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Dzikovska, Myroslava; Steinhauser, Natalie; Farrow, Elaine; Moore, Johanna; Campbell, Gwendolyn – International Journal of Artificial Intelligence in Education, 2014
Within STEM domains, physics is considered to be one of the most difficult topics to master, in part because many of the underlying principles are counter-intuitive. Effective teaching methods rely on engaging the student in active experimentation and encouraging deep reasoning, often through the use of self-explanation. Supporting such…
Descriptors: Intelligent Tutoring Systems, Electronics, Energy, Science Instruction
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
Zhang, Lishan; VanLehn, Kurt – Interactive Learning Environments, 2017
The paper describes a biology tutoring system with adaptive question selection. Questions were selected for presentation to the student based on their utilities, which were estimated from the chance that the student's competence would increase if the questions were asked. Competence was represented by the probability of mastery of a set of biology…
Descriptors: Biology, Science Instruction, Intelligent Tutoring Systems, Probability
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2016
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the literature on writing. Previous research suggests that higher quality…
Descriptors: Role, Writing (Composition), Natural Language Processing, Hypothesis Testing
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Journal of Educational Psychology, 2016
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the literature on writing. Previous research suggests that higher quality…
Descriptors: Role, Writing (Composition), Natural Language Processing, Hypothesis Testing
Katz, Sandra; Albacete, Patricia L. – Journal of Educational Psychology, 2013
For some time, it has been clear that students who are tutored generally learn more than students who experience classroom instruction (e.g., Bloom, 1984). Much research has been devoted to identifying features of tutorial dialogue that can explain its effectiveness, so that these features can be simulated in natural-language tutoring systems. One…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Interaction, Rhetorical Theory
Katz, Sandra; Albacete, Patricia L. – Grantee Submission, 2013
For some time, it has been clear that students who are tutored generally learn more than students who experience classroom instruction (e.g., Bloom, 1984). Much research has been devoted to identifying features of tutorial dialogue that can explain its effectiveness, so that these features can be simulated in natural-language tutoring systems. One…
Descriptors: Rhetorical Theory, Tutoring, Intelligent Tutoring Systems, Secondary School Science
Crossley, Scott A.; Varner, Laura K.; Roscoe, Rod D.; McNamara, Danielle S. – Grantee Submission, 2013
We present an evaluation of the Writing Pal (W-Pal) intelligent tutoring system (ITS) and the W-Pal automated writing evaluation (AWE) system through the use of computational indices related to text cohesion. Sixty-four students participated in this study. Each student was assigned to either the W-Pal ITS condition or the W-Pal AWE condition. The…
Descriptors: Intelligent Tutoring Systems, Automation, Writing Evaluation, Writing Assignments
Vlugter, P.; Knott, A.; McDonald, J.; Hall, C. – Computer Assisted Language Learning, 2009
We describe a computer assisted language learning (CALL) system that uses human-machine dialogue as its medium of interaction. The system was developed to help students learn the basics of the Maori language and was designed to accompany the introductory course in Maori running at the University of Otago. The student engages in a task-based…
Descriptors: College Students, Introductory Courses, Malayo Polynesian Languages, Pretests Posttests
Pechenizkiy, Mykola; Calders, Toon; Conati, Cristina; Ventura, Sebastian; Romero, Cristobal; Stamper, John – International Working Group on Educational Data Mining, 2011
The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions…
Descriptors: Academic Achievement, Logical Thinking, Profiles, Tutoring
Lane, H. Chad; VanLehn, Kurt – Computer Science Education, 2005
For beginning programmers, inadequate problem solving and planning skills are among the most salient of their weaknesses. In this paper, we test the efficacy of natural language tutoring to teach and scaffold acquisition of these skills. We describe ProPL (Pro-PELL), a dialogue-based intelligent tutoring system that elicits goal decompositions and…
Descriptors: Control Groups, Intelligent Tutoring Systems, Programming, Natural Language Processing