Improving Reading Through Videogames and Digital Apps: A Systematic Review.

Background: The use of electronic interventions to improve reading is becoming a common resource. This systematic review aims to describe the main characteristics of randomized controlled trials or quasi-experimental studies that have used these tools to improve first-language reading, in order to highlight the features of the most reliable studies and guide future research. Methods: The whole procedure followed the PRISMA guidelines, and the protocol was registered before starting the process (doi: 10.17605/OSF.IO/CKM4N). Searches in Scopus, PubMed, Web of Science and an institutional reference aggregator (Unika) yielded 6,230 candidate articles. After duplicate removal, screening, and compliance of eligibility criteria, 55 studies were finally included. Results: They were research studies on improving first-language reading, both in children and adults, and including a control group. Thirty-three different electronic tools were employed, most of them in English, and studies were very diverse in sample size, length of intervention, and control tasks. Risk of bias was analyzed with the PEDro scale, and all studies had a medium or low risk. However, risk of bias due to conflicts of interest could not be evaluated in most studies, since they did not include a statement on this issue. Conclusion: Future research on this topic should include randomized intervention and control groups, with sample sizes over 65 per group, interventions longer than 15 h, and a proper disclosure of possible conflicts of interest. Systematic Review Registration: The whole procedure followed the PRISMA guidelines, and the protocol was registered before starting the process in the Open Science Framework (doi: 10.17605/OSF.IO/CKM4N).

Predicting risk of dyslexia with an online gamified test.

Dyslexia is a specific learning disorder related to school failure. Detection is both crucial and challenging, especially in languages with transparent orthographies, such as Spanish. To make detecting dyslexia easier, we designed an online gamified test and a predictive machine learning model. In a study with more than 3,600 participants, our model correctly detected over 80% of the participants with dyslexia. To check the robustness of the method we tested our method using a new data set with over 1,300 participants with age customized tests in a different environment -a tablet instead of a desktop computer- reaching a recall of over 78% for the class with dyslexia for children 12 years old or older. Our work shows that dyslexia can be screened using a machine learning approach. An online screening tool in Spanish based on our methods has already been used by more than 200,000 people.