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Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma – International Educational Data Mining Society, 2016
How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…
Descriptors: Intelligent Tutoring Systems, Sequential Approach, Problem Solving, Learning Processes
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2015
To be able to provide better support for collaborative learning in Intelligent Tutoring Systems, it is important to understand how collaboration patterns change. Prior work has looked at the interdependencies between utterances and the change of dialogue over time, but it has not addressed how dialogue changes during a lesson, an analysis that…
Descriptors: Intelligent Tutoring Systems, Feedback (Response), Cooperative Learning, Group Dynamics
Rau, Martina A.; Aleven, Vincent; Rummel, Nikol – Instructional Science: An International Journal of the Learning Sciences, 2017
Prior research shows that representational competencies that enable students to use graphical representations to reason and solve tasks is key to learning in many science, technology, engineering, and mathematics domains. We focus on two types of representational competencies: (1) "sense making" of connections by verbally explaining how…
Descriptors: Elementary School Students, Grade 3, Grade 4, Grade 5
Crossley, Scott; Liu, Ran; McNamara, Danielle – Grantee Submission, 2017
A number of studies have demonstrated links between linguistic knowledge and performance in math. Studies examining these links in first language speakers of English have traditionally relied on correlational analyses between linguistic knowledge tests and standardized math tests. For second language (L2) speakers, the majority of studies have…
Descriptors: Predictor Variables, Mathematics Achievement, English (Second Language), Natural Language Processing
Rau, Martina A.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2017
Prior research shows that representational competencies that enable students to use graphical representations to reason and solve tasks is key to learning in many science, technology, engineering, and mathematics (STEM) domains. We focus on two types of representational competencies: (1) "sense making" of connections by verbally…
Descriptors: Elementary School Students, Grade 3, Grade 4, Grade 5
Olsen, Jennifer K.; Rummel, Nikol; Aleven, Vincent – Grantee Submission, 2017
Collaborative and individual learning are both frequently used in classrooms to support learning. However, little research has investigated the benefits of combining individual and collaborative learning, as compared to learning only individually or only collaboratively. With our study, we address this research gap. We compared a combined…
Descriptors: Cooperative Learning, Grade 4, Grade 5, Elementary School Students
Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2014
While collaborative Intelligent Tutoring Systems (ITSs) have been designed for older students and have been shown to support sense-making behaviors, there has not been as much work on creating systems to support collaboration between elementary school students. We have developed and tested, with 84 students, individual and collaborative versions…
Descriptors: Intelligent Tutoring Systems, Elementary School Students, Fractions, Cooperative Learning
Olsen, Jennifer K.; Rummel, Nikol; Aleven, Vincent – Grantee Submission, 2015
To learn from an error, students must correct the error by engaging in sense-making activities around the error. Past work has looked at how supporting collaboration around errors affects learning. This paper attempts to shed further light on the role that collaboration can play in the process of overcoming an error. We found that good…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Cooperative Learning
Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2013
Collaborative and individual instruction may support different types of knowledge. Optimal instruction for a subject domain may therefore need to combine these two modes of instruction. There has not been much research, however, on combining individual and collaborative learning with Intelligent Tutoring Systems (ITSs). A first step is to expand…
Descriptors: Cooperative Learning, Intelligent Tutoring Systems, Teaching Methods, Educational Technology
Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma – International Educational Data Mining Society, 2015
The field of EDM has focused more on modeling student knowledge than on investigating what sequences of different activity types achieve good learning outcomes. In this paper we consider three activity types, targeting sense-making, induction and refinement, and fluency building. We investigate what mix of the three types might be most effective…
Descriptors: Information Retrieval, Data Analysis, Learning Activities, Grade 4
Maloy, Robert W.; Razzaq, Leena; Edwards, Sharon A. – Journal of Interactive Learning Research, 2014
This study explored the use of an online mathematics tutoring system in eight fourth grade classrooms in two Massachusetts communities--a small rural city with a low 2010 Adequate Yearly Progress (AYP) math performance rating and a small suburban district with a high 2010 AYP math performance rating. 165 fourth graders completed 11 modules…
Descriptors: Intelligent Tutoring Systems, Multimedia Instruction, Mathematics Instruction, Elementary School Mathematics
Cetintas, Suleyman; Si, Luo; Xin, Yan Ping; Hord, Casey – International Working Group on Educational Data Mining, 2009
This paper proposes a learning based method that can automatically determine how likely a student is to give a correct answer to a problem in an intelligent tutoring system. Only log files that record students' actions with the system are used to train the model, therefore the modeling process doesn't require expert knowledge for identifying…
Descriptors: Programming, Evidence, Intelligent Tutoring Systems, Regression (Statistics)

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