A manual for blended mobility

This manual has been designed for teachers, researchers, and course administrators involved in developing online programmes. For that reason, it has been written in accessible language and avoids being overly prescriptive.Section 1 introduces the EUCERMAT project, which is concerned with the promotion of the field of ceramic and material science and the development of educational programmes in that area.Section 2 deals with the setting-up and recognition of international common modules in the field of ceramic and material science, but some of the guidelines will be useful to faculty members in other disciplines who are thinking of developing international modules.Section 3 has been written for teachers in any discipline and describes how best to design and develop online materials. Some of the guidelines can be used in on-campus, blended, and fully online courses.Section 3 also provides some practical guidelines for EUCERMAT teachers, to ensure a consistent look-and-feel for their online courses, but the guidelines may of use to teachers in other disciplines also.The appendices comprise links to useful resources for teaching and learning online

Facilitating interaction, collaboration, community, and problem-solving capabilities in blended and fully online technical communication programs: an introduction to the special issue

I first started teaching technical communication online over a decade ago. While teaching online was new to me, I had been teaching courses about instructional design and e-learning for a few years, so I learned—through preparing those courses—how best to teach online. In particular, I learned about the importance of clear objectives, structured content, information design, aligned assessment, and engaging activities. I learned about constructivism, connectivism, and the benefits of problem-based learning to encourage deeper learning

Using financial event phrases and keywords to classify form 8-K disclosures by likely share price response

It is generally agreed that there are three different types of financial information: information in past stock prices, information that is available to all the public, and information that is both available to the public and available privately to insiders (Fama 1970; Haugen 1990; Hellstrom and Holmstrom 1998; Elton et al 2003). There is considerable debate about the possible impact that different kinds of information can have on the value of financial instruments. On the one hand, the efficient markets hypothesis (EMH) states that the price of a financial instrument properly reflects all available information immediately (Fama 1970). If security prices respond to all available information quickly, then the market is deemed efficient and no excess profits or returns can be made. On the other hand, fundamental and technical analysts argue that the market is inefficient because information disseminates slowly through the market and prices under- or over-react to the information (Haugen 1990). A number of different data sources, features, goals, and methods have been used to automatically analyse content in financial documents. However, there has been very little research undertaken in the area of automatic event phrase recognition and classification of online disclosures. Our research study focuses on content contained in Form 8-K disclosures filed on EDGAR, a system maintained by the Securities and Exchange Commission (SEC). In our research study, we developed a prototype automatic financial event phrase (FEP) recogniser and we automatically classified a small sample of 8-Ks by likely share price response, using the automatically recognised FEPs and hand-chosen keywords as features. In four comparative classification experiments, we used the C4.5 suite of programs and the SVM-Light support vector machine program. Our datasets comprised 8-Ks filed by 50 randomlychosen S&P 500 companies from 1997 to 2000 and 2005 to 2008. Our research experiments yielded some interesting findings. In an experiment on the 2005 to 2008 dataset comprising 280 8-Ks, C4.5 was able to correctly classify 63.2% of the ‘ups’1 (as against 58.2% at chance), when using FEPs and keywords. We also found that C4.5 appears to be better at identifying patterns in the training cases than SVM-Light, regardless of whether they were ‘ups’ or ‘downs’. When we compared the results from our FEP experiments with the results from two baseline approaches—n-gram classification and Naïve Bayes bag-of-words classification—we found that C4.5 using FEPs and keywords yielded marginally higher overall classification accuracy than C4.5 using n-grams or Naïve Bayes bag-of-words. A detailed description of the classification experiments is provided in the thesis, along with a discussion of the strengths and limitations of the research study. Recommendations for future work include further refinement of the FEPs and keywords, classification of larger datasets, and incorporation of additional classification variables beyond financial event phrases and hand-chosen keywords

Using financial event phrases and keywords to classify form 8-K disclosures by likely share price response

