Using knowledge space theory to compare expected and real knowledge spaces in learning stoichiometry

Segedinac, Milan; Horvat, Saša A.; Rodić, Dušica D.; Rončević, Tamara N.; Savić, Goran

doi:10.1039/c8rp00052b

Cited by 8 publications

(9 citation statements)

References 37 publications

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“…Even though some of them tend to reduce the involvement of experts to some extent (e.g., the one that decomposes the problems in the sets of motives), all of them require a substantial amount of manual work. Another disadvantage of such methods, identified in [11] is that knowledge spaces that experts expect, often do not fit the test data properly so it was concluded that the real knowledge space often differs from the expected one. Theory-driven techniques are also inappropriate for constructing large knowledge spaces.…”

Section: Knowledge Space Constructionmentioning

confidence: 99%

A neuroevolutionary method for knowledge space construction

et al. 2022

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In this paper we propose a novel method for the construction of knowledge spaces based on neuroevolution. The main advantage of the proposed approach is that it is more suitable for constructing large knowledge spaces than other traditional data-driven methods. The core idea of the method is that if knowledge states are considered as neurons in a neural network, the optimal topology of such a neural network is also the optimal knowledge space. To apply the neuroevolutionary method, a set of analogies between knowledge spaces and neural networks was established and described in this paper. This approach is evaluated in comparison with the minimized and corrected inductive item tree analysis, de facto standard algorithm for the data-driven knowledge space construction, and the comparison confirms the assumptions.

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Section: Knowledge Space Constructionmentioning

confidence: 99%

A neuroevolutionary method for knowledge space construction

et al. 2022

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“…In the literature, a variety of research methods have been conducted on the study of knowledge structure in science education. The methods include concept map (Adamov et al, 2009;Burrows & Mooring, 2015;Chiang et al, 2014), word association (Bahar & Tongac, 2009;Nakiboglu, 2008), phenomenological approach (Choi & Oh, 2021;Tóth & Ludányi, 2007), think-aloud interview (Ahmadian et al, 2019;King et al, 2022), multi-dimensional scaling (MDS) (Chiou & Anderson, 2010;Tilga et al, 2017), knowledge space theory (Segedinac et al, 2018), pathfinder network algorithm (Casas-Garcia & Luengo-Gonzalez, 2013), factor analysis , and reaction time technique .…”

Section: Knowledge Structure and Factor Analysismentioning

confidence: 99%

Applying Factor Analysis for Assessing Knowledge Structure of Students in Grade 10: The Subject of Redox Reaction

Tang

Zhu

Qian

2022

JBSE

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Redox reaction is an important concept in chemistry, and a well-organized knowledge structure of redox reaction is beneficial for concept learning. This study investigated the knowledge structure regarding redox reaction from 459 Grade 10 students. The pool of 15 redox reaction concepts was developed by content analysis, questionnaire survey, and interview. Six initial competing models with 15 concepts were identified via exploratory factor analysis (EFA) and paper-pencil test. Confirmatory factor analysis (CFA) was conducted to test and modify the six competing models according to the rating data of the students. As a result, six modified models fit the data well. However, the high inter-factor correlations indicate that the two- and three-factor models are the students' knowledge structures of redox reaction. The two-factor model is comprised of two distinct but correlated factors: the process of redox reaction and metrology. The three-factor model is comprised of three factors: the process of redox reaction, reaction ability, and metrology. The finding inflects the abstract relationships between the concepts related to redox reaction in students' minds. Keywords: redox reaction, chemistry education, knowledge structure, factor analysis

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“…For the validation of this procedure, linear regression analysis was used, correlating student achievement and applied mental effort as dependent variables with the numerical rating of the cognitive complexity of the problem as an independent variable. In addition to the statistical procedure for validating the method for assessing the cognitive complexity of stoichiometric tasks, this method was further validated by applying Knowledge Space Theory (Segedinac, Horvat, Rodić, Rončević, & Savić, 2018). Knowledge Space Theory enabled the fine differentiation of concepts and the identification of differences between the expected knowledge space, which was constructed based on the numerical rating of cognitive complexity, and the real knowledge space, which was constructed based on the students' achievements.…”

Section: Examination Of the Effectiveness Of Instructional Strategiesmentioning

confidence: 99%

The Development of Research in the Field of Chemistry Education at the University of Novi Sad since the Breakup of the Socialist Federal Republic of Yugoslavia

Segedinac

Rodić

Rončević

et al. 2020

CEPSj

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The first PhD thesis in the field of Chemistry Education at the Faculty of Sciences, University of Novi Sad, was defended in 1992. This can be regarded as the symbolic dawn of Chemistry Education as a scientific discipline in this region. After the official breakup of the Socialist Federal Republic of Yugoslavia, research that had started in the 1980s, and which was focused on the development of tools for assessing the quality and flexibility of student knowledge, was continued through the 1990s. This research included the application of computers to chemistry teaching, as well as the development of appropriate chemistry learning programmes. In the following period, research focused on the analysis of chemical teaching programmes in the Republic of Serbia, with a special emphasis on the possibility of including eco-chemical content in curricula. Accordingly, potentially efficient models were suggested. The most recent research has been focused on the investigation of the effectiveness of instructional strategies based on a systemic approach and a triplet model of content representation, using combined measures of students’ performance and mental effort. In this regard, tools for the efficient assessment of knowledge (systemic synthesis questions, context-based questions) have been developed along with tools for the efficient assessment of students’ misconceptions (multi-tier tests). Furthermore, in order to make teaching more effective, procedures for assessing the cognitive complexity of chemical problems have recently been developed and subsequently validated both statistically and by applying Knowledge Space Theory.

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Using knowledge space theory to compare expected and real knowledge spaces in learning stoichiometry

Cited by 8 publications

References 37 publications

A neuroevolutionary method for knowledge space construction

A neuroevolutionary method for knowledge space construction

Applying Factor Analysis for Assessing Knowledge Structure of Students in Grade 10: The Subject of Redox Reaction

The Development of Research in the Field of Chemistry Education at the University of Novi Sad since the Breakup of the Socialist Federal Republic of Yugoslavia

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