A content analysis method to measure critical thinking in face-to-face and computer supported group learning

This paper gives a detailed account of the content analysis method developed at Queen's University Belfast to measure critical thinking during group learning, as used in our controlled comparisons between learning in face-to-face and computer conference seminars. From Garrison's 5 stages of critical thinking, and Henri's cognitive skills needed in CMC, we have developed two research instruments: a student questionnaire and this content analysis method. The content analysis relies on identifying, within transcripts, examples of indicators of obviously critical and obviously uncritical thinking, from which several critical thinking ratios can be calculated.

Search engine content analysis

Search engines have forever changed the way people access and discover knowledge, allowing information about almost any subject to be quickly and easily retrieved within seconds. As increasingly more material becomes available electronically the influence of search engines on our lives will continue to grow. This presents the problem of how to find what information is contained in each search engine, what bias a search engine may have, and how to select the best search engine for a particular information need. This research introduces a new method, search engine content analysis, in order to solve the above problem. Search engine content analysis is a new development of traditional information retrieval field called collection selection, which deals with general information repositories. Current research in collection selection relies on full access to the collection or estimations of the size of the collections. Also collection descriptions are often represented as term occurrence statistics. An automatic ontology learning method is developed for the search engine content analysis, which trains an ontology with world knowledge of hundreds of different subjects in a multilevel taxonomy. This ontology is then mined to find important classification rules, and these rules are used to perform an extensive analysis of the content of the largest general purpose Internet search engines in use today. Instead of representing collections as a set of terms, which commonly occurs in collection selection, they are represented as a set of subjects, leading to a more robust representation of information and a decrease of synonymy. The ontology based method was compared with ReDDE (Relevant Document Distribution Estimation method for resource selection) using the standard R-value metric, with encouraging results. ReDDE is the current state of the art collection selection method which relies on collection size estimation. The method was also used to analyse the content of the most popular search engines in use today, including Google and Yahoo. In addition several specialist search engines such as Pubmed and the U.S. Department of Agriculture were analysed. In conclusion, this research shows that the ontology based method mitigates the need for collection size estimation.

Strategy content analysis for service identification : a case study on government agencies

In a resource constrained business world, strategic choices must be made on process improvement and service delivery. There are calls for more agile forms of enterprises and much effort is being directed at moving organizations from a complex landscape of disparate application systems to that of an integrated and flexible enterprise accessing complex systems landscapes through service oriented architecture (SOA). This paper describes the analysis of strategies to detect supporting business services. These services can then be delivered in a variety of ways: web-services, new application services or outsourced services. The focus of this paper is on strategy analysis to identify those strategies that are common to lines of business and thus can be supported through shared services. A case study of a state government is used to show the analytical method and the detection of shared strategies.

Determining the appropriate proportion of owner-provided design in design-build contracts - a content analysis approach

The Request For Proposal (RFP) with the design‐build (DB) procurement arrangement is a document in which an owner develops his requirements and conveys the project scope to DB contractors. Owners should provide an appropriate level of design in DB RFPs to adequately describe their requirements without compromising the prospects for innovation. This paper examines and compares the different levels of owner‐provided design in DB RFPs by the content analysis of 84 requests for RFPs for public DB projects advertised between 2000 and 2010 with an aggregate contract value of over $5.4 billion. A statistical analysis was also conducted in order to explore the relationship between the proportion of owner‐provided design and other project information, including project type, advertisement time, project size, contractor selection method, procurement process and contract type. The results show that the majority (64.8%) of the RFPs provide less than 10% of the owner‐provided design. The owner‐provided design proportion has a significant association with project type, project size, contractor selection method and contract type. In addition, owners are generally providing less design in recent years than hitherto. The research findings also provide owners with perspectives to determine the appropriate level of owner‐provided design in DB RFPs.

Content analysis of international research in geographical and environmental education : eighteen years of academic publishing

This paper examines the history of the IRGEE Journal in terms of its sustainable future. The development of geographical and environmental education is evaluated, as reflected from the articles published in the Journal “International Research in Geographical and Environmental Education” (IRGEE). A content analysis of all papers and forum sections which have appeared in the journal since Volume 1 Number 1 was published in 1992 has been conducted, examining the content of as many as 526 articles. The method was a content analysis, and revealed themes which have experienced an increasing or declining interest over the 18 years of publication of IRGEE (1992-2009), while other themes have remained current during this period. The main findings of this analysis are: a) the total number of articles has increased more than threefold, b) articles related to geographical education (sensu stricto) outweighed those related to environmental education, c) the themes “syllabi, textbooks, curricula” and “values, attitudes” attract the attention of researchers with increasing strength and d) emerging subjects, such as GIS and sustainability have appeared dynamically in the last years.