It is generally agreed that there are three different types of financial information: information in past stock prices, information that is available to all the public, and information that is both available to the public and available privately to insiders (Fama 1970; Haugen 1990; Hellstrom and Holmstrom 1998; Elton et al 2003). There is considerable debate about the possible impact that different kinds of information can have on the value of financial instruments. On the one hand, the efficient markets hypothesis (EMH) states that the price of a financial instrument properly reflects all available information immediately (Fama 1970). If security prices respond to all available information quickly, then the market is deemed efficient and no excess profits or returns can be made. On the other hand, fundamental and technical analysts argue that the market is inefficient because information disseminates slowly through the market and prices under- or over-react to the information (Haugen 1990). A number of different data sources, features, goals, and methods have been used to automatically analyse content in financial documents. However, there has been very little research undertaken in the area of automatic event phrase recognition and classification of online disclosures. Our research study focuses on content contained in Form 8-K disclosures filed on EDGAR, a system maintained by the Securities and Exchange Commission (SEC). In our research study, we developed a prototype automatic financial event phrase (FEP) recogniser and we automatically classified a small sample of 8-Ks by likely share price response, using the automatically recognised FEPs and hand-chosen keywords as features. In four comparative classification experiments, we used the C4.5 suite of programs and the SVM-Light support vector machine program. Our datasets comprised 8-Ks filed by 50 randomlychosen S&P 500 companies from 1997 to 2000 and 2005 to 2008. Our research experiments yielded some interesting findings. In an experiment on the 2005 to 2008 dataset comprising 280 8-Ks, C4.5 was able to correctly classify 63.2% of the ‘ups’1 (as against 58.2% at chance), when using FEPs and keywords. We also found that C4.5 appears to be better at identifying patterns in the training cases than SVM-Light, regardless of whether they were ‘ups’ or ‘downs’. When we compared the results from our FEP experiments with the results from two baseline approaches—n-gram classification and Naïve Bayes bag-of-words classification—we found that C4.5 using FEPs and keywords yielded marginally higher overall classification accuracy than C4.5 using n-grams or Naïve Bayes bag-of-words. A detailed description of the classification experiments is provided in the thesis, along with a discussion of the strengths and limitations of the research study. Recommendations for future work include further refinement of the FEPs and keywords, classification of larger datasets, and incorporation of additional classification variables beyond financial event phrases and hand-chosen keywords

The power of language in corporate financial reports

Financial information is extremely valuable to investors and other interested parties. This information, which can be qualitative or quantitative in nature, can be analyzed and subsequently used to try to predict future share prices and/or determine market sentiment. Financial writers need to bear this in mind when writing reports, as their message(s) could be interpreted in unexpected ways and this could cause undesirable market reactions. In this article, I provide an overview of some studies that examined the writing style and tone of financial reports. I also provide an overview of some studies that examined the use of positive and negative words in financial reports. I conclude with reference to some recent studies that involved the automatic analysis and classification of financial content. Whilst the success of automated tools has been limited, to a certain extent, tools are being used increasingly to assist with the daunting task of interpreting complicated and lengthy financial documents. Once these tools improve, it will not be so easy for financial writers to disguise bad news in the midst of good news

Training technical communication students to work with translators

Much of the content produced by technical communicators and content developers will later be translated for users from other cultures. For example, instruction manuals, web sites, e-learning courses, software tools and their components (e.g. messages, menus, and dialog boxes) frequently need to be available in many languages and for many locales. However, good translation is only possible when the source text (the text to be translated) is written clearly and with translation in mind

Use of collaboration assignments to support online learning communities

During the past few decades, increased use of information and communication technologies has led to educational innovations such as synchronous and asynchronous online collaboration tools and learning management systems. The range of information and communication technologies that are now available can support many types of collaboration that would have been previously impossible. Instructors can use information and communication technologies to facilitate collaboration that might not otherwise take place between on-campus and online learners, and between learners in different countries and universities. In collaborative learning environments, a community of inquiry supports student learning. Successful learning communities can increase learner motivation, facilitate deep learning, and reduce the potential isolation that online learners often experience. This paper provides an overview of relevant literature. The paper then outlines collaboration assignments that postgraduate students undertake in technical communication and instructional design courses. Many instructors are interested in developing their awareness of, and expertise in, innovative online teaching practices; to that end, this paper presents a number of teaching cases

Implementing reflective writing in a problem-based learning civil engineering programme

Some issues of current concern in engineering education are described. The theory, rationale and implementation of reflective practice in educational settings are briefly reviewed. The use of reflective writing in the University of Limerick’s (UL) Problem-Based Learning (PBL) Civil Engineering programme is described. The habit of ‘reflection’ is embedded in the context of a full scale design-and-construct problem in year two of the programme. Student reflections were captured in learning logs over two successive years. Aids to prepare students for reflective writing are described. Outcomes before and after implementation of the more recent aids are examined. Analyses of these data are presented and discussed. The paper concludes with some proposals for further development

Virtual teams in higher education: challenges and rewards for teachers and students

As virtual teams become more common in the workplace, a growing body of research has examined the factors critical to their success. Many studies have focused on practitioners or on students in business programs. This paper examines virtual team collaboration among technical communication students at the University of Limerick (UL) and at the University of Central Florida (UCF) in Orlando, Florida, USA. The paper describes the projects we have run, the technologies we have used, and the challenges and rewards of the experience for both students and teachers

University of Limerick's MA in technical communication and e-learning

This article describes the mission, history, development, structure, and curriculum of the MA in Technical Communication and E-Learning, which is offered by the University of Limerick. The program started as a Graduate Diploma/ MA in Technical Communication but merged with the MA in E-Learning Design and Development in 2010. While the curriculum has evolved over the years, the overriding skill set of graduates remains constant; graduates are able to write clear, concise content for a range of media. In addition to discussing the curricular changes and structure, this article describes the typical roles filled by graduates, the faculty involved in the program, and the challenges they face administering the program