Text Comprehension Research Articles

Improving reading comprehension of explanatory texts in indonesian language subject, fifth grade students through RADEC learning model

This study aims to improve the reading comprehension of explanatory texts in Indonesian subjects, fifth grade elementary school students through a problem based learning model based on RADEC. The subjects of this study were the fifth grade students of SD Gemala Ananda as many as 16 people. The method of data collection was done through test techniques in the form of multiple choice test questions and non-tests in the form of observation sheets and interviews. This classroom action research was conducted in two cycles, each cycle having systematic steps consisting of action planning, implementation, and observation and reflection. The results of this study indicate that the use of the RADEC-based problem-based learning model can improve the reading comprehension of the fifth grade elementary school explanatory text. In addition, student activities in learning are increasing and more interactive. Students are also more critical and dare to express their ideas, and can find answers to the problems presented by the teacher.

Reading Comprehension Ability of Tharu and Non Tharu Students

Reading comprehension is crucial because it enables students to understand, interpret, and engage with texts, fostering critical thinking and effective communication skills. This study investigates the reading proficiency of Tharu and non-Tharu students within a multilingual educational framework. The data was collected from a sample of 30 grade four students (15 Tharu and 15 non-Tharu) who studied at a community school in Kohalpur Municipality, Banke District during the academic year 2080/81 B.S. The researcher employed stratified simple random sampling method to ensure representativeness. Data collection included reading comprehension tests, vocabulary assessments, and other skill-based tasks aligned with the multilingual education curriculum. Basic statistical tools were used for analysis. The findings indicate marginal differences in overall academic performance between Tharu and non-Tharu students. Tharu students showed strengths in specific skill domains such as comprehension of unseen texts and vocabulary application. Despite this, it underscores the influence of educational backgrounds and cultural factors on academic outcomes. This highlights the need for tailored pedagogical strategies for teaching reading in diverse linguistic contexts.

What Quality Talk in a Reading Circle Does for Interthinking

ABSTRACT In the English for Academic Purposes (EAP) classroom, speaking is a relatively marginalised learning activity, often employed merely to facilitate transition between activities which prioritise communication skills deemed more important. A significant consequence of this privation is limited practice in situated discourse. This paper presents a theorised account of an instance of situated discourse: Quality Talk in a reading circle within an EAP classroom. With reference to a single dialogic spell unfolding around a specific issue, I examine participants’ verbal transactions and the ways in which these enhance high-level comprehension of text. Overall, this account seeks to highlight the efficacy and affordances of situated discourse as a social mode of cognition in EAP instruction.

Impact de la gestion planifiée du tableau blanc en classe de FLE sur la compétence de compréhension de l’écrit d’un texte en l2 : cas des apprenants de 4eme AM

Simple, inexpensive and relatively durable, the board seems a natural part of class. Paradoxically, considering it as a teaching technique in its own right (Cuq & Gruca, 2005) may seem surprising, but in reality, it is the most widespread technological medium in the classroom. Therefore, writing on the board is a practice considered an integral part of the teaching profession in order to streamline the transmission of knowledge. Despite the fact that its presence is almost systematic in all classes, its use and management are little studied. Reorganizing, witnessing interactions and materializing the transition from oral to written, the functions of the board are multiple, however, are teachers and learners aware of this? What representations do they have of the painting? Indeed, we attempted through a semi-directive interview, intended for 4th AMlearners, to show whether they consider the whiteboard as a didactic tool and, to identify their representations in relation to the role that this tool would play in their learning in class, more particularly during a session of reading comprehension of an argumentative text. Furthermore, the preliminary results showed on the one hand the preponderant role played by the blackboard in the FFL class and on the other hand, that its management and organization are two factors which allowed optimal performance and a considerable contribution current teaching/learning techniques.

Accuracy Analysis of DeepL: Breakthroughs in Machine Translation Technology

This study examines the accuracy and technological innovations of DeepL, a prominent machine translation tool. Through a comprehensive literature review, we analyze DeepL's performance compared to other translation systems, exploring its advanced neural network architecture and training methods. Key findings indicate that DeepL consistently outperforms other tools in BLEU scores and human evaluations, particularly excelling in handling context, idiomatic expressions, and specialized terminology. The research highlights DeepL's use of the Transformer model, diverse training data, and techniques like transfer learning and data augmentation. Practical applications across academic, professional, and educational sectors are discussed, with special emphasis on how DeepL benefits students and teachers by facilitating multilingual learning, enhancing comprehension of foreign texts, and assisting in accurate translation of academic materials. User feedback underscores DeepL's accuracy and user-friendly features. While demonstrating significant advancements in machine translation technology, this study also acknowledges areas for potential improvement, contributing to the ongoing development of AI-driven language solutions.

