Reading Assistance Research Articles

Pendampingan Pembacaan Doa Selamat Setelah Belajar Sebagai Pembentukan Spiritual Siswa XI BRL 2 di SMKN 2 Palangka Raya

Prayer is an expression or communication between a person and God, which usually includes requests, praise, gratitude, or a request for forgiveness. The problems faced in the field are related to students' lack of understanding of prayer and the importance of spirituality in the learning process. Many students are not used to reading prayers correctly, so that religious values ​​are not fully absorbed in daily activities at school. The purpose of this service is to increase students' awareness of the importance of spirituality in the learning process and to create a positive culture in the school environment. The method used is Participatory Action Research (PAR). Data were collected through direct observation and interviews with students where students were actively involved in the activity of reading a prayer of congratulations at the end of learning. The results showed that students better understood the meaning of prayer and were more involved and interested in reading it after studying. It is hoped that this activity can improve students' character and increase their gratitude for the knowledge they have learned. The results of the study also showed that, as part of student character development, schools should involve similar activities in the formation of religious character. Therefore, prayer reading assistance activities can be used as a way to show that students have gained a better understanding of the importance of prayer and have improved their ability to read prayers correctly and regularly. It is recommended that such activities be conducted regularly to strengthen students' religious principles and improve the learning environment.

A comprehensive review of the application of NLP technology in language learning

The rapid development of Natural Language Processing (NLP) technology has provided new perspectives and tools for the acquisition of second languages. As our world becomes increasingly interconnected, the role of NLP in facilitating language learning has become more prominent. This paper reviews the multifaceted applications of NLP technology in language learning, including auxiliary teaching functions such as reading assistance, writing feedback, oral interaction, and personalized learning. These applications have significantly enhanced language learners' abilities in vocabulary acquisition, grammatical application, pronunciation accuracy, and reading comprehension through real-time feedback, enhanced interactivity, and promotion of cultural understanding. Despite the immense potential of NLP technology in second language learning, challenges such as technical accuracy, cultural adaptability, and data privacy exist. This paper proposes strategies, such as ensuring technical accuracy, curating diverse datasets and safeguarding data privacy to address these challenges. Looking forward, the future development of NLP technology in second language education holds great promise. As NLP continues to evolve, it is expected to contribute to more personalized, effective, and accessible language learning solutions. This paper aims to provide valuable references and insights for educators, technology developers, and policymakers, enabling them to harness the transformative potential of NLP in language education and to navigate the future of educational technology with confidence and foresight.

Tajweed Learning Education and Al-Qur'an Reading Assistance with the Ummi Method for 'Aisyiyah Jiken Branch Mothers

This community service activity aims to improve the ability of Aisyiyah mothers at the Al-Jihad Jiken Tulangan mosque to read the Qur'an correctly according to the rules of tajwid through the Ummi method with the Quran Explore method. The Ummi method was chosen because of its simplicity and effectiveness in teaching tajwid to adults. This activity was carried out through several stages, namely the introduction of the Ummi method, learning the theory of tajwid, application in reading the Qur'an, and group incentive assistance. The implementation of the activity was carried out in 4 meetings, with an evaluation carried out at the end of the program. The results obtained after the tajwid learning assistance program for the mothers of the 'Aisiyah Jiken branch leaders showed significant results, where students were able to read more fluently by understanding the basic science of tajwid. This assistance program succeeded in motivating students to continue learning and practicing independently. With this activity, it is hoped that it can be sustainable as a routine program to improve reading the Qur'an among the community.

The Semantic Reader Project

Scholarly publications are key to the transfer of knowledge from scholars to others. However, research papers are information-dense, and as the volume of the scientific literature grows, the greater the need for new technology to support scholars. In contrast to the process of finding papers, which has been transformed by Internet technology, the experience of reading research papers has changed little in decades. For instance, the PDF format for sharing papers remains widely used due to its portability but has significant downsides, inter alia, static content and poor accessibility for low-vision readers. This paper explores the question “Can recent advances in AI and HCI power intelligent, interactive, and accessible reading interfaces—even for legacy PDFs?” We describe the Semantic Reader Project, a collaborative effort across multiple institutions to explore automatic creation of dynamic reading interfaces for research papers. Through this project, we’ve developed a collection of novel reading interfaces and evaluated them with study participants and real-world users to show improved reading experiences for scholars. We’ve also released a production research paper reading interface that will continuously incorporate novel features from our research as they mature. We structure this paper around five key opportunities for AI assistance in scholarly reading —discovery, efficiency, comprehension, synthesis, and accessibility—and present an overview of our progress and discuss remaining open challenges.

Weakly-supervised learning-based pathology detection and localization in 3D chest CT scans.

