Tablet-based educational technologies provide a supplement to traditional classroom-based early literacy education, especially in regions with limited schooling resources. Prior work has probed how children generally interact with and learn from these technologies, however, there is limited research on student engagement with applications that utilize valuable input techniques such as automatic handwriting and speech recognition. In our study, we designed and field-tested early literacy speech and handwriting recognition applications with the primary aim of maximizing student engagement. We designed the applications based on prior research insights and classroom observations from our target population and field-tested the applications with 283 children living in rural Tanzania. We found that observing a small set of classrooms can produce design insights that increase engagement on tablet-based learning systems on a much larger scale. We also demonstrate the importance of domain familiarity in students' choice to persist through activities while learning with technology. [This paper was published in: "COMPASS '19: Proceedings of the 2nd ACM SIGCAS Conference on Computing and Sustainable Societies," Association for Computing Machinery, 2019, pp.99-110.]