programs (2008-present). All her classes embed real-world, data-driven projects in partnership with industry professionals.
‘Managing Digital Information Projects’ is a theory-informed, empirically-driven module at the MSc level, which reflects on the growing complexity of digital projects (e.g., developing digital products) and discusses diverse strategies for founding, managing, and maintaining these projects. The course covers topics such as digital workforce, agile development, risk management, user participation, crowd-based business models, digital products' sustainability, and digital projects' ethics and activism.
‘Modelling Dynamic Business Systems’ is a final-year, transformative undergraduate course, which introduces students to systems thinking, drawing mental models, and simulation-based modelling (system dynamics). Students learn to ground their models in archival and civic datasets—often from Manchester City Council on housing, health, and transport. This course cultivates longitudinal thinking skills vital for policy design, social and organisational change, and sustainable development. Through examples, cases, and software use, students practice to "expand their understanding of different phenomena" by drawing holistic mental models accounting for mechanisms, loops, delays, and non-linear dynamics.
'A Cognitive Method for Comparing and Elaborating on Technology Frames' is designed in collaboration with the Consumer Data Research Centre (CDRC). This is a complementary PhD/policy researchers course on interpretive methods, centred on the concept of “technology frames.” This course addresses a growing need for academics and policy researchers to "systematically" examine, compare, and make sense of these frames—for example, how employees interpret the value and risks of AI, or how consumers differ in their beliefs about data privacy. Participants learn a step-by-step approach for eliciting, comparing, and elaborating technology frames to produce richer, more nuanced analyses and sense-making.