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Sarah Novicoff; Susanna Loeb – Phi Delta Kappan, 2024
Since the COVID-19 pandemic, tutoring has gained popularity as a strategy to improve the academic achievement of struggling students. Intensive, relationship-based tutoring is a highly effective academic support for many students. A range of tutoring approaches are available to accelerate young students' literacy. Sarah Novicoff and Susanna Loeb…
Descriptors: Emergent Literacy, Tutoring, COVID-19, Pandemics
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Briana Alford; Sarah Celt; Kylie Gottlieb; Aaron Mickulas-Mesco; Aedan Sennett; John Zilvinskis – Assessment Update, 2024
Tutoring can be an effective high-impact practice (HIP) to support diverse students across academic majors. Using 2017-2019 Community College Survey of Student Engagement (CCSSE) data, Zilvinskis (2021) found participating in tutoring was significantly related to the engagement measures of Academic Challenge, Support for Learners, and…
Descriptors: Peer Teaching, Tutoring, Learner Engagement, Educational Practices
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Milos Ilic; Goran Kekovic; Vladimir Mikic; Katerina Mangaroska; Lazar Kopanja; Boban Vesin – IEEE Transactions on Learning Technologies, 2024
In recent years, there has been an increasing trend of utilizing artificial intelligence (AI) methodologies over traditional statistical methods for predicting student performance in e-learning contexts. Notably, many researchers have adopted AI techniques without conducting a comprehensive investigation into the most appropriate and accurate…
Descriptors: Artificial Intelligence, Academic Achievement, Prediction, Programming
Meghan Jacquelynn Malloy – ProQuest LLC, 2024
While systems of support are used in schools to assist students' academic growth, parents are not always informed of the support process or the academic goals set for their child (RTI Action Network, n.d.; Troisi, 2014; Weingarten et al., 2020). In the aftermath of the pandemic, students present a wide variety of academic needs (Lewis et al.,…
Descriptors: Parent Attitudes, Parent Participation, Advocacy, Literacy
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Galafassi, Cristiano; Galafassi, Fabiane Flores Penteado; Vicari, Rosa Maria; Reategui, Eliseo Berni – International Journal of Artificial Intelligence in Education, 2023
This work presents the intelligent tutoring system, EvoLogic, developed to assist students in problems of natural production in propositional logic. EvoLogic has been modeled as a multiagent system composed of three autonomous agents: interface, pedagogical and specialist agents. It supports pedagogical strategies inspired by the theory of…
Descriptors: Intelligent Tutoring Systems, Logical Thinking, Models, Teaching Methods
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Ren, Ping; Dou, Zhongchen; Wang, Xici; Li, Simeng; Wang, Lidong – Asia-Pacific Education Researcher, 2023
Private supplementary tutoring (PT) has expanded significantly and attracted widespread public interest in China in recent years. It deserves systematic empirical research and reflection, given its crucial theoretical and practical implications. Based on the data of a large-scale survey and testing project, this study examined its effects on the…
Descriptors: Private Education, Supplementary Education, Tutoring, Mathematics Instruction
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Jha, Sanjeev Kumar – Journal of Education, 2023
Private tuition (PT) is a common phenomenon in India. Today, it is a multi-billion U.S. dollar (USD) market and the third major contributor of household expenses in India. However, "the effect of PT on academic achievement of the students" is a subjective statement and is being questioned by its very outcomes. Literature reveals that PT…
Descriptors: Private Education, Tutoring, Foreign Countries, Supplementary Education
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Lu, Yu; Wang, Deliang; Chen, Penghe; Meng, Qinggang; Yu, Shengquan – International Journal of Artificial Intelligence in Education, 2023
As a prominent aspect of modeling learners in the education domain, knowledge tracing attempts to model learner's cognitive process, and it has been studied for nearly 30 years. Driven by the rapid advancements in deep learning techniques, deep neural networks have been recently adopted for knowledge tracing and have exhibited unique advantages…
Descriptors: Learning Processes, Artificial Intelligence, Intelligent Tutoring Systems, Data Analysis
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Harrison, Dorian – Urban Review: Issues and Ideas in Public Education, 2023
This article challenges and explores an after-school literacy tutor program in a semi-urban midwestern state. As after-school programs continue to be widely used across the United States, there is also continued efforts to engage students in continued academic learning after school. Hynes and Sanders (2011) studied the experiences of various…
Descriptors: After School Programs, Tutoring, Literacy Education, Racial Differences
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Wang, Huanhuan; Tlili, Ahmed; Huang, Ronghuai; Cai, Zhenyu; Li, Min; Cheng, Zui; Yang, Dong; Li, Mengti; Zhu, Xixian; Fei, Cheng – Education and Information Technologies, 2023
Intelligent Tutoring Systems (ITSs) have a great potential to effectively transform teaching and learning. As more efforts have been put on designing and developing ITSs and integrating them within learning and instruction, mixed types of results about the effectiveness of ITS have been reported. Therefore, it is necessary to investigate how ITSs…
Descriptors: Intelligent Tutoring Systems, Literature Reviews, Research Methodology, Instructional Effectiveness
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Bray, Mark; Suante, Peter Kamtungtuang – International Review of Education, 2023
Around the world, the provision of private supplementary tutoring, widely known as "shadow education", is attracting increased attention. In many countries, teachers are major providers of such tutoring outside their official school hours. Other providers include personnel in tutorial centres, and university students who operate…
Descriptors: Foreign Countries, Tutoring, Private Education, Teaching Methods
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Sanz Ausin, Markel; Maniktala, Mehak; Barnes, Tiffany; Chi, Min – International Journal of Artificial Intelligence in Education, 2023
While Reinforcement learning (RL), especially Deep RL (DRL), has shown outstanding performance in video games, little evidence has shown that DRL can be successfully applied to human-centric tasks where the ultimate RL goal is to make the "human-agent interactions" productive and fruitful. In real-life, complex, human-centric tasks, such…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Teaching Methods, Learning Activities
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DeFeo, Dayna Jean; Mammo, Behailu – Journal of Teacher Education and Educators, 2023
Though teacher education programs must document candidates' teaching dispositions, there is a gap in the literature around what faculty may learn by observing students in contexts outside of the k-12 classroom. This case study explores what faculty may learn about teaching dispositions by observing tutors. For our study, three mathematics…
Descriptors: Teaching Styles, Tutoring, College Mathematics, College Faculty
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Griffith, John – Online Journal of Distance Learning Administration, 2023
Three years of data for 5,617 college online introductory statistics students were examined to determine if embedded course videos reduced incidences of external course tutoring. The frequency of external tutoring in course sections that used embedded videos was significantly reduced by 55% when compared to courses that did not use embedded course…
Descriptors: Tutoring, Video Technology, Tutorial Programs, Program Implementation
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Pelánek, Radek; Effenberger, Tomáš; Cechák, Jaroslav – International Journal of Artificial Intelligence in Education, 2022
Complexity and difficulty are two closely related but distinct concepts. These concepts are important in the development of intelligent learning systems, e.g., for sequencing items, student modeling, or content management. We show how to use complexity and difficulty measures in the development of learning systems and provide guidance on how to…
Descriptors: Difficulty Level, Intelligent Tutoring Systems, Measurement Techniques, Computer System Design
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