A Systematic Review and Meta-analysis of Text Entry Studies

Text entry is a notably standardized research field in human-computer interaction, with established benchmarks and methodologies enabling rigorous comparisons across studies. Nevertheless, meta research in text-entry is scarce. This meta-analysis summarizes findings and effects from text entry experiments published from 1990 to 2024. Our records show that most text-entry experiments feature a baseline and an experimental UI, and that they mostly show that the experimental UI is superior (g = 1.68), with regards to text entry speed. We found that earlier text entry research focused mostly on the development of novel techniques, whereas recent text entry research, to a larger extent, adapts existing input methods to new devices, such as smartwatches or virtual reality headsets. We also find that text entry research often lacks statistical power (M = 0.66, SD = 0.37), relies on small sample sizes (Mdn = 12), and is mostly conducted with within-subjects designs (84%). Subjective evaluations of text entry systems beyond objective performance are rare. Our analysis found evidence for systematic publication bias in text entry research, as indicated by funnel plot asymmetry and a significant weight-function model adjustment. This underlines the research field’s competitive culture of publishing research only if entry speed is beaten in comparison to some baseline.