Scientific Texts Research Articles

ChatGPT, a Friend or a Foe in Medical Education: A Review of Strengths, Challenges, and Opportunities

Background: ChatGPT is a large-scale language model that utilizes artificial intelligence (AI) to answer a broad range of scientific inquiries, create clinical scenarios, and evaluate educational programs. While its use offers numerous advantages, it also presents several challenges. Objectives: The aim of this study is to conduct a comprehensive review of ChatGPT's functionality and explore the benefits, challenges, existing solutions, and future prospects of using AI in medical education. Method: A comprehensive literature review was conducted using PubMed, Scopus, Web of Science, and Google Scholar. The search phrases used were ChatGPT, Artificial Intelligence, Chatbot, Medical Education, and large language models (LLMs). Results: The application of ChatGPT in medical education offers several advantages, such as enhanced quality of interaction between medical students and patients, improved education quality, enhanced research opportunities, personalized learning, virtual patient simulations, and cost-effectiveness. However, there are also critical challenges, such as ethical and transparency concerns, limited access to reliable databases, restricted information availability after 2021, limited development of students' critical thinking ability, and the risk of generating AI hallucinations. Conclusions: Artificial intelligence models have become a popular tool for researchers to access scientific resources, comprehend articles and textbooks, and create scientific texts. ChatGPT has been used extensively in medicine and medical education in a short period. It is essential to weigh the benefits and challenges, use expert supervision, conduct frequent assessments, and provide feedback reviews to guarantee its efficacy. Although this technology should not replace human labor, it is essential to prepare for the changes brought by AI and create appropriate guidelines and curricula by reviewing existing solutions and conducting extensive studies.

The effects of generating examples on comprehension and metacomprehension.

Teachers and students often report using examples to support learning. Research has shown benefits of viewing provided examples and generating examples during declarative concept learning; however, there is less work showing clear benefits when learners generate their own examples on comprehension measures while students are attempting to learn from expository science texts. The present study tested whether generating examples would be useful for improving comprehension and comprehension monitoring in the context of an undergraduate science course. In a pre-post design, students completed an initial reading activity, followed by taking practice tests on each topic. Some students were assigned to complete an additional example generation activity after taking the practice tests. Some students also evaluated the quality of generated examples and received explanatory feedback. While there was an overall improvement in comprehension for all students, those who generated examples without the opportunity to evaluate the quality had the smallest overall learning gains. Students who evaluated the quality of examples showed the greatest learning gains on application-based test questions. And, although overall overconfidence decreased, there were no differences between conditions. These results suggest that example generation may not always be as helpful for improving learning as many students and teachers assume. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Semantic potential of L. Andreev’s story “Kusaka”

INTRODUCTION. The research will be useful not only to linguists and literary scholars, but also to literature teachers, since the works of L. Andreev are included in the school curriculum. The purpose of the work is to identify the semantic potential of L. Andreev’s story “Kusaka”. The relevance of the study is due to the need to study L. Andreev’s literary texts for modern philological science from the point of view of identifying the ability of units of different levels that are interconnected to act as markers of the mythical-poetic code.MATERIALS AND METHODS. The material of this work is the text of L. Andreev’s story “Kusaka”, which is a system of multi-level units, the analysis of which contributes to a deeper penetration into the author’s artistic intention. The work uses both general scientific and special linguistic methods: the method of linguistic observation and description, etymological, word-formation, onomastic, contextual, stylistic and linguocultural types of analysis.RESULTS AND DISCUSSION. It is shown that the literary text of L. Andreev is characterized by the interrelation of units of different levels, revealing the mythopoetic basis of the story, represented by the oppositions friend–foe, ligh–darkness, sound–silence. The dominant elements of the story are the lexemes house, yard, garden, sun, darkness. The diminutives used by the author when describing the girl and the dog create the image of a toy that is interesting and desirable in the present, but may be abandoned in the future due to loss of interest in it. Proper names (zoonyms Zhuchka, Kusaka, Kusachka and anthroponyms Lelya, Ilyusha, Dogaevs) and their absence have a special meaning.CONCLUSION. As in most of L. Andreev’s works, the story “Kusaka”, demonstrating the struggle of light with darkness, presents the path of gaining (Kusaka) and losing the soul (Lyolya and other people who for some reason are called kind). All this happens against the background of natural cyclicality – winter– spring–summer–autumn–... correlate with the natural processes of birth-development-old agedeath. Coming after the departure of the people who abandoned Kusaka, who again turned into just a nameless dog, the hopeless dark night becomes a symbol of lost hope, lost happiness.

