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Moore, Robert L.; Jiang, Shiyan; Abramowitz, Brian – Journal of Research on Technology in Education, 2023
This systematic review examines the empirical literature published between 2014 and 2021 that situates artificial intelligence within K-12 educational contexts. Our review synthesizes 12 articles and highlights artificial intelligence's instructional contexts and applications in K-12 learning environments. We focused our synthesis on the learning…
Descriptors: Artificial Intelligence, Technology Uses in Education, Elementary Secondary Education, Computer Assisted Instruction
Philip Oreopoulos; Chloe R. Gibbs; Michael Jensen; Joseph P. Price – Annenberg Institute for School Reform at Brown University, 2024
Mastery learning -- the process by which students must demonstrate proficiency with a single topic before moving on -- is well recognized as one of the best ways to learn, yet many teachers struggle or remain unsure about how to implement it into a classroom setting. This study leverages two field experiments to test the efficacy of a program…
Descriptors: Elementary School Teachers, Middle School Teachers, Mathematics Teachers, Computer Assisted Instruction
Lu, Jijian; Tao, Yan; Xu, Jinghao; Stephens, Max – Interactive Learning Environments, 2023
This study is the extension of our previous visualizing study on the commognition processes in computer-supported one-to-one tutoring. With the help of the scale of commognitive responsibility score, we found that the main triggers of the commognition process shift are the positive transfer of knowledge and cognitive conflict. On the basis of…
Descriptors: Cognitive Processes, Computer Assisted Instruction, Tutoring, Artificial Intelligence
Choice of Pedagogical Agents as Virtual Math Tutors: Perspectives from Children and College Students
Huang, Xiaoxia; Mathews, Justin L.; Hsiao, E-Ling – Journal of Educators Online, 2022
The central research question of this empirical study was: How do student demographics, math self-efficacy, and math anxiety relate to and predict their choice of pedagogical agents serving as virtual math tutors? A total of 152 middle school students and 135 college students were surveyed on their perceived math self-efficacy, math anxiety, and…
Descriptors: Tutoring, Mathematics Instruction, Middle School Students, College Students
Cukurova, Mutlu; Khan-Galaria, Madiha; Millán, Eva; Luckin, Rose – Journal of Learning Analytics, 2022
One-to-one online tutoring provided by human tutors can improve students' learning outcomes. However, monitoring the quality of such tutoring is a significant challenge. In this paper, we propose a learning analytics approach to monitoring online one-to-one tutoring quality. The approach analyzes teacher behaviours and classifies tutoring sessions…
Descriptors: Learning Analytics, Tutoring, Educational Quality, Behavior Patterns
Balyan, Renu; Arner, Tracy; Taylor, Karen; Shin, Jinnie; Banawan, Michelle; Leite, Walter L.; McNamara, Danielle S. – International Educational Data Mining Society, 2022
The National Council of Teachers of Mathematics (NCTM) has been emphasizing the importance of teachers' pedagogical communication as part of mathematical teaching and learning for decades. Specifically, NCTM has provided guidance on how teachers can foster mathematical communication that positively impacts student learning. A teacher may have…
Descriptors: Tutoring, Guidelines, Mathematics Instruction, Computer Assisted Instruction
Lu, Jijian; Zhang, Xiaojie; Stephens, Max – Interactive Learning Environments, 2019
This study aims to visualize the commognitive processes in computer-supported one-to-one teaching and learning. By commognitive processes we mean cognitive processes and interpersonal communication. A 6-years mathematics teacher and a 15-year-old boy in China, who have done computer-supported one-to-one tutoring, were chosen to be the samples. We…
Descriptors: Communication (Thought Transfer), Learning Processes, Computer Assisted Instruction, Tutoring
Mohammadhasani, Nasrin; Fardanesh, Hashem; Hatami, Javad; Mozayani, Naser; Fabio, Rosa Angela – Education and Information Technologies, 2018
