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Dennis Murphy Odo – Applied Linguistics, 2023
Texts used in L2 classrooms have traditionally been simplified manually, but recent technological advances allow us to investigate whether automatic text simplification (ATS) software can help L2 learners comprehend texts in second and foreign languages. Participants were divided into low and high L2 reading proficiency groups and assigned to read…
Descriptors: Automation, Computer Software, Second Language Learning, Reading Ability
Peter Organisciak; Selcuk Acar; Denis Dumas; Kelly Berthiaume – Grantee Submission, 2023
Automated scoring for divergent thinking (DT) seeks to overcome a key obstacle to creativity measurement: the effort, cost, and reliability of scoring open-ended tests. For a common test of DT, the Alternate Uses Task (AUT), the primary automated approach casts the problem as a semantic distance between a prompt and the resulting idea in a text…
Descriptors: Automation, Computer Assisted Testing, Scoring, Creative Thinking
David W. Brown; Dean Jensen – International Society for Technology, Education, and Science, 2023
The growth of Artificial Intelligence (AI) chatbots has created a great deal of discussion in the education community. While many have gravitated towards the ability of these bots to make learning more interactive, others have grave concerns that student created essays, long used as a means of assessing the subject comprehension of students, may…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Software, Writing (Composition)
Bonnie Stewart; Erica Miklas; Samantha Sczyrek; Thu Le – OTESSA Conference Proceedings, 2023
Datafied digital systems have permeated higher education over the past decade. Registration, grading, financial operations, and often teaching all take place through digital platforms that extract and collate data about students as well as faculty and staff. At the level of these data system processes, academics may not have the knowledge or…
Descriptors: Foreign Countries, Higher Education, Data Use, Technology Integration
Das, Syaamantak; Mandal, Shyamal Kumar Das; Basu, Anupam – Contemporary Educational Technology, 2020
Cognitive learning complexity identification of assessment questions is an essential task in the domain of education, as it helps both the teacher and the learner to discover the thinking process required to answer a given question. Bloom's Taxonomy cognitive levels are considered as a benchmark standard for the classification of cognitive…
Descriptors: Classification, Difficulty Level, Test Items, Identification
Sahu, Archana; Bhowmick, Plaban Kumar – IEEE Transactions on Learning Technologies, 2020
In this paper, we studied different automatic short answer grading (ASAG) systems to provide a comprehensive view of the feature spaces explored by previous works. While the performance reported in previous works have been encouraging, systematic study of the features is lacking. Apart from providing systematic feature space exploration, we also…
Descriptors: Automation, Grading, Test Format, Artificial Intelligence
Thaker, Khushboo; Zhang, Lei; He, Daqing; Brusilovsky, Peter – International Educational Data Mining Society, 2020
Assessment plays a vital role in learning, as it provides both instructors and students with feedback on the overall effectiveness of their teaching or learning. However, when a student fails to correctly answer certain questions in an assessment (such as a quiz), the student needs specific recommendations that are tailored to their learning needs…
Descriptors: Automation, Textbooks, Electronic Learning, Artificial Intelligence
Somers, Rick; Cunningham-Nelson, Samuel; Boles, Wageeh – Australasian Journal of Educational Technology, 2021
In this study, we applied natural language processing (NLP) techniques, within an educational environment, to evaluate their usefulness for automated assessment of students' conceptual understanding from their short answer responses. Assessing understanding provides insight into and feedback on students' conceptual understanding, which is often…
Descriptors: Natural Language Processing, Student Evaluation, Automation, Feedback (Response)
Keller-Margulis, Milena A.; Mercer, Sterett H.; Matta, Michael – Reading and Writing: An Interdisciplinary Journal, 2021
Existing approaches to measuring writing performance are insufficient in terms of both technical adequacy as well as feasibility for use as a screening measure. This study examined the validity and diagnostic accuracy of several approaches to automated text evaluation as well as written expression curriculum-based measurement (WE-CBM) to determine…
Descriptors: Writing Evaluation, Validity, Automation, Curriculum Based Assessment
Tsiakmaki, Maria; Kostopoulos, Georgios; Kotsiantis, Sotiris; Ragos, Omiros – Journal of Computing in Higher Education, 2021
Predicting students' learning outcomes is one of the main topics of interest in the area of Educational Data Mining and Learning Analytics. To this end, a plethora of machine learning methods has been successfully applied for solving a variety of predictive problems. However, it is of utmost importance for both educators and data scientists to…
Descriptors: Active Learning, Predictor Variables, Academic Achievement, Learning Analytics
Marchman, Virginia A.; Weisleder, Adriana; Hurtado, Nereyda; Fernald, Anne – Journal of Child Language, 2021
Laboratory observations are a mainstay of language development research, but transcription is costly. We test whether speech recognition technology originally designed for day-long contexts can be usefully applied to this use-case. We compared automated adult word and child vocalization counts from Language Environment Analysis (LENA[TM]) to those…
Descriptors: Accuracy, Audio Equipment, Word Recognition, Oral Language
Rangraz, Masood; Pareto, Lena – International Journal of Lifelong Education, 2021
Small manufacturing plants nowadays need to consider Industry 4.0 to stay competitive in the market. Among the challenges regarding the transformation towards Industry 4.0 are requirements to re-skill the staff for the new work environment. The staff have to either adapt to the workplace transformation brought by digitalisation, automation and…
Descriptors: Workplace Learning, Experiential Learning, Manufacturing Industry, Job Training
Saripan, Hartini; Mohd Shith Putera, Nurus Sakinatul Fikriah; Abdullah, Sarah Munirah; Abu Hassan, Rafizah; Abd Ghadas, Zuhairah Ariff – Asian Journal of University Education, 2021
Digitization across the healthcare industry has witnessed the advent of emerging Cognitive Computing (CC) healthcare technologies that improve diagnostic accuracy and efficiency, predict illnesses, automate routine healthcare tasks, and refine processes and care beyond human capabilities. Increased adoption of this technology can be attributed to…
Descriptors: Information Technology, Health Services, Artificial Intelligence, Automation
Thacker, Donald; Berardi, Victor; Kaur, Vaneet; Blundell, Greg – Information Systems Education Journal, 2021
Understanding students' perceptions, aptitudes, and interest in using technology, and in developing technological solutions to problems, is important for effectively incorporating it into course pedagogy. This paper presents an effort to understand student technological self-conception, especially regarding the use-of-technology versus the…
Descriptors: Business Administration Education, Technological Literacy, Self Concept, Readiness
Ockey, Gary J.; Neiriz, Reza – Assessment in Education: Principles, Policy & Practice, 2021
As our understanding of the construct of oral communication (OC) has evolved, so have the possibilities of computer technology undertaking the delivery of tests that measure this ability. It is paramount to understand to what extent such developments lead to accurate, comprehensive, and useful assessment of OC. In this paper, we discuss five…
Descriptors: Speech Communication, Computer Assisted Testing, Speech Tests, English (Second Language)

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