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Xin Qiao; Akihito Kamata; Cornelis Potgieter – Grantee Submission, 2024
Oral reading fluency (ORF) assessments are commonly used to screen at-risk readers and evaluate interventions' effectiveness as curriculum-based measurements. Similar to the standard practice in item response theory (IRT), calibrated passage parameter estimates are currently used as if they were population values in model-based ORF scoring.…
Descriptors: Oral Reading, Reading Fluency, Error Patterns, Scoring
Prathiba Natesan Batley; Erica B. McClure; Brandy Brewer; Ateka A. Contractor; Nicholas John Batley; Larry Vernon Hedges; Stephanie Chin – Grantee Submission, 2023
N-of-1 trials, a special case of Single Case Experimental Designs (SCEDs), are prominent in clinical medical research and specifically psychiatry due to the growing significance of precision/personalized medicine. It is imperative that these clinical trials be conducted, and their data analyzed, using the highest standards to guard against threats…
Descriptors: Medical Research, Research Design, Data Analysis, Effect Size
Kiana Hines; Carla Wood; Keisey Fumero – Grantee Submission, 2023
School-aged English Learners (ELs) are faced with the challenging task of acquiring a foreign language while simultaneously reading academically demanding literature. Therefore, the current research aimed to examine the relation between the rate of grammatical tense marking errors made by ELs and their performance on measures of reading…
Descriptors: English Language Learners, Grammar, Morphemes, Error Patterns
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Grantee Submission, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Davison, Mark L.; Davenport, Ernest C., Jr.; Jia, Hao; Seipel, Ben; Carlson, Sarah E. – Grantee Submission, 2022
A regression model of predictor trade-offs is described. Each regression parameter equals the expected change in Y obtained by trading 1 point from one predictor to a second predictor. The model applies to predictor variables that sum to a constant T for all observations; for example, proportions summing to T=1.0 or percentages summing to T=100…
Descriptors: Regression (Statistics), Prediction, Predictor Variables, Models
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
Charles J. Fitzsimmons; Pooja G. Sidney; Marta Mielicki; Lauren K. Schiller; Daniel A. Scheibe; Jennifer M. Taber; Percival G. Matthews; Erika A. Waters; Karin G. Coifman; Clarissa A. Thompson – Grantee Submission, 2023
Comparing health risks that include ratios of integers (e.g., 12 in 1,000) is challenging. We tested whether a worked-example intervention with number-line visual displays improved adults' risk-comparison accuracy, whether pretest confidence moderated learning, and which individual differences related to accuracy. Replicating prior work, U.S.…
Descriptors: Adult Literacy, Numeracy, Mathematics Skills, Health
Eglington, Luke G.; Pavlik, Philip I., Jr. – Grantee Submission, 2022
An important component of many Adaptive Instructional Systems (AIS) is a 'Learner Model' intended to track student learning and predict future performance. Predictions from learner models are frequently used in combination with mastery criterion decision rules to make pedagogical decisions. Important aspects of learner models, such as learning…
Descriptors: Computer Assisted Instruction, Intelligent Tutoring Systems, Learning Processes, Individual Differences
Botarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2022
Automated scoring of student language is a complex task that requires systems to emulate complex and multi-faceted human evaluation criteria. Summary scoring brings an additional layer of complexity to automated scoring because it involves two texts of differing lengths that must be compared. In this study, we present our approach to automate…
Descriptors: Automation, Scoring, Documentation, Likert Scales
Burhan Ogut; Blue Webb; Juanita Hicks; Ruhan Circi; Michelle Yin – Grantee Submission, 2024
In this study, we explore the application of process mining techniques on assessment log data to explore problem-solving strategies in Algebra. By analyzing sequences of student activities, we demonstrate the significant potential of process mining in identifying problem-solving strategies that lead to successful and unsuccessful outcomes. Our…
Descriptors: Mathematics Skills, Problem Solving, Learning Analytics, Algebra
Metcalfe, Janet; Huelser, Barbie J. – Grantee Submission, 2020
Many recent studies have shown that memory for correct answers is enhanced when an error is committed and then corrected, as compared to when the correct answer is provided without intervening error commission. The fact that the kind of errors that produced such a benefit, in past research, were those that were semantically related to the correct…
Descriptors: Recall (Psychology), Memory, Learning Processes, Error Patterns
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Jorge Salas – Grantee Submission, 2024
Despite the growing interest in incorporating response time data into item response models, there has been a lack of research investigating how the effect of speed on the probability of a correct response varies across different groups (e.g., experimental conditions) for various items (i.e., differential response time item analysis). Furthermore,…
Descriptors: Item Response Theory, Reaction Time, Models, Accuracy
Ashish Gurung; Morgan P. Lee; Sami Baral; Adam C. Sales; Kirk P. Vanacore; Andrew A. McReynolds; Hilary Kreisberg; Cristina Heffernan; Aaron Haim; Neil T. Heffernan – Grantee Submission, 2023
Solving mathematical problems is cognitively complex, involving strategy formulation, solution development, and the application of learned concepts. However, gaps in students' knowledge or weakly grasped concepts can lead to errors. Teachers play a crucial role in predicting and addressing these difficulties, which directly influence learning…
Descriptors: Error Patterns, Mathematical Applications, Grade 6, Grade 7
Olney, Andrew M. – Grantee Submission, 2021
In contrast to simple feedback, which provides students with the correct answer, elaborated feedback provides an explanation of the correct answer with respect to the student's error. Elaborated feedback is thus a challenge for AI in education systems because it requires dynamic explanations, which traditionally require logical reasoning and…
Descriptors: Feedback (Response), Error Patterns, Artificial Intelligence, Test Format
Fumero, Keisey; Wood, Carla – Grantee Submission, 2021
The ability to express oneself through written language is a critically important skill for long-term educational, emotional, and social success. However, despite the importance of writing, English Learner students continue to perform at or below basic levels which warrants additional efforts to identify specific areas of weakness that impact…
Descriptors: Written Language, Verbs, Error Patterns, Grade 5