What motivates enrolment in programming MOOCs?

Learners who enrol in massive open online courses (MOOCs) have different backgrounds and tend to have different motivations than learners in traditional courses. Based on value-expectancy theory, an instrument was developed to measure motivation for enrolling in a programming MOOC. A study with 1229 adult participants in Estonian-language programming course “About Programming” was conducted to validate the instrument. Results of confirmatory factor analysis validated the 7-factor scale named factors influencing enrolment in MOOC (FIEM). FIEM comprises three factors of expectancies, three factors of values and one factor of social influence. The highest and lowest rated motivational factors influencing enrolment in programming MOOC are discussed in the paper. Interest in and expectations for the course, personal suitability of distance learning and suitability for family and work are the highest-rated motivational factors for those who enrol in MOOC. Usefulness related to own children, social influence and usefulness to related to certification were the lowest rated. The results of this study can be useful for designers of programming MOOCs and the developed scale might be used in future studies.     

Recording the war effort: immigrant communities in Latin America and the memory of the Great War

ABSTRACT

This paper aims to analyse the initiatives undertaken by some immigrant communities residing in Latin America to record their mobilisation around the First World War. After the armistice, European communities in Argentina, Bolivia, Brazil, Chile, Mexico, Paraguay, Peru, Uruguay and other countries gathered detailed information about their activities during the conflict, published as profusely illustrated books of remembrance, offered to their governments as proof of their loyalty. The article intends to establish the peculiar nature of these publications as records of the war effort, and analyse the agents and processes of their elaboration, and their role as commemorative but also as archival documents.     

Personal reactions to ‘strange’ situations: Attachment styles and acculturation attitudes of immigrants and majority members

A growing number of studies examine the influence of individual factors on acculturation attitudes of immigrants, but few studies focus on majority members’ attitudes. In this paper, two studies are reported on the relation between attachment styles and acculturation attitudes of both immigrants (N=177) and majority members (N=243) in the Netherlands. Until now very few studies have associated cultural adjustment with attachment styles. This is remarkable, because attachment theory refers to interaction with others in new situations. Four different styles of attachment (the secure, dismissing, preoccupied and fearful attachment styles) are related to Berry's classification of acculturation attitudes. People, both immigrants and majority members, with a secure attachment style were positive towards integration, whereas people with a dismissing attachment style were not. Dismissing immigrants were more positive towards separation. Whereas both immigrants and majority members with a secure attachment style showed a similar pattern of correlations between attachment and acculturation, they seem to react quite differently, and even in opposite ways, when they have a preoccupied attachment style. Yet, the different reactions may be caused by the same psychological process: The existential ambivalence of preoccupied people may lead to diverse reactions.     

Scientific literacy and informal science teaching

Two stages in research on scientific literary are identified: a composite saturation stage in which definitions covered all objects of science education and a stage where researchers focused on small manageable portions of scientific literary. Initial and continuous scientific literacy research in which the focus is on cognitive preference for science and informal science teaching is described. Underlying cognitive preference is a value preference for science. Three interdependent but clearly distinguishable forms of science teaching, formal, nonformal and informal, are described. Informal science teaching is identified as a condition for and an outcome of scientific literacy.     

Hierarchical clustering of a Finnish newspaper article collection with graded relevance assessments

Search facilitated with agglomerative hierarchical clustering methods was studied in a collection of Finnish newspaper articles (N = 53,893). To allow quick experiments, clustering was applied to a sample (N = 5,000) that was reduced with principal components analysis. The dendrograms were heuristically cut to find an optimal partition, whose clusters were compared with each of the 30 queries to retrieve the best-matching cluster. The four-level relevance assessment was collapsed into a binary one by (A) considering all the relevant and (B) only the highly relevant documents relevant, respectively. Single linkage (SL) was the worst method. It created many tiny clusters, and, consequently, searches enabled with it had high precision and low recall. The complete linkage (CL), average linkage (AL), and Ward's methods (WM) returned reasonably-sized clusters typically of 18–32 documents. Their recall (A: 27–52%, B: 50–82%) and precision (A: 83–90%, B: 18–21%) was higher than and comparable to those of the SL clusters, respectively. The AL and WM clustering had 1–8% better effectiveness than nearest neighbor searching (NN), and SL and CL were 1–9% less efficient that NN. However, the differences were statistically insignificant. When evaluated with the liberal assessment A, the results suggest that the AL and WM clustering offer better retrieval ability than NN. Assessment B renders the AL and WM clustering better than NN, when recall is considered more important than precision. The results imply that collections in the highly inflectional and agglutinative languages, such as Finnish, may be clustered as the collections in English, provided that documents are appropriately preprocessed.     

Seeking Nettle Textiles – Utilizing a Combination of Microscopic Methods for Fibre Identification

Bast fibres have been commonly used as a textile material in Northern Europe since Neolithic times. However, the process of identifying the different species has been problematic, and many important questions related to their cultural history are still unanswered. For example, a modified Herzog test and the presence of calcium oxalate crystals have both been used in identification. In order to generate more reliable results, further research and advancement in multi-methodological methods is required. This paper introduces a combination of methods which can be used to identify and distinguish flax (Linum usitatissimum), hemp (Cannabis sativa), and stinging nettle (Urtica dioica). The research material consisted of reference fibres and 25 fibre samples obtained from 12 textiles assumed to be made of nettle. The textiles were from the Finno-Ugric and Historical Collections of The National Museum of Finland. The fibre samples were studied by observing the surface characteristics and cross sections with transmitted light microscopy, and by using a modified Herzog test with polarized light, in order to identify the distinguishable features in their morphological structures. The study showed that five out of 25 samples were cotton, 16 nettle, one flax, and one hemp. Findings from two samples were inconsistent. The results show that it is possible to distinguish common north European bast fibres from each other by using a combination of microscopic methods. Furthermore, by utilizing these combined methods, new and more reliable information could be obtained from historical ethnographic textiles, which creates new vistas for the interpretation of their cultural history.     

Shared Entertainment,Shared Opinions: The Influence of Social TV Comments on the Evaluation of Talent Shows

The present research investigated whether co-viewer comments in social TV interactions are able to enhance or weaken media effects. With the example of talent shows, the valence of co-viewer comments (pro/contra/none) as well as the type of content (antisocial behavior vs. conventional performance) were varied in an experiment (N = 117). Results showed that participants’ own comments and their private attitudes about the judges varied in line with comment valence. Findings suggest that social TV viewers are prone to social influence of their co-viewers, which might amplify problems regarding the portrayal of antisocial behavior in reality TV.     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.