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Pu Wang; Yifeng Lin; Tiesong Zhao – Education and Information Technologies, 2025
With the emergence of Artificial Intelligence (AI), smart education has become an attractive topic. In a smart education system, automated classrooms and examination rooms could help reduce the economic cost of teaching, and thus improve teaching efficiency. However, existing AI algorithms suffer from low surveillance accuracies and high…
Descriptors: Supervision, Artificial Intelligence, Technology Uses in Education, Automation
Joseph E. Aoun – MIT Press, 2024
In 2017, "Robot-Proof," the first edition, foresaw the advent of the AI economy and called for a new model of higher education designed to help human beings flourish alongside smart machines. That economy has arrived. Creative tasks that, seven years ago, seemed resistant to automation can now be performed with a simple prompt. As a…
Descriptors: Artificial Intelligence, Higher Education, Educational Technology, Technology Uses in Education
Brian E. Clauser; Victoria Yaneva; Peter Baldwin; Le An Ha; Janet Mee – Applied Measurement in Education, 2024
Multiple-choice questions have become ubiquitous in educational measurement because the format allows for efficient and accurate scoring. Nonetheless, there remains continued interest in constructed-response formats. This interest has driven efforts to develop computer-based scoring procedures that can accurately and efficiently score these items.…
Descriptors: Computer Uses in Education, Artificial Intelligence, Scoring, Responses
Eleni Dimitriadou; Andreas Lanitis – Education and Information Technologies, 2025
The body language of an educator during a class can affect student's level of interest and concentration. As an attempt to assist educators to improve their body language and speaking characteristics, a pilot body language analysis system that assesses the body language of educators was developed. The proposed application makes use of specific…
Descriptors: Automation, Nonverbal Communication, Feasibility Studies, Pilot Projects
Fan Zhang; Xiangyu Wang; Xinhong Zhang – Education and Information Technologies, 2025
Intersection of education and deep learning method of artificial intelligence (AI) is gradually becoming a hot research field. Education will be profoundly transformed by AI. The purpose of this review is to help education practitioners understand the research frontiers and directions of AI applications in education. This paper reviews the…
Descriptors: Learning Processes, Artificial Intelligence, Technology Uses in Education, Educational Research
Alejandra J. Magana; Syed Tanzim Mubarrat; Dominic Kao; Bedrich Benes – IEEE Transactions on Learning Technologies, 2024
Fostering productive engagement within teams has been found to improve student learning outcomes. Consequently, characterizing productive and unproductive time during teamwork sessions is a critical preliminary step to increase engagement in teamwork meetings. However, research from the cognitive sciences has mainly focused on characterizing…
Descriptors: Artificial Intelligence, Technology Uses in Education, Teamwork, Learner Engagement
Blaženka Divjak; Barbi Svetec; Damir Horvat – Journal of Computer Assisted Learning, 2024
Background: Sound learning design should be based on the constructive alignment of intended learning outcomes (LOs), teaching and learning activities and formative and summative assessment. Assessment validity strongly relies on its alignment with LOs. Valid and reliable formative assessment can be analysed as a predictor of students' academic…
Descriptors: Automation, Formative Evaluation, Test Validity, Test Reliability
Hosnia M. M. Ahmed; Shaymaa E. Sorour – Education and Information Technologies, 2024
Evaluating the quality of university exam papers is crucial for universities seeking institutional and program accreditation. Currently, exam papers are assessed manually, a process that can be tedious, lengthy, and in some cases, inconsistent. This is often due to the focus on assessing only the formal specifications of exam papers. This study…
Descriptors: Higher Education, Artificial Intelligence, Writing Evaluation, Natural Language Processing
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
Davis, Van L. – WICHE Cooperative for Educational Technologies (WCET), 2023
This resource is a quick primer on AI, with examples of what the different programs can generate based on user prompts, challenges and opportunities, discussion of implications and our recommendations for higher education institutions.
Descriptors: Artificial Intelligence, Higher Education, Automation, Writing (Composition)
Singh, Anil; Bhadauria, Vikram S.; Mangalaraj, George – Journal of Information Systems Education, 2023
Large parts of the enterprise resource planning (ERP) processes are automated. One example is the item values in the sales order process. To execute a sales order, the ERP system applies a specific "find" strategy on a wide variety of data sources such as customer master, material master, and customer price-specific data tables, and…
Descriptors: Teaching Methods, Business Administration Education, Entrepreneurship, Planning
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
Frisby, Joshua C. – ProQuest LLC, 2022
Higher education institutions adopt conversational agents, or chatbots, to perform and automate certain business functions. While chatbots exist to support Enrollment Services, Financial Aid, and other departments within an institution, Institutional Research lacks options. Institutional Research supports higher education institutions by providing…
Descriptors: Institutional Research, Artificial Intelligence, Higher Education, State Universities
David Eubanks; Scott A. Moore – Assessment Update, 2025
Assessment and institutional research offices have too much data and too little time. Standard reporting often crowds out opportunities for innovative research. Fortunately, advancements in data science now offer a clear solution. It is equal parts technique and philosophy. The first and easiest step is to modernize data work. This column…
Descriptors: Higher Education, Educational Assessment, Data Science, Research Methodology
Paula Cristina R. Azevedo; Christine B. Valadez – Impacting Education: Journal on Transforming Professional Practice, 2025
Artificial Intelligence (AI) has seen a significant rise in public use since the release of ChatGPT in November of 2022. Higher education institutions (HEI) have struggled to negotiate how best to manage AI technologies within their academic communities, acknowledging both positive and negative impacts of AI on education. Focused primarily on…
Descriptors: Higher Education, Artificial Intelligence, Technology Uses in Education, Educational Policy