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Doewes, Afrizal; Pechenizkiy, Mykola – International Educational Data Mining Society, 2021
Scoring essays is generally an exhausting and time-consuming task for teachers. Automated Essay Scoring (AES) facilitates the scoring process to be faster and more consistent. The most logical way to assess the performance of an automated scorer is by measuring the score agreement with the human raters. However, we provide empirical evidence that…
Descriptors: Man Machine Systems, Automation, Computer Assisted Testing, Scoring
Xin Qiao; Akihito Kamata; Cornelis Potgieter – Grantee Submission, 2023
Oral reading fluency (ORF) assessments are commonly used to screen at-risk readers and to evaluate the effectiveness of interventions as curriculum-based measurements. As with other assessments, equating ORF scores becomes necessary when we want to compare ORF scores from different test forms. Recently, Kara et al. (2023) proposed a model-based…
Descriptors: Error of Measurement, Oral Reading, Reading Fluency, Equated Scores
Zhang, Haoran; Litman, Diane – Grantee Submission, 2020
While automated essay scoring (AES) can reliably grade essays at scale, automated writing evaluation (AWE) additionally provides formative feedback to guide essay revision. However, a neural AES typically does not provide useful feature representations for supporting AWE. This paper presents a method for linking AWE and neural AES, by extracting…
Descriptors: Computer Assisted Testing, Scoring, Essay Tests, Writing Evaluation
Andersen, Øistein E.; Yuan, Zheng; Watson, Rebecca; Cheung, Kevin Yet Fong – International Educational Data Mining Society, 2021
Automated essay scoring (AES), where natural language processing is applied to score written text, can underpin educational resources in blended and distance learning. AES performance has typically been reported in terms of correlation coefficients or agreement statistics calculated between a system and an expert human examiner. We describe the…
Descriptors: Evaluation Methods, Scoring, Essays, Computer Assisted Testing
Mahmoud M. S. Abdallah; Heba Hassan Hemdan; Laila Kamel Eid Ibrahim – Online Submission, 2024
The current research paper investigates the impact of McCarthy's 4MAT model on developing writing skills among upper-grade primary pupils. Sixty-four pupils in six primary-stage grades were chosen as the study participants and were divided randomly into two matched groups (a control group and an experimental one). The researcher adopted the…
Descriptors: Elementary School Students, Models, Writing Instruction, Teaching Methods
Sami Baral; Eamon Worden; Wen-Chiang Lim; Zhuang Luo; Christopher Santorelli; Ashish Gurung; Neil Heffernan – Grantee Submission, 2024
The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…
Descriptors: Automation, Scoring, Computer Assisted Testing, Natural Language Processing
Fromm, Davida; Katta, Saketh; Paccione, Mason; Hecht, Sophia; Greenhouse, Joel; MacWhinney, Brian; Schnur, Tatiana T. – Journal of Speech, Language, and Hearing Research, 2021
Purpose: Analysis of connected speech in the field of adult neurogenic communication disorders is essential for research and clinical purposes, yet time and expertise are often cited as limiting factors. The purpose of this project was to create and evaluate an automated program to score and compute the measures from the Quantitative Production…
Descriptors: Speech, Automation, Statistical Analysis, Adults
Ma, Xiaowen – Mathematics Education Research Group of Australasia, 2023
This paper reports on the development of six student teachers' knowledge of instructional strategies (KOIS) for teaching proportions during a 2-month practicum in China. Development of four subcomponents was explored through Content Representation (CoRe) questionnaires and follow-up interviews. Data was analysed deductively and levels of each…
Descriptors: Teaching Methods, Pedagogical Content Knowledge, Mathematics Instruction, Teacher Education Programs
McCarthy, Kathryn S.; Magliano, Joseph P.; Snyder, Jacob O.; Kenney, Elizabeth A.; Newton, Natalie N.; Perret, Cecile A.; Knezevic, Melanie; Allen, Laura K.; McNamara, Danielle S. – Grantee Submission, 2021
The objective in the current paper is to examine the processes of how our research team negotiated meaning using an iterative design approach as we established, developed, and refined a rubric to capture comprehension processes and strategies evident in students' verbal protocols. The overarching project comprises multiple data sets, multiple…
Descriptors: Scoring Rubrics, Interrater Reliability, Design, Learning Processes
Zhang, Mengxue; Baral, Sami; Heffernan, Neil; Lan, Andrew – International Educational Data Mining Society, 2022
Automatic short answer grading is an important research direction in the exploration of how to use artificial intelligence (AI)-based tools to improve education. Current state-of-the-art approaches use neural language models to create vectorized representations of students responses, followed by classifiers to predict the score. However, these…
Descriptors: Grading, Mathematics Instruction, Artificial Intelligence, Form Classes (Languages)
Ashish Gurung; Anthony F. Botelho; Russell Thompson; Adam C. Sales; Sami Baral; Neil T. Heffernan – Grantee Submission, 2022
It is particularly important to identify and address issues of fairness and equity in educational contexts as academic performance can have large impacts on the types of opportunities that are made available to students. While it is always the hope that educators approach student assessment with these issues in mind, there are a number of factors…
Descriptors: Equal Education, Middle School Mathematics, Middle School Students, Educational Assessment
Zhang, Haoran; Litman, Diane – Grantee Submission, 2017
Manually grading the Response to Text Assessment (RTA) is labor intensive. Therefore, an automatic method is being developed for scoring analytical writing when the RTA is administered in large numbers of classrooms. Our long-term goal is to also use this scoring method to provide formative feedback to students and teachers about students' writing…
Descriptors: Automation, Scoring, Evidence, Scoring Rubrics
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
Zhang, Mengxue; Heffernan, Neil; Lan, Andrew – International Educational Data Mining Society, 2023
Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score…
Descriptors: Scoring, Computer Assisted Testing, Mathematics Instruction, Mathematics Tests
Salaheddin J. Juneidi – International Society for Technology, Education, and Science, 2023
Assessment is not an end in itself but a vehicle for educational improvement. Assessment is vital to the educational process as it enhances teaching and learning, promotes accountability, motivates students, guides instructional decisions, and drives systemic improvements. Assessment plays a crucial role in the educational process as it serves…
Descriptors: Engineering Education, Feedback (Response), Scoring Rubrics, Value Added Models