## 5 Conclusions, Recommendations, and Limitations  
This study examined the perspectives of primary school mathematics teachers in Tanzania concerning the integration of social robots into classroom practice. While the teachers expressed overall optimism regarding the potential of such technologies to alleviate their workload, they also articulated several reservations. In particular, ensuring the quality and effective delivery of instructional content will require targeted research efforts to expand Swahili-language training data and to further refine LLMs and speech processing services for the particular linguistic and cultural context. Furthermore, enhancing human-robot interaction necessitates addressing issues related to conversation latency, especially in rural settings, and mitigating dependence on continuous Internet connectivity. In this regard, experimentation with offline LLM implementations may offer a way forward. Equally important is the role of government in establishing an enabling environment through the provision of adequate infrastructure, sustainable operational budgets, and clear policy guidelines for the deployment of intelligent tutoring systems. As social robots represent an emergent educational technology, comprehensive public awareness will also be essential to facilitate their acceptance and effective adoption. By presenting the considered perspectives of teachers, who constitute critical stakeholders in this endeavour, our study contributes insights into the practical challenges and opportunities associated with implementing social robots in schools situated in low-resource contexts, a dimension that remains insufficiently explored in the literature. It is important to acknowledge certain limitations inherent in this study. For instance, the qualitative setup of our study limited the breadth of coverage, potentially constraining the generalisability of the findings. Future research could therefore benefit from broader surveys that encompass more diverse samples within Tanzania and in other countries with comparable educational contexts. Moreover, the findings presented here are based on the deployment of a NAO social robot with GPT-3.5 and Microsoft Azure Speech Services. Alternative hardware, more advanced LLMs, or new speech technologies may yield different outcomes. Finally, as this study focused exclusively on mathematics instruction, further research is needed to assess the applicability and impact of social robots across other subject areas. Conceptualisation, E.P.R., K.S. and T.B. ; methodology, E.P.R., K.S. and T.B. ; software, E.P.R. ; validation, E.P.R. ; formal analysis, E.P.R. ; investigation, E.P.R. ; resources, K.S. and T.B. ; data curation, E.P.R. ; writing--original draft preparation, E.P.R. ; writing--review and editing, K.S. and T.B. ; supervision, K.S. and T.B. ; funding acquisition, K.S. and T.B. All authors have read and agreed to the published version of the manuscript. This research was funded by VLIR-UOS through Ghent University's Global Minds Fund-Explore and/or Valorise project titled: \"Improving the Mathematics Learning Experience for Disadvantage Primary School Students in Tanzania Through the Use of Intelligent Agents\". This study was approved by the Tanzanian President's Office - Regional Administration and Local Government (PO-RALG), reference AB.307/323/01/40, 25 January 2024. Informed consent was obtained from all subjects involved in this study. Permission was granted by the PO-RALG to publish the results (reference AB.307/323/01/228), 12 June 2024. The data used in this study cannot be publicly shared due to respondents' confidentiality and terms of the research permit. Further inquiries can be directed to the corresponding author. We are extremely grateful to VLIR-UOS for funding this research. We also thank the participants for their time and invaluable inputs that enriched our study. Lastly, we register our appreciation to the Government of Tanzania for the research permits and constant support throughout our research.