Comparing learning from observing and from human tutoring.

2014 ◽  
Vol 106 (1) ◽  
pp. 69-85 ◽  
Author(s):  
Kasia Muldner ◽  
Rachel Lam ◽  
Michelene T. H. Chi
Keyword(s):  
Human Tutoring

Evaluation of an Automated Reading Tutor That Listens: Comparison to Human Tutoring and Classroom Instruction

2003 ◽  
Vol 29 (1) ◽  
pp. 61-117 ◽  
Author(s):  
Jack Mostow ◽  
Greg Aist ◽  
Paul Burkhead ◽  
Albert Corbett ◽  
Andrew Cuneo ◽  
...  
Keyword(s):  
Classroom Instruction ◽  
Human Tutoring ◽  
Reading Tutor

Discourse cohesion in text and tutorial dialogue

2007 ◽  
Vol 15 (3) ◽  
pp. 199-213 ◽  
Author(s):  
Arthur C. Graesser ◽  
Moongee Jeon ◽  
Yan Yan ◽  
Zhiqiang Cai
Keyword(s):  
College Students ◽  
Natural Language ◽  
Semantic Similarity ◽  
Software Tool ◽  
Pedagogical Agent ◽  
Newtonian Physics ◽  
Tutorial Dialogue ◽  
Logical Operators ◽  
Different Types ◽  
Human Tutoring

Discourse cohesion is presumably an important facilitator of comprehension when individuals read texts and hold conversations. This study investigated components of cohesion and language in different types of discourse about Newtonian physics: A textbook, textoids written by experimental psychologists, naturalistic tutorial dialoguebetween expert human tutors and college students, andAutoTutor tutorial dialogue between a computer tutor and students (AutoTutor is an animated pedagogical agent that helps students learn about physics by holding conversations in natural language). We analyzed the four types of discourse with Coh-Metrix, a software tool that measures discourse on different components of cohesion, language, and readability. The cohesion indices included co-reference, syntactic and semantic similarity, causal cohesion, incidence of cohesion signals (e.g., connectives, logical operators), and many other measures. Cohesion data were quite similar for the two forms of discourse in expository monologue (textbooks and textoids) and for the two types of tutorial dialogue (i.e., students interacting with human tutors and AutoTutor), but very different between the discourse of expository monologue and tutorial dialogue. Coh-Metrix was also able to detect subtle differences in the language and discourse of AutoTutor versus human tutoring.

Why Do Only Some Events Cause Learning During Human Tutoring?

2003 ◽  
Vol 21 (3) ◽  
pp. 209-249 ◽  
Author(s):  
Kurt VanLehn ◽  
Stephanie Siler ◽  
Charles Murray ◽  
Takashi Yamauchi ◽  
William B. Baggett
Keyword(s):  
Human Tutoring

Using Intelligent Tutoring Technologies to Enhance Online Learning Environments

2011 ◽  
pp. 2246-2251
Author(s):  
Kausalai Kay Wijekumar
Keyword(s):  
Online Learning ◽  
Distance Learning ◽  
Learning Environments ◽  
Intelligent Tutoring Systems ◽  
Interactive Learning ◽  
Intelligent Tutoring ◽  
Interactive Learning Environments ◽  
Group Instruction ◽  
Tutoring Systems ◽  
Human Tutoring

Online and distance learning environments have changed dramatically over the last 20 years and are now sophisticated interactive learning environments. However, much more improvement is possible, and some of that improvement might come from mining some of the technologies developed as part of intelligent tutoring systems. Intelligent tutoring systems combine the best of human tutoring by capturing one on one tutoring interactions between a teacher and student on all topics for a learning module and converting them to a computerized version. The computerized version is designed to gauge the understanding of the student and adapt the instruction, modeling, hints, interactions, and activities to particular students. The systems are usually designed to assess the student’s learning continuously and scaffold the learning of the student. Ideally, these interactions will mimic human tutoring that has been shown to significantly improve learning beyond large group instruction.

Human Tutoring Dialogues and their Analysis

2021 ◽  
pp. 51-84
Author(s):  
Stellan Ohlsson ◽  
Mehrdad Alizadeh ◽  
Lin Chen ◽  
Rachel Harsley
Keyword(s):  
Human Tutoring
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