LuCiD and the World of Educational Apps: My Summer Internship

Digital media, particularly apps, have been introduced as a tool for education and have consequently shaped children’s development in the 21^st century. But how effective are these tools in terms of language development, and how can they be improved to ensure children are receiving a rich linguistic input? This was the question at the centre of the research I engaged with during my LuCiD internship, alongside my mentor, Prof. Padraic Monaghan at Lancaster University, Dr Gemma Taylor at Salford University, and Dr Joanna Kolak at UCL. Over the course of six weeks, I conducted a quantitative and qualitative analysis on a set of educational apps by Edurino, examining the efficacy of their language and assessing how they could be improved.

This project was inspired by the lack of research surrounding the linguistic contribution of apps towards children’s language development and the lack of regulation surrounding the educational value of educational apps. Adapting methods of analysis used in the Kolak et al. (2023) paper, we analysed Edurino, an educational app developed to help children learn maths, phonics, computer coding and more.

For the sample, I was tasked with recording transcripts which were 5-minute extracts from using each of the Edurino games. We were also given access to full transcripts for each of the games for a reliability check.

The quantitative analysis involved using four word-level measures and one sentence-level measure: Concreteness, Age of Acquisition, Word Frequency, Lexical Diversity and Length of Utterance which investigated how appropriate and varied the language was for children. This aspect of the analysis helped to build on my skills and knowledge of R studios. The qualitative analysis required me to split the transcripts into utterances and code them according to different utterance types: Imperative, Question, Subject-Predicates, Copulas, Fragments and Complex utterances, each of which has a different role in communication and tend to occur with different proportions as children get older in natural speech. The proportion of the presence for each of these utterance types was calculated. This aspect of the analysis allowed me to learn how specific sentence types can help strengthen children’s linguistic knowledge. These measures collectively assess the richness of the linguistic input Edurino offers. Finally, the results of this analysis were compared with other apps previous analysed by Kolak et al. (2023) to see where Edurino stood in comparison to the marketplace.

Not only did this internship help develop my analysis skills, but it also gave me valuable insight into the research process and has shown me the different pathways a research career can open. I’ve been able to collaborate with many different researchers and hear their career stories which has been important in helping me shape my own career. The LuCiD internship also allowed to present a poster about our research at the ECGBL conference, which is a conference centred around game-based learning.

I would like to finish by offering my sincere gratitude to Professor Padraic Monaghan, Dr Joanna Kolak, Dr Gemma Taylor and Dr Ning Ding at Edurino, for their support, guidance and advice throughout this internship. This has been valuable experience, and I would recommend this to anyone interested in the field of research!

• Kolak, J., Monaghan, P., & Taylor, G. (2023). Language in educational apps for pre-schoolers. A comparison of grammatical constructions and psycholinguistic features in apps, books and child directed speech. Journal of Child Language, 50(4), 895-921.
• Taylor, G., Kolak, J., Norgate, S. H., & Monaghan, P. (2022). Assessing the educational potential and language content of touchscreen apps for preschool children. Computers and Education Open, 3, 100102.
• von Hippel, P., Workman, J., & Downey, D.B. (2017). Inequality in reading and math skills comes mainly from early childhood: A replication, and partial correction, of ‘Are schools the great equalizer?’ SSRN working paper, 3036094.