Communicating research to practitioners – between scientific rigor, easy science and practitioners' self-perception of expertise

PurposeResearch shows that there are mechanisms of information simplification that lead to the danger that first, laypeople rely on their own epistemological skills when assessing scientific claims. Second, laypeople underestimate their dependence on experts when they receive simplified information. This underestimation can be problematic because scientific knowledge, due to its complexity, usually cannot be fully understood without further advice from experts. Compared to laypersons, adult education practitioners can be expected to have a higher level of scientific literacy in relation to knowledge in their professional field because they are familiar with the structure of knowledge through their formal education. The present study examines whether the “easiness effect” also occurs in adult education practitioners when they read simplified and highly simplified texts about research findings.Design/methodology/approach The sample consisted of 1.267 continuing education institutions. For the survey experiment, particioants were randomly assigned to tree text types at the end of the survey: easy, less scientific and scientific text. We used the difference-in-difference method to analyze the data. FindingsThe study examined whether easily presented research findings influenced self-assessment and reliance on experts. The results of our study support the hypothesis that the easiness effect is also present among professional practitioners.Originality/valueThe use of clear and nontechnical language is essential for ensuring that scientific knowledge is accessible and utilizable outside of academic circles. This aspect gains particular significance in educational research, as it enables professional practitioners to comprehend and ideally implement, research findings in their daily routines to address and resolve real-world challenges in their educational environments. Previous studies have demonstrated that the way text is presented influences laypeople's perceived reliance on experts. Building upon the conceptual framework of the easiness effect, this survey experiment took an additional step by focusing specifically on a targeted audience: professional practitioners in adult education.

Proteus (Proteus)

Beginning with his botanical epiphany in Sicily in 1787, Goethe turned to the ancient Greek sea god Proteus as a key figure for imagining natural metamorphosis. “Proteus” is perhaps a surprising term for a lexicon of philosophical concepts. Its connection to symbol, myth, and what Hegel would call representational thinking (Vorstellungsdenken) contrasts with more overtly abstract terms of philosophy. Yet for the unorthodox thinker, Goethe, who consistently straddled the line between literature and philosophy, the boundaries between symbolic representation and speculative abstraction were often porous. Nowhere is this more evident than in his theory of metamorphosis, which was developed throughout his life in an aggregate of scientific, poetic, and biographical texts. The lexeme “Proteus,” as Goethe used it, grows out of and defines this uniquely interdisciplinary thinking. Itself a deeply protean concept in his oeuvre, it gives occasion to consider the mutually productive relationship between philosophy, literature, and life within the broader constellation of Goethe’s thought. In this entry, I situate Goethe’s “protean” model of metamorphosis vis-à-vis his engagement with maritime environments and literature, specifically Homer’s Odyssey, during the period of the Italian journey (1786-1788). As a symbol, I argue, Proteus played an especially important role in Goethe’s dynamic reconception of natural forms as well as his rebuttal to the “terrestrially biased” imagery of Carl Linnaeus, who construed the formal characteristics of plants through metaphors of geographical enclosure. Additionally, I consider how Goethe’s “protean” botany informed his theory of natural types (Typen) and prepared his theory and practice of science as “zarte Empirie” (WA IV/45:11; delicate empiricism). By reading the mythical figure of Proteus back into the adjective “protean,” which is used to characterize Goethe’s view of nature in his scientific and poetic writings, we can uncover a uniquely Goethean conception of metamorphosis and creativity.

