
Integrating the Coding & Robotics (C&R) subject in South African schools signifies the nation's commitment to Fourth Industrial Revolution preparedness. However, challenges like inadequate teacher preparation and limited technological infrastructure must be addressed to ensure equity. Although Generative Artificial Intelligence (GenAI) may not address the infrastructural deficiencies directly, in this scoping review we examine its potential to complement existing resources and support teachers in delivering C&R instruction. Following Arksey and O'Malley's framework, we conducted a systematic literature search in numerous databases, followed by a screening procedure: 10 of the 61 eligible papers satisfied the inclusion criteria. Our findings reveal that GenAI can optimise C&R teacher development through personalised learning, content generation, feedback on teaching methods, and fostering collaboration with other teachers. Despite its potential, issues including equity, ethical concerns, technological fluency gaps, and overreliance on GenAI tools, must be navigated to enhance equitable C&R instruction and prepare learners for the digital era.
teacher preparation, equity, Coding & Robotics, GenAI, scoping review
teacher preparation, equity, Coding & Robotics, GenAI, scoping review
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
