scholarly journals Multivariable Analysis Methods On Identifying Factors and Groups of Students in the Environment of the Discovery Learning/Constructivistic Approach Using Cognitive Tools

2019 ◽  
pp. 7-12
Author(s):  
Konstantinos Korres
Keyword(s):  
Cluster Analysis ◽  
Data Analysis ◽  
Multivariable Analysis ◽  
Discovery Learning ◽  
Cognitive Tools ◽  
Analysis Methods ◽  
Multiple Variables ◽  
Students Attitudes ◽  
And Cluster Analysis ◽  
The University

This paper studies the environment of the discovery learning/constructivistic approach using cognitive tools regarding students’ performance in tests involving different kinds of learning and in the final formal examinations and students’ attitudes towards the approach in Mathematics’ higher education. In particular the paper aims in identifying factors regarding students’ scores and attitudes affected by the approach and groups of students with similar characteristics based on these factors. Data was obtained by a study realized at the Department of Statistics and Insurance Sciences of the University of Piraeus, concerning the application of the discovery learning/constructivistic approach using Mathematica on the course Calculus (Functions of multiple variables). Multivariable analysis methods are used in the data analysis, in particular factor analysis in identifying factors and cluster analysis in identifying groups of students with similar characteristics, in combination with inferential statistics’ methods. The statistical package SPSS was used for the data analysis.

scholarly journals Online Discovery/Constructivistic Learning Using Cognitive Tools in Mathematics’ Higher Education

2020 ◽  
pp. 26-32
Author(s):  
Konstantinos Korres
Keyword(s):  
Higher Education ◽  
Statistical Analysis ◽  
Discovery Learning ◽  
Synchronous Communication ◽  
Cognitive Tools ◽  
Students Attitudes ◽  
Mixed Approach ◽  
Video Group ◽  
The University

This paper analyzes online discovery learning/ constructivistic approach using cognitive tools in higher Mathematics’ education, via a combination of electronic worksheets designed and implemented in Mathematica and online synchronous communication via the tools of a Learning Management System (LMS) and voice and video group calls. Moreover, the paper presents empirical research results of a case study concerning the approach’s application at the Department of Statistics and Insurance Sciences of the University of Piraeus and focuses on students’ attitudes towards the approach. We used a mixed approach in the study, in particular a quantitative approach with open-ended questions. A questionnaire was handed out and was answered by the students that participated. We performed statistical analysis via SPSS to data obtained by questions with binary answers and answers on a 7-point Likert scale. Also we included several open-ended questions, in order for the students to express their views and attitudes towards the benefits and the disadvantages of the tools and the approach used.

scholarly journals Students’ Attitudes towards Discovery Learning / Constructivistic Approach using Computers as Cognitive Tools in Higher Mathematics Education

2018 ◽  
pp. 44 ◽  
Author(s):  
Korres Konstantinos
Keyword(s):  
Mathematics Education ◽  
Quantitative Methods ◽  
Higher Order Thinking ◽  
Thinking Skills ◽  
Discovery Learning ◽  
Cognitive Tools ◽  
Higher Order Thinking Skills ◽  
Correlational Approach ◽  
Students Attitudes ◽  
The University

This paper analyses the discovery learning / constuctivistic approach using cognitive tools in higher Mathematics education and focuses on electronic worksheets designed and implemented in Mathematica. The approach was applied at the University of Piraeus. Students from the Department of Statistics and Insurance Sciences participated in the research. The paper focuses on empirical research results on students’ attitudes towards the approach, concerning the cognitive tool used (Mathematica), the approach’s discovery learning and constructivistic characteristics and the development of higher order thinking skills supported by the approach. Regarding factors that could influence students’ attitudes, gender and experience in using computers are investigated. This paper uses quantitative methods in analyzing data collected via the use of a questionnaire and the research approaches used are the descriptive / investigative and the correlational approach.

scholarly journals Patterns of Italian high school and university students’ attitudes towards physics: an analysis based on semiotic-cultural perspective

