Problems of Repertory Grid Analysis and a Cluster Analysis Solution

1979 ◽  
Vol 134 (5) ◽  
pp. 516-521 ◽  
Author(s):  
Peter Goodge
Keyword(s):  
Cluster Analysis ◽  
Comparative Analysis ◽  
Repertory Grid ◽  
Difficult Problem ◽  
Grid Analysis

SummaryStatistical and requirement difficulties encountered with existing methods of Repertory Grid Analysis are considered. A simple purpose-built method of Cluster Analysis is outlined, and its extension to the difficult problem of comparative analysis described.

Unordinary: An evaluation of lecture-free activities using a repertory grid

2021 ◽  
pp. 030641902110583
Author(s):  
Libby (Elizabeth) Osgood
Keyword(s):  
Cluster Analysis ◽  
Knowledge Acquisition ◽  
Repertory Grid ◽  
Creative Expression ◽  
Descriptive Statistics ◽  
Personal Constructs ◽  
Grid Analysis ◽  
Activity Evaluation ◽  
Directed Learning ◽  
Break Up

Lecture-free activities afford students with an engaging approach to knowledge acquisition and integration. When peppered throughout a course, experiential activities inject spontaneity, break up familiar patterns, and empower students to take responsibility of their learning. For an instructor, iteration is required to develop effective lecture-free engineering activities, necessitating thoughtful evaluation. The paper adopts Kelly's personal constructs theory, using repertory grid analysis to consider the effectiveness of six unordinary, lecture-free activities. Through a structured comparison of activities, 29 constructs were elicited with inherently subjective, dichotomous poles. The grid was populated ranking each activity between the poles of each construct such as directed learning or creative expression. Using a cluster analysis and descriptive statistics, various themes emerged revealing the author's preference, and connections between seemingly unrelated constructs such as how summative actives use the entire building whereas formative activities are in the classroom. Recommendations are made to generalize the tool to aid instructors in activity evaluation and development through understanding and challenging existing patterns.

Analysis method ofrecruitment needs for the regional economy: Occupational section

2017 ◽  
pp. 142-149 ◽  
Author(s):  
E. Pitukhin ◽  
S. Shabaeva ◽  
I. Stepus ◽  
D. Moroz
Keyword(s):  
Cluster Analysis ◽  
Labor Market ◽  
Comparative Analysis ◽  
Regional Economy ◽  
Dimensional Space ◽  
Analysis Method ◽  
Scalar Form ◽  
Regional Labor Market ◽  
Regional Labor ◽  
Regional Specificity

The paper deals with comparative analysis of occupations in the regional labor market. Occupation is treated as a multi-dimensional space of characte- ristics, whereas a scalar form of a characteristic makes it possible to carry out a comparative analysis of occupations. Using cluster analysis of a pilot region indicators five meaningfully interpretable clusters of occupations were identified, reflecting their regional specificity.

scholarly journals Understanding the Usage Patterns of Bicycle-Sharing Systems to Predict Users’ Demand: A Case Study in Wenzhou, China

2018 ◽  
Vol 2018 ◽  
pp. 1-21 ◽  
Author(s):  
Xiaomei Xu ◽  
Zhirui Ye ◽  
Jin Li ◽  
Mingtao Xu
Keyword(s):  
Cluster Analysis ◽  
Comparative Analysis ◽  
Prediction Models ◽  
Transportation Network ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Demand Prediction ◽  
Usage Patterns ◽  
Accuracy Of Prediction

Bicycle-sharing systems (BSSs) have become a prominent feature of the transportation network in many cities. Along with the boom of BSSs, cities face the challenge of bicycle unavailability and dock shortages. It is essential to conduct rebalancing operations, the success of which largely depend on users’ demand prediction. The objective of this study is to develop users’ demand prediction models based on the rental data, which will serve rebalancing operations. First, methods to collect and process the relevant data are presented. Bicycle usage patterns are then examined from both trip-based aspect and station-based aspect to provide some guidance for users’ demand prediction. After that, the methodology combining cluster analysis, a back-propagation neural network (BPNN), and comparative analysis is proposed to predict users’ demand. Cluster analysis is used to identify different service types of stations, the BPNN method is utilized to establish the demand prediction models for different service types of stations, and comparative analysis is employed to determine if the accuracy of the prediction models is improved by making a distinction among stations and working/nonworking days. Finally, a case study is conducted to evaluate the performance of the proposed methodology. Results indicate that making a distinction among stations and working/nonworking days when predicting users’ demand can improve the accuracy of prediction models.

scholarly journals REPERTORY GRID ANALYSIS AND CONCEPT MAPPING: PROBLEMS AND ISSUES

2012 ◽  
Vol 48 (1) ◽  
pp. 91-106
Author(s):  
Thomas J.J. McCloughlin ◽  
Philip S. C. Matthews
Keyword(s):  
Concept Mapping ◽  
Concept Maps ◽  
Repertory Grid ◽  
Assessment Procedure ◽  
Research Needs ◽  
Traditional Concept ◽  
Grid Analysis ◽  
Common Structure ◽  
Living Things ◽  
Work Concept

'Repertory grid analysis' was used as a way of constructing representations of learners conceptions of living things; and finding a common structure or understanding; this was described in previous work. 'Concept mapping' has been stated as an appropriate assessment procedure in science curricula in a number of countries. Previous relevant published work describing the benefits of 'concept mapping' as a learning, teaching, and assessing tool is large. However, the existence of a large literature is not justification in itself, and in this work we provide a critique of the current literature. Problems with 'concept mapping' are simply ignored. However, it is thought that 'repertory grid analysis' does overcome some of the recognized problems of 'concept mapping' such as: i) comparison of concept maps between students or between students and educators: in repertory grid this becomes not only possible but a reliable method - this has proven to be one of the more problematic areas in traditional 'concept mapping'; ii) quantification of concept mapping - integer scoring of whole concept maps in 'repertory grid analysis' is eliminated since the arranged structure of the graph produced holds significance for the conceptual structure. More research needs to be done in repertory grid analysis and its implications and applications in curricular research have yet to be fully explored. Key words: concept mapping, conceptual frameworks, repertory grid analysis.

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