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Singla, Adish; Theodoropoulos, Nikitas – International Educational Data Mining Society, 2022
Block-based visual programming environments are increasingly used to introduce computing concepts to beginners. Given that programming tasks are open-ended and conceptual, novice students often struggle when learning in these environments. AI-driven programming tutors hold great promise in automatically assisting struggling students, and need…
Descriptors: Programming, Computer Science Education, Task Analysis, Introductory Courses
Paquette, Luc; Baker, Ryan S. – Interactive Learning Environments, 2019
Learning analytics research has used both knowledge engineering and machine learning methods to model student behaviors within the context of digital learning environments. In this paper, we compare these two approaches, as well as a hybrid approach combining the two types of methods. We illustrate the strengths of each approach in the context of…
Descriptors: Comparative Analysis, Student Behavior, Models, Case Studies
Mendes, Skyler H.; Fede, Jacquelyn H.; Wilks, Megan B. – Learning Assistance Review, 2017
The aim of this analysis was to determine from a pilot project whether a new style of course-connected learning support for students in gateway STEM courses could be more successful on the University of Rhode Island's campus than the traditional Supplemental Instruction (SI) model. The new model, Weekly Tutoring Groups (WTG), addressed several of…
Descriptors: Pilot Projects, STEM Education, College Students, Teaching Methods
Hull, Alison; du Boulay, Benedict – Computer Science Education, 2015
Motivation and metacognition are strongly intertwined, with learners high in self-efficacy more likely to use a variety of self-regulatory learning strategies, as well as to persist longer on challenging tasks. The aim of the research was to improve the learner's focus on the process and experience of problem-solving while using an Intelligent…
Descriptors: Motivation, Metacognition, Feedback (Response), Intelligent Tutoring Systems
Wan, Hao; Beck, Joseph Barbosa – International Educational Data Mining Society, 2015
The phenomenon of wheel spinning refers to students attempting to solve problems on a particular skill, but becoming stuck due to an inability to learn the skill. Past research has found that students who do not master a skill quickly tend not to master it at all. One question is why do students wheel spin? A plausible hypothesis is that students…
Descriptors: Skill Development, Problem Solving, Knowledge Level, Learning Processes
Adamson, Reesha M.; Lewis, Timothy J. – Behavioral Disorders, 2017
A single subject alternating treatment design across three student-teacher dyads was used to investigate the comparative impact on student academic engaged time of three opportunity-to-respond (OTR) strategies: guided notes, class-wide peer tutoring, and response cards. Participants were three high school students with disabilities with noted…
Descriptors: Student Behavior, Behavior Problems, High School Students, Comparative Analysis
Somers, Cheryl L.; Wang, Dan; Piliawsky, Monte – Journal of Applied School Psychology, 2016
This quasi-experimental study examined the effectiveness of a combined tutoring and mentoring intervention for urban, low-income Black youth during the transition to high school. Participants were 118 ninth-grade students (experimental n = 69; comparison n = 49). After 7 months in the intervention program, students in the experimental group showed…
Descriptors: Quasiexperimental Design, Tutoring, Mentors, Intervention
Rodrigo, Ma. Mercedes T.; Baker, Ryan S. J. D.; Rossi, Lisa – Teachers College Record, 2013
Background: Off-task behavior can be defined as any behavior that does not involve the learning task or material, or where learning from the material is not the primary goal. One suggested path for understanding how to address off-task behavior is to study classrooms where off-task behavior is less common, particularly in Asia, in order to…
Descriptors: Student Behavior, Foreign Countries, Time on Task, Intelligent Tutoring Systems
Malone, Amelia S.; Fuchs, Lynn S. – Grantee Submission, 2014
The purpose of this study was to assess the relative contribution of teacher and tutor ratings of inattentive behavior in two different instructional settings in predicting students' performance on fraction concepts and whole-number calculations. Classroom teachers rated each student's attentive behavior in a whole-class setting and tutors rated…
Descriptors: Elementary School Students, Mathematics Instruction, Teacher Attitudes, Elementary School Teachers
Sabourin, Jennifer L.; Rowe, Jonathan P.; Mott, Bradford W.; Lester, James C. – Journal of Educational Data Mining, 2013
Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…
Descriptors: Student Behavior, Classification, Learner Engagement, Data Analysis
Ben-Naim, Dror; Bain, Michael; Marcus, Nadine – International Working Group on Educational Data Mining, 2009
It has been recognized that in order to drive Intelligent Tutoring Systems (ITSs) into mainstream use by the teaching community, it is essential to support teachers through the entire ITS process: Design, Development, Deployment, Reflection and Adaptation. Although research has been done on supporting teachers through design to deployment of ITSs,…
Descriptors: Foreign Countries, Intelligent Tutoring Systems, Computer System Design, Computer Managed Instruction
Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2009
The Cognitive Tutor Authoring Tools (CTAT) support creation of a novel type of tutors called example-tracing tutors. Unlike other types of ITSs (e.g., model-tracing tutors, constraint-based tutors), example-tracing tutors evaluate student behavior by flexibly comparing it against generalized examples of problem-solving behavior. Example-tracing…
Descriptors: Feedback (Response), Student Behavior, Intelligent Tutoring Systems, Problem Solving
Xu, Yaoying; Gelfer, Jeffrey I.; Sileo, Nancy; Filler, John; Perkins, Peggy G. – Early Child Development and Care, 2008
This study examined the effects of peer tutoring on children's social interactions and compared social interaction behaviors between children who are English-language learners (ELL) and children who are primary English speakers (PES). Single-subject withdrawal design (ABA) was applied in this study and classwide peer tutoring was used as the…
Descriptors: Predictor Variables, Young Children, Interpersonal Relationship, Interaction
Morrow, Lesley Mandel; And Others – 1997
A study determined the impact of a literacy program including social cooperative literacy experiences on literacy achievement of first-, second-, and third-grade children. Treatment in the experimental groups, which consisted of 204 children from 3 first-, 3 second-, and 3 third-grade urban classrooms included designing classroom literacy centers,…
Descriptors: Classroom Research, Comparative Analysis, Cooperative Learning, Elementary School Students

Greenwood, Charles R.; And Others – Journal of Educational Psychology, 1989
This longitudinal study assessed differences in classroom arrangements (peer tutoring versus teacher instruction) and student behaviors for students of low versus high socioeconomic status (SES). Results with 94 teachers and 416 students indicate that peer tutoring was more effective in increasing academic engagement of low-SES students than…
Descriptors: Classroom Techniques, Comparative Analysis, Compensatory Education, Economically Disadvantaged
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