Content analysis: What are they talking about?

Quantitative content analysis is increasingly used to surpass surface level analyses in Computer-Supported Collaborative Learning (e.g., counting messages), but critical reflection on accepted practice has generally not been reported. A review of CSCL conference proceedings revealed a general vagueness in definitions of units of analysis. In general, arguments for choosing a unit were lacking and decisions made while developing the content analysis procedures were not made explicit. In this article, it will be illustrated that the currently accepted practices concerning the ‘unit of meaning’ are not generally applicable to quantitative content analysis of electronic communication. Such analysis is affected by ‘unit boundary overlap’ and contextual constraints having to do with the technology used. The analysis of e-mail communication required a different unit of analysis and segmentation procedure. This procedure proved to be reliable, and the subsequent coding of these units for quantitative analysis yielded satisfactory reliabilities. These findings have implications and recommendations for current content analysis practice in CSCL research

Effectiveness of the Chest Strap Electrocardiogram to Detect Atrial Fibrillation

Atrial fibrillation (AF) is a significant cause of cardioembolic strokes. AF is often symptomless and intermittent, making its detection challenging. The aim of this study was to assess the possibility to use a chest strap (Suunto Movesense) to detect AF both by cardiologists and automated algorithms. A single channel electrocardiogram (ECG) from a chest strap of 220 patients (107 AF and 111 sinus rhythm SR with 2 inconclusive rhythms) were analyzed by 2 cardiologists (Doc1 and Doc2) and 2 different algorithms (COSEn and AFE-vidence). A 3-lead Holter served as the gold standard ECG for rhythm analysis. Both cardiologists evaluated the quality of the chest strap ECG to be superior to the quality of the Holter ECG; pPeer reviewe

The influence of learner characteristics on degree and type of participation in a CSCL environment

Computer-Supported Collaborative Learning (CSCL) is often presented as a promising learning method. However, it is also facing some new challenges. Apart from answering the question of whether or not working with CSCL generates satisfying learning outcomes, it is important to determine whether or not all participants profit from collaboration, with the computer as a means of communication. This paper describes the implementation and effects of an experimental program in 5 classes with a total of 120 students in elementary education who, in groups of four, engaged in Knowledge Forum discussion tasks on the subject of healthy eating. The study explores whether or not differences occur in the participation of students who differ in gender, sociocultural background and ability, and whether or not computer skills, computer attitudes, comprehensive reading scores and popularity with classmates are related to student participation. Students’ participation in this CSCL environment appears to be dependent on a number of learner characteristics. Girls contribute more words to the discussions than boys do and are more dependent on their computer skills in this production. Students who are good at comprehensive reading also contribute more words. Popularity among classmates appears to influence the degree of participation further. We also found indications that students with immigrant parents write fewer contributions than those whose parents are not immigrants