Scientific text citation analysis using CNN features and ensemble learning model.

Citation illustrates the link between citing and cited documents. Different aspects of achievements like the journal's impact factor, author's ranking, and peers' judgment are analyzed using citations. However, citations are given the same weight for determining these important metrics. However academics contend that not all citations can ever have equal weight. Predominantly, such rankings are based on quantitative measures and the qualitative aspect is completely ignored. For a fair evaluation, qualitative evaluation of citations is needed in addition to quantitative ones. Many existing works that use qualitative evaluation consider binary class and categorize citations as important or unimportant. This study considers multi-class tasks for citation sentiments on imbalanced data and presents a novel framework for sentiment analysis in in-text citations of research articles. In the proposed technique, features are retrieved using a convolutional neural network (CNN), and classification is performed using a voting classifier that combines Logistic Regression (LR) and Stochastic Gradient Descent (SGD). The class imbalance problem is handled by the synthetic minority oversampling technique (SMOTE). Extensive experiments are performed in comparison with the proposed approach using SMOTE-generated data and machine learning models by term frequency (TF), and term frequency-inverse document frequency (TF-IDF) to evaluate the efficacy of the proposed approach for citation analysis. It is found that the proposed voting classifier using CNN features achieves an accuracy, precision, recall, and F1 score of 0.99 for all. This work not only advances the field of sentiment analysis in academic citations but also underscores the importance of incorporating qualitative aspects in evaluating the impact and sentiments conveyed through citations.

Kajian Penulisan Teks Akademik Bagi Mahasiswa Terhadap Peningkatan Keterampilan Menulis

Essays or essays and students, whether at elementary, intermediate, or higher levels, often produce poor results. Many mistakes are made regarding spelling, word choice, and sentence structure. Many students do not understand scientific texts and their rules. This misunderstanding These misconceptions are very seriously researched considering the efforts of the government, educational institutions, including universities, to improve the culture of research in the academics. This research uses a qualitative method with the type of approach in the form of a library study. The results of the research It was found that the factors that cause difficulties in writing scientific papers are, for example, the low motivation of students in writing, lack of confidence and in writing, lack of confidence and lack of mood, low interest in reading, low student curiosity, and students' understanding of scientific papers that are not good scientific writing as well as low mastery of the writing the rules of writing.

Readers’ Behavior during a Monitoring Task in English as a Foreign Language: Connecting Outcomes and Mental Processing

Metacognitive skills are important for text comprehension, especially at university where most learning processes are unsupervised, and students rely on self-control and regulation when reading for comprehension. In today’s universities, English as L2 has become the vehicle language for teaching and learning. However, some studies have concluded that university students who read English as L2 have inadequate metacognitive monitoring skills. Higher level processing skills, such as comprehension monitoring, are difficult to study and then improve. The main goal of the present study was to analyze the mental processing of readers when they monitored expository texts in English as L2 considering their English proficiency. Mental processing was related to readers’ behavior when performing a reading task by using a set of variables guided by a psychological mechanism proposed for inconsistency detection. A total of 169 university students participated. The task was modeled on the error detection paradigm, which involved assessing the comprehensibility of scientific texts in English and reporting comprehension difficulties encountered. A special software was used to collect detailed data online about the readers’ text processing and written reports. The results confirmed the set of processing variables and the theory-based predictions.

