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Sainan Xu; Jing Lu; Jiwei Zhang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…
Descriptors: Educational Assessment, Bayesian Statistics, Statistical Inference, Item Response Theory
Atsushi Miyaoka; Lauren Decker-Woodrow; Nancy Hartman; Barbara Booker; Erin Ottmar – Grantee Submission, 2023
More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for…
Descriptors: Coding, Models, Qualitative Research, Focus Groups
Joe Olsen; Amy Adair; Janice Gobert; Michael Sao Pedro; Mariel O'Brien – Grantee Submission, 2022
Many national science frameworks (e.g., Next Generation Science Standards) argue that developing mathematical modeling competencies is critical for students' deep understanding of science. However, science teachers may be unprepared to assess these competencies. We are addressing this need by developing virtual lab performance assessments that…
Descriptors: Mathematical Models, Intelligent Tutoring Systems, Performance Based Assessment, Data Collection
Chen, Zhanwen; Li, Shiyao; Rashedi, Roxanne; Zi, Xiaoman; Elrod-Erickson, Morgan; Hollis, Bryan; Maliakal, Angela; Shen, Xinyu; Zhao, Simeng; Kunda, Maithilee – Grantee Submission, 2020
Modern social intelligence includes the ability to watch videos and answer questions about social and theory-of-mind-related content, e.g., for a scene in "Harry Potter," "Is the father really upset about the boys flying the car?" Social visual question answering (social VQA) is emerging as a valuable methodology for studying…
Descriptors: Visual Stimuli, Questioning Techniques, Social Cognition, Video Technology
Polikoff, Morgan S.; Gasparian, Hovanes; Korn, Shira; Gamboa, Martin; Porter, Andrew C.; Smith, Toni; Garet, Michael S. – Grantee Submission, 2019
As the standards movement continues into its third decade, there remains a need for alignment methodologies that can be broadly applied to study instruction and policy. This article reports on a series of development efforts meant to revise the Surveys of Enacted Curriculum (SEC) surveys and methods to study the implementation of new college- and…
Descriptors: Alignment (Education), Surveys, College Readiness, Career Readiness
Shute, Valerie; Rahimi, Seyedahmad; Smith, Ginny – Grantee Submission, 2019
Well-designed digital games hold promise as effective learning environments. However, designing games that support both learning and engagement without disrupting flow is quite tricky. In addition to including various game design features (e.g., interactive problem solving, adaptive challenges, and player control of gameplay) to engage players,…
Descriptors: Physics, Science Instruction, Educational Games, Educational Technology
Duppong Hurley, Kristin; Farley, Jennifer; Huscroft D'Angelo, Jacqueline – Grantee Submission, 2021
Assessing treatment integrity is essential to understanding how well school-based interventions are delivered. The assessment of treatment integrity is especially challenging for interventions that provide one-on-one peer support over the phone. To address this gap, we explored treatment integrity approaches used for the "Parent…
Descriptors: Outcomes of Treatment, Program Implementation, Delivery Systems, Fidelity
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Hubbard, Aleata – Grantee Submission, 2017
The results of educational research studies are only as accurate as the data used to produce them. Drawing on experiences conducting large-scale efficacy studies of classroom-based algebra interventions for community college and middle school students, I am developing practice-based data cleaning procedures to support scholars in conducting…
Descriptors: Educational Research, Mathematics Education, Algebra, Intervention
Wang, Yutao; Heffernan, Neil T.; Heffernan, Cristina – Grantee Submission, 2015
The well-studied Baker et al., affect detectors on boredom, frustration, confusion and engagement concentration with ASSISTments dataset were used to predict state tests scores, college enrollment, and even whether a student majored in a STEM field. In this paper, we present three attempts to improve upon current affect detectors. The first…
Descriptors: Majors (Students), Affective Behavior, Psychological Patterns, Predictor Variables
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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
Gobert, Janice Darlene; Sao Pedro, Michael A.; Baker, Ryan S. – Grantee Submission, 2012
In this paper we explored whether engaging in two inquiry skills associated with data collection, designing controlled experiments and testing stated hypotheses, within microworlds for one physical science domain (density) impacted the acquisition of inquiry skills in another domain (phase change). To do so, we leveraged educational data mining…
Descriptors: Data Collection, Learning Analytics, Inquiry, Science Process Skills