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Howard, Cynthia; Jordan, Pamela; Di Eugenio, Barbara; Katz, Sandra – International Journal of Artificial Intelligence in Education, 2017
Despite a growing need for educational tools that support students at the earliest phases of undergraduate Computer Science (CS) curricula, relatively few such tools exist--the majority being Intelligent Tutoring Systems. Since peer interactions more readily give rise to challenges and negotiations, another way in which students can become more…
Descriptors: Computer Science Education, Undergraduate Study, Intelligent Tutoring Systems, Artificial Intelligence
L2 Learner Cognitive Psychological Factors about Artificial Intelligence Writing Corrective Feedback
Wu, LiQin; Wu, Yong; Zhang, XiangYang – English Language Teaching, 2021
Although the study of artificial intelligence (AI) used in language teaching and learning is increasingly prevailing, research on language two (L2) learner cognitive psychological factors about AI writing corrective feedback (WCF) is scarce. This paper explores L2 learner cognitive psychology of pigai, an AI evaluating system for English writings…
Descriptors: Artificial Intelligence, Error Correction, Feedback (Response), Second Language Instruction
Bastiaens, Theo J., Ed. – Association for the Advancement of Computing in Education, 2021
The Association for the Advancement of Computing in Education (AACE) is an international, non-profit educational organization. The Association's purpose is to advance the knowledge, theory, and quality of teaching and learning at all levels with information technology. The "EdMedia + Innovate Learning" conference took place online July…
Descriptors: Educational Media, Conferences (Gatherings), Electronic Learning, Distance Education
Obari, Hiroyuki; Lambacher, Steve; Kikuchi, Hisayo – Research-publishing.net, 2020
This study focuses on the use of emerging technologies such as Artificial Intelligence (AI) smart speakers and smartphone applications for improving the English language skills of L1 Japanese undergraduates. An empirical investigation was carried out with 82 Japanese students. Participants were required to study a variety of online English…
Descriptors: Artificial Intelligence, Computer Simulation, Audio Equipment, Handheld Devices
Polyzou, Agoritsa; Karypis, George – International Educational Data Mining Society, 2018
Developing tools to support students and learning in a traditional or online setting is a significant task in today's educational environment. The initial steps towards enabling such technologies using machine learning techniques focused on predicting the student's performance in terms of the achieved grades. The disadvantage of these approaches…
Descriptors: Low Achievement, Predictor Variables, Classification, Student Characteristics
Barros, Thiago M.; Souza Neto, Plácido A.; Silva, Ivanovitch; Guedes, Luiz Affonso – Education Sciences, 2019
Predicting school dropout rates is an important issue for the smooth execution of an educational system. This problem is solved by classifying students into two classes using educational activities related statistical datasets. One of the classes must identify the students who have the tendency to persist. The other class must identify the…
Descriptors: Predictor Variables, Models, Dropout Rate, Classification
Auerbach, Joshua E.; Concordel, Alice; Kornatowski, Przemyslaw M.; Floreano, Dario – IEEE Transactions on Learning Technologies, 2019
It has often been found that students appreciate hands-on work, and find that they learn more with courses that include a project than those relying solely on conventional lectures and tests. This type of project driven learning is a key component of "Inquiry-based learning" (IBL), which aims at teaching methodology as well as content by…
Descriptors: Active Learning, Inquiry, Robotics, Artificial Intelligence
Lin, Vivien; Liu, Gi-Zen; Chen, Nian-Shing – Computer Assisted Language Learning, 2022
The use of technology such as online software has been examined in English as a foreign language (EFL) writing contexts. However, few studies have incorporated context-aware ubiquitous technology into EFL writing instruction. To develop multimodal and digital literacy of target EFL undergraduates in this pilot project, the researchers designed and…
Descriptors: Writing Instruction, Teaching Methods, Schemata (Cognition), Second Language Learning
Moussalli, Souheila; Cardoso, Walcir – Computer Assisted Language Learning, 2020
Second/foreign language (L2) classrooms do not always provide opportunities for input and output practice [Lightbown, P. M. (2000). Classroom SLA research and second language teaching. Applied Linguistics, 21(4), 431-462]. The use of smart speakers such as Amazon Echo and its associated voice-controlled intelligent personal assistant (IPA) Alexa…
Descriptors: Artificial Intelligence, Pronunciation, Native Language, Listening Comprehension
Brown, Phillip – Journal of Education and Work, 2020
A fundamental shift is taking place in the way we think about the future of work and its relationship to education, training and the labour market. Until recently, expanding higher education was widely believed to result in higher earnings, reflecting an insatiable demand for knowledge workers. In the United Kingdom, this race to higher education…
Descriptors: Higher Education, Foreign Countries, Outcomes of Education, Job Training
Koc-Januchta, Marta M.; Schönborn, Konrad J.; Tibell, Lena A. E.; Chaudhri, Vinay K.; Heller, H. Craig – Journal of Educational Computing Research, 2020
Applying artificial intelligence (AI) to support science learning is a prominent aspect of the digital education revolution. This study investigates students' interaction and learning with an AI book, which enables the inputting of questions and receiving of suggested questions to understand biology, in comparison with a traditional E-book.…
Descriptors: Artificial Intelligence, Textbook Content, Science Materials, Biology
Mack Shelley, Editor; Valarie Akerson, Editor; Mevlut Unal, Editor – International Society for Technology, Education, and Science, 2023
"Proceedings of International Conference on Social and Education Sciences" includes full papers presented at the International Conference on Social and Education Sciences (IConSES), which took place on October 19-22, 2023, in Las Vegas, Nevada. The aim of the conference is to offer opportunities to share ideas, discuss theoretical and…
Descriptors: Conference Papers, Social Sciences, Educational Research, Education
Vivitsou, Marianna – Center for Educational Policy Studies Journal, 2019
The metaphor of digitalisation in education emerged during a period when phenomena such as budget cuts and privatisation, layoffs and outsourcing of labour marked the ethos of the twenty-first century. During this time, digitalisation was constructed as an ultimate purpose and an all-encompassing matter in education. As a result, these narratives…
Descriptors: Educational Technology, Technology Uses in Education, Foreign Countries, Economic Factors
Vrba, Tony; Mitchell, Kerry – Journal of Instructional Pedagogies, 2019
Today's students expect more than lectures more from higher education. Contemporary students are searching for the education they need to advance in the workplace, though they want their education to be engaging, applicable, and relevant to the real-world. Technology and innovation are in the news almost every day and people automatically think…
Descriptors: Classroom Techniques, Educational Innovation, Relevance (Education), Education Work Relationship
Deep Learning + Student Modeling + Clustering: A Recipe for Effective Automatic Short Answer Grading
Zhang, Yuan; Shah, Rajat; Chi, Min – International Educational Data Mining Society, 2016
In this work we tackled the task of Automatic Short Answer Grading (ASAG). While conventional ASAG research makes prediction mainly based on student answers referred as Answer-based, we leveraged the information about questions and student models into consideration. More specifically, we explore the Answer-based, Question, and Student models…
Descriptors: Automation, Grading, Artificial Intelligence, Test Format