Gaining the attention is the first key step to enhance learning. In Attention-Deficit/Hyperactivity Disorder (ADHD) as the most prevalent deficit in school age, the learners face some impairment in attention that requires appropriate intervention. An environment that embedded Pedagogical Agent in computer-assisted instruction (CAI) has been…
Descriptors: Attention Deficit Hyperactivity Disorder, Teaching Methods, Computer Assisted Instruction, Educational Technology
Hrastinski, Stefan; Cleveland-Innes, Martha; Stenbom, Stefan – British Journal of Educational Technology, 2018
Online tutors play a critical role in e-learning and need to have an appropriate set of skills in addition to subject matter expertise. This paper explores how digital badges can be used to encourage the development of online tutoring skills. Based on previous research, we defined three digital badges, which are examples of essential tutoring…
Descriptors: Tutoring, Tutors, Mathematics Instruction, Pedagogical Content Knowledge
Bernacki, Matthew L.; Walkington, Candace – Journal of Educational Psychology, 2018
Context personalization--the incorporation of students' out-of-school interests into learning tasks--has recently been shown to positively affect students' situational interest and their performance and learning in mathematics. However, few studies have shown effects on both interest and achievement, drawing into question whether context…
Descriptors: High School Students, Student Interests, Individualized Instruction, Mathematics Instruction
Bringula, Rex P.; Basa, Roselle S.; Dela Cruz, Cecilio; Rodrigo, Ma. Mercedes T. – Journal of Educational Computing Research, 2016
This study attempted to determine the influence of prior knowledge in mathematics of students on learner-interface interactions in a learning-by-teaching intelligent tutoring system. One hundred thirty-nine high school students answered a pretest (i.e., the prior knowledge in mathematics) and a posttest. In between the pretest and posttest, they…
Descriptors: Mathematics, Tutoring, Mathematics Instruction, Foreign Countries
Hodgen, Jeremy; Barclay, Nancy; Foster, Colin; Gilmore, Camila; Marks, Rachel; Simms, Victoria – Education Endowment Foundation, 2020
This document presents a review of evidence commissioned by the Education Endowment Foundation to inform the writing of the guidance report "Improving Mathematics in the Early Years and Key Stage One" (ED612298). The review aimed to synthesise the best available international evidence regarding teaching and learning of mathematics for…
Descriptors: Mathematics Instruction, Elementary School Mathematics, Early Childhood Education, Instructional Effectiveness
Xin, Yan Ping; Tzur, Ron; Hord, Casey; Liu, Jia; Park, Joo Young; Si, Luo – Learning Disability Quarterly, 2017
The Common Core Mathematics Standards have raised expectations for schools and students in the United States. These standards demand much deeper content knowledge from teachers of mathematics and their students. Given the increasingly diverse student population in today's classrooms and shortage of qualified special education teachers,…
Descriptors: Intelligent Tutoring Systems, Computer Assisted Instruction, Mathematics Instruction, Learning Disabilities
Martins, Igor; de Morais, Felipe; Schaab, Bruno; Jaques, Patricia – International Journal of Information and Communication Technology Education, 2016
In most Intelligent Tutoring Systems, the help messages (hints) are not very clear for students as they are only presented textually and have little connection with the task elements. This can lead to students' undesired behaviors, like gaming the system, associated with low performance. In this paper, the authors aim at evaluating if the gestures…
Descriptors: Teaching Methods, Intelligent Tutoring Systems, Problem Solving, Equations (Mathematics)
Arnau, David; Arevalillo-Herráez, Miguel; González-Calero, José Antonio – IEEE Transactions on Learning Technologies, 2014
This paper presents an intelligent tutoring system (ITS) for the learning of arithmetical problem solving. This is based on an analysis of (a) the cognitive processes that take place during problem solving; and (b) the usual tasks performed by a human when supervising a student in a one-to-one tutoring situation. The ITS is able to identify the…
Descriptors: Intelligent Tutoring Systems, Arithmetic, Problem Solving, Supervision