Theory-based knowledge modeling in a subdomain of elementary algebra

2001 ◽  
Vol 209 (3) ◽  
pp. 277-315 ◽  
Author(s):  
Klaus Korossy ◽  
Theo Held
Keyword(s):  
Knowledge Structure ◽  
Knowledge Structures ◽  
Subsequent Paper ◽  
Large Set ◽  
Knowledge Modeling ◽  
Knowledge Domain ◽  
Elementary Algebra ◽  
Empirical Examination ◽  
Tree Analysis ◽  
Data Analytic

Summary. The knowledge structures theory has been developing highly efficient computer-based procedures for the assessment of knowledge. However, a crucial precondition of a practical application of these assessment procedures in some knowledge domain is the establishment of a psychologically valid knowledge structure capturing the solvability dependencies among items of the domain. Several approaches for establishing a knowledge structure have been developed - each with its benefits and drawbacks. In an earlier paper ( Held and Korossy, 1998 ) we contrasted an a-priori structure generated by an expert with an a-posteriori structure generated by a data-analytic method (the Item Tree Analysis) and discussed the possible contribution of data-analytic methods (such as the Item Tree Analysis) to an integrated methodology of establishing well-founded solvability structures on item sets. The current investigation takes up this line of research. Based on a large set of 21 carefully constructed problems, a theory-based knowledge modeling of a subdomain of elementary algebra has been developed and empirically examined. Moreover, the sample of observed response patterns has been taken as input for a data-analytic procedure (the Item Tree Analysis). The comparison of the theory-based knowledge structure with the data-analytically generated structure provides convincing arguments for the theory-based construction of knowledge structures. The present paper describes in detail the theoretical modeling of surmised solution dependencies and the results of the empirical examination of the model. A subsequent paper will present the aspects of applying the Item Tree Analysis to the empirical data.

Skills and fuzzy knowledge structures

2021 ◽  
pp. 1-17
Author(s):  
Yinfeng Zhou ◽  
Jinjin Li ◽  
Hongkun Wang ◽  
Wen Sun
Keyword(s):  
Adaptive Learning ◽  
Knowledge Structure ◽  
Knowledge Structures ◽  
Knowledge Domain ◽  
Specific Knowledge ◽  
Knowledge Domains ◽  
Research Problems ◽  
Learning Paths ◽  
Future Learning ◽  
Fuzzy Knowledge

In knowledge space theory (KST), knowledge structure is an effective feature to evaluate individuals’ knowledge and guide future learning. How to construct knowledge structures is one of the key research problems in KST. At present, the knowledge structure has been generalized to the polytomous knowledge structure. This article mainly focuses on the special polytomous knowledge structures delineated by Skills, which are called fuzzy knowledge structures. We consider how to construct fuzzy knowledge structures based on the relationship between items and skills, and how to find the learning paths for specific knowledge domains. First, we construct knowledge structures in four models, which are the conjunctive model of skill maps, the disjunctive and conjunctive models of fuzzy skill maps, and the competency model of fuzzy skill multimaps. Second, we assess individuals’ skills and find the learning paths for the specific knowledge domains in the first three models. Finding the learning paths for a specific knowledge domain can guide learning and improve the learning efficiency of individuals. Finally, we analyze some data sets to show that the algorithms proposed are effective and applicable. These works can be applied to adaptive learning systems, which bring great convenience for assessing individuals’ knowledge and guiding future learning.

Effects of Stories and Checklist Decision Aids on Knowledge Structure Development and Auditor Judgment

2017 ◽  
Vol 32 (2) ◽  
pp. 1-24 ◽  
Author(s):  
James L. Bierstaker ◽  
Denise Hanes-Downey ◽  
Jacob M. Rose ◽  
Jay C. Thibodeau
Keyword(s):  
Knowledge Management ◽  
Decision Aids ◽  
Knowledge Structure ◽  
Knowledge Structures ◽  
Management Systems ◽  
Professional Judgment ◽  
Structure Development ◽  
Auditor Judgment ◽  
Audit Firms ◽  
Training Materials

ABSTRACT The purpose of this paper is to compare the usefulness of a story versus traditional checklist decision aids for enhancing knowledge structure development and for improving the judgments of auditors related to fraud risks. The results from the first experiment indicate that novice participants who read stories develop knowledge structures that more closely resemble the knowledge structures of experts than do participants who read checklists. The second experiment reveals that auditors who read stories make judgments more like experts than do auditors who use checklists. The findings demonstrate that stories may have the capacity to train auditors and improve their judgments. Audit firms constantly seek methods to improve auditors' knowledge and judgments, and our findings suggest opportunities for firms to employ fraud stories to enhance knowledge of fraud and improve professional judgment. This study's results hold important implications for the design of training materials, decision aids, and knowledge management systems.