Advancing language models through domain knowledge integration: a comprehensive approach to training, evaluation, and optimization of social scientific neural word embeddings

This article proposes a comprehensive strategy for training, evaluating, and optimizing domain-specific word2vec-based word embeddings, using social science literature as an example. Our primary objectives are: (1) to train the embeddings utilizing a corpus of social science text, (2) to test their performance against domain-unspecific embeddings using our developed intrinsic and extrinsic evaluation strategy, and (3) to enhance their performance even further by using domain knowledge. As an integral part of this approach, we present SociRel-461, a domain-knowledge dictionary designed for the intrinsic evaluation and subsequent refinement of social science word embeddings. Using a dataset of 100,000 full-text scientific articles in sociology, we train multiple vector space models, which we then benchmark against a larger, pre-trained general language embedding model as part of our extrinsic evaluation. Furthermore, we developed a transfer learning multi-label classification task for extrinsic evaluation. Our findings reveal that domain-specific embeddings outperform their domain-unspecific counterparts in both intrinsic and extrinsic evaluations. We also investigated the retrofitting post-processing method to enhance domain-unspecific embeddings with the domain knowledge embedded in SociRel-461. While retrofitting does not enhance our domain-specific vector space models, it significantly improves the performance of the domain-unspecific embeddings. This highlights the potential of retrofitting for the transfer of domain knowledge to domain-unspecific embeddings. Our results emphasize the importance of utilizing domain-specific word embeddings for better performance in domain specific transfer learning tasks, as they outperform conventional embeddings trained on everyday language.

Exploring named‐entity recognition techniques for academic books

Recent advances in the natural language processing (NLP) field have achieved impressive results in various tasks. However, NLP techniques are underrepresented in the analysis of Humanities and Social Science texts and in languages other than English. In particular, academic books are a highly valuable source of information that has not been exploited by these techniques at all. The recognition of named entities (person names, organizations or locations) and their semantic annotation over books could enrich the visibility and discoverability of the information by users. This is an opportunity for academia and the academic publishing industry in which semantic search is a central task and now books can be queried by named entities of interest that are in their content. This work proposes a methodology to apply named‐entity recognition to publish the results into an ontological semantic‐web format. The work has been performed over a corpus of academic books provided by UNE (Unión de Editoriales Universitarias Españolas, Union of Spanish University Presses). Results show an enrichment of the information extracted over the books and of the possibilities of querying them at the individual level but also within the whole set of books, increasing the possibilities for books to be discovered or retrieved beyond metadata.

Annotating Materials Science Text: A Semi-automated Approach for Crafting Outputs with Gemini Pro

Annotating Materials Science Text: A Semi-automated Approach for Crafting Outputs with Gemini Pro

READING INTEREST CHARACTER OF PROSPECTIVE ELEMENTARY SCHOOL TEACHERS AT UNIVERSITAS PENDIDIKAN INDONESIA

Reading interest is one of the fundamental skills in language and is a highly effective learning activity for acquiring knowledge and literacy. Reading literacy is an essential skill, particularly for prospective educators; however, many students experience challenges in cultivating a reading habit. This research aims to: (1) describe the reading interest conditions of prospective teacher students at Universitas Pendidikan Indonesia (UPI), (2) elucidate the supporting and inhibiting factors for prospective teacher students (PTS) at UPI in their reading activities. This study employs a quantitative approach with a survey design. The research subjects are UPI PGSD (Elementary School Teacher Education) students. Data collection methods include questionnaires, surveys, and interviews. Data analysis involves descriptive analysis, frequency distribution, and percentage calculation. The findings reveal that: (1) the overall reading interest of PTS is categorized as low, (2) students' activities on campus before class hours mainly involve waiting and chatting with friends; only a small portion of students utilize their free time to read books or visit the library. (3) PTS' preferred books are novels and fiction, while scientific texts are less favored due to unappealing design and layout, (4) the time spent on reading books by PTS is relatively short, with less than 1 hour daily, and some do not allocate any time for reading, except when there are assignments or exams, (5) the major inhibiting factors for PTS in reading are internal, indicated by low reading habits or preferences for other interests over reading.

Blackout Poetry: Eclipsing With Words and Images to Illuminate Ideas.