Developing Poster as Media in Teaching Reading Comprehension of Descriptive Text

Developing Poster as Media in Teaching Reading Comprehension of Descriptive Text

Primary students’ empathic text comprehension and transportation and their relations to childrens’ personal and motivational characteristics and text presentation types

Primary students’ empathic text comprehension and transportation and their relations to childrens’ personal and motivational characteristics and text presentation types

Factors Influencing Comprehension of Metaphors in Academic Reading Texts among Iraqi EFL Learners

Metaphor is recognized as a valuable tool for analysis and as a means to effectively convey meaning. Although metaphor is supposed to be used to effectively convey meaning, learners of English, particularly those in the foreign language context, often have difficulty comprehending metaphors in academic text. The current study aims to contribute to understand deeply of the influencing factors on metaphor comprehension among Iraqi EFL learners when they read academic texts. The study draws on Steen’s (2010) MIPVU model and Lakoff and Johnson’s (1980) Conceptual Metaphor Theory to identify and analyze the metaphorical expressions. The data for the study were collected from two academic reading comprehension texts. Five Iraqi EFL university learners participated in determining the metaphors contained in the texts. The findings revealed that authors of academic texts often incorporate a wide range of metaphorical expressions. These expressions can vary in their familiarity, ranging from very familiar to less familiar and even unfamiliar, to engage readers’ cognitive processes and facilitate the conceptualization of the metaphor. The findings revealed that the factors influencing metaphor comprehension are varied and that they are of two broad types: external factors related to cultural and social considerations, and internal factors related to linguistic and educational settings. The findings could enable practitioners to devise more effective approaches for teaching metaphor comprehension to EFL learners.

BUILDING A SCALABLE DATASET FOR FRIDAY SERMONS OF AUDIO AND TEXT (SAT)

Context. Today, collecting and creating datasets in various sectors has become increasingly prevalent. Despite this widespread data production, a gap still exists in specialized domains, particularly in the Islamic Friday Sermons (IFS) domain. It is rich with theological, cultural, and linguistic studies that are relevant to Arab and Muslim countries, not just religious discourses. Objective. The goal of this research is to bridge this lack by introducing a comprehensive Sermon Audio and Text (SAT) dataset with its metadata. It seeks to provide an extensive resource for religion, linguistics, and sociology studies. Moreover, it aims to support advancements in Artificial Intelligence (AI), such as Natural Language Processing and Speech Recognition technologies. Method. The development of the SAT dataset was conducted through four distinct phases: planning, creation and processing, measurement, and deployment. The SAT dataset contains a collection of 21,253 audio and corresponding transcript files that were successfully created. Advanced audio processing techniques were used to enhance speech recognition and provide a dataset that is suitable for wide-range use. Results. The fine-tuned SAT dataset achieved a 5.13% Word Error Rate (WER), indicating a significant improvement in accuracy compared to the baseline model of Microsoft Azure Speech. This achievement indicates the dataset’s quality and the employed processing techniques’ effectiveness. In light of this, a novel Closest Matching Phrase (CMP) algorithm was developed to enhance the high confidence of equivalent speech-to-text by adjusting lower ratio phrases. Conclusions. This research contributes significant impact and insight into different studies, such as religion, linguistics, and sociology, providing invaluable insights and resources. In addition, it is demonstrating its potential in Artificial Intelligence (AI) and supporting its applications. In future research, we will focus on enriching this dataset expansion by adding a sign language video corpus, using advanced alignment techniques. It will support ongoing Machine Translation (MT) developments for a broader understanding of Islamic Friday Sermons across different linguistics and cultures.

