Modeling and intervening across time in scientific inquiry exploratory learning environment

This article aims at discussing how Dynamic Decision Network (DDN) can be employed to tackle the challenges in modeling temporally variable scientific inquiry skills and provision of adaptive pedagogical interventions in INQPRO, a scientific inquiry exploratory learning environment for learning O�...

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Main Authors: Ting, Choo Yee, Phon-Amnuaisuk, Somnuk, Chong, Yen Kuan
Format: Article
Published: International Forum of Educational Technology & Society 2008
Subjects:
Online Access:http://shdl.mmu.edu.my/2817/
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author Ting, Choo Yee
Phon-Amnuaisuk, Somnuk
Chong, Yen Kuan
author_facet Ting, Choo Yee
Phon-Amnuaisuk, Somnuk
Chong, Yen Kuan
author_sort Ting, Choo Yee
building MMU Institutional Repository
collection Online Access
description This article aims at discussing how Dynamic Decision Network (DDN) can be employed to tackle the challenges in modeling temporally variable scientific inquiry skills and provision of adaptive pedagogical interventions in INQPRO, a scientific inquiry exploratory learning environment for learning O'level Physics. We begin with an overview of INQPRO and a highlight of the computer algorithm as well as the design of our proposed DDN model. We then present an instance of interactions with INQPRO to describe how the proposed model can be generated dynamically by aggregating different INQPRO Graphical User Interfaces (GUIs) in real-time basis to perform probabilistic assessments of the two scientific inquiry skills (Hypothesis Formulation. and Variable Identification zeta). In this study, we carried out a two-phase empirical evaluation to investigate the performance of the proposed DDN model in categorizing different groups of learners. The performance of the proposed DDN model is identified by its matching accuracies elicited from a total of 6 domain experts and 77 learners who participated in both evaluation phases. Based on the empirical results, we summarized that the proposed DDN model is practically sound as it has demonstrated acceptable estimation accuracies with reference to the classification results obtained from the pretest, posttest, and from domain experts.
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spelling mmu-28172020-12-29T18:43:22Z http://shdl.mmu.edu.my/2817/ Modeling and intervening across time in scientific inquiry exploratory learning environment Ting, Choo Yee Phon-Amnuaisuk, Somnuk Chong, Yen Kuan T Technology (General) QA75.5-76.95 Electronic computers. Computer science This article aims at discussing how Dynamic Decision Network (DDN) can be employed to tackle the challenges in modeling temporally variable scientific inquiry skills and provision of adaptive pedagogical interventions in INQPRO, a scientific inquiry exploratory learning environment for learning O'level Physics. We begin with an overview of INQPRO and a highlight of the computer algorithm as well as the design of our proposed DDN model. We then present an instance of interactions with INQPRO to describe how the proposed model can be generated dynamically by aggregating different INQPRO Graphical User Interfaces (GUIs) in real-time basis to perform probabilistic assessments of the two scientific inquiry skills (Hypothesis Formulation. and Variable Identification zeta). In this study, we carried out a two-phase empirical evaluation to investigate the performance of the proposed DDN model in categorizing different groups of learners. The performance of the proposed DDN model is identified by its matching accuracies elicited from a total of 6 domain experts and 77 learners who participated in both evaluation phases. Based on the empirical results, we summarized that the proposed DDN model is practically sound as it has demonstrated acceptable estimation accuracies with reference to the classification results obtained from the pretest, posttest, and from domain experts. International Forum of Educational Technology & Society 2008 Article NonPeerReviewed Ting, Choo Yee and Phon-Amnuaisuk, Somnuk and Chong, Yen Kuan (2008) Modeling and intervening across time in scientific inquiry exploratory learning environment. Educational Technology & Society, 11 (3). pp. 239-258. ISSN 1436-4522, 1176-3647 https://eric.ed.gov/?id=EJ814128
spellingShingle T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
Ting, Choo Yee
Phon-Amnuaisuk, Somnuk
Chong, Yen Kuan
Modeling and intervening across time in scientific inquiry exploratory learning environment
title Modeling and intervening across time in scientific inquiry exploratory learning environment
title_full Modeling and intervening across time in scientific inquiry exploratory learning environment
title_fullStr Modeling and intervening across time in scientific inquiry exploratory learning environment
title_full_unstemmed Modeling and intervening across time in scientific inquiry exploratory learning environment
title_short Modeling and intervening across time in scientific inquiry exploratory learning environment
title_sort modeling and intervening across time in scientific inquiry exploratory learning environment
topic T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/2817/
http://shdl.mmu.edu.my/2817/