2021 ◽  
Author(s):  
Italo Testa ◽  
Raffaele De Luca Picione ◽  
Umberto Scotti di Uccio
Keyword(s):  
High School ◽  
Cluster Analysis ◽  
University Students ◽  
Correspondence Analysis ◽  
Multiple Correspondence Analysis ◽  
Psychological Theory ◽  
Cultural Perspective ◽  
Undergraduate Level ◽  
Students Attitudes ◽  
And Cluster Analysis

AbstractThe purpose of this study was to analyse Italian high school and university students’ attitudes towards physics using the Semiotic Cultural Psychological Theory (SCPT). In the SCPT framework, attitudes represent how individuals interpret their experience through the mediation of generalized meaning with which they are identified. A view-of-physics questionnaire was used as an instrument to collect data with 1603 high school and university students. Data were analysed through multiple correspondence analysis and cluster analysis. We identified four generalized meanings of physics: (a) interesting and important for society; (b) a quite interesting, but badly taught subject at school and not completely useful for society; (c) difficult to study and irrelevant for society; and (d) a fascinating and protective niche from society. The identified generalized meanings are significantly correlated to the choice to study physics at undergraduate level and to the choice of attending physics-related activities in high school. Implications for research are discussed.

Genetic variation between and within two populations of Trifolium glomeratum (cluster clover) in Western Australia

1997 ◽  
Vol 48 (7) ◽  
pp. 969 ◽  
Author(s):  
Sarita Jane Bennett
Keyword(s):  
Cluster Analysis ◽  
Genetic Variation ◽  
Western Australia ◽  
Morphological Characters ◽  
Field Station ◽  
Site Variation ◽  
Components Analysis ◽  
And Cluster Analysis ◽  
The University ◽  
Two Populations

Genetic variation between and within populations of Trifolium glomeratum (cluster clover) was studied using seed collected from 2 sites in Western Australia: Mount Barker in the south and Kwelkan in the wheatbelt. Seed was collected at 64 subplots within each site and the material was grown at the University Field Station at Shenton Park, Perth. Seventeen morphological characters were scored and the results were analysed using analysis of variance, principal components analysis, and cluster analysis. Within-site variation was much greater than had previously been shown, and a considerable amount of between-site variation was present. It is suggested that within-site variation is due to a small amount of heterozygosity, as a result of limited outbreeding, being present in each population. The 2 populations are shown to be distinct from each other, with the population from Mount Barker containing more within-site variation. It is suggested that this is a result of climatic stress influencing and reducing the amount of variation being maintained in the Kwelkan population.

Data Analysis in Agricultural Experimentation. III. Multiple Comparisons

1993 ◽  
Vol 29 (1) ◽  
pp. 1-8 ◽  
Author(s):  
S. C. Pearce
Keyword(s):  
Cluster Analysis ◽  
Data Analysis ◽  
Bayesian Methods ◽  
Multiple Comparisons ◽  
Multiple Comparison ◽  
Comparison Methods ◽  
Alternative Approach ◽  
And Cluster Analysis ◽  
Multiple Comparison Methods

SummaryMultiple comparison methods are described. It is noted that they have always been controversial, partly because they emphasize testing at the expense of estimation, partly because they pay no regard to the purpose of the investigation, partly because there are so many competing forms and, not least, because they can lead to illogical conclusions. There are many identified instances where they have been found misleading.An alternative approach is to designate ‘contrasts of interest’ from the start and to concentrate estimation and testing upon them. In many experiments the approach is powerful and definite in use, but sometimes there is no reason to designate one contrast rather than another, for example, in the assessment of new strains or new chemicals. In such circumstances some have found multiple comparisons useful, especially when the problem is to ‘pick the winner’. Bayesian methods and cluster analysis are considered briefly as other alternatives.The current over-use of multiple comparisons is deplored. It is thought to arise in part from bad teaching and in part from the general reluctance of non-statisticians to venture into the unknown territory of specifying contrasts. A bad situation is made worse by the availability of software that carries out multiple comparisons as a matter of course.

