Knowledge States in the Learning of "Time": Comparison of Primary Six Pupils' from Different Types of Schools in Penang.

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Title: Knowledge States in the Learning of "Time": Comparison of Primary Six Pupils' from Different Types of Schools in Penang.
Authors: SIA, Carolyn1 c.sjling@gmail.com, Chap Sam LIM1
Source: Mathematics Enthusiast. Jan2020, Vol. 17 Issue 1, p7-31. 25p.
Subject Terms: *School children, *Students, *Primary schools, Artificial neural networks
Geographic Terms: Pinang
Abstract: The findings in this paper were a part of a bigger study which aimed to develop a cognitive diagnostic assessment [CDA] for primary mathematics learning of "Time". This paper aimed to discuss and compare the knowledge state of primary pupils from different types of schools in Penang. Knowledge state represented a pupil's mastery level on a defined set of attributes. These attributes were assessed by using a set of items and the responses were observed to find out a pupil's knowledge state. Two hundred and sixty-nine Primary Six pupils from 11 primary schools in Penang involved in the study. A set of CDA with 35 items consisting of four cognitive models were administered to the pupils. However, only three cognitive models were discussed in this paper. Students' responses were analysed by using Artificial Neural Network [ANN] to find the attribute probability of every pupil on each attribute. This probability was then classified and this set of classified attribute probability represented knowledge state of a pupil. Finding out the knowledge state of pupils helps teacher to investigate pupils' learning progress, identify pupils' misconception and thus make effective instructional decision. Results showed that Chinese Vernacular School pupils performed better than National School and Tamil Vernacular School pupils. Besides, the most common knowledge state in each cognitive model for each type of school was quite similar. The findings of this paper could be a preliminary step to demonstrate the usability and practicality of using CDA to obtain meaningful instructional inferences. [ABSTRACT FROM AUTHOR]
Copyright of Mathematics Enthusiast is the property of Prof. Bharath Sriraman and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Knowledge States in the Learning of "Time": Comparison of Primary Six Pupils' from Different Types of Schools in Penang.
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  Data: <searchLink fieldCode="JN" term="%22Mathematics+Enthusiast%22">Mathematics Enthusiast</searchLink>. Jan2020, Vol. 17 Issue 1, p7-31. 25p.
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  Data: *<searchLink fieldCode="DE" term="%22School+children%22">School children</searchLink><br />*<searchLink fieldCode="DE" term="%22Students%22">Students</searchLink><br />*<searchLink fieldCode="DE" term="%22Primary+schools%22">Primary schools</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink>
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– Name: Abstract
  Label: Abstract
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  Data: The findings in this paper were a part of a bigger study which aimed to develop a cognitive diagnostic assessment [CDA] for primary mathematics learning of "Time". This paper aimed to discuss and compare the knowledge state of primary pupils from different types of schools in Penang. Knowledge state represented a pupil's mastery level on a defined set of attributes. These attributes were assessed by using a set of items and the responses were observed to find out a pupil's knowledge state. Two hundred and sixty-nine Primary Six pupils from 11 primary schools in Penang involved in the study. A set of CDA with 35 items consisting of four cognitive models were administered to the pupils. However, only three cognitive models were discussed in this paper. Students' responses were analysed by using Artificial Neural Network [ANN] to find the attribute probability of every pupil on each attribute. This probability was then classified and this set of classified attribute probability represented knowledge state of a pupil. Finding out the knowledge state of pupils helps teacher to investigate pupils' learning progress, identify pupils' misconception and thus make effective instructional decision. Results showed that Chinese Vernacular School pupils performed better than National School and Tamil Vernacular School pupils. Besides, the most common knowledge state in each cognitive model for each type of school was quite similar. The findings of this paper could be a preliminary step to demonstrate the usability and practicality of using CDA to obtain meaningful instructional inferences. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Group: Ab
  Data: <i>Copyright of Mathematics Enthusiast is the property of Prof. Bharath Sriraman and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.54870/1551-3440.1478
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      – Code: eng
        Text: English
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      – SubjectFull: Artificial neural networks
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