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Kobakhidze, Magda Nutsa – Globalisation, Societies and Education, 2020
This study focuses on the changed roles and symbolic identities of Myanmar teachers under the forces of marketisation and the privatisation of education. Private tutoring by school teachers is used as an example of what society perceives to be the incursion into education of market-oriented values that are incompatible with traditional morals. The…
Descriptors: Teacher Role, Professional Identity, Privatization, Tutoring
Briant, Elizabeth; Doherty, Catherine; Dooley, Karen; English, Rebecca – Pedagogy, Culture and Society, 2020
Australia's private tutoring market is expanding in a context where parents' trust in school personnel as educational experts is vulnerable. Simultaneously, a parentocratic logic is nudging parents to infuse the resources at their disposal into their pedagogic work in order to achieve the educational outcomes that they wish for their children.…
Descriptors: Parent Attitudes, Advertising, Tutoring, Private Education
Dooley, Karen; Liu, Liwei Livia; Yin, Yue Melody – Discourse: Studies in the Cultural Politics of Education, 2020
This article reports a study of the supply of private supplementary tuition in literacy for primary school students. The data set consisted of websites and advertisements of 46 suppliers active in an area of suburban Australia with a substantial population of migrants from East Asia. To conceptualise the supply of private tuition as edu-business,…
Descriptors: Foreign Countries, Private Education, Tutoring, Supplementary Education
Grubišic, Ani; Žitko, Branko; Stankov, Slavomir – Journal of Technology and Science Education, 2020
In intelligent e-learning systems that adapt a learning and teaching process to student knowledge, it is important to adapt the system as quickly as possible. However, adaptation is not possible until the student model is initialized. In this paper, a new approach to student model initialization using domain knowledge representative subset is…
Descriptors: Electronic Learning, Educational Technology, Models, Intelligent Tutoring Systems
Patikorn, Thanaporn; Heffernan, Neil T. – Grantee Submission, 2020
It has been shown in multiple studies that expert-created on-demand assistance, such as hint messages, improves student learning in online learning environments. However, there are also evident that certain types of assistance may be detrimental to student learning. In addition, creating and maintaining on-demand assistance are hard and…
Descriptors: Electronic Publishing, Group Experience, Tutoring, Electronic Learning
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 2020
For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…
Descriptors: Natural Language Processing, Artificial Intelligence, Man Machine Systems, Classification
Li, Haiying; Graesser, Art C. – Grantee Submission, 2020
This study investigated how computer agents' language style affects summary writing in an Intelligent Tutoring System, called CSAL AutoTutor. Participants interacted with two computer agents in one of three language styles: (1) a "formal" language style; (2) an "informal" language style; and (3) a "mixed" language…
Descriptors: Intelligent Tutoring Systems, Language Styles, Writing (Composition), Writing Improvement
Elaine Allensworth; Nate Schwartz – EdResearch for Recovery Project, 2020
This brief is one in a series aimed at providing K-12 education decision makers and advocates with an evidence base to ground discussions about how to best serve students during and following the novel coronavirus pandemic. Learning losses are likely to show up differently across grades and subjects, with intensive recovery needs concentrated in…
Descriptors: Retention (Psychology), Intervention, COVID-19, Pandemics
Michela Carlana; Eliana La Ferrara – National Bureau of Economic Research, 2024
We study the Tutoring Online Program (TOP), where: (i) tutoring is entirely online; (ii) tutors are volunteer university students, matched with underprivileged middle school students. We leverage random assignment to estimate effects during and after the pandemic (2020 and 2022), investigating channels of impact. Three hours of individual tutoring…
Descriptors: Tutoring, Computer Mediated Communication, College Students, Middle School Students
Cheng Ching Ho – Online Learning, 2024
Artificial intelligence (AI) tools have become a popular topic in the education field. Most of the schools in Hong Kong focus on how to properly use AI software to help students' learning experience. As this is still a relatively new technology, the stance for most of the schools in Hong Kong is skeptical. This study aims to find out whether…
Descriptors: Artificial Intelligence, Writing Ability, Technology Uses in Education, Foreign Countries
Claudia De Barros Camargo; Antonio Hernández Fernández – Educational Process: International Journal, 2024
Background/Purpose: This study investigates the integration of neuropedagogy, neuroimaging, artificial intelligence (AI), and deep learning in educational systems. The research aims to elucidate how these technologies can be synergistically applied to optimize learning processes based on individual neurocognitive profiles, thereby enhancing…
Descriptors: Artificial Intelligence, Educational Practices, Intelligent Tutoring Systems, Neurosciences
Kevin Wai Ho Yung; Shu Fai Philip Wong – Language Learning Journal, 2024
With a focus on the neglected 'L2 learning experience' component in Dörnyei's L2 Motivational Self System (L2MSS), this study investigated secondary students' L2 motivation in the context of online English private tutoring (EPT). Through narrative inquiry, students narrated their EPT experience online and reflected on it in comparison with that in…
Descriptors: Second Language Learning, Student Motivation, Student Experience, Electronic Learning
Tzu-Yu Tai; Howard Hao-Jan Chen – Computer Assisted Language Learning, 2024
Intelligent Personal Assistant (IPA) has emerged as a valuable tool for EFL learning by offering interactive authentic contexts. Although IPA is believed to be motivational and useful, empirical evidence is limited and contradictory, especially the efficacy of listening comprehension. Therefore, the study investigated the impact of IPA on…
Descriptors: English (Second Language), English Language Learners, Adolescents, Listening Comprehension
Maria V. Carbonari; Anna McDonald; Michael DeArmond; Andrew McEachin; Daniel Dewey; Emily Morton; Elise Dizon-Ross; Atsuko Muroga; Dan Goldhaber; Alejandra Salazar; Thomas J. Kane; Douglas O. Staiger – National Center for Analysis of Longitudinal Data in Education Research (CALDER), 2024
The COVID-19 pandemic devastated student achievement, with declines rivaling those after Hurricane Katrina. These losses widened achievement gaps between historically marginalized students and their peers. Three years later, achievement remains behind pre-pandemic levels for many students. This paper examines 2022-23 academic recovery efforts…
Descriptors: Elementary Secondary Education, Federal Aid, Grants, Emergency Programs
Drametrice T. Smith – ProQuest LLC, 2024
Student athletes often enter college unprepared for academic rigor, making them particularly vulnerable in terms of academic success. At a faith-based university in the southeast United States, low retention of student athletes results from poor class attendance, course failures, and low grade point averages. The purpose of this basic qualitative…
Descriptors: Males, Student Athletes, At Risk Students, School Holding Power

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