Empirical usage metadata in learning objects

Gwen C Nugent, Kevin A Kupzyk, S. A. Riley, L. D. Miller, Jesse Hostetler, Leen-Kiat Soh, Ashok K Samal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

The iLOG Project (Intelligent Learning Object Guide) is designed to augment multimedia learning objects with information about (1) how a learning object has been used, (2) how it has impacted instruction and learning, and (3) how it should be used. The goal of the project is to generate metadata tags from data collected while students interact with learning objects; these metadata tags can then be used to help teachers identify learning objects that match the educational and experiential backgrounds of their students. The project involves the development of an agent-based intelligent system for tracking student interaction with learning objects, in tandem with an extensive learning research agenda. This paper provides an overview of this NSF-funded project, focusing on the instructional approach and research on varying levels of active learning and feedback. Using a randomized design and a hierarchical linear modeling framework, research showed that the active learning conditions resulted in significantly higher student learning. The elaborative feedback results approached (p = .056), but did not reach, the established significance criteria of alpha = .05. Both active learning conditions and one of the elaborative feedback conditions resulted in significantly higher content assessment scores compared to a control group.

Original languageEnglish (US)
Title of host publication39th Annual Frontiers in Education Conference
Subtitle of host publicationImagining and Engineering Future CSET Education, FIE 2009
DOIs
StatePublished - Dec 1 2009
Event39th Annual Frontiers in Education Conference: Imagining and Engineering Future CSET Education, FIE 2009 - San Antonio, TX, United States
Duration: Oct 18 2009Oct 21 2009

Publication series

NameProceedings - Frontiers in Education Conference, FIE
ISSN (Print)1539-4565

Other

Other39th Annual Frontiers in Education Conference: Imagining and Engineering Future CSET Education, FIE 2009
CountryUnited States
CitySan Antonio, TX
Period10/18/0910/21/09

Fingerprint

Metadata
Students
Feedback
learning
Intelligent systems
learning prerequisite
student
Problem-Based Learning
multimedia
instruction
teacher
interaction

Keywords

  • Active learning
  • Computer science education
  • Feedback
  • Learning objects

ASJC Scopus subject areas

  • Software
  • Education
  • Computer Science Applications

Cite this

Nugent, G. C., Kupzyk, K. A., Riley, S. A., Miller, L. D., Hostetler, J., Soh, L-K., & Samal, A. K. (2009). Empirical usage metadata in learning objects. In 39th Annual Frontiers in Education Conference: Imagining and Engineering Future CSET Education, FIE 2009 [5350779] (Proceedings - Frontiers in Education Conference, FIE). https://doi.org/10.1109/FIE.2009.5350779

Empirical usage metadata in learning objects. / Nugent, Gwen C; Kupzyk, Kevin A; Riley, S. A.; Miller, L. D.; Hostetler, Jesse; Soh, Leen-Kiat; Samal, Ashok K.

