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Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…
Descriptors: Intervention, Outcomes of Education, Randomized Controlled Trials, Data Use
Erin Ottmar; Ji-Eun Lee; Kirk Vanacore; Siddhartha Pradhan; Lauren Decker-Woodrow; Craig A. Mason – Grantee Submission, 2023
This paper provides information on datasets for the research project that examined the efficacy of three educational technologies including "From Here to There!", a research-based game for improving algebraic understanding. The dataset contains 4,092 7th-grade students' data collected through a randomized control trial conducted in…
Descriptors: Data, Mathematics Achievement, Algebra, Educational Technology
Kaitlyn G. Fitzgerald; Elizabeth Tipton – Grantee Submission, 2022
As the body of scientific evidence about effective policies and practices grows, so does the need to effectively communicate that evidence to policy-makers and practitioners. Clearinghouses have emerged to facilitate the evidence-based decision-making process for education practitioners. While the results and methods for developing and analyzing…
Descriptors: Meta Analysis, Scientific Research, Evidence Based Practice, Decision Making
Gobert, Janice D.; Moussavi, Raha; Li, Haiying; Sao Pedro, Michael; Dickler, Rachel – Grantee Submission, 2018
This chapter addresses students' data interpretation, a key NGSS inquiry practice, with which students have several different types of difficulties. In this work, we unpack the difficulties associated with data interpretation from those associated with warranting claims. We do this within the context of Inq-ITS (Inquiry Intelligent Tutoring…
Descriptors: Scaffolding (Teaching Technique), Data Interpretation, Intelligent Tutoring Systems, Science Instruction
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Sao Pedro, Michael A.; Gobert, Janice D.; Baker, Ryan S. – Grantee Submission, 2014
We explore in this paper if automated scaffolding delivered via a pedagogical agent within a simulation can help students acquire data collection inquiry skills. Our initial analyses revealed that such scaffolding was effective for helping students who initially did not know two specific skills, designing controlled experiments and testing stated…
Descriptors: Automation, Scaffolding (Teaching Technique), Intelligent Tutoring Systems, Data Collection