Cultural analysis of mathematical content in teacher education: the case of Elementary Arithmetic Theorems     

Elda Guala  Paolo Boero 《Educational Studies in Mathematics》2017,96(2):207-227

This paper deals with the competence of Cultural (epistemological, historical and anthropological) Analysis of the Content (CAC), which is important for teachers’ awareness and autonomy when dealing with educational choices in a changing cultural and institutional context. We report on an 18-hour intervention in a teacher education course at the undergraduate level attended by 12 participants during the fall of 2013. The goal of the intervention was to enhance participants’ CAC in the case of Elementary Arithmetic Theorems by using the rationality construct derived from Habermas’ work. Qualitative analyses of participants’ discussions showed how the construct was gradually appropriated by them and contributed to their CAC. Trends emerging from quantitative comparisons with previous implementations of the same course provided some evidence regarding the effects of the intervention on the quality of participants’ CAC performances at the end of the course. The method chosen for participants’ assessment and their cultural background will be discussed as conditions for the success of the intervention.  相似文献   

Inter-letter spacing,inter-word spacing,and font with dyslexia-friendly features: testing text readability in people with and without dyslexia     

Jessica Galliussi  Luciano Perondi  Giuseppe Chia  Walter Gerbino  Paolo Bernardis 《Annals of dyslexia》2020,70(1):141-152

Over the last years, several studies have suggested a possible link between dyslexia and deficits in low-level visual processing (e.g., excessive crowding). At the same time, specially designed “dyslexia-friendly” fonts appeared on the market. This class of fonts presents two main features: the particular graphic characteristics of the letterform designed to avoid confusion between similarly shaped letters, and wider inter-letter and inter-word spacing to limit crowding. The literature testing the efficacy of “dyslexia-friendly” fonts in improving reading accuracy and increasing reading speed is controversial. We evaluated the impact of letterform (with vs. without dyslexia-friendly graphic features), inter-letter spacing (standard vs. increased), and inter-word spacing (standard vs. increased) on reading accuracy and speed. Two groups of 64 children each, with and without dyslexia, read aloud 8 equivalent texts. The data collected failed to show any effect from the letterform. As regards spacing, the data showed that reading speed is impaired by an increase in inter-letter spacing not combined with an adequate increase in inter-word spacing.  相似文献   

The influence of reading literacy on mathematics and science achievement     

Elisa Caponera  Paolo Sestito  Paolo M. Russo 《The Journal of educational research》2016,109(2):197-204

  相似文献   

Detecting ethnicity-targeted hate speech in Russian social media texts     

Ekaterina Pronoza  Polina Panicheva  Olessia Koltsova  Paolo Rosso 《Information processing & management》2021,58(6):102674

Ethnicity-targeted hate speech has been widely shown to influence on-the-ground inter-ethnic conflict and violence, especially in such multi-ethnic societies as Russia. Therefore, ethnicity-targeted hate speech detection in user texts is becoming an important task. However, it faces a number of unresolved problems: difficulties of reliable mark-up, informal and indirect ways of expressing negativity in user texts (such as irony, false generalization and attribution of unfavored actions to targeted groups), users’ inclination to express opposite attitudes to different ethnic groups in the same text and, finally, lack of research on languages other than English. In this work we address several of these problems in the task of ethnicity-targeted hate speech detection in Russian-language social media texts. This approach allows us to differentiate between attitudes towards different ethnic groups mentioned in the same text – a task that has never been addressed before. We use a dataset of over 2,6M user messages mentioning ethnic groups to construct a representative sample of 12K instances (ethnic group, text) that are further thoroughly annotated via a special procedure. In contrast to many previous collections that usually comprise extreme cases of toxic speech, representativity of our sample secures a realistic and, therefore, much higher proportion of subtle negativity which additionally complicates its automatic detection. We then experiment with four types of machine learning models, from traditional classifiers such as SVM to deep learning approaches, notably the recently introduced BERT architecture, and interpret their predictions in terms of various linguistic phenomena. In addition to hate speech detection with a text-level two-class approach (hate, no hate), we also justify and implement a unique instance-based three-class approach (positive, neutral, negative attitude, the latter implying hate speech). Our best results are achieved by using fine-tuned and pre-trained RuBERT combined with linguistic features, with F1-hate=0.760, F1-macro=0.833 on the text-level two-class problem comparable to previous studies, and F1-hate=0.813, F1-macro=0.824 on our unique instance-based three-class hate speech detection task. Finally, we perform error analysis, and it reveals that further improvement could be achieved by accounting for complex and creative language issues more accurately, i.e., by detecting irony and unconventional forms of obscene lexicon.  相似文献   

Irony detection via sentiment-based transfer learning     

Shiwei Zhang  Xiuzhen Zhang  Jeffrey Chan  Paolo Rosso 《Information processing & management》2019,56(5):1633-1644