The Impact of Social Capital, Managerial Human Capital and Managerial Knowledge Structure on Firm Performance

2019 ◽  
Vol 10 (3) ◽  
pp. 95-113
Author(s):  
Abdulkareem Salameh Awwad ◽  
Mamoun Nadim Akroush ◽  
Majdy Issa Zuriekat ◽  
Yassir Yahya Al Masoudi
Keyword(s):  
Social Capital ◽  
Human Capital ◽  
Firm Performance ◽  
Structural Equation ◽  
Knowledge Structure ◽  
Knowledge Structures ◽  
Equation Modeling ◽  
Telecommunications Sector ◽  
Managerial Knowledge ◽  
The Impact

This article aims to examine the relationships between external and internal social capital, managerial human capital, and managerial knowledge structures, respectively. It also examines the effect of managerial human capital and managerial knowledge structures on firm performance in the telecommunications sector in Jordan. A questionnaire was distributed to 250 managers in the telecommunications sector in Jordan. Utilizing structural equation modeling, it was found that external social capital has a positive significant effect on internal social capital and managerial human capital. Internal social capital has positively and significantly affected managerial knowledge structures. Furthermore, both managerial human capital and managerial knowledge structure had affected firm performance positively. As technology is expanding in this sector, relevant knowledge and information is becoming a source of competitive advantage, thus managers in this sector should build beneficial ties that might enhance human resources' capabilities that benefit the decision-making processes.

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

2018 ◽  
Vol 19 (3) ◽  
pp. 670-680
Author(s):  
M. T. Segedinac ◽  
S. Horvat ◽  
D. D. Rodić ◽  
T. N. Rončević ◽  
G. Savić
Keyword(s):  
Cognitive Complexity ◽  
Knowledge Structure ◽  
Space Theory ◽  
Knowledge Space ◽  
Knowledge Space Theory ◽  
The Real ◽  
Knowledge Spaces ◽  
Problem Solving Process ◽  
Constructing Knowledge ◽  
Data Analytic

This paper proposes a novel application of knowledge space theory for identifying discrepancies between the knowledge structure that experts expect students to have and the real knowledge structure that students demonstrate on tests. The proposed approach combines two methods of constructing knowledge spaces. The expected knowledge space is constructed by analysing the problem-solving process, while the real knowledge space is identified by applying a data-analytic method. These two knowledge spaces are compared for graph difference and the discrepancies between the two are analysed. In this paper, the proposed approach is applied to the domain of stoichiometry. Although there was a decent agreement between expected and real knowledge spaces, a number of relations that were not present in the expected one appeared in the real knowledge space. The obtained results led to a general conclusion for teaching stoichiometry and pointed to some potential improvements in the existing methods for evaluating cognitive complexity.

When Critical Knowledge Is Most Critical

2011 ◽  
Vol 42 (6) ◽  
pp. 669-699 ◽  
Author(s):  
Siyuan Huang ◽  
Jonathon N. Cummings
Keyword(s):  
Team Performance ◽  
Negative Relationship ◽  
Knowledge Structure ◽  
Knowledge Structures ◽  
Multinational Organization ◽  
Know How ◽  
Critical Knowledge ◽  
Group Research ◽  
Single Person ◽  
Knowledge Intensive

Knowledge-intensive teams rely on the task-relevant knowledge held by members to perform effectively. In this article, we focus on critical knowledge, defined as the most influential information, know-how, or feedback that contributes directly to task outcomes. From a social network perspective, the critical knowledge structure in a team can be defined by who shares critical knowledge with whom. In a highly centralized critical knowledge structure, everyone shares critical knowledge with a single person on the team. Alternatively, in a highly decentralized critical knowledge structure, critical knowledge is shared evenly across members of the team. Drawing from small group research and network theory, we theorize about critical knowledge structures in teams and make hypotheses regarding the consequences of centralized critical knowledge structures for executive-rated team performance. Data analyses from a field study of 177 teams in a multinational organization indicate support for our theory that centralized critical knowledge structures are negatively related to executive-rated team performance. Furthermore, the negative relationship is exacerbated when (a) business unit diversity on the team is greater, and (b) critical knowledge shared in the team is exploratory rather than exploitative.