Review of community facilities in Australian retirement villages : a content analysis

Aim Facilities in retirement villages form a supportive environment for older residents. The purpose of this paper is to investigate the provision of these facilities in retirement villages, which are regarded as a viable accommodation option for the ever-increasing ageing population in Australia. Method A content analysis of 124 retirement villages operated by 22 developers in Queensland and South Australia was conducted for the research purpose. Results The most widely provided facilities are community centres, libraries, barbeque facilities, hairdressers/salons and billiards/snooker/pool tables. Commercial operators provide more facilities than not-for-profit organisations and larger retirement villages normally have more facilities due to the economics of scale involved. Conclusions The results of the study provide a useful reference for providing facilities within retirement villages that may support the quality lifestyles for the older residents.

Introduction of high-content screening method for studying drug-induced mitochondrial dysfunction in hepatocytes

Drug induced liver injury is one of the frequent reasons for the drug removal from the market. During the recent years there has been a pressure to develop more cost efficient, faster and easier ways to investigate drug-induced toxicity in order to recognize hepatotoxic drugs in the earlier phases of drug development. High Content Screening (HCS) instrument is an automated microscope equipped with image analysis software. It makes the image analysis faster and decreases the risk for an error caused by a person by analyzing the images always in the same way. Because the amount of drug and time needed in the analysis are smaller and multiple parameters can be analyzed from the same cells, the method should be more sensitive, effective and cheaper than the conventional assays in cytotoxicity testing. Liver cells are rich in mitochondria and many drugs target their toxicity to hepatocyte mitochondria. Mitochondria produce the majority of the ATP in the cell through oxidative phosphorylation. They maintain biochemical homeostasis in the cell and participate in cell death. Mitochondria is divided into two compartments by inner and outer mitochondrial membranes. The oxidative phosphorylation happens in the inner mitochondrial membrane. A part of the respiratory chain, a protein called cytochrome c, activates caspase cascades when released. This leads to apoptosis. The aim of this study was to implement, optimize and compare mitochondrial toxicity HCS assays in live cells and fixed cells in two cellular models: human HepG2 hepatoma cell line and rat primary hepatocytes. Three different hepato- and mitochondriatoxic drugs (staurosporine, rotenone and tolcapone) were used. Cells were treated with the drugs, incubated with the fluorescent probes and then the images were analyzed using Cellomics ArrayScan VTI reader. Finally the results obtained after optimizing methods were compared to each other and to the results of the conventional cytotoxicity assays, ATP and LDH measurements. After optimization the live cell method and rat primary hepatocytes were selected to be used in the experiments. Staurosporine was the most toxic of the three drugs and caused most damage to the cells most quickly. Rotenone was not that toxic, but the results were more reproducible and thus it would serve as a good positive control in the screening. Tolcapone was the least toxic. So far the conventional analysis of cytotoxicity worked better than the HCS methods. More optimization needs to be done to get the HCS method more sensitive. This was not possible in this study due to time limit.

A purposive approach to content analysis : designing analytical frameworks

Content analysis of computer conferences provides a rich source of data for researching and understanding online learning. However, the complexities of using content analysis in a relatively new research field have resulted in researchers often avoiding this method and using more familiar methods such as survey and interview instead. This article discusses content analysis as a methodology, with emphasis on the development of analytical frameworks. The literature indicates that researchers either use or modify existing frameworks or, more commonly, develop new ones, either through grounded theory approaches or the adaptation of existing theories, concepts or models. The development and implementation of two frameworks are then discussed in detail. Both were developed purposively to investigate and evaluate firstly collaborative learning and secondly deep and surface approaches to learning as evidenced in computer conferences. The article concludes with recommendations for framework development.

Investigating the impact of computer conferencing: content analysis as a manageable research tool

Content analysis of computer conferences provides a rich source of data for researching and understanding online learning. However the complexities of using content analysis in a relatively new research field have resulted in researchers avoiding its use as a qualitative or quantitative method and using more familiar methods such as survey and interview instead. Ethical issues are also raised that, though ensuring students’ rights, particularly to privacy and with no fear of coercion, are making it difficult for researchers to access and analyse archives of conference data as a research source. This paper suggests a pragmatic but systematic approach to solving these research issues by using several research strategies that are described in the context of the authors’ research and practice.

Can qualitative content analysis be adapted for use by social informaticians to study social media discourse? A position paper

IS research on social media (e.g. Facebook, Twitter, blogs) has so far used user surveys or quantitative content analysis (QuantCA) research methods almost exclusively. There is considerable potential for social informatics research to use qualitative content analysis (QualCA) to explore social media discourse and its appropriation by people “in situ”. This paper presents the position that QualCA offers researchers the flexibility to identify emergent research questions and units of analysis which they may not have preconceived. This is likely to be important for IS research because of the infancy and evolving nature of social media discourse. The paper puts forward suggestions on how the QualCA research method can be adapted for this type of research.