Digital and print media texts and their comprehension by young adults – preliminary research results

The purpose of this article is to identify differences in the comprehension of print and digital media texts among young adults. This is due to the paradigm of transactional communication models (Yaros 2009 et al.), which assumes interaction between the medium and the audience, which corresponds to current changes in the media environment (Herkman 2008) and the accelerated digitization of mass media. The discussion of interaction with electronic texts and hypertexts (Singer 2017; Mangen 2013; DeStefano 2007 and others) opens up new research horizons and topics. Researchers from abroad (Norway, UK, etc.) have reported conflicting results regarding the level of comprehension of print and digital media texts, due to the length of the text, type of digital medium, target groups, etc. The recent COVID-19 pandemic has highlighted the importance of digital communication in both media and other areas (education). In order to solve the formulated research problems, a descriptive-mapping and correlation research plan was developed, using a standardized method adapted to the digital environment. A total of 486 respondents were surveyed, 173 of whom met the criteria for participation in both measurements, with an average age of 21.82. The results (compiled using MS Excel and SPSS software) show that there is no difference in the level of comprehension of media texts presented in print and digital form. At the same time, we found that although the values of correlation coefficients indicate that a higher level of text difficulty can lead to lower text comprehension scores (negative “r” values), a higher level of text difficulty is not related to the level of text comprehension. The results are discussed, not only limitations but also broader contexts (e.g., non-cognitive factors) are considered, and some implications for media practice and education are proposed.

Socio-emotional behavior, learning, and the distinct contributions of Executive Functions in primary graders

Socio-emotional school behavior and learning are both fundamental aspects of children’s development influenced by cognitive control processes named Executive Functions (EF). Yet, research on school-age children has often focused on the relationship between EF and learning skills overlooking that of EF and school behavior, which has usually been examined among preschoolers. The current study investigated the contribution of EF in both school behavior and learning in school-age children. One hundred forty-six III–V graders were assessed using text comprehension and EF tasks and evaluated by teachers-rated inventories on behavioral difficulties and EF within the school context. The results suggested a different involvement of direct and indirect EF measures in the two domains considered: controlling for socioeconomic level and age, an EF direct measure, predicted reading comprehension whereas teacher-reported EF related to both behavior and text comprehension. The results contribute to defining the role of cognitive control processes on school behavior and learning in school-age children.

Evaluating computer science students reading comprehension of educational multimedia-enhanced text using scalable eye-tracking methodology

In this research, a mixed-method approach was employed to conduct large-scale eye-tracking measurements, traditionally associated with high costs and extensive time commitments. Utilizing consumer-grade webcams in conjunction with open-source software, data was collected from an expansive cohort of students, thereby demonstrating the scalability and cost-effectiveness of this innovative methodology. The primary objective of this research was to discern the disparities in reading behaviour when students were presented with standard text accompanied by illustrations, compared to the same text with highlighted key terms. The participants, comprised of first-year university students, completed a questionnaire and an introductory test to ascertain their knowledge level. Subsequently, they were segregated into two groups and participated in two reading sessions, during which their ocular movements were recorded. The amassed data underwent both qualitative analyses, facilitated by visualizations, and quantitative analysis, employing statistical measures on the data and test results. Notably, no significant difference was observed in the gaze patterns or test results between the experimental and control groups. However, a significant divergence in gaze patterns was identified between high-achieving students and those experiencing difficulties, as evidenced by the averaged composite heatmaps generated from the data. The findings underscore two pivotal points. Firstly, the feasibility of conducting large-scale eye-tracking experiments is demonstrated. Traditional studies in this field often employ small population samples due to the time and financial constraints associated with methods that utilize specialized eye-tracking hardware. In contrast, our methodology is scalable, relying on low-end hardware and enabling students to record data on their personal devices. Secondly, while eye-tracking may not provide substantial benefits for fine-tuning text already optimized for readability, it could serve as a valuable tool for identifying and assisting learners who are struggling. This mixed-method approach holds significant potential to revolutionize the conduct and interpretation of eye-tracking studies within educational settings.

Children's Interpretations of Numerically Quantified Expression Ambiguities: Evidence from Quantified Noun Phrases and Bare Cardinals.

Understanding how children comprehend text by forming links between sentences has been the focus of research for decades. Such research has consistently shown that children use anaphors and resolve ambiguities in a different manner than adults. The present study examined a less-studied anaphoric reference that arises when two numerically quantified expressions (e.g., "three cats… two cats…") are used in the text. Focusing on 249 six- to eight-year-old children and 50 adults for comparison, the study employed a picture selection task across six experiments to assess interpretative preferences in ambiguous and unambiguous discourses containing numerically quantified expressions. The findings indicate a pronounced difference in interpretative strategies: unlike adults, who predominantly adopted an anaphoric subset reading, children showed a consistent preference for the non-anaphoric reading, even in contexts explicitly disambiguated towards this interpretation. This preference persisted across various experimental manipulations, highlighting challenges in text integration and comprehension among children. Contributing to the developmental trajectory of language comprehension, this study underscores the complexity of cognitive development and linguistic interpretation, revealing significant developmental differences in processing numerically quantified expressions and anaphoric references within discourse.

