Conversational agents for dialogic reading
Xu, Ying; Warschauer, Mark (2021), Conversational agents for dialogic reading, Dryad, Dataset, https://doi.org/10.7280/D10Q3P
This dataset contains data collected from a randomized control trial that exmines the effects of storybook reading with conversational agents on children's comprehension and engagement. This study used a two (reading partner as conversational agent vs. adult) by two (dialogic reading vs. non-dialogic reading) factorial design, with participants randomly assigned into one of four conditions. Specifically, we utilized a randomized block design, in which participants in each school site were randomly assigned into an experimental condition. The purpose of such a design is to increase the homogeneity of experimental units, thus reducing experimental errors and increasing the power for detecting treatment factor effects. The four conditions were as follows: 1) Agent Dialogic Reading where the agent narrated the story to a child and engaged the child in dialogue by asking questions and providing feedback; 2) Agent Non-Dialogic Reading where the agent merely narrated the same story to a child but did not ask any questions to engage the child in dialogue; 3) Human Dialogic Reading where an adult narrated the story to a child and engaged the child in dialogue by asking questions and providing feedback; and 4) Human Non-Dialogic Reading where an adult merely narrated the same story to a child but did not ask any questions to engage the child in dialogue. The dataset includes variable on children's backgroun information, engagement during storybook reading, and comprehension assessment outcomes.
This data was collected via a randomized control trial at participants' schools. Participants filled out a survey and completed a pretest on their expressive vocabulary. After the storybook reading, participants completed a posttest on story comprehension. Participants' engagement during the storybook reading was analyzed from video coding.