Designing Decision Aids to Promote the Development of Expertise

2012 ◽  
Vol 26 (1) ◽  
pp. 7-34 ◽  
Author(s):  
Jacob M. Rose ◽  
Britton A. McKay ◽  
Carolyn Strand Norman ◽  
Anna M. Rose
Keyword(s):  
Decision Aid ◽  
Expert Knowledge ◽  
Decision Aids ◽  
Knowledge Structure ◽  
Knowledge Structures ◽  
Risk Assessments ◽  
Accounting Students ◽  
Fraud Risk ◽  
Expert Knowledge Structures ◽  
Novice Users

ABSTRACT We investigate whether the use of decision aids that integrate experts' knowledge structures into their designs can effectively promote the acquisition of expert-like knowledge and improve future judgments. Results of two laboratory experiments (one involving 115 senior accounting students and one involving 78 master of accounting students) indicate that: (1) novice users of a decision aid that has an expert knowledge structure embedded into its interface make complex fraud risk assessments that are more similar to experts' risk assessments than do users of aids without expert knowledge structures; (2) users of a decision aid that has an expert knowledge structure embedded into its interface develop knowledge structures that are more similar to the knowledge structures of experts than do users of aids without expert knowledge structures; (3) knowledge structures mediate the relationship between decision aid design and judgment performance; and (4) novices develop expertise through decision aid use even when they are not instructed to learn from the decision aid.

Manage of Basic Nursing to Construct Knowledge Structure

2014 ◽  
Vol 1079-1080 ◽  
pp. 686-689
Author(s):  
Jui Chiao Tseng
Keyword(s):  
Structure Analysis ◽  
Classical Test Theory ◽  
Knowledge Structure ◽  
Educational Measurement ◽  
Knowledge Structures ◽  
Test Theory ◽  
Remedial Instruction ◽  
Integrated Method ◽  
Classical Test ◽  
Testing Data

This study is to provide an integrated method and algorithm for knowledge structure analysis and cognition diagnosis. Most researchers of educational measurement analyzed testing data from paper-pencil test by classical test theory (CTT) or interviewed with students in order to acquire students’ knowledge structures. Moreover, it is considered that knowledge structures are important for instruction. Information of knowledge structures is useful because it will be helpful for cognition diagnosis so that remedial instruction becomes feasible.

Where do high-impact ideas come from? The interplay between the cumulative knowledge structures and search strategies of researchers

2017 ◽  
Vol 55 (5) ◽  
pp. 808-825 ◽  
Author(s):  
Le Wang ◽  
Jun Lin ◽  
Jie Yan ◽  
Wentian Cui
Keyword(s):  
Local Search ◽  
Knowledge Structure ◽  
Search Strategies ◽  
High Impact ◽  
Knowledge Structures ◽  
Short Term ◽  
Content Type ◽  
Search Behaviors ◽  
Cumulative Knowledge ◽  
Knowledge Depth

Purpose The purpose of this paper is to investigate the combined effects of different modalities of long-term knowledge accumulation and short-term knowledge searching on the generation of high-impact ideas. The authors aim at providing useful conclusions for academic scholars. Design/methodology/approach Two dimensions of the cumulative knowledge structures of researchers are measured: knowledge depth and knowledge breadth. The search strategies employed by researchers are classified as local search and distant search. The authors use researchers’ historical publications to measure cumulative knowledge structures. References contained in these publications serve as an indicator of knowledge searching behaviors and are used to measure search strategies. Highly cited papers with random-but-matched papers from the same journal published in the same year are adopted to test the hypotheses. Findings The knowledge depth of researchers positively predicts the generation of high-impact ideas. Knowledge breadth has a bell-shaped relationship to the generation of high-impact ideas. Two instances of “strategic fit” between the knowledge structures and search strategies of researchers are identified; namely, knowledge breadth combines most effectively with local search, and knowledge depth combines most effectively with distant search in generating high-impact ideas. Research limitations/implications Using article references to measure authors’ knowledge search behaviors may lead to biases. Future research should perform a survey to obtain a comprehensive understanding of the knowledge search behaviors of scholars. Practical implications A “T-shaped” knowledge structure in the long run is recommended for maximal generation of high-impact ideas. Researchers who have not adopted this optimal knowledge structure can employ a matched search strategy to leverage their existing knowledge structures. Originality/value This paper is among the first to examine the interactive effects between the cumulative knowledge structures and short-term knowledge searching strategies of researchers. The authors have enriched the exploration and exploitation theory by adding the dimension of time into the analysis.

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