What Do Preservice Teachers Think about Teaching Media Literacy?: An Exploratory Study Using the Theory of Planned Behavior

Despite the numerous benefits of media & information literacy for students in today’s digital society, the lack of teacher preparation in teaching media & information literacy skills suggests that the societal rationale for students becoming media literate and the sustainable preparation of teachers in that area may differ. The purpose of this exploratory study was to explore the factors and beliefs underlying preservice teachers’ intention to teach media & information literacy in their future classroom according to the Theory of Planned Behavior. Findings suggest that preservice teachers’ have positive attitudes towards media & information literacy as an essential skill for students, yet do not feel that it is highlighted in their teacher education program, and that they would benefit from learning about media literacy pedagogies from faculty and instructors. We provide recommendations for teacher educators and researchers to improve preservice teacher’s intention to teach media & information literacy in their future classroom

Natural Language Processing Through Transfer Learning: A Case Study on Sentiment Analysis

Artificial intelligence and machine learning have significantly bolstered the technological world. This paper explores the potential of transfer learning in natural language processing focusing mainly on sentiment analysis. The models trained on the big data can also be used where data are scarce. The claim is that, compared to training models from scratch, transfer learning, using pre-trained BERT models, can increase sentiment classification accuracy. The study adopts a sophisticated experimental design that uses the IMDb dataset of sentimentally labelled movie reviews. Pre-processing includes tokenization and encoding of text data, making it suitable for NLP models. The dataset is used on a BERT based model, measuring its performance using accuracy. The result comes out to be 100 per cent accurate. Although the complete accuracy could appear impressive, it might be the result of overfitting or a lack of generalization. Further analysis is required to ensure the model's ability to handle diverse and unseen data. The findings underscore the effectiveness of transfer learning in NLP, showcasing its potential to excel in sentiment analysis tasks. However, the research calls for a cautious interpretation of perfect accuracy and emphasizes the need for additional measures to validate the model's generalization.Comment: 12 pages, 1 table, 4 figure

Walking the Line between Reality and Fiction in Online Spaces: Understanding the Effects of Narrative Transportation

Recent contentions about fake news and misinformation online has shed light on the critical need for media literacy at a global scale. Indeed, digital stories are one of the main forms of communication in the 21st century through blogs, videos-sharing websites, forums, or social networks. However, the line between facts and fiction can often become blurry in these online spaces, and being able to distinguish between reality and fantasy can have important consequences in the lives of young Internet users. Using contemporary examples from news stories, fanfiction, advertising, and radicalization, this article outlines the features, affordances, and real-life implications of digital stories. As a result, we provide recommendations for educators to create awareness and empower students about digital storytelling practices

Smart Learning

Artificial intelligence applied to the educational field has a vast potential, especially after the e ects worldwide of the COVID-19 pandemic. Online or blended educational modes are needed to respond to the health situation we are living in. The tutorial e ort is higher than in the traditional face-to-face approach. Thus, educational systems are claiming smarter learning technologies that do not pretend to substitute the faculty but make their teaching activities easy. This Special Issue is oriented to present a collection of papers of original advances in educational applications and services propelled by artificial intelligence, big data, machine learning, and deep learning

STABILITY INDICATING METHOD DEVELOPMENT AND VALIDATION FOR ESTIMATION OF DORIPENEM IN BULK AND IN SOLID DOSAGE FORM BY RP-HPLC

A robust and reliable high performance liquid chromatographic (HPLC) approach was developed and validated for the analysis of Doripenem in pharmaceutical dosage form. The method is characterised by its simplicity, selectivity, precision, and capacity to accurately determine the stability of Doripenem. The experimental setup included the use of a Hypersil BDS-C18 column (250 X 4.6 mm ID, 5 µm) as the stationary phase in a chromatographic system. The mobile phase consisted of a combination of methanol and potassium dihydrogen orthophosphate with a pH of 6.7, in a ratio of 20:80. The flow rate of the mobile phase was set at 1 ml/min. The detection of the eluents occurred at a wavelength of 290 nm. The observed retention time for Doripenem was 5.56 minutes. Doripenem underwent acid and alkali hydrolysis, oxidation, photochemical degradation, and heat degradation. The results obtained from the linear regression analysis of the calibration plot demonstrated a strong linear connection within the concentration range of 70 – 130 µg/ml, as shown by a correlation coefficient value of 0.9995. The methodology was assessed to determine its precision, accuracy, ruggedness, and robustness. The medication experiences deterioration when exposed to environments characterised by acidity, alkalinity, photochemical reactions, and thermal stress. The active medicinal component exhibited distinct retention periods for each of its degradation product peaks, indicating successful resolution. The approach's ability to successfully isolate the medication from its degradation products renders it suitable for use as a stability-indicating method