MANTiS: a program for the analysis of X-ray spectromicroscopy data

2014 ◽  
Vol 21 (5) ◽  
pp. 1206-1212 ◽  
Author(s):  
Mirna Lerotic ◽  
Rachel Mak ◽  
Sue Wirick ◽  
Florian Meirer ◽  
Chris Jacobsen
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Data Analysis ◽  
Principal Component ◽  
Analysis Tool ◽  
X Ray ◽  
Manual Analysis ◽  
X Ray Imaging ◽  
Data Analysis Tool ◽  
And Cluster Analysis

Spectromicroscopy combines spectral data with microscopy, where typical datasets consist of a stack of images taken across a range of energies over a microscopic region of the sample. Manual analysis of these complex datasets can be time-consuming, and can miss the important traits in the data. With this in mind we have developedMANTiS, an open-source tool developed in Python for spectromicroscopy data analysis. The backbone of the package involves principal component analysis and cluster analysis, classifying pixels according to spectral similarity. Our goal is to provide a data analysis tool which is comprehensive, yet intuitive and easy to use.MANTiSis designed to lead the user through the analysis using story boards that describe each step in detail so that both experienced users and beginners are able to analyze their own data independently. These capabilities are illustrated through analysis of hard X-ray imaging of iron in Roman ceramics, and soft X-ray imaging of a malaria-infected red blood cell.

scholarly journals Comparing the utilities consumptions in Dubai per category and community: MANOVA and cluster analysis approaches

2021 ◽  
Vol 958 (1) ◽  
pp. 012022
Author(s):  
A Saihi ◽  
A Alzaatreh
Keyword(s):  
Cluster Analysis ◽  
Data Analysis ◽  
Water Desalination ◽  
Analysis Technique ◽  
Open Government Data ◽  
Government Data ◽  
Increasing Demand ◽  
And Cluster Analysis ◽  
Cluster Analysis Technique ◽  
Desalination Plants

Abstract UAE is marked by the increasing demand for water and electricity due to demographic, environmental and economic factors, coupled with the dependence on water desalination process, which is costly, consumes a lot of energy and is non-environmentally friendly. Like most of the authorities in UAE, Dubai Electricity and Water Authority is facing the challenges of balancing supply with demand and responding to consumer requirements, from one side, and addressing the continuously increasing consumption and slowing it down from another side. Therefore, policy makers can benefit from statistical data analysis in order to make informed decisions. This study aims to equip decision makers with useful tools and analysis to address some of their short- and long-term objectives related to production and consumption. The current study focused on three main objectives: (i) analysing the production of the desalination plants in Dubai, (ii) comparing the consumptions of water and electricity based on the four categories residential, commercial, industrial and others, and (iii) segmenting the various communities in Dubai depending on their consumption behavior. The data used for this study is collected from the open government data and SAS Programming is adopted for data analysis. The results of the analysis revealed that the desalinated water production follows an upward trend, yet still not in line with the consumption growth. Furthermore, there are significant differences between the four categories for both water and electricity consumptions. The highest levels of consumptions are associated with the residential and commercial categories. Finally, the cluster analysis technique revealed fifteen clusters of communities depending on the consumption levels.

scholarly journals Undergraduate Students Attitudes toward Biotechnology Crop

2020 ◽  
Vol 142 ◽  
pp. 06004
Author(s):  
Evita Soliha Hani ◽  
Mustapit
Keyword(s):  
Logistic Regression ◽  
Data Analysis ◽  
Undergraduate Students ◽  
Random Sampling ◽  
Factors Affecting ◽  
Analysis Technique ◽  
Students Attitudes ◽  
Biotechnology Crops ◽  
The University ◽  
Crop Biotechnology

Crop biotechnology is not yet entirely accepted by all of the countries, even though biotechnology can give a lot of benefits in production. This research aims to explain undergraduate students attitudes toward crop biotechnology and to analyse factors affecting their attitudes toward crop biotechnology. This research is carried out at the University of Jember campus with a disproportionate random sampling of 80 respondents consisting of 40 students from the Faculty of Agriculture and 40 students from other faculties. The data analysis technique is logistic regression. The result of this research showed that most of the undergraduate students (61,25%) are agree toward biotechnology crops. While factors that affected their attitudes toward biotechnology crops are information, sex, and knowledge.

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