Using the Task Analysis Process with Teachers to Uncover Language Demands within an Eight-Week NGSS Summer Course

• Main Author: Plack, Leah
• Format: Others
• Published: PDXScholar 2017
• Subjects: English language > Ability testing; Elementary school teachers > In-service training; English language > Study and teaching (Elementary) > Evaluation; Science > Study and teaching (Elementary); Next Generation Science Standards (Education); Elementary Education; Science and Mathematics Education
• Online Access: https://pdxscholar.library.pdx.edu/open_access_etds/4014; https://pdxscholar.library.pdx.edu/cgi/viewcontent.cgi?article=5023&context=open_access_etds

The state of Oregon has adopted the Next Generation Science Standards as well as the English Language Proficiency standards, both of which affect elementary school teachers. These standards adoptions challenge teachers and professional developers to rethink how they approach science conceptual understanding and language acquisition. The Math Science Partnership K-6 Instructional Specialist Grant made the decision to incorporate a Task Analysis process, which asks the participant to analyze the demands of a content-based task in the domains of content knowledge, analytical skills and language, into six eight-week summer courses focused on the Next Generation Science Standards. A pre and post-assessment was created to determine if any growth in teacher understanding of the demands of a science task could be observed as a result of engaging in the Task Analysis process. A four point rubric was created to score participant responses. Two research questions were developed: 1. How well does the ELPA21 Task Analysis tool help participants understand the language demands of a science task when used as part of an NGSS summer professional development course? 2. How effective is a work sample and scoring rubric protocol for measuring the impact of the Task Analysis process? Participants showed statistically significant growth in their analysis of a science task from pre to post-assessment responses, with particularly strong growth demonstrated in the domains of content and language. Further coding of responses revealed that participants frequently discussed vocabulary as both a language and content knowledge demand of a science task.