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Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
Fatima Abu Deeb; Timothy Hickey – Computer Science Education, 2024
Background and Context: Auto-graders are praised by novice students learning to program, as they provide them with automatic feedback about their problem-solving process. However, some students often make random changes when they have errors in their code, without engaging in deliberate thinking about the cause of the error. Objective: To…
Descriptors: Reflection, Automation, Grading, Novices
Hossein Kermani; Alireza Bayat Makou; Amirali Tafreshi; Amir Mohamad Ghodsi; Ali Atashzar; Ali Nojoumi – International Journal of Social Research Methodology, 2024
Despite the increasing adaption of automated text analysis in communication studies, its strengths and weaknesses in framing analysis are so far unknown. Fewer efforts have been made to automatic detection of networked frames. Drawing on the recent developments in this field, we harness a comparative exploration, using Latent Dirichlet Allocation…
Descriptors: COVID-19, Pandemics, Automation, Foreign Countries
Regan Mozer; Luke Miratrix – Grantee Submission, 2024
For randomized trials that use text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by trained human raters. This process, the current standard, is both time-consuming and limiting: even the largest human coding efforts are typically constrained to…
Descriptors: Artificial Intelligence, Coding, Efficiency, Statistical Inference
Rebeckah K. Fussell; Emily M. Stump; N. G. Holmes – Physical Review Physics Education Research, 2024
Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…
Descriptors: Physics, Educational Researchers, Artificial Intelligence, Natural Language Processing
Yifan Li; Anmin Liu; Runming Si; Leyan Liu; Qidong Zhao – Journal of Chemical Education, 2024
The plate and frame filtration experiment is one of the essential experiments performed by undergraduate students during their practical education. While this experiment often relies on the conventional manual recording of data and calculation, there are frequent problems with data collection because capturing transient data of filtrate volume and…
Descriptors: Internet, Automation, Undergraduate Study, College Science
Xiner Liu; Andres Felipe Zambrano; Ryan S. Baker; Amanda Barany; Jaclyn Ocumpaugh; Jiayi Zhang; Maciej Pankiewicz; Nidhi Nasiar; Zhanlan Wei – Journal of Learning Analytics, 2025
This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are most successful for different types of constructs. Specifically, we assess three different prompt engineering strategies -- Zero-shot, Few-shot, and Fewshot with…
Descriptors: Coding, Artificial Intelligence, Automation, Data Analysis
Fromm, Davida; MacWhinney, Brian; Thompson, Cynthia K. – Journal of Speech, Language, and Hearing Research, 2020
Purpose: Analysis of spontaneous speech samples is important for determining patterns of language production in people with aphasia. To accomplish this, researchers and clinicians can use either hand coding or computer-automated methods. In a comparison of the two methods using the hand-coding NNLA (Northwestern Narrative Language Analysis) and…
Descriptors: Automation, Computational Linguistics, Aphasia, Coding
Liu, Houjun; MacWhinney, Brian; Fromm, Davida; Lanzi, Alyssa – Journal of Speech, Language, and Hearing Research, 2023
Purpose: A major barrier to the wider use of language sample analysis (LSA) is the fact that transcription is very time intensive. Methods that can reduce the required time and effort could help in promoting the use of LSA for clinical practice and research. Method: This article describes an automated pipeline, called Batchalign, that takes raw…
Descriptors: Automation, Language Tests, Computational Linguistics, Morphology (Languages)
Linxuan Zhao; Dragan Gaševic; Zachari Swiecki; Yuheng Li; Jionghao Lin; Lele Sha; Lixiang Yan; Riordan Alfredo; Xinyu Li; Roberto Martinez-Maldonado – British Journal of Educational Technology, 2024
Effective collaboration and teamwork skills are critical in high-risk sectors, as deficiencies in these areas can result in injuries and risk of death. To foster the growth of these vital skills, immersive learning spaces have been created to simulate real-world scenarios, enabling students to safely improve their teamwork abilities. In such…
Descriptors: Automation, Transcripts (Written Records), Coding, Teamwork
Figen Durkaya – Shanlax International Journal of Education, 2023
The present study has been developed in order to inquire the cognitive awareness of the 2nd grade-level students of the Science Teaching program on "sensors", which has an important place in the development of the robotic and automation systems. In the study, the method of case study, which is one of the qualitative research motifs, was…
Descriptors: Preservice Teachers, Science Teachers, Grade 2, Teacher Education Programs
Asmaa Bengueddach; Djamila Hamdadou – International Society for Technology, Education, and Science, 2024
The COVID-19 pandemic, an unprecedented global health crisis, has not only significantly impacted public health but has also caused substantial disruptions to conventional education systems. In response to these challenges, our institution has undertaken innovative measures within the realm of education. A pivotal aspect of our response involves…
Descriptors: Personal Autonomy, Online Courses, Educational Change, Coding
Carla Wood; Miguel Garcia-Salas; Christopher Schatschneider – Grantee Submission, 2023
Purpose: The aim of this study was to advance the analysis of written language transcripts by validating an automated scoring procedure using an automated open-access tool for calculating morphological complexity (MC) from written transcripts. Method: The MC of words in 146 written responses of students in fifth grade was assessed using two…
Descriptors: Automation, Computer Assisted Testing, Scoring, Computation
Audette, Lillian M.; Hammond, Marie S.; Rochester, Natalie K. – Educational and Psychological Measurement, 2020
Longitudinal studies are commonly used in the social and behavioral sciences to answer a wide variety of research questions. Longitudinal researchers often collect data anonymously from participants when studying sensitive topics to ensure that accurate information is provided. One difficulty gathering longitudinal anonymous data is that of…
Descriptors: Research Methodology, Longitudinal Studies, Research Design, Social Science Research
McHugh, Meaghan C.; Saperstein, Sandra L.; Gold, Robert S. – Health Education & Behavior, 2019
Cyberbullying, defined as bullying that takes place using technology, includes similar tactics found in traditional bullying as well as unique approaches such as viral repetition. Nationally, prevalence rates for cyberbullying range from 10% to as high as 40% of school-aged children, depending on the definition and measurement tool applied. The…
Descriptors: Bullying, Computer Mediated Communication, Handheld Devices, Telecommunications
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