|Title:||Early Language Comprehension Individualized Instruction (ELCII)|
|Principal Investigator:||Kendeou, Panayiota||Awardee:||University of Minnesota|
|Program:||Literacy [Program Details]|
|Award Period:||3 years (08/29/2017–08/28/2020)||Award Amount:||$1,399,651|
|Type:||Development and Innovation||Award Number:||R305A170242|
Co-Principal Investigator: Kristen McMaster
Purpose: In this project, researchers will develop the automated, interactive, cloud-based, instructional software, Early Language Comprehension Individualized Instruction (ELCII), meant to improve reading comprehension of kindergarten students by focusing on teaching students how to make inferences when they read. Many elementary school students are not able to understand the overall meaning of text or to make simple inferences about what is happening in the text. One possible response to this education problem is to focus on teaching children to make inferences when they are still in kindergarten. Individualized instruction is also important for students as it allows students to move at their own pace.
Project Activities: The ELCII intervention will use fiction and nonfiction videos to teach students vocabulary and inference making skills. It will also include modules that allow teachers to transfer the skills learned in the ELCII software into the classroom. In the first year of the project, the researchers will develop the ELCII software, conduct lab testing, and a brief test to see if the software is usable and feasible in classrooms. In the second year, researchers will make revisions to the software, and develop teacher materials and manuals. Finally, in the third year, the researchers will conduct a pilot study in which students will be randomly assigned to receive either ELCII or the literacy instruction that is already in place in their classrooms.
Products: The products of this project will be a fully developed ELCII intervention, evidence of ELCII's promise to improve student reading outcomes, and peer reviewed publications.
Setting: This project will take place in urban, rural, and suburban schools in Minnesota.
Sample: Participants in this study will include approximately 870 kindergarten students, their 36 teachers, and six parents of kindergarteners.
Intervention: ELCII will be designed to improve reading comprehension for kindergarten students by focusing on inference making. The intervention will be interactive, automated, and cloud-based, with twenty-four thirty-minute learning modules that engage students to watch fiction and nonfiction videos, to learn academic vocabulary from the videos, to respond to inferential questions both during and after viewing the videos, and to receive scaffolding and specific feedback after each inferential question. ELCII will also include eighteen thirty-minute transfer modules during which the teacher will use an interactive questioning activity while reading a narrative of informational text to a small group of children. The final version of ELCII will include manuals and fidelity tools.
Research Design and Methods: Iterative development of ELCII will take place over the first two years of the project. Researchers will select fiction and nonfiction videos and create learning modules around the videos. Focus groups of literacy experts and parents will provide input and feedback on cultural sensitivity, usability, and feasibility. Field tests will provide information to the researchers on usability, feasibility, and how well the intervention is working. Transfer modules will also be created and field tested. For the pilot study in the third year, 30 teachers and their 750 kindergarten students will be randomly assigned to either an ELCII treatment condition or a business-as-usual control condition.
Control Condition: In the control condition, students receive standard classroom practices in place at the school.
Key Measures: Questionnaires, logs, and bug sheets will be used to assess feasibility and usability. The Test of Language Competence-Expanded (TLC-E) Listening Comprehension: Making Inferences subtest will be used to assess language comprehension at pre-test. Student outcome measures include a video comprehension measure to assess inference skills, and QRI-5 to assess inference and comprehension in reading contexts. The Gates-MacGinitie Reading Test will be used to assess reading comprehension. Finally, the FAST early Reading battery will be used to assess decoding, the Peabody Picture Vocabulary Test, Fourth edition will be used to assess vocabulary, and the Automated Working Memory Assessment will be used to assess working memory.
Data Analytic Strategy: Researchers will use multilevel models with students nested within teachers to examine the promise of ELCII for improving kindergarten students' outcomes. The research team will enter covariates such as instructional condition and pretest scores into the models.