PROTECTION OF THE HAIR CELLS FROM THE OTOTOXIC EFFECT OF STREPTOMYCIN

Ototoxicity is the property of being toxic to the ear (oto), specifically the cochlea or auditory nerve and sometimes the vestibular system; it is commonly medication-induced. It has long been known that the major irreversible toxicity of aminoglycosides is ototoxicity. In many developing countries, where drugs such as the aminoglycosides are frequently prescribed to treat pneumonia, diarrhoea, and tuberculosis, the incidence of ototoxicity is high. Physicians in practice need to recognize that ototoxic drugs can cause significant auditory and in many instances, poorly recognized, vestibular toxicity. Aminoglycosides can cause eighth cranial nerve damage, resulting in vestibular and/or auditory toxicities. Aminoglycosides appear to generate free radicals within the inner ear, with subsequent permanent damage to sensory cells and neurons, resulting in permanent hearing loss. Two mutations in the mitochondrial 12S ribosomal RNA gene have been previously reported to predispose carriers to aminoglycoside-induced ototoxicity. As aminoglycosides are indispensable agents both in the treatment of infections and Menieres disease, a great effort has been made to develop strategies to prevent aminoglycoside ototoxicity. Efforts have been made against streptomycin toxicity using corticosteroid and Caffeic acid phenethyl ester. Chemicals are being evaluated for their ability to prevent ototoxicity and that might be prescribed in tandem with ototoxic drugs in the future. Investigators are also studying methods of hair-cell and nerve-cell regeneration

Conceptions and Misconceptions about Computational Thinking among Italian Primary School Teachers

International audienceMany advanced countries are recognizing more and more the importance of teaching computing, in some cases even as early as in primary school. "Computational thinking" is the term often used to denote the conceptual core of computer science or "the way a computer scientist thinks", as Wing put it. Such term - given also the lack of a widely accepted definition - has become a "buzzword" meaning different things to different people. We investigated the Italian primary school teachers' conceptions about computational thinking by analyzing the results of a survey (N=972) conducted in the context of "Programma il Futuro" project. Teachers have been asked to provide a definition of computational thinking and to answer three additional related closed-ended questions. The analysis shows that, while almost half of teachers (43.4%) have included in their definitions some fundamental elements of computational thinking, very few (10.8%) have been able to provide an acceptably complete definition. On a more positive note, the majority is aware that computational thinking is not characterized by coding or by the use of information technology

Stock Market Analysis of 10 Different Countries in the Period of Disease COVID-19

Our effort is to analyze the effect of the rampant over the economies of 10 affected nations by studying their stock market values during the COVID-19 episode. We have endowed the nations with their respective stock markets stated in brackets - Brazil(Ibovespa), Canada (S&P/TSX Composite), France (AEX), Germany (DAX 30), India (NIFTY 50), Italy (FTSE MIB), Russia (IMOEX), Spain (IBEX 35), U.K. (FTSE 100), U.S.A. (DOW JONES INDUSTRIAL AVERAGE). We have gathered the indices of stock per country from 2 March to 23rd June, collected from official website of respective stocks. In order to collect data, we had to inculcate the fundamental lessons of Statistics. R-software aided us to plot the curves of stock values providing an ease to master our project. We also formulated a Python 3.7 language program code to solidify analysis on various aspects of economy of the countries and comparison between these aspects

Isolation and Characterization of Mannheimia varigena from a Murrah Buffalo

The present study was aimed to isolate and characterize phenotypically as well as genotypically bacterial strain from tracheal froth of a Murrah buffalo on the Government livestock farm (GLF) located at Hisar, Haryana. The isolate showed the cultural, morphological and biochemical properties of Mannheimia haemolytica as per Bergey's manual of determinative bacteriology and as confirmed by GENIII microplate (biolog). However, the isolate was further confirmed as Mannheimia varigena by 16S rRNA sequencing.