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Alexey Kopyl; Yuki Yew; Jian Wern Ong; Thomas Hiscox; Calem Young; Murat Muradoglu; Tuck Wah Ng – Journal of Chemical Education, 2024
Efforts to encourage laboratory automation through student access to and usage of commercial equipment are hampered by prohibitive acquisition costs. Here, an automated liquid handler using manual pipettes was developed to operate on a commercial hobbyist 3D printer at a cost of US $325. Arising from an iterative design process that ensured…
Descriptors: Science Laboratories, Laboratory Equipment, Computer Peripherals, Printing
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
Ferrara, Steve; Qunbar, Saed – Journal of Educational Measurement, 2022
In this article, we argue that automated scoring engines should be transparent and construct relevant--that is, as much as is currently feasible. Many current automated scoring engines cannot achieve high degrees of scoring accuracy without allowing in some features that may not be easily explained and understood and may not be obviously and…
Descriptors: Artificial Intelligence, Scoring, Essays, Automation
Alexandra C. Salem; Robert C. Gale; Mikala Fleegle; Gerasimos Fergadiotis; Steven Bedrick – Journal of Speech, Language, and Hearing Research, 2023
Purpose: To date, there are no automated tools for the identification and fine-grained classification of paraphasias within discourse, the production of which is the hallmark characteristic of most people with aphasia (PWA). In this work, we fine-tune a large language model (LLM) to automatically predict paraphasia targets in Cinderella story…
Descriptors: Aphasia, Prediction, Story Telling, Oral Language
Munish Saini; Eshan Sengupta; Naman Sharma – Education and Information Technologies, 2025
To be an effective teacher, one must possess strong learning abilities. Developing lesson planning, pursuing learning objectives, and assessing post-lesson accomplishments all these depend on reflection and ongoing learning. As education is context-specific, the iterative process of preparing, reflecting, and improving is what makes teaching…
Descriptors: Artificial Intelligence, Technology Uses in Education, Nonverbal Communication, Feedback (Response)
Andreea Dutulescu; Stefan Ruseti; Denis Iorga; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
The process of generating challenging and appropriate distractors for multiple-choice questions is a complex and time-consuming task. Existing methods for an automated generation have limitations in proposing challenging distractors, or they fail to effectively filter out incorrect choices that closely resemble the correct answer, share synonymous…
Descriptors: Multiple Choice Tests, Artificial Intelligence, Attention, Natural Language Processing
Zirou Lin; Hanbing Yan; Li Zhao – Journal of Computer Assisted Learning, 2024
Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…
Descriptors: Peer Evaluation, Automation, Grading, Models
Daniel J. Carragher; Daniel Sturman; Peter J. B. Hancock – Cognitive Research: Principles and Implications, 2024
The human face is commonly used for identity verification. While this task was once exclusively performed by humans, technological advancements have seen automated facial recognition systems (AFRS) integrated into many identification scenarios. Although many state-of-the-art AFRS are exceptionally accurate, they often require human oversight or…
Descriptors: Automation, Human Body, Man Machine Systems, Accuracy
Heng Zhang; Minhong Wang – Knowledge Management & E-Learning, 2024
With the fast development of artificial intelligence and emerging technologies, automatic recognition of students' facial expressions has received increased attention. Facial expressions are a kind of external manifestation of emotional states. It is important for teachers to assess students' emotional states and adjust teaching activities…
Descriptors: Artificial Intelligence, Models, Recognition (Psychology), Nonverbal Communication
Zaki, Nazar; Turaev, Sherzod; Shuaib, Khaled; Krishnan, Anusuya; Mohamed, Elfadil – Education and Information Technologies, 2023
Quality control and assurance plays a fundamental role within higher education contexts. One means by which quality control can be performed is by mapping the course learning outcomes (CLOs) to the program learning outcomes (PLO). This paper describes a system by which this mapping process can be automated and validated. The proposed AI-based…
Descriptors: Program Evaluation, Outcomes of Education, Natural Language Processing, Higher Education
Muller, Ashley Elizabeth; Ames, Heather Melanie R.; Jardim, Patricia Sofia Jacobsen; Rose, Christopher James – Research Synthesis Methods, 2022
Systematic reviews are resource-intensive. The machine learning tools being developed mostly focus on the study identification process, but tools to assist in analysis and categorization are also needed. One possibility is to use unsupervised automatic text clustering, in which each study is automatically assigned to one or more meaningful…
Descriptors: Artificial Intelligence, Man Machine Systems, Automation, Literature Reviews
Ferrando, Pere J.; Lorenzo-Seva, Urbano – Educational and Psychological Measurement, 2021
Unit-weight sum scores (UWSSs) are routinely used as estimates of factor scores on the basis of solutions obtained with the nonlinear exploratory factor analysis (EFA) model for ordered-categorical responses. Theoretically, this practice results in a loss of information and accuracy, and is expected to lead to biased estimates. However, the…
Descriptors: Scores, Factor Analysis, Automation, Fidelity
Jimmy Tobin; Phillip Nelson; Bob MacDonald; Rus Heywood; Richard Cave; Katie Seaver; Antoine Desjardins; Pan-Pan Jiang; Jordan R. Green – Journal of Speech, Language, and Hearing Research, 2024
Purpose: This study examines the effectiveness of automatic speech recognition (ASR) for individuals with speech disorders, addressing the gap in performance between read and conversational ASR. We analyze the factors influencing this disparity and the effect of speech mode--specific training on ASR accuracy. Method: Recordings of read and…
Descriptors: Foreign Countries, Speech Impairments, Computational Linguistics, Artificial Intelligence
Altena, Allard J.; Spijker, René; Leeflang, Mariska M. G.; Olabarriaga, Sílvia Delgado – Research Synthesis Methods, 2021
When performing a systematic review, researchers screen the articles retrieved after a broad search strategy one by one, which is time-consuming. Computerised support of this screening process has been applied with varying success. This is partly due to the dependency on large amounts of data to develop models that predict inclusion. In this…
Descriptors: Screening Tests, Automation, Diagnostic Tests, Models
Ullah, Mohammad Aman; Tahrin, Anika; Marjan, Sumaiya – International Journal of Web-Based Learning and Teaching Technologies, 2020
The web is the largest world-wide communication system of computers. The web has local, academic, commercial and government sites. As the types of websites increases in numbers, the cost and accuracy of manual classification became cumbersome and cannot satisfy the increasing internet service demands, thereby automated classification became…
Descriptors: Web Sites, Classification, Mathematics, Automation