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Beccaria, Lisa; Kek, Megan; Huijser, Henk – Journal of University Teaching and Learning Practice, 2019
Undergraduate nursing students often find essay writing challenging, and feel underprepared, yet the impact of using online feedback to support essay writing has been underexplored. First-year nursing students from a regional university were involved in a project that encouraged them to access an online tutoring service, as part of their…
Descriptors: College Freshmen, Nursing Students, Undergraduate Students, Essays
Krishnaswamy, Jayaraman; Seow, Soo Koon; Annamalai, Nagaletchimee – Malaysian Journal of Learning and Instruction, 2019
Purpose: In Malaysia, numerous families devote a portion of their income to private tutorial learning fees. Many parents, especially those who stay in urban areas, send their children for private tutorial learning. This research investigated the challenges of a shadow education system by analysing Malaysian secondary school students' reactions to…
Descriptors: Private Education, Tutoring, Foreign Countries, Secondary School Students
Fuchs, Douglas; Kearns, Devin M.; Fuchs, Lynn S.; Elleman, Amy M.; Gilbert, Jennifer K.; Patton, Samuel; Peng, Peng; Compton, Donald L. – Exceptional Children, 2019
Because of the importance of teaching reading comprehension to struggling young readers and the infrequency with which it has been implemented and evaluated, we designed a comprehensive first-grade reading comprehension program. We conducted a component analysis of the program's decoding/fluency and reading comprehension dimensions (DF and COMP),…
Descriptors: Grade 1, Reading Instruction, Reading Comprehension, Reading Programs
Bakare, Jimoh; Orji, Chibueze Tobias – Education and Information Technologies, 2019
Some of the factors that influence students' academic achievement, and retention of learning include teacher's mode of teaching, his/her experiences and personality, workload, ability to make use of the available resource materials for teaching and learning. However, literature and some researchers have made it known that adopting students' driven…
Descriptors: Peer Teaching, Tutoring, Academic Achievement, College Students
Lehman, Beth M.; Martin, Jenny M.; Rogers, Karen Santos – Teacher Educators' Journal, 2019
Providing meaningful feedback to student writers is a nuanced, fully human endeavor. Thus, teaching preservice teachers, in all disciplines, to respond to students' writing is a complex task, one that requires intentional instruction and practice. In this article, we use practitioner inquiry to analyze our experiences and teaching approaches with…
Descriptors: Preservice Teachers, Writing Evaluation, Feedback (Response), Middle School Students
Marshall, Jeffery H.; Fukao, Tsuyoshi – Comparative Education Review, 2019
This study analyzes private tutoring (or extra class) participation and provision in Cambodia using nationally representative data from 138 lower secondary schools. Higher socioeconomic status (SES) students are more likely to have access to feebased extra classes offered by teachers from their same school and are more likely to enroll when…
Descriptors: Secondary School Students, Tutoring, Private Education, Foreign Countries
Rajendran, Ramkumar; Iyer, Sridhar; Murthy, Sahana – IEEE Transactions on Learning Technologies, 2019
The importance of affective states in learning has led many Intelligent Tutoring Systems (ITS) to include students' affective states in their learner models. The adaptation and hence the benefits of an ITS can be improved by detecting and responding to students' affective states. In prior work, we have created and validated a theory-driven model…
Descriptors: Feedback (Response), Individualized Instruction, Intelligent Tutoring Systems, Psychological Patterns
Broisin, Julien; Hérouard, Clément – International Educational Data Mining Society, 2019
How to support students in programming learning has been a great research challenge in the last years. To address this challenge, prior works have mainly focused on proposing solutions based on syntactic analysis to provide students with personalized feedback about their grammatical programming errors and misconceptions. However, syntactic…
Descriptors: Semantics, Programming, Syntax, Feedback (Response)
Ausin, Markel Sanz; Azizsoltani, Hamoon; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2019
Deep Reinforcement Learning (DRL) has been shown to be a very powerful technique in recent years on a wide range of applications. Much of the prior DRL work took the "online" learning approach. However, given the challenges of building accurate simulations for modeling student learning, we investigated applying DRL to induce a…
Descriptors: Reinforcement, Intelligent Tutoring Systems, Teaching Methods, Instructional Effectiveness
Oueini, Simela – ProQuest LLC, 2019
This purpose of this paper is to deepen the understanding for a problem of practice in the mathematics educators' classroom of low retention of information thus leading to poor mathematics achievement. The identification of the problem of practice led to a development of a research focus examining the effects of using intelligent tutoring software…
Descriptors: Intelligent Tutoring Systems, Geometry, Mathematics Instruction, Retention (Psychology)
Timms, Michael; DeVelle, Sacha; Lay, Dulce – Australian Journal of Education, 2016
It is well known that learners using intelligent learning environments make different use of the feedback provided by the intelligent learning environment and exhibit different patterns of behaviour. Traditional approaches to measuring such behaviour have focused on observational methods, think-aloud protocols, ratings and log data. More recently,…
Descriptors: Feedback (Response), Learning Processes, Intelligent Tutoring Systems, Models
Mitrovic, Antonija; Suraweera, Pramuditha – International Journal of Artificial Intelligence in Education, 2016
Design tasks are difficult to teach, due to large, unstructured solution spaces, underspecified problems, non-existent problem solving algorithms and stopping criteria. In this paper, we comment on our approach to develop KERMIT, a constraint-based tutor that taught database design. In later work, we re-implemented KERMIT as EER-Tutor, and…
Descriptors: Database Design, Intelligent Tutoring Systems, Problem Solving, Semantics
Weber, Gerhard; Brusilovsky, Peter – International Journal of Artificial Intelligence in Education, 2016
This paper present provides a broader view on ELM-ART, one of the first Web-based Intelligent Educational systems that offered a creative combination of two different paradigms--Intelligent Tutoring and Adaptive Hypermedia technologies. The unique dual nature of ELM-ART contributed to its long life and research impact and was a result of…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Hypermedia
VanLehn, Kurt – International Journal of Artificial Intelligence in Education, 2016
Although the Andes project produced many results over its 18 years of activity, this commentary focuses on its contributions to understanding how a goal-free user interface impacts the overall design and performance of a step-based tutoring system. Whereas a goal-aligned user interface displays relevant goals as blank boxes or empty locations that…
Descriptors: Computer Interfaces, Intelligent Tutoring Systems, Technology Uses in Education, Performance
Muramatsu, Keiichi; Tanaka, Eiichirou; Watanuki, Keiichi; Matsui, Tatsunori – Research and Practice in Technology Enhanced Learning, 2016
Many studies have been conducted during the last two decades examining learner reactions within e-learning environments. In an effort to assist learners in their scholastic activities, these studies have attempted to understand a learner's mental states by analyzing participants' facial images, eye movements, and other physiological indices and…
Descriptors: Electronic Learning, Psychological Patterns, Intelligent Tutoring Systems, Emotional Response

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