Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

To elicit or to tell: Does it matter

Chi, M and Jordan, P and Vanlehn, K and Litman, D (2009) To elicit or to tell: Does it matter. In: UNSPECIFIED.

[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)

Abstract

While high interactivity has been one of the main characteristics of one-on-one human tutoring, a great deal of controversy surrounds the issue of whether interactivity is indeed the key feature of tutorial dialogue that impacts students' learning results. There are two commonly held hypotheses regarding the issue: a widely-believed monotonic interactivity hypothesis and a better supported interaction plateau hypothesis. The former hypothesis predicts increasing in interactivity causes an increase in learning while the latter states that increasing interactivity yields increasing learning until it hits a plateau, and further increases in interactivity do not cause noticeably increase in learning. In this study, we proposed the tactical interaction hypothesis which predicts beyond a certain level of interactivity, further increases in interactivity do not cause increase in learning unless they are guided by effective tutorial tactics. Overall our results support this hypothesis. However, finding effective tactics is not easy. This paper sheds some light on how to apply Reinforcement Learning to derive effective tutorial tactics. © 2009 The authors and IOS Press. All rights reserved.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Chi, M
Jordan, Ppjordan@pitt.eduPJORDAN
Vanlehn, K
Litman, Ddlitman@pitt.eduDLITMAN
Centers: University Centers > Learning Research and Development Center (LRDC)
Date: 1 January 2009
Date Type: Publication
Journal or Publication Title: Frontiers in Artificial Intelligence and Applications
Volume: 200
Number: 1
Page Range: 197 - 204
Event Type: Conference
DOI or Unique Handle: 10.3233/978-1-60750-028-5-197
Schools and Programs: Dietrich School of Arts and Sciences > Computer Science
Dietrich School of Arts and Sciences > Intelligent Systems
Refereed: Yes
ISBN: 9781607500285
ISSN: 0922-6389
Date Deposited: 23 Sep 2014 02:40
Last Modified: 09 Oct 2020 12:55
URI: http://d-scholarship.pitt.edu/id/eprint/22965

Metrics

Monthly Views for the past 3 years

Plum Analytics

Altmetric.com


Actions (login required)

View Item View Item