Construct Validation of an Approach to Modeling Cognitive Structure of U.S. History Knowledge

Herl, Howard E.; Baker, Eva L.; Niemi, David

doi:10.1080/00220671.1996.9941206

Cited by 59 publications

(37 citation statements)

References 35 publications

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“…It can also be used to assess the effectiveness of learning by comparing the students' cognitive structures to those of instructors, domain experts, and even to the knowledge structures of other outstanding students (Acton et al 1994;Herl et al 1996;Jonassen 1987).…”

Section: Introductionmentioning

confidence: 99%

The mystery of cognitive structure and how we can detect it: tracking the development of cognitive structures over time

2009

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Many research studies have clearly demonstrated the importance of cognitive structures as the building blocks of meaningful learning and retention of instructional materials. Identifying the learners' cognitive structures will help instructors to organize materials, identify knowledge gaps, and relate new materials to existing slots or anchors within the learners' cognitive structures. The purpose of our empirical investigation is to track the development of cognitive structures over time. Accordingly, we demonstrate how various indicators derived from graph theory can be used for a precise description and analysis of cognitive structures. Our results revealed several patterns that helped us to better understand the construction and development of cognitive structures over time. We conclude by identifying applications of our approach for learning and instruction and proposing possibilities for the further development of our approach.

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Section: Introductionmentioning

confidence: 99%

The mystery of cognitive structure and how we can detect it: tracking the development of cognitive structures over time

2009

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“…Early attempts to establish the reliability and validity of knowledge mapping for assessment revealed poor correlations between mapping and other measures of learner achievement such as course grades and performance on standardized tests (Aidman & Egan, 1998;Shavelson et al, 1994), Data from recent studies, however, provide mounting evidence that knowledge maps are both reliable (Herl, Baker, & Niemi, 1996;Heil et al, 1999) and valid (McClure, Sonak, & Suen, 1999;Rice, Ryan, & Samson, 1998; …”

Section: Knowledge Map Validitymentioning

confidence: 99%

“…Results of MDS analyses have been used to create computer-generated, "implicit" knowledge maps (Aidman & Egan, 1998) that are compared to ones constructed by experts. Alternatively, MDS analyses of rating data have been directly compared against knowledge map scores (based on an expert map) to validate the assessment of the learners' cognitive structure (Herl et al, 1996). While the two approaches exemplify Trochim's (1999b) recommendation of contrasting knowledge mapping results with those obtained from another method to establish mapping validity, both involve the use of expert maps.…”

Section: Assessment Instrumentsmentioning

confidence: 99%

“…One promising strategy for observing the degree of homogeneity among learners in their cognitive structure is to have them rate the similarity or contras t between pairs of concepts, In the past few years, researchers have begun to combine the practice of concept ratings with knowledge mapping procedures in innovative ways for improving map construction as well as map assessment (Aidman & Egan, 1998;Herl et al, 1996;Trochim, Cook, & Setze, 1994). In some instances, ratings have been used to form similarity or proximity matrices that are then analyzed using multidimensional scaling (MDS) techniques.…”

Section: Assessment Instrumentsmentioning

confidence: 99%

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Knowledge Maps and Their Use in Computer-Based Collaborative Learning Environments

Kealy

2001

Journal of Educational Computing Research

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Abstract:Conceptual learning of 13 graduate students at a university in the southeastern United States was studied during a six-week course that employed the Internet for collaborative learning of online articles, Five groups were formed with each creating a knowledge map a diagram that graphically arranges and interconnects concepts to show their relationship--during the first and fifth week of the course. Multidimensional scaling (MDS) analysis was used to study the change in each group's mapping over time to determine the influence of a computer-based collaborative learning environment on conceptual understanding. MDS analysis was also used to compare a knowledge map and a similarity rating (of the same 10 concepts) completed by each student at the end of the course. Results of the first analysis indicated that, despite the collaborative nature of the learning environment, groups did not become more similar over time in their understanding of key concepts, However, the second analysis revealed common student perceptions about the dimensions that characterized the conceptual relationships involved, Importantly, this analysis provided evidence that knowledge maps are comparable to rating instruments, thereby supporting recent research claims that they are valid representations of conceptual knowledge. Prescriptions are made for the expanded role of MDS in collaborative knowledge mapping activities. Article:An important question that continues to interest educators is how to integrate sound instructional practices with educational technologies in ways that most effectively enhance student learning. Two responses to this question during the past decade have been the emergence of computer-based learning environments and computer-based learning tools. An example of the former is a computer-supported intentional learning environment (CSILE)-a network within which learners can collaboratively generate and share knowledge (Scardamelia & Bereiter, 1994).Computer-based learning tools, on the other hand, are designed to assist learners in their thinking and reasoning processes.

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“…In turn, Herl and colleagues [9] use a matching algorithm that includes several expert maps evaluating each learner's concept map. In their work two evaluation indicators are calculated: (a) stringent semantic content score on the basis of the exact relationships matches between learner's and expert's concept Incremental Improvement of the Evaluation Algorithm in the Concept Map Based Knowledge Assessment System 9 maps, and b) categorized semantic content score, when learner's defined relationship matches some set of possible relationships in the expert concept map.…”

Section: Related Workmentioning

confidence: 99%

Incremental Improvement of the Evaluation Algorithm in the Concept Map Based Knowledge Assessment System

Anohina

Viļķelis

Lukašenko

2009

INT J COMPUT COMMUN

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The paper is devoted to the knowledge assessment system that has been developed at the Department of Systems Theory and Design of Riga Technical University for the last four years. The system is based on concept maps that allow displaying the knowledge structure of a particular learner in the form of a graph. Teacher's created concept maps serve as a standard against which learner's concept maps are compared. However, it is not correct to compare teacher's and learners' concept maps by examining the exact equivalence of relationships in both maps, because people construct knowledge in different ways. Thus, an appropriate mechanism is needed for the flexible evaluation of learners' concept maps. The paper describes the algorithm implemented in the concept map based knowledge assessment system and its evolution through four prototypes of the system.

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Construct Validation of an Approach to Modeling Cognitive Structure of U.S. History Knowledge

Cited by 59 publications

References 35 publications

The mystery of cognitive structure and how we can detect it: tracking the development of cognitive structures over time

The mystery of cognitive structure and how we can detect it: tracking the development of cognitive structures over time

Knowledge Maps and Their Use in Computer-Based Collaborative Learning Environments

Incremental Improvement of the Evaluation Algorithm in the Concept Map Based Knowledge Assessment System

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