A content analysis of sponsor representation across professional sport websites : extension of attribute typology

The sport industry has identified the importance of using the internet as a tool that can benefit the organisation. Much like the purpose of entering into sponsorship of sporting events, corporate partners are also attracted to the opportunities that professional sport team websites offer to fulfil similar objectives. The major purpose of this research is to explore the various ways in which sponsor logos are represented across professional sport websites and to extend previous advertising research, specifically the work developing advertising attribute typologies. The subjects for this research are professional sport websites and a qualitative approach is adopted with a content analysis as the main method of analysis used. To ensure reliability and validity within the coding instruments used, percentage agreement and Cohen’s kappa were adopted as indexes to verify this. The findings show sponsors’ logos exist on most professional sport websites and are represented in a variety of ways. Furthermore, a typology for sponsor representation and location across sport websites has been established to present a reliable foundation for future research in the area of consumer attitudes, behaviour and response towards sponsors and their presence on sport websites.

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.

Originator or propagator? Incorporating social role theory into topic models for twitter content analysis

A large number of studies have been devoted to modeling the contents and interactions between users on Twitter. In this paper, we propose a method inspired from Social Role Theory (SRT), which assumes that a user behaves differently in different roles in the generation process of Twitter content. We consider the two most distinctive social roles on Twitter: originator and propagator, who respectively posts original messages and retweets or forwards the messages from others. In addition, we also consider role-specific social interactions, especially implicit interactions between users who share some common interests. All the above elements are integrated into a novel regularized topic model. We evaluate the proposed method on real Twitter data. The results show that our method is more effective than the existing ones which do not distinguish social roles. Copyright 2013 ACM.

Incorporating social role theory into topic models for social media content analysis

In this paper, we explore the idea of social role theory (SRT) and propose a novel regularized topic model which incorporates SRT into the generative process of social media content. We assume that a user can play multiple social roles, and each social role serves to fulfil different duties and is associated with a role-driven distribution over latent topics. In particular, we focus on social roles corresponding to the most common social activities on social networks. Our model is instantiated on microblogs, i.e., Twitter and community question-answering (cQA), i.e., Yahoo! Answers, where social roles on Twitter include "originators" and "propagators", and roles on cQA are "askers" and "answerers". Both explicit and implicit interactions between users are taken into account and modeled as regularization factors. To evaluate the performance of our proposed method, we have conducted extensive experiments on two Twitter datasets and two cQA datasets. Furthermore, we also consider multi-role modeling for scientific papers where an author's research expertise area is considered as a social role. A novel application of detecting users' research interests through topical keyword labeling based on the results of our multi-role model has been presented. The evaluation results have shown the feasibility and effectiveness of our model.

Customer relationship management: A content analysis of issues and best practices

This dissertation is a study of customer relationship management theory and practice. Customer Relationship Management (CRM) is a business strategy whereby companies build strong relationships with existing and prospective customers with the goal of increasing organizational profitability. It is also a learning process involving managing change in processes, people, and technology. CRM implementation and its ramifications are also not completely understood as evidenced by the high number of failures in CRM implementation in organizations and the resulting disappointments. ^ The goal of this dissertation is to study emerging issues and trends in CRM, including the effect of computer software and the accompanying new management processes on organizations, and the dynamics of the alignment of marketing, sales and services, and all other functions responsible for delivering customers a satisfying experience. ^ In order to understand CRM better a content analysis of more than a hundred articles and documents from academic and industry sources was undertaken using a new methodological twist to the traditional method. An Internet domain name (http://crm.fiu.edu) was created for the purpose of this research by uploading an initial one hundred plus abstracts of articles and documents onto it to form a knowledge database. Once the database was formed a search engine was developed to enable the search of abstracts using relevant CRM keywords to reveal emergent dominant CRM topics. The ultimate aim of this website is to serve as an information hub for CRM research, as well as a search engine where interested parties can enter CRM-relevant keywords or phrases to access abstracts, as well as submit abstracts to enrich the knowledge hub. ^ Research questions were investigated and answered by content analyzing the interpretation and discussion of dominant CRM topics and then amalgamating the findings. This was supported by comparisons within and across individual, paired, and sets-of-three occurrences of CRM keywords in the article abstracts. ^ Results show that there is a lack of holistic thinking and discussion of CRM in both academics and industry which is required to understand how the people, process, and technology in CRM impact each other to affect successful implementation. Industry has to get their heads around CRM and holistically understand how these important dimensions affect each other. Only then will organizational learning occur, and overtime result in superior processes leading to strong profitable customer relationships and a hard to imitate competitive advantage. ^