Implementation of explanatory texts output for bridge damage in a bridge inspection web system

Bridge photographs contain significant technical information, such as damaged structural parts and types of damage, yet interpreting these details is not always straightforward. Despite the advancements in image analysis for bridge inspection, there remains a significant gap in converting these images into comprehensible explanatory texts that can be readily used by less experienced engineers and administrative staff for effective maintenance decision-making. In this study, we developed a model that generates explanatory texts from bridge images based on a deep learning model, and we also developed a web system that can be utilized during bridge inspections. The proposed method enables the provision of user-friendly, text-based explanations of bridge damage within images, allowing relatively inexperienced engineers and administrative staff without extensive technical expertise to understand the representation of bridge damage in text form. Additionally, we have developed a system that continually trains and improves its performance by accumulating data as users interact with it. This paper describes the image captioning technique for generating explanatory texts and the structure of the web system.

PELATIHAN PENGGUNAAN STRATEGI HÖR-SEHEN DALAM MENINGKATKAN KEMAMPUAN MEMAHAMI TEKS BAGI GURU BAHASA JERMAN DI KOTA AMBON

Hör-Sehen is a strategy that combines what is heard and what is seen, or what is called an audio-visual technique, making it easier for students to understand the content of the text. This community service aims to prepare teachers through training on the use of the Hör-Sehen strategy for improving text comprehension skills for German language teachers. In addition, this training is very appropriate to be implemented as a strategy to be used by teachers not only in listening skills but as a combination of what is heard and what is seen. Thus, teachers can apply it to the teaching and learning process in the classroom. The PKM activities carried out by the team for German language teachers in Ambon City are expected to help teachers improve students' understanding of German texts.

SPROUT: an Interactive Authoring Tool for Generating Programming Tutorials with the Visualization of Large Language Models.

The rapid development of large language models (LLMs), such as ChatGPT, has revolutionized the efficiency of creating programming tutorials. LLMs can be instructed with text prompts to generate comprehensive text descriptions for code snippets provided by users. However, the lack of transparency in the end-to-end generation process has hindered the understanding of model behavior and limited user control over the generated results. To tackle this challenge, we introduce a novel approach that breaks down the programming tutorial creation task into actionable steps. By employing the tree-of-thought method, LLMs engage in an exploratory process to generate diverse and faithful programming tutorials. We then present SPROUT, an authoring tool equipped with a series of interactive visualizations that empower users to have greater control and understanding of the programming tutorial creation process. A formal user study demonstrated the effectiveness of SPROUT, showing that our tool assists users to actively participate in the programming tutorial creation process, leading to more reliable and customizable results. By providing users with greater control and understanding, SPROUT enhances the user experience and improves the overall quality of programming tutorial.A free copy of this paper and all supplemental materials are available at https://osf.io/uez2t/?view only = 5102e958802341daa414707646428f86.

Clinical research text summarization method based on fusion of domain knowledge

ObjectiveThe objective of this study is to integrate PICO knowledge into the clinical research text summarization process, aiming to enhance the model’s comprehension of biomedical texts while capturing crucial content from the perspective of summary readers, ultimately improving the quality of summaries. MethodsWe propose a clinical research text summarization method called DKGE-PEGASUS (Domain-Knowledge and Graph Convolutional Enhanced PEGASUS), which is based on integrating domain knowledge. The model mainly consists of three components: a PICO label prediction module, a text information re-mining unit based on Graph Convolutional Neural Networks (GCN), and a pre-trained summarization model. First, the PICO label prediction module is used to identify PICO elements in clinical research texts while obtaining word embeddings enriched with PICO knowledge. Then, we use GCN to reinforce the encoder of the pre-trained summarization model to achieve deeper text information mining while explicitly injecting PICO knowledge. Finally, the outputs of the PICO label prediction module, the GCN text information re-mining unit, and the encoder of the pre-trained model are fused to produce the final coding results, which are then decoded by the decoder to generate summaries. ResultsExperiments conducted on two datasets, PubMed and CDSR, demonstrated the effectiveness of our method. The Rouge-1 scores achieved were 42.64 and 38.57, respectively. Furthermore, the quality of our summarization results was found to significantly outperform the baseline model in comparisons of summarization results for a segment of biomedical text. ConclusionThe method proposed in this paper is better equipped to identify critical elements in clinical research texts and produce a higher-quality summary.

