Article

Dynamically adjusting to learner's competencies and styles in an online technology course

Author:

Jack P. KrichenAuthors Info & Claims

SIGITE '05: Proceedings of the 6th conference on Information technology education

Pages 149 - 154

https://doi.org/10.1145/1095714.1095750

Published: 20 October 2005 Publication History

Abstract

This paper explores the process of designing and creating a course that is somewhat remedial in nature but is offered at the masters level to provide basic knowledge and experience in key information technology areas required for matriculation in a masters degree in this program. The course is useful to learners of varying levels of competencies in information technology, but whose skill set is not sufficient to enter the program directly because it automatically adjusts the delivery of instruction to the style and learning capability of the students. . Characteristics of adult learners and related theories of instructional design are considered in the development of this course. The capabilities that new learning technologies and standards (i.e. Sharable Content Relational Model (SCORM) and Learning Management Systems (LMS)) offer in the design and implementation of this course are also discussed.

References

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Carnegie Mellon - Learning Systems Architecture Lab. (2003, 2/28/2003). SCORM best practices guide for content developers. Carnegie Mellon - Learning Systems Architecture Lab. Retrieved December 18, 2003, from the World Wide Web: http://www.lsal.cmu.edu/lsal/expertise/projects/developersguide/developersguide/guide-v1p0-20030228.pdf

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IMS. (2003, March). IMS simple sequencing specification information and behavior model version 1.0 final specification. IMS Global Learning Consortium, Inc. Retrieved August 23, 2005, from the World Wide Web: http://www.imsglobal.org/simplesequencing/ssv1p0/imsss_infov1p0.html.

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Digital Library

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Smith, D. M., & Kolb, D. A. (1986). The user's guide for the learning-style inventory: A manual for teachers and trainers. Boston, MA: McBer & Company.

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Cited By

Berger FMüller W(2021)Back to Basics: Explainable AI for Adaptive Serious GamesSerious Games10.1007/978-3-030-88272-3_6(67-81)Online publication date: 5-Oct-2021
https://doi.org/10.1007/978-3-030-88272-3_6
Berger F(2012)Evaluating an implementation of an adaptive game-based learning architectureProceedings of the 20th international conference on User Modeling, Adaptation, and Personalization10.1007/978-3-642-31454-4_34(351-355)Online publication date: 16-Jul-2012
https://dl.acm.org/doi/10.1007/978-3-642-31454-4_34
Berger FMüller W(2009)Adaptivity in Game-Based LearningProceedings of the 2nd Joint International Conference on Interactive Digital Storytelling: Interactive Storytelling10.1007/978-3-642-10643-9_38(316-319)Online publication date: 21-Nov-2009
https://dl.acm.org/doi/10.1007/978-3-642-10643-9_38

Index Terms

Dynamically adjusting to learner's competencies and styles in an online technology course
1. Applied computing
  1. Law, social and behavioral sciences

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cover image ACM Conferences

SIGITE '05: Proceedings of the 6th conference on Information technology education

October 2005

402 pages

ISBN:1595932526

DOI:10.1145/1095714

General Chair:
Rob Friedman
New Jersey Institute of Technology, Newark, NJ

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 October 2005

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SIGITE05

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SIGITE05: ACM Special Interest Group for Information Technology Education Conference 2005

October 20 - 22, 2005

NJ, Newark, USA

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Overall Acceptance Rate 176 of 429 submissions, 41%

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Cited By

Berger FMüller W(2021)Back to Basics: Explainable AI for Adaptive Serious GamesSerious Games10.1007/978-3-030-88272-3_6(67-81)Online publication date: 5-Oct-2021
https://doi.org/10.1007/978-3-030-88272-3_6
Berger F(2012)Evaluating an implementation of an adaptive game-based learning architectureProceedings of the 20th international conference on User Modeling, Adaptation, and Personalization10.1007/978-3-642-31454-4_34(351-355)Online publication date: 16-Jul-2012
https://dl.acm.org/doi/10.1007/978-3-642-31454-4_34
Berger FMüller W(2009)Adaptivity in Game-Based LearningProceedings of the 2nd Joint International Conference on Interactive Digital Storytelling: Interactive Storytelling10.1007/978-3-642-10643-9_38(316-319)Online publication date: 21-Nov-2009
https://dl.acm.org/doi/10.1007/978-3-642-10643-9_38

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