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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
Zesch, Torsten; Horbach, Andrea; Zehner, Fabian – Educational Measurement: Issues and Practice, 2023
In this article, we systematize the factors influencing performance and feasibility of automatic content scoring methods for short text responses. We argue that performance (i.e., how well an automatic system agrees with human judgments) mainly depends on the linguistic variance seen in the responses and that this variance is indirectly influenced…
Descriptors: Influences, Academic Achievement, Feasibility Studies, Automation
Matthews, Benjamin; Shannon, Barrie; Roxburgh, Mark – International Journal of Art & Design Education, 2023
Digital automation is on the rise in a diverse range of industries. The technologies employed here often make use of artificial intelligence (AI) and its common form, machine learning (ML) to augment or replace the work completed by human agents. The recent emergence of a variety of design automation platforms inspired the authors to undertake a…
Descriptors: Artificial Intelligence, Automation, Design, Electronic Learning
Arantes, Janine Aldous; Vicars, Mark – Qualitative Research Journal, 2023
Purpose: The purpose of this paper is to examine how automation in the ever-changing technological landscape is increasing integrated into, and has become a significant presence in, our personal lives. Design/methodology/approach: Through post qualitative inquiry, the authors provide a contemplation of automation and its effect on creativity, as a…
Descriptors: Automation, Creativity, Computer Mediated Communication, Interaction
Abbas, Mohsin; van Rosmalen, Peter; Kalz, Marco – IEEE Transactions on Learning Technologies, 2023
For predicting and improving the quality of essays, text analytic metrics (surface, syntactic, morphological, and semantic features) can be used to provide formative feedback to the students in higher education. In this study, the goal was to identify a sufficient number of features that exhibit a fair proxy of the scores given by the human raters…
Descriptors: Feedback (Response), Automation, Essays, Scoring
Joel M. Cooper; Kaedyn W. Crabtree; Amy S. McDonnell; Dominik May; Sean C. Strayer; Tushig Tsogtbaatar; Danielle R. Cook; Parker A. Alexander; David M. Sanbonmatsu; David L. Strayer – Cognitive Research: Principles and Implications, 2023
Vehicle automation is becoming more prevalent. Understanding how drivers use this technology and its safety implications is crucial. In a 6-8 week naturalistic study, we leveraged a hybrid naturalistic driving research design to evaluate driver behavior with Level 2 vehicle automation, incorporating unique naturalistic and experimental control…
Descriptors: Motor Vehicles, Automation, Information Technology, Behavior
Owen Henkel; Hannah Horne-Robinson; Libby Hills; Bill Roberts; Josh McGrane – International Journal of Artificial Intelligence in Education, 2025
This paper reports on a set of three recent experiments utilizing large-scale speech models to assess the oral reading fluency (ORF) of students in Ghana. While ORF is a well-established measure of foundational literacy, assessing it typically requires one-on-one sessions between a student and a trained rater, a process that is time-consuming and…
Descriptors: Foreign Countries, Oral Reading, Reading Fluency, Literacy
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
Agnes Wittrich – International Journal of Learning and Change, 2024
The article is a call for project professionals to recognise the potential of emerging megatrends for the further development of project management. It inspires project leaders to educate their ethical beliefs and organisations to provide the appropriate environment to enable formation of ethical sensitivity. The systematic literature review is…
Descriptors: Program Administration, Ethics, Trend Analysis, Futures (of Society)
Marcus Messer; Neil C. C. Brown; Michael Kölling; Miaojing Shi – ACM Transactions on Computing Education, 2024
We conducted a systematic literature review on automated grading and feedback tools for programming education. We analysed 121 research papers from 2017 to 2021 inclusive and categorised them based on skills assessed, approach, language paradigm, degree of automation, and evaluation techniques. Most papers assess the correctness of assignments in…
Descriptors: Automation, Grading, Feedback (Response), Programming
Anderson Pinheiro Cavalcanti; Rafael Ferreira Mello; Dragan Gaševic; Fred Freitas – International Journal of Artificial Intelligence in Education, 2024
Educational feedback is a crucial factor in the student's learning journey, as through it, students are able to identify their areas of deficiencies and improve self-regulation. However, the literature shows that this is an area of great dissatisfaction, especially in higher education. Providing effective feedback becomes an increasingly…
Descriptors: Prediction, Feedback (Response), Artificial Intelligence, Automation
Jessy Hsieh – ProQuest LLC, 2024
This dissertation proposes a strategy, or set of decision-making principles, for the education of adults. It explores two related questions: What is the purpose of andragogy and why does this work matter? This philosophical inquiry is situated within a broader context of the automation of knowledge work. As advances in information and…
Descriptors: Adult Education, Andragogy, Decision Making, Information Technology
Larry J. LeBlanc; Thomas A. Grossman; Michael R. Bartolacci – INFORMS Transactions on Education, 2024
The COVID-19 pandemic has forced the rapid adoption of remote teaching modalities including "hyflex" where students attend some class sessions in person and some online. Managing the hyflex course requires faculty to quickly generate several reports and to update these reports rapidly when the authorities adjust the rules, students…
Descriptors: Blended Learning, Scheduling, Spreadsheets, COVID-19
Chaudhuri, Nandita Bhanja; Dhar, Debayan; Yammiyavar, Pradeep G. – International Journal of Technology and Design Education, 2022
Evaluating novelty in design education is subjective and generally depends on expert's referential metrics. Presently, practitioners in this field perform subjective evaluation of answers of prospective students, but many a time, humans are prone to errors when associated with repetitive tasks on large-scale. Therefore, this paper attempts to…
Descriptors: Novelty (Stimulus Dimension), Automation, Evaluation, Aptitude