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Aaron Haim; Eamon Worden; Neil T. Heffernan – Grantee Submission, 2024
Since GPT-4's release it has shown novel abilities in a variety of domains. This paper explores the use of LLM-generated explanations as on-demand assistance for problems within the ASSISTments platform. In particular, we are studying whether GPT-generated explanations are better than nothing on problems that have no supports and whether…
Descriptors: Artificial Intelligence, Learning Management Systems, Computer Software, Intelligent Tutoring Systems
Khaled ElEbyary; Ramy Shabara; Deena Boraie – Language Testing in Asia, 2024
Despite the plethora of studies on the role of noticing in second language learning, little is known about the role of AI-operated feedback in noticing errors and uptake "during" and "after" writing. To address this gap, this study primarily aimed to investigate the impact of feedback modes and timing on L2 students' noticing…
Descriptors: Foreign Countries, Artificial Intelligence, Second Language Learning, English (Second Language)
Amber J. Dood; Field M. Watts; Megan C. Connor; Ginger V. Shultz – Journal of Chemical Education, 2024
Generating a testable hypothesis is a necessary skill for engaging in science, requiring both general reasoning skills and specific content knowledge of the phenomenon being investigated. While many students have the reasoning skills necessary for developing testable hypotheses in a general science context, it can be challenging for students to…
Descriptors: Automation, Organic Chemistry, Writing (Composition), Scientific Concepts
Ricardo Conejo Muñoz; Beatriz Barros Blanco; José del Campo-Ávila; José L. Triviño Rodriguez – IEEE Transactions on Learning Technologies, 2024
Automatic question generation and the assessment of procedural knowledge is still a challenging research topic. This article focuses on the case of it, the techniques of parsing grammars for compiler construction. There are two well-known techniques for parsing: top-down parsing with LL(1) and bottom-up with LR(1). Learning these techniques and…
Descriptors: Automation, Questioning Techniques, Knowledge Level, Language
Samuel S. Davidson – ProQuest LLC, 2024
Automated corrective feedback (ACF), in which a computer system helps language learners identify and correct errors in their writing or speech, is considered an important tool for language instruction by many researchers. Such systems allow learners to correct their own mistakes, thereby reducing teacher workload and potentially preventing issues…
Descriptors: Computer Assisted Testing, Automation, Student Evaluation, Feedback (Response)
Emmanuel Dumbuya – Online Submission, 2025
The integration of artificial intelligence (AI) into educational ecosystems represents a paradigm shift in pedagogical practices and educational governance. While AI offers unprecedented opportunities to personalize learning, optimize administrative processes, and provide intelligent tutoring, it poses significant challenges to maintaining human…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Technology Integration
Guher Gorgun; Okan Bulut – Educational Measurement: Issues and Practice, 2025
Automatic item generation may supply many items instantly and efficiently to assessment and learning environments. Yet, the evaluation of item quality persists to be a bottleneck for deploying generated items in learning and assessment settings. In this study, we investigated the utility of using large-language models, specifically Llama 3-8B, for…
Descriptors: Artificial Intelligence, Quality Control, Technology Uses in Education, Automation
Sghaier Guizani; Tehseen Mazhar; Tariq Shahzad; Wasim Ahmad; Afsha Bibi; Habib Hamam – Discover Education, 2025
Artificial intelligence-driven Chatbots, especially large language models (LLMs) like GPT-4, represent significant progress in digital education. These models excel in mimicking human-like text and transforming learning and teaching methods. This study examines the development, application, and impact of LLMs in education. It highlights their role…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
Jessie S. Barrot – Technology, Knowledge and Learning, 2025
Significant advancements in artificial intelligence (AI) technologies have led to the development of Google Gemini, which can be used to provide automated writing assistance. Within higher education, this feature extends to research writing. However, skepticism is particularly evident as students, teachers, and researchers in universities explore…
Descriptors: Artificial Intelligence, Computer Software, Computer Uses in Education, Educational Research
Pinandito, Aryo; Prasetya, Didik D.; Hayashi, Yusuke; Hirashima, Tsukasa – Research and Practice in Technology Enhanced Learning, 2021
This research, to design and develop a concept map authoring support tool, adopts a semi-automatic concept mapping approach to help teachers create concept maps from English readings. A concept map is widely regarded as a useful teaching and learning tool. It offers many potential advantages apart from representing the students' knowledge and…
Descriptors: Automation, Concept Mapping, Computer Uses in Education, Educational Technology
Silva, Warley Almeida; Carchedi, Luiz Carlos; Junior, Jorão Gomes; Victor de Souza, João; Barrere, Eduardo; Francisco de Souza, Jairo – International Journal of Distance Education Technologies, 2021
Learning assessments are important to monitor the progress of students throughout the teaching process. In the digital era, many local and large-scale learning assessments are conducted through technological tools. In this view, a large-scale learning assessment can be designed to tackle one or multiple parts of the teaching process. Oral reading…
Descriptors: Oral Reading, Reading Fluency, Reading Tests, Automation
Das, Bidyut; Majumder, Mukta; Phadikar, Santanu; Sekh, Arif Ahmed – Research and Practice in Technology Enhanced Learning, 2021
Learning through the internet becomes popular that facilitates learners to learn anything, anytime, anywhere from the web resources. Assessment is most important in any learning system. An assessment system can find the self-learning gaps of learners and improve the progress of learning. The manual question generation takes much time and labor.…
Descriptors: Automation, Test Items, Test Construction, Computer Assisted Testing
Ryan H. Rindlisbacher – ProQuest LLC, 2021
The Vehicle Routing Problem (VRP) has been widely studied. However, very little research can be found that includes driver considerations. Many professional trades, such as plumbers, electricians, or concrete cutters, carry specialized certifications. Unlike traditional VRP, where the driver is excluded from all considerations, not every driver…
Descriptors: Transportation, Certification, Motor Vehicles, Paraprofessional Personnel
Casabianca, Jodi M.; Donoghue, John R.; Shin, Hyo Jeong; Chao, Szu-Fu; Choi, Ikkyu – Journal of Educational Measurement, 2023
Using item-response theory to model rater effects provides an alternative solution for rater monitoring and diagnosis, compared to using standard performance metrics. In order to fit such models, the ratings data must be sufficiently connected in order to estimate rater effects. Due to popular rating designs used in large-scale testing scenarios,…
Descriptors: Item Response Theory, Alternative Assessment, Evaluators, Research Problems
Jiang, Michael Yi-Chao; Jong, Morris Siu-Yung; Lau, Wilfred Wing-Fat; Chai, Ching-Sing; Wu, Na – Journal of Computer Assisted Learning, 2023
Background: While automatic speech recognition (ASR) is increasingly used for commercial purposes, its influence on the learners' linguistic performance in terms of oral complexity, accuracy and fluency was under-explored. To date, few studies have been conducted to investigate how the dictation ASR technology could be incorporated into language…
Descriptors: Speech Communication, Automation, Accuracy, Language Fluency