Data Science is a multifaceted field of study that has continued to permeate nearly every sphere of learning and is also revolutionizing multiple domains, including but not limited to mathematics, statistics, computer science, and engineering. In Morocco, there is a paucity of data scientists, because data science is taught mainly in engineering schools and in some specialized master's programs. With the emergence of the COVID-19 pandemic and its devastating impact on the economies of many countries, there has been a rise in alternative teaching methods. Hitherto, blended learning was scarcely used in Moroccan classrooms. Learning before the pandemic was predominantly presential (in-person or face-to-face learning), but this has changed significantly with the inclusion of online learning. There are a few studies on blended learning in Morocco (see Tadlaoui et al., 2021, Mounjid et al., 2021, Slimani, 2021 & Lakssoumi et al., 2022). These studies have shown in part that online learning improves students’ interest and performance, but have failed to place emphasis on the practical solutions to the inherent challenges. This research is motivated by the gaps in the studies and goes further to propose solutions with specific on blended learning as it relates to Morocco. Schools in Morocco have not entirely recovered from the effects of the closure of schools. Blended Learning is gradually being embraced through incorporating online or e-learning via Microsoft Teams, Zoom, Webex, and also via e-learning platforms such as online webinars, massive Open Online Courses (MOOCs), and active learning. Further, during the lockdown, some teachers recorded lectures so that students who had technical issues or misunderstood concepts could get back to the recordings and revisit the lectures. One major challenge with blended learning is poor internet connections, especially in rural settlements. Another is the cost of acquiring the technological tools (hardware, software, and platforms), including the cost of maintenance and the demand for training the users. In addition, many professors in Morocco have not yet embraced this style of learning and there are many people that believe that we cannot completely abandon the conventional approaches. In order to account for all categories of learners, the design of blended learning for teaching data science should entail online for the content with complimentary in-person sessions where students are able to ask questions and make clarifications on specific elements in the lecture. In addition to that, the presential model handles practical labs and hands-on projects on real-world problems. This ensures properly monitored and supervision of the two modes of instructional delivery, because the strategies and design of online instructional materials are completely different from those used for physical learning. We conclude that for the purpose of teaching and learning data science, we propose a review and a redesign of the curriculum in order to incorporate blended learning approaches.