39th Annual Frontiers in Education Conference: Imagining and Engineering Future CSET Education, FIE 2009. 2009. 5350779 (Proceedings - Frontiers in Education Conference, FIE).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nugent, GC, Kupzyk, KA, Riley, SA, Miller, LD, Hostetler, J, Soh, L-K & Samal, AK 2009, Empirical usage metadata in learning objects. in 39th Annual Frontiers in Education Conference: Imagining and Engineering Future CSET Education, FIE 2009., 5350779, Proceedings - Frontiers in Education Conference, FIE, 39th Annual Frontiers in Education Conference: Imagining and Engineering Future CSET Education, FIE 2009, San Antonio, TX, United States, 10/18/09. https://doi.org/10.1109/FIE.2009.5350779
Nugent GC, Kupzyk KA, Riley SA, Miller LD, Hostetler J, Soh L-K et al. Empirical usage metadata in learning objects. In 39th Annual Frontiers in Education Conference: Imagining and Engineering Future CSET Education, FIE 2009. 2009. 5350779. (Proceedings - Frontiers in Education Conference, FIE). https://doi.org/10.1109/FIE.2009.5350779
Nugent, Gwen C ; Kupzyk, Kevin A ; Riley, S. A. ; Miller, L. D. ; Hostetler, Jesse ; Soh, Leen-Kiat ; Samal, Ashok K. / Empirical usage metadata in learning objects. 39th Annual Frontiers in Education Conference: Imagining and Engineering Future CSET Education, FIE 2009. 2009. (Proceedings - Frontiers in Education Conference, FIE).
@inproceedings{be8f87a2969a4d04992360e037d13f83,
title = "Empirical usage metadata in learning objects",
abstract = "The iLOG Project (Intelligent Learning Object Guide) is designed to augment multimedia learning objects with information about (1) how a learning object has been used, (2) how it has impacted instruction and learning, and (3) how it should be used. The goal of the project is to generate metadata tags from data collected while students interact with learning objects; these metadata tags can then be used to help teachers identify learning objects that match the educational and experiential backgrounds of their students. The project involves the development of an agent-based intelligent system for tracking student interaction with learning objects, in tandem with an extensive learning research agenda. This paper provides an overview of this NSF-funded project, focusing on the instructional approach and research on varying levels of active learning and feedback. Using a randomized design and a hierarchical linear modeling framework, research showed that the active learning conditions resulted in significantly higher student learning. The elaborative feedback results approached (p = .056), but did not reach, the established significance criteria of alpha = .05. Both active learning conditions and one of the elaborative feedback conditions resulted in significantly higher content assessment scores compared to a control group.",
keywords = "Active learning, Computer science education, Feedback, Learning objects",
author = "Nugent, {Gwen C} and Kupzyk, {Kevin A} and Riley, {S. A.} and Miller, {L. D.} and Jesse Hostetler and Leen-Kiat Soh and Samal, {Ashok K}",
year = "2009",
month = "12",
day = "1",
doi = "10.1109/FIE.2009.5350779",
language = "English (US)",
isbn = "9781424447152",
series = "Proceedings - Frontiers in Education Conference, FIE",
booktitle = "39th Annual Frontiers in Education Conference",

}

TY - GEN

T1 - Empirical usage metadata in learning objects

AU - Nugent, Gwen C

AU - Kupzyk, Kevin A

AU - Riley, S. A.

AU - Miller, L. D.

AU - Hostetler, Jesse

AU - Soh, Leen-Kiat

AU - Samal, Ashok K

PY - 2009/12/1

Y1 - 2009/12/1

N2 - The iLOG Project (Intelligent Learning Object Guide) is designed to augment multimedia learning objects with information about (1) how a learning object has been used, (2) how it has impacted instruction and learning, and (3) how it should be used. The goal of the project is to generate metadata tags from data collected while students interact with learning objects; these metadata tags can then be used to help teachers identify learning objects that match the educational and experiential backgrounds of their students. The project involves the development of an agent-based intelligent system for tracking student interaction with learning objects, in tandem with an extensive learning research agenda. This paper provides an overview of this NSF-funded project, focusing on the instructional approach and research on varying levels of active learning and feedback. Using a randomized design and a hierarchical linear modeling framework, research showed that the active learning conditions resulted in significantly higher student learning. The elaborative feedback results approached (p = .056), but did not reach, the established significance criteria of alpha = .05. Both active learning conditions and one of the elaborative feedback conditions resulted in significantly higher content assessment scores compared to a control group.

AB - The iLOG Project (Intelligent Learning Object Guide) is designed to augment multimedia learning objects with information about (1) how a learning object has been used, (2) how it has impacted instruction and learning, and (3) how it should be used. The goal of the project is to generate metadata tags from data collected while students interact with learning objects; these metadata tags can then be used to help teachers identify learning objects that match the educational and experiential backgrounds of their students. The project involves the development of an agent-based intelligent system for tracking student interaction with learning objects, in tandem with an extensive learning research agenda. This paper provides an overview of this NSF-funded project, focusing on the instructional approach and research on varying levels of active learning and feedback. Using a randomized design and a hierarchical linear modeling framework, research showed that the active learning conditions resulted in significantly higher student learning. The elaborative feedback results approached (p = .056), but did not reach, the established significance criteria of alpha = .05. Both active learning conditions and one of the elaborative feedback conditions resulted in significantly higher content assessment scores compared to a control group.

KW - Active learning

KW - Computer science education

KW - Feedback

KW - Learning objects

UR - http://www.scopus.com/inward/record.url?scp=77951469890&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77951469890&partnerID=8YFLogxK

U2 - 10.1109/FIE.2009.5350779

DO - 10.1109/FIE.2009.5350779

M3 - Conference contribution

SN - 9781424447152

T3 - Proceedings - Frontiers in Education Conference, FIE

BT - 39th Annual Frontiers in Education Conference

ER -