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Doewes, Afrizal; Kurdhi, Nughthoh Arfawi; Saxena, Akrati – International Educational Data Mining Society, 2023
Automated Essay Scoring (AES) tools aim to improve the efficiency and consistency of essay scoring by using machine learning algorithms. In the existing research work on this topic, most researchers agree that human-automated score agreement remains the benchmark for assessing the accuracy of machine-generated scores. To measure the performance of…
Descriptors: Essays, Writing Evaluation, Evaluators, Accuracy
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
Jia, Qinjin; Young, Mitchell; Xiao, Yunkai; Cui, Jialin; Liu, Chengyuan; Rashid, Parvez; Gehringer, Edward – International Educational Data Mining Society, 2022
Providing timely feedback is crucial in promoting academic achievement and student success. However, for multifarious reasons (e.g., limited teaching resources), feedback often arrives too late for learners to act on the feedback and improve learning. Thus, automated feedback systems have emerged to tackle educational tasks in various domains,…
Descriptors: Student Projects, Feedback (Response), Natural Language Processing, Guidelines
Johnson, Carol; Cardoso, Walcir; Zuercher, Beau; Brannen, Kathleen; Springer, Suzanne – Research-publishing.net, 2022
This study examined the use of a popular Automatic Speech Recognition (ASR), Google Voice Typing (GVT), to automatically assess English as second language pronunciation. It aimed to answer the following question: What is the relationship between GVT-rated scores and human-rated scores? To answer this question, we compared audio recordings of 56…
Descriptors: Teaching Methods, Computer Software, Pronunciation, Second Language Learning
Yarbro, Jeffrey T.; Olney, Andrew M. – Grantee Submission, 2021
This paper explores the concept of dynamically generating definitions using a deep-learning model. We do this by creating a dataset that contains definition entries and contexts associated with each definition. We then fine-tune a GPT-2 based model on the dataset to allow the model to generate contextual definitions. We evaluate our model with…
Descriptors: Definitions, Learning Processes, Models, Context Effect
Kovalkov, Anastasia; Paassen, Benjamin; Segal, Avi; Gal, Kobi; Pinkwart, Niels – International Educational Data Mining Society, 2021
Promoting creativity is considered an important goal of education, but creativity is notoriously hard to define and measure. In this paper, we make the journey from defining a formal creativity and applying the measure in a practical domain. The measure relies on core theoretical concepts in creativity theory, namely fluency, flexibility, and…
Descriptors: Creativity, Theory Practice Relationship, Evaluators, Specialists
Unnam, Abhishek; Takhar, Rohit; Aggarwal, Varun – International Educational Data Mining Society, 2019
Email has become the most preferred form of business communication. Writing "good" email has become an essential skill required in the industry. "Good" email writing not only facilitates clear communication, but also makes a positive impression on the recipient, whether it be one's colleague or a customer. The aim of this paper…
Descriptors: Grading, Electronic Mail, Feedback (Response), Written Language
Roscoe, Rod D.; Crossley, Scott A.; Snow, Erica L.; Varner, Laura K.; McNamara, Danielle S. – Grantee Submission, 2014
Automated essay scoring tools are often criticized on the basis of construct validity. Specifically, it has been argued that computational scoring algorithms may be unaligned to higher-level indicators of quality writing, such as writers' demonstrated knowledge and understanding of the essay topics. In this paper, we consider how and whether the…
Descriptors: Correlation, Essays, Scoring, Writing Evaluation
Solano-Flores, Guillermo; Raymond, Bruce; Schneider, Steven A. – 1997
The need for effective ways of monitoring the quality of scoring of portfolios resulted in the development of a software package that provides scoring leaders with updated information on their assessors' scoring quality. Assessors with computers enter data as they score, and this information is analyzed and reported to scoring leaders. The…
Descriptors: Art Teachers, Computer Assisted Testing, Computer Software, Computer Software Evaluation
Barrett, Andrew J.; And Others – 1990
The Center for Interactive Technology, Applications, and Research at the College of Engineering of the University of South Florida (Tampa) has developed objective and descriptive evaluation models to assist in determining the educational potential of computer and video courseware. The computer-based courseware evaluation model and the video-based…
Descriptors: Computer Assisted Instruction, Computer Software, Computer Software Evaluation, Content Validity
Costa, Crist H. – 1985
Evaluators, by the nature of their work, must be concerned with data management activities ranging from the collection and recording of data to the analyses, summation, and presentation of those data. Though word processing has been cited as the most frequently used microcomputer package by educational evaluators, spreadsheets are among the most…
Descriptors: Computer Software, Data Analysis, Data Collection, Documentation
Lunz, Mary E.; And Others – 1989
A method for understanding and controlling the multiple facets of an oral examination (OE) or other judge-intermediated examination is presented and illustrated. This study focused on determining the extent to which the facets model (FM) analysis constructs meaningful variables for each facet of an OE involving protocols, examiners, and…
Descriptors: Computer Software, Difficulty Level, Evaluators, Examiners

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