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Showing 1 to 15 of 28 results Save | Export
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Alexandra M. Pierce; Lisa M. H. Sanetti; Melissa A. Collier-Meek; Austin H. Johnson – Grantee Submission, 2024
Visual analysis is the primary methodology used to determine treatment effects from graphed single-case design data. Previous studies have demonstrated mixed findings related to interrater agreement between both expert and novice visual analysts, which represents a critical limitation of visual analysis and supports calls for also presenting…
Descriptors: Graphs, Interrater Reliability, Statistical Analysis, Expertise
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Alexander D. Latham; David A. Klingbeil – Grantee Submission, 2024
The visual analysis of data presented in time-series graphs are common in single-case design (SCD) research and applied practice in school psychology. A growing body of research suggests that visual analysts' ratings are often influenced by construct-irrelevant features including Y-axis truncation and compression of the number of data points per…
Descriptors: Intervention, School Psychologists, Graphs, Evaluation Methods
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Ethan R. Van Norman; Jaclin Boorse; David A. Klingbeil – Grantee Submission, 2024
Despite the increased number of quantitative effect sizes developed for single-case experimental designs (SCEDs), visual analysis remains the gold standard for evaluating methodological rigor of SCEDs and determining whether a functional relation between the treatment and the outcome exists. The physical length and range of values plotted on x and…
Descriptors: Visual Aids, Outcomes of Education, Oral Reading, Reading Comprehension
Dragos Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2023
Reading comprehension is essential for both knowledge acquisition and memory reinforcement. Automated modeling of the comprehension process provides insights into the efficacy of specific texts as learning tools. This paper introduces an improved version of the Automated Model of Comprehension, version 3.0 (AMoC v3.0). AMoC v3.0 is based on two…
Descriptors: Reading Comprehension, Models, Concept Mapping, Graphs
Arsenault, Tessa L.; Powell, Sarah R. – Grantee Submission, 2022
Word-problem features such as text complexity, charts and graphs, position of the unknown, calculation complexity, irrelevant information, and schemas impact word-problem performance. We compared the word-problem performance of typically achieving (TA) students and students with mathematics difficulty (MD). First, we measured the word-problem…
Descriptors: Word Problems (Mathematics), Mathematics Achievement, Models, Charts
Joshua R. Polanin; Qi Zhang; Joseph Taylor; Ryan T. Williams; Megha Joshi; Lauren Burr – Grantee Submission, 2022
Systematic reviews and meta-analyses are important techniques because they synthesize results from multiple primary studies on a similar topic. To influence policy, practice, and research, however, synthesis researchers must translate the results for various audiences. Ideally, the translation drives future research agendas, informs policymaking,…
Descriptors: Evidence, Educational Research, Meta Analysis, Concept Mapping
Fansher, Madison; Adkins, Tyler J.; Shah, Priti – Grantee Submission, 2022
Media articles often communicate the latest scientific findings, and readers must evaluate the evidence and consider its potential implications. Prior work has found that the inclusion of graphs makes messages about scientific data more persuasive (Tal & Wansink, 2016). One explanation for this finding is that such visualizations evoke the…
Descriptors: Graphs, Correlation, Visual Aids, News Reporting
Dascalu, Marina-Dorinela; Ruseti, Stefan; Dascalu, Mihai; McNamara, Danielle; Trausan-Matu, Stefan – Grantee Submission, 2020
Reading comprehension requires readers to connect ideas within and across texts to produce a coherent mental representation. One important factor in that complex process regards the cohesion of the document(s). Here, we tackle the challenge of providing researchers and practitioners with a tool to visualize text cohesion both within (intra) and…
Descriptors: Network Analysis, Graphs, Connected Discourse, Reading Comprehension
Conrad Borchers; Paulo F. Carvalho; Meng Xia; Pinyang Liu; Kenneth R. Koedinger; Vincent Aleven – Grantee Submission, 2023
In numerous studies, intelligent tutoring systems (ITSs) have proven effective in helping students learn mathematics. Prior work posits that their effectiveness derives from efficiently providing eventually-correct practice opportunities. Yet, there is little empirical evidence on how learning processes with ITSs compare to other forms of…
Descriptors: Problem Solving, Intelligent Tutoring Systems, Mathematics Education, Learning Processes
Corlatescu, Dragos-Georgian; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2021
Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader's mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of…
Descriptors: Reading Comprehension, Reading Processes, Memory, Schemata (Cognition)
Xu, Ziqian; Hai, Jiarui; Yang, Yutong; Zhang, Zhiyong – Grantee Submission, 2022
Social network data often contain missing values because of the sensitive nature of the information collected and the dependency among the network actors. As a response, network imputation methods including simple ones constructed from network structural characteristics and more complicated model-based ones have been developed. Although past…
Descriptors: Social Networks, Network Analysis, Data Analysis, Bayesian Statistics
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Theories of discourse argue that comprehension depends on the coherence of the learner's mental representation. Our aim is to create a reliable automated representation to estimate readers' level of comprehension based on different productions, namely self-explanations and answers to open-ended questions. Previous work relied on Cohesion Network…
Descriptors: Network Analysis, Reading Comprehension, Automation, Artificial Intelligence
Cioaca, Valentin Sergiu; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2021
Numerous approaches have been introduced to automate the process of text summarization, but only few can be easily adapted to multiple languages. This paper introduces a multilingual text processing pipeline integrated in the open-source "ReaderBench" framework, which can be retrofit to cover more than 50 languages. While considering the…
Descriptors: Documentation, Computer Software, Open Source Technology, Algorithms
Marta K. Mielicki; Charles J. Fitzsimmons; Lauren K. Schiller; Dan Scheibe; Jennifer M. Taber; Pooja G. Sidney; Percival G. Matthews; Erika A. Waters; Karin G. Coifman; Clarissa A. Thompson – Grantee Submission, 2022
Visual displays, such as icon arrays and risk ladders, are often used to communicate numerical health information. Number lines improve reasoning with rational numbers but are seldom used in health contexts. College students solved ratio problems related to COVID-19 (e.g., number of deaths and number of cases) in one of four randomly-assigned…
Descriptors: Visual Aids, Health, Decision Making, Number Concepts
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Amy Adair; Ellie Segan; Janice Gobert; Michael Sao Pedro – Grantee Submission, 2023
Developing models and using mathematics are two key practices in internationally recognized science education standards, such as the Next Generation Science Standards (NGSS). However, students often struggle with these two intersecting practices, particularly when developing mathematical models about scientific phenomena. Formative…
Descriptors: Artificial Intelligence, Mathematical Models, Science Process Skills, Inquiry
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