Integrating literacy practices in science classrooms can help students read complex scientific text, write arguments as part of shared cross-disciplinary practices, and engage with content. In the Linking Science, Mathematics, and Literacy for All Learners program, middle school science, mathematics, ELA, and special education teachers have been implementing multimodal STEM text sets that include a range of texts and scaffolds that support instruction and students' content learning. One of these strategies combines reading and writing in unique and creative ways: poetry writing! Blackout and found poems are accessible approaches to help students focus on key words and ideas in a complex text, pull out those words to work with them, and then reconstruct them into a poem. This approach can be used in a variety of ways, and in some of the examples provided, students include an altered page from a scientific article on which they find their words, black out the rest of the text, and then illustrate the entire document to help show their message.

Policy Dialogue on Twenty-First-Century Book Banning in the US

AbstractBook banning is a topic covered in many US history classrooms. Students learn that in the first decades of the twentieth century, fights over the teaching of evolution led to restrictions on science texts. Meanwhile, fears about the spread of communism sparked campaigns to limit access to “subversive” ideas. Well into the 1960s, textbooks usually explain, Americans remained at odds about what schools should be free to teach.What’s old is new, it seems. And tomorrow’s textbooks will have to be updated with stories from the present. As this issue goes to press, conservative groups across the United States have sought to remove hundreds of titles from schools and libraries. Such attempts range from challenges filed by individual parents—often inspired by the list curated on BookLooks.org—to statewide legislative efforts to recall books from schools. Thousands of books have been removed from libraries and classrooms, and the chilling effect has led cautious educators to self-censor even further.For this policy dialogue, the HEQ editors asked Adam Laats and Kasey Meehan to discuss book banning in the US, focusing particularly on the motivations of groups seeking to limit what young people can read. Adam Laats is a professor of education and history at SUNY Binghamton. A leading scholar of conservative activism in education, he is the author of several books including The Other School Reformers (Harvard University Press, 2015) and Fundamentalist U (Oxford University Press, 2018). Kasey Meehan is the director of the Freedom to Read program at PEN America, where she leads initiatives to protect the right of students to freely access literature in schools. Founded in 1922, PEN America is the largest of the more than one hundred centers worldwide that make up the PEN International network. PEN America works to ensure that people everywhere have the freedom to create literature, to convey information and ideas, to express their views, and to access the views, ideas, and literatures of others.HEQ policy dialogues are, by design, intended to promote an informal, free exchange of ideas between scholars. At the end of the exchange, we offer a list of references for readers who wish to follow up on sources relevant to the discussion.

Language Use: A study on the Differences Between Scientific Texts, Non-Scientific Texts and Oral Expression

Language Use: A study on the Differences Between Scientific Texts, Non-Scientific Texts and Oral Expression

The legacy of Nizami Ganjavi in Transoxiana: An analysis of Khamsa's influence on oral narrative

Nizami Ganjavi, one of the distinguished poets of the 12th century, has a special place in world literature with his works from ancient times to the present. This poet is famous not only in Persian literature but also in Turkish and Indian literature. Nizami Ganjavi is related to the Mesnevi works, which were translated into Turkish and even translated by many Turkish poets and writers in the following centuries. Among these, we can count the essential figures of Chagatai Turkish literature (Transoxiana), especially Emir Alişer Nevai, who cared about Mesnevi Khamsa Nizami and made changes and wrote examples based on his stories. Nizâmî, with the dreams and images created in the Mesnevi above, has revealed an original style that is very important in today's comparative literature field at the international level. He proved his success by creating a new style of fantasy drawing using imaginary images, and many poets influenced by him entered the field of literature. This article refers to Panj Ganj or Khamsa Nizami Ganjavi's works and tries to explore his influence on Transoxiana writers. The study uses a qualitative, library, and comparative methodology and is founded on the laws and categories of scientific research. Researchers applied modern research approaches and methods (general scientific analysis, comparison, generalization, systematization, text analysis, and retrospective analysis).