모의재판식 토론을 통해 포의 ｢검은 고양이｣ 가르치기

This essay explores the effects of teaching Edgar Allan Poe’s “The Black Cat” through mock trial debate. Based on the assumption that the mock trial debate form can complement the shortcomings of general discussion, the project assigns each student a different role - the accused narrator and his lawyer, the policeman as a witness and prosecutor, judge and court clerk. After preparing for 25 minutes, students start the mock trial under the judge’s moderation. The clerk records the process and presents the final verdict to the whole class. Through this approach, students are expected to improve skills not only for close reading, but also for reading with the grain and against the grain altogether; they are also expected to learn how to support their argument with evidence, persuade others, make a balanced decision, and deliver it neutrally. The mock trial debate was carried out in the fall semesters of 2022 and 2023, and was followed by a survey that asked students whether the experienced improvement in five areas: interest, text comprehension, critical thinking ability, communication skills, and other skills. The students answered most of the questions positively, thereby affirming the effectiveness of mock trial debate in the lesson on “The Black Cat.” The experiment exemplifies how we can develop our expertise as researchers and teachers to maximize the effectiveness of discussion.

SMOG (Simple Measure of Goobledygook) Readibility Index in Selecting Reading Materials and Reading Literacy Skills of Primary School Student

Reading materials for elementary school students generally do not have readability in accordance with the measurement results so that the literacy level of students is low, as shown by the survey results from the United Nations Educational, Scientific and Cultural Organization which noted that the literacy level of Indonesian society was only 0.001 percent. Therefore, it is necessary to measure readability so that the material in books used in learning is in accordance with the age level of readers and can be understood by students. With these conditions, this study aims to overcome the problem of reading materials in elementary schools that are not in accordance with their readability so that they do not support efforts to develop reading literacy. Reading materials in elementary schools need to be measured through a readability measurement in order to know the suitability of readability with the age of the reader. One of the formulas that can be used to measure readability is the SMOG formula (Simple Measure of Goobledygook), this formula is simpler because it does not use graphs only considers the number of sentences and difficult words. This research uses quantitative methods in the process of measuring and collecting data. The research instruments used text readability measurement, text comprehension instrument questionnaire, literacy measurement and student reading habit questionnaire. Based on the results of the linear regression test, there is a relationship between the results of the readability measurement and the results of the student comprehension measurement of 0.688. The positive correlation shows that the higher the score value of the readability measurement results, the lower the students' understanding of the reading. The results show that reading books used in elementary schools have a high readability index value, so that it can reduce students' understanding of reading materials used in learning.

Molecular NMR shieldings, J-couplings, and magnetizabilities from numeric atom-centered orbital based density-functional calculations

This paper reports and benchmarks a new implementation of nuclear magnetic resonance shieldings, magnetizabilities, and J-couplings for molecules within semilocal density functional theory, based on numeric atom-centered orbital (NAO) basis sets. NAO basis sets are attractive for the calculation of these nuclear magnetic resonance (NMR) parameters because NAOs provide accurate atomic orbital representations especially near the nucleus, enabling high-quality results at modest computational cost. Moreover, NAOs are readily adaptable for linear scaling methods, enabling efficient calculations of large systems. The paper has five main parts: (1) It reviews the formalism of density functional calculations of NMR parameters in one comprehensive text to make the mathematical background available in a self-contained way. (2) The paper quantifies the attainable precision of NAO basis sets for shieldings in comparison to specialized Gaussian basis sets, showing similar performance for similar basis set size. (3) The paper quantifies the precision of calculated magnetizabilities, where the NAO basis sets appear to outperform several established Gaussian basis sets of similar size. (4) The paper quantifies the precision of computed J-couplings, for which a group of customized NAO basis sets achieves precision of ∼Hz for smaller basis set sizes than some established Gaussian basis sets. (5) The paper demonstrates that the implementation is applicable to systems beyond 1000 atoms in size.