Irony as a literary technique is widely used in online texts such as Twitter posts. Accurate irony detection is crucial for tasks such as effective sentiment analysis. A text’s ironic intent is defined by its context incongruity. For example in the phrase “I love being ignored”, the irony is defined by the incongruity between the positive word “love” and the negative context of “being ignored”. Existing studies mostly formulate irony detection as a standard supervised learning text categorization task, relying on explicit expressions for detecting context incongruity. In this paper we formulate irony detection instead as a transfer learning task where supervised learning on irony labeled text is enriched with knowledge transferred from external sentiment analysis resources. Importantly, we focus on identifying the hidden, implicit incongruity without relying on explicit incongruity expressions, as in “I like to think of myself as a broken down Justin Bieber – my philosophy professor.” We propose three transfer learning-based approaches to using sentiment knowledge to improve the attention mechanism of recurrent neural models for capturing hidden patterns for incongruity. Our main findings are: (1) Using sentiment knowledge from external resources is a very effective approach to improving irony detection; (2) For detecting implicit incongruity, transferring deep sentiment features seems to be the most effective way. Experiments show that our proposed models outperform state-of-the-art neural models for irony detection.  相似文献   

Universities’ attractiveness to students: The Darwinism effect     

Mattia Cattaneo  Hugo Horta  Paolo Malighetti  Michele Meoli  Stefano Paleari 《Higher Education Quarterly》2019,73(1):85-99

Due to significant government cuts to Higher Education funding in Southern European systems, their already underfunded universities were forced to increasingly compete for students as sources of additional revenue. Concurrently, families and students that continued to afford participation in Higher Education became more selective when choosing a university, realising the riskier investment that Higher Education participation had become. Through a competing destinations model and relying on all Italian private and public universities, this study finds that the competition forces characterising universities’ attractiveness over the last decade have changed since the financial crisis of 2008. In a context of lower demand for Higher Education, the competition for students grew and universities in close proximity were better prepared to face the new challenges, leading to the growth of Higher Education clusters.  相似文献   

Light-driven directional ion transport for enhanced osmotic energy harvesting     

Kai Xiao  Paolo Giusto  Fengxiang Chen  Ruotian Chen  Tobias Heil  Shaowen Cao  Lu Chen  Fengtao Fan  Lei Jiang 《国家科学评论(英文版)》2021,8(8)

Light-driven ion (proton) transport is a crucial process both for photosynthesis of green plants and solar energy harvesting of some archaea. Here, we describe use of a TiO₂/C₃N₄ semiconductor heterojunction nanotube membrane to realize similar light-driven directional ion transport performance to that of biological systems. This heterojunction system can be fabricated by two simple deposition steps. Under unilateral illumination, the TiO₂/C₃N₄ heterojunction nanotube membrane can generate a photocurrent of about 9 μA/cm², corresponding to a pumping stream of ∼5500 ions per second per nanotube. By changing the position of TiO₂ and C₃N₄, a reverse equivalent ionic current can also be realized. Directional transport of photogenerated electrons and holes results in a transmembrane potential, which is the basis of the light-driven ion transport phenomenon. As a proof of concept, we also show that this system can be used for enhanced osmotic energy generation. The artificial light-driven ion transport system proposed here offers a further step forward on the roadmap for development of ionic photoelectric conversion and integration into other applications, for example water desalination.  相似文献   

Men’s health: Renaissance medicine and the male body     

Paolo Savoia 《Metascience》2016,25(2):255-258

  相似文献   

Symptomatology of Collective Knowledge and the Social to Come     

Paolo Vignola 《Parallax》2017,23(2):184-201

  相似文献   

Evaluating the Efficiency of Research in Academic Departments: an Empirical Analysis in an Italian Region     

Tommaso Agasisti  Antonio Dal Bianco  Paolo Landoni  Alessandro Sala  Mario Salerno 《Higher Education Quarterly》2011,65(3):267-289

This paper investigates the efficiency of university departments in science, technology and medicine in an Italian Region (Lombardy). The aim of the paper is twofold: (i) to analyse the changes in productivity in recent years (from 2004 and 2007); and (ii) to detect factors that are potentially affecting efficiency. The research benefited from a new and unique dataset (called QuESTIO) developed by the Lombardy Regional Government. Using facilities and academic staff as inputs and research grants and publications as outputs, the research activity of academic departments was modelled. The methodological approach for computing efficiency scores is (DEA) Data Envelopment Analysis; Malmquist indexes have been used to measure changes in productivity, while Kruskal‐Wallis tests were employed to study the potential determinants of efficiency. Two main results were obtained. First, the academic departments improved their efficiency but, at the same time, the efficiency frontier worsened. Second, external and measurable factors (such as scientific sector, proportion of tenured staff, location, etc.) have a limited impact in explaining efficiency differentials. The policy implications of both results are discussed.  相似文献