The Effect of an Inquiry Strategy Based on Employing Educational Explanations in the Acquisition of Scientific Concepts among Third-Grade Students

The study aimed to identifying the effect of of an inquiry strategy based on employing educational explanations in the acquisition of scientific concepts among third-grade students. The study sample consisted of two divisions with a total of (39) students. One of these divisions was randomly selected to be a control group. It consisted of (19) students. The educational material was taught in the usual method. The other was an experimental group. Consisted of (20) students. The educational material was taught using a directed inquiry strategy based on the employment of educational explanations. To achieve the objectives of the study, the quasi- experimental methodology was used. A test for acquiring scientific concepts was prepared. The findings showed that there was a significance slgnificant difference at (α≤0.05), in favor of the experimental group that was taught by using directed inquiry strategy based on employing educational explanations. The size of the effect was large according to the standard used in the study. The study also showed a positive correlation between the acquisition of scientific concepts and achievement in science. Based on the findings of the study, it was recommended to use this strategy in teaching science text topics to achieve better learning.

Informing research on generative artificial intelligence from a language and literacy perspective: A meta‐synthesis of studies in science education

AbstractResearch in languages and literacies in science education (LLSE) has developed substantial theoretical and pedagogical insights into how students learn science through language, discourse, and multimodal representations. At the same time, language is central to the functioning of generative artificial intelligence (GenAI). On this common basis concerning the role of language, this paper explores how foundational ideas from LLSE studies can inform the use of GenAI in science education. A bibliometric analysis of 412 journal articles from Web of Science provided the initial step to identify major themes and relationships in the LLSE literature. The analysis revealed four clusters of research in LLSE: reading and writing scientific text, science discourse and interaction, multilingual science classroom, and multimodality and representations. Each cluster was further analyzed through close reading of selected articles to identify and connect key constructs to the potential use of GenAI. These constructs include the interactive‐constructive reading model, text genre, reading‐writing integration, dialogic interaction, critical questioning, argumentation, translanguaging, hybridity, thematic pattern, modal affordance, and transduction. From these ideas and connections, the paper recommends several pedagogical principles for science educators to guide the use of GenAI. It concludes that LLSE research offers valuable insights for researchers and teachers to investigate and design the use of GenAI in science education. In turn, the impending use of GenAI also calls for a rethinking of literacy that will shape future research in LLSE.

The challenges and perspectives of remote teaching in the pandemic period: reflections on teaching practice in online geography teaching

Remote teaching requires that families have the appropriate equipment to monitor the content and activities that are passed on by the school, in addition to knowledge focused on the pedagogical axes of the teaching-learning process. The objective of this article is to understand the students'/families' conception of remote teaching and the main challenges and perspectives during the pandemic period. To develop this study, a bibliographical research was used, carrying out a survey on scientific journal websites, databases and texts of theses, dissertations, articles and/other printed and online scientific productions. It was noticed that this form of remote teaching brought a lot of difficulty, both for students in terms of learning and for families. As classes have been suspended since March 2020 to prevent the spread of COVID-19, there was no other teaching possibility for this pandemic moment. Therefore, it is understood that this is a moment of overcoming for all education professionals, students, families and new forms of social coexistence.

Methods of Automatic Analysis of Information Presentation Dynamics in Texts Based on Adaptable Dictionaries of Scientific Terms

The paper proposes a method for determining the dynamics of aspectual content of scientific texts. The problems arising in the automatic processing of scientific texts are discussed, approaches to the creation of a combined method of aspect-oriented analysis of scientific texts are proposed. The results of experiments of aspect analysis of scientific publications in the field of mathematics are given. The algorithm of aspect analysis is built on the basis of processing both the semantic domain graph formed as a result of automatic extraction of information from the text of the mathematical encyclopedia and the weighted semantic graph of the publication. Weighting functions for calculating the dependence of links between professional terms of the semantic domain graph are proposed. During the processing the text of a scientific publication, the semantic domain graph is transformed into the semantic graph of the publication, the two-phase processing algorithm of which forms semantic dependencies between text fragments.