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APT and AppleTree Institute Announce Key Findings from Data Dive Partnership
  • USA - English


News provided by

Applied Predictive Technologies

Dec 16, 2014, 09:00 ET

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Washington, D.C. (PRWEB) December 16, 2014 -- Applied Predictive Technologies (APT) and AppleTree Institute, a leading developer and provider of early childhood education in Washington, D.C., announced today the results of their recent data dive partnership. The data dive partnership was focused on helping AppleTree better understand how teaching strategies and teacher training impact student achievement.

APT is a purely cloud-based predictive analytics software company. APT’s software solutions are revolutionizing the way leading organizations make decisions by harnessing their Big Data to accurately measure the impact of various strategic and tactical initiatives. APT’s “data dive” projects are focused on helping local non-profit organizations improve their decision-making capabilities through the use of software and data analysis. APT employees from across the company volunteer on data dive teams to analyze key areas of interest for the partnering organization. Previous data dive partnerships have included projects with DC Prep and the Capital Area Food Bank.

Teaching Strategies

AppleTree conducts rigorous evaluations for all teachers throughout the year according to its proprietary observational assessment, the “Quality Indicators.” Through the data dive, AppleTree was interested in learning how performance in certain Quality Indicator criteria impacted student performance.

After controlling for various structural differences among students, such as socioeconomic status, age, and historical test scores, APT analyzed which Quality Indicators were most correlated with high student performance (as measured by student improvement in math, literacy, and behavioral assessments).

Findings -- Impact on Language and Literacy Scores:
• Out of 20 teacher qualities, high performance in qualities such as checking for student understanding, providing feedback, literacy/writing environment, time management, teacher responsiveness, and classroom organization was highly predictive of student performance
• Interestingly, specific qualities such as language environment and supporting pro-social behavior were more effective in helping lower-performing students grow

Findings -- Impact on Math Scores:
• On average, high teacher performance for nearly every Quality Indicator category was correlated with higher student Math scores; however, among lower performing students, only a select few qualities influenced high student performance, including time management, providing effective feedback, supporting pro-social behavior, and teacher responsiveness

AppleTree plans to use these learnings to inform the focus of professional development provided to teachers, particularly teachers with lower-performing students. The learnings may also be used to inform hiring decisions.

Teacher Training

AppleTree Institute’s Every Child Ready instructional model includes data-driven teacher training as a key component alongside curriculum and assessment tools. Ongoing, responsive support for teachers and instructional leaders is a key part of AppleTree’s approach.

By analyzing natural variations in elective training participation among teachers, APT measured the incremental benefit of additional coaching and conducted analyses to understand which areas of student and teacher development were most impacted by the training.

Findings -- Impact of Coaching Hours:
• APT found that exceeding AppleTree’s goal of recommended training hours significantly benefitted teacher evaluation (“Quality Indicator”) scores
• However, when analyzing student performance, the additional hours did not have a significant impact on Language and Literacy or Math scores, on average

APT was also able to identify the specific types of teachers and classes for whom additional coaching was impactful: For teachers, APT found that additional coaching significantly impacted how a teacher was scored in supporting diverse learners, independent learning skills, and direct instruction. For students, the analysis showed that the extra coaching hours significantly benefitted student rhyme, phoneme blending, and phoneme substitution skills.

APT recommended that AppleTree sets higher coaching hours for teachers with low Quality Indicator scores in the areas that were most impacted by the training, as well as teachers with students who have lower rhyme, phoneme blending, and phoneme substitution scores.

Classroom Dashboard

APT engineers also built an easily accessible, cloud-based dashboard for teachers, designed to help them understand how individual students in their classes are progressing over time. The dashboard will allow teachers to identify students who may need extra attention in class and enable them to make recommendations to parents about which learning areas to focus on at home.

Lydia Carlis, AppleTree Chief of Research and Innovation, commented, “We were very excited when APT offered the opportunity to partner on a data dive together, giving us the chance to gain valuable insights from their expertise in data analytics and technology. We have always been a data-driven organization, constantly evolving our Every Child Ready program, so this project was the perfect opportunity to improve our strategies even further. We plan to use these findings to help us refine our assessment tools and fine-tune our professional development program to more effectively achieve our mission of closing the achievement gap before children enter kindergarten.”

APT CEO Anthony Bruce added, “Data dives continue to be one of APT’s favorite traditions, and we were pleased to have the opportunity to work with an organization as innovative and mission-driven as AppleTree Institute.”

About AppleTree Institute

AppleTree’s mission is to close the achievement gap before children get to kindergarten by providing three- and four-year-olds with the social, emotional, and cognitive foundations they need to succeed in school. AppleTree Institute has developed Every Child Ready, a comprehensive instructional model that drives how to teach, what to teach, and how to tell it’s being done correctly in early childhood classrooms. Every Child Ready increases teacher effectiveness and children’s learning, erasing the achievement gap before children begin kindergarten. In 2014-2015, AppleTree is supporting eight schools throughout Washington, D.C. in implementing Every Child Ready, reaching more than 1,500 students. For more information, please visit http://www.appletreeinstitute.org.

About APT

APT is a purely cloud-based predictive analytics software company. APT’s Test and Learn® software is revolutionizing the way organizations harness their Big Data to accurately measure the profit impact of advertising, marketing, pricing, merchandising, operations and capital initiatives, tailoring investments in these areas to maximize ROI. APT’s customer portfolio includes Walmart, Staples, Lowe’s, SunTrust, Hilton Hotels, Anheuser-Busch InBev, and others. APT has offices in Washington, D.C., San Francisco, Bentonville, London, Tokyo, and Taipei. For more information, please visit http://www.predictivetechnologies.com.

Cathy Baker, Applied Predictive Technologies, http://www.predictivetechnologies.com, +1 703.875.7748, [email protected]

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