Recent advancements in anomaly detection have paved the way for novel radiological reading assistance tools that support the identification of findings, aimed at saving time. The clinical adoption of such applications requires a low rate of false positives while maintaining high sensitivity. In light of recent interest and development in multi pathology identification, we present a novel method, based on a recent contrastive self-supervised approach, for multiple chest-related abnormality identification including low lung density area ("LLDA"), consolidation ("CONS"), nodules ("NOD") and interstitial pattern ("IP"). Our approach alerts radiologists about abnormal regions within a computed tomography (CT) scan by providing 3Dlocalization. We introduce a new method for the classification and localization of multiple chest pathologies in 3D Chest CT scans. Our goal is to distinguish four common chest-related abnormalities: "LLDA", "CONS", "NOD", "IP" and "NORMAL". This method is based on a 3D patch-based classifier with a Resnet backbone encoder pretrained leveraging recent contrastive self supervised approach and a fine-tuned classification head. We leverage the SimCLR contrastive framework for pretraining on an unannotated dataset of randomly selected patches and we then fine-tune it on a labeled dataset. During inference, this classifier generates probability maps for each abnormality across the CT volume, which are aggregated to produce a multi-label patient-level prediction. We compare different training strategies, including random initialization, ImageNet weight initialization, frozen SimCLR pretrained weights and fine-tuned SimCLR pretrained weights. Each training strategy is evaluated on a validation set for hyperparameter selection and tested on a test set. Additionally, we explore the fine-tuned SimCLR pretrained classifier for 3D pathology localization and conduct qualitativeevaluation. Validated on 111 chest scans for hyperparameter selection and subsequently tested on 251 chest scans with multi-abnormalities, our method achieves an AUROC of 0.931 (95% confidence interval [CI]: [0.9034, 0.9557], -value < 0.001) and 0.963 (95% CI: [0.952, 0.976], -value < 0.001) in the multi-label and binary (i.e., normal versus abnormal) settings, respectively. Notably, our method surpasses the area under the receiver operating characteristic (AUROC) threshold of 0.9 for two abnormalities: IP (0.974) and LLDA (0.952), while achieving values of 0.853 and 0.791 for NOD and CONS, respectively. Furthermore, our results highlight the superiority of incorporating contrastive pretraining within the patch classifier, outperforming Imagenet pretraining weights and non-pretrained counterparts with uninitialized weights (F1 score = 0.943, 0.792, and 0.677 respectively). Qualitatively, the method achieved a satisfactory 88.8% completeness rate in localization and maintained an 88.3% accuracy rate against falsepositives. The proposed method integrates self-supervised learning algorithms for pretraining, utilizes a patch-based approach for 3D pathology localization and develops an aggregation method for multi-label prediction at patient-level. It shows promise in efficiently detecting and localizing multiple anomalies within a singlescan.

Application of E-Learning entertainment learning based on intelligent interactive experience in English reading assistance mode

In the process of E-Learning, interactive entertainment experiences and digital technology provide new models for strengthening the development of online education. This article studies the application of E-Learning entertainment learning based on intelligent interactive experience in English reading assistance mode. The E-Learning entertainment learning mode based on intelligent interactive experience focuses on creating interest and interaction, designing an interesting and stimulating learning environment, selecting appropriate technology tools to achieve E-Learning intelligent interactive experience, and designing appropriate learning content and activities according to learning objectives. Firstly, this article designs a semantic inference system that is more convenient in calculating and storing resources, and can perform semantic inference on uncertain knowledge. Secondly, this article delves into the basic principles of Bayesian network algorithms and explores the construction mechanism of Bayesian networks. Then compared with traditional algorithms, the accuracy and stability of this method were demonstrated. Digital technology and artificial intelligence provide new technological support for E-Learning, allowing students to better experience entertaining learning experiences and customize learning content according to personal needs, enhancing educational value. Experiments have shown that using computer-assisted English reading can effectively improve students’ English proficiency. This system not only reduces the boredom in traditional English reading, but also provides students with a brand new English learning atmosphere, which can effectively improve their learning efficiency.

SciSpace Copilot: Empowering Researchers through Intelligent Reading Assistance

We introduce SciSpace Copilot, an AI research assistant that helps in understanding and reading research papers faster by providing a plethora of features. Answering questions from a document has recently become popular using the Retrieval Augmented Generation (RAG) approach. Our tool uses an advanced question-answering pipeline to get accurate answers and also provide exact citations for the same. We provide many more valuable features on scientific text, including generating explanations, generating summaries, adding notes and highlights, and finding related papers from our 200 million corpus. Our tool supports 100+ languages, making research more accessible across language barriers. Thousands of users use SciSpace Copilot on a daily basis by uploading their articles to understand research faster and better. Our tool can be accessed at this link: https://typeset.io.

Improving Children’s Reading Motivation and Skills Through Read Aloud: A Mixed-Method Study in Orphanage Context

Generally speaking, children's reading motivation and skills are low, notably those in orphanages requiring solution, one of which is through reading activities applying read-aloud method. Most studies on the read-aloud method were qualitative. This study attempted to address the gap by employing a mixed-methods design with 10 foster children from an orphanage chosen using purposive sampling technique. Observations, tests, and interviews were used to collect the data. Quantitative data from observations and tests were statistically analyzed and reported in frequency and percentage to determine the difference in the number of children who improved following the program. Additionally, interviews were conducted to obtain qualitative data on children's and orphanages' perspectives of the program and its impacts, and the results were assessed using qualitative data analysis including data reduction, data display, and conclusion drawing. Both quantitative and qualitative data were gathered and analyzed concurrently. They were then merged and interpreted through a side-by-side comparison approach. Finally, convergence or divergence between the two sources of data was determined. The findings show that quantitative and qualitative data confirm each other, demonstrating that the read-aloud method improved children's reading motivation by significantly increasing the length of time for reading and the number of books read, as well as a slight increase in children's reading comprehension and confidence. In addition, the children's reading fluency improved substantially, while their reading accuracy and clarity improved slightly. Future research should focus on areas that need the most improvement and entail a larger sample size. Additionally, reading assistance for foster children is always recommended.

READING CORNER IMPLEMENTATION TO IMPROVE CHILDREN'S ENGLISH LITERACY IN KAMPUNG LITERASI 26 ILIR

One of the skills that must be possessed by the younger generation in the Society 5.0 era is communicating in English. Literacy activities can improve English as a basic skill for communication. Kampung Literasi 26 Ilir tried to provide English literacy facilities for children with a reading corner to hone their ability to understand analytical, critical, and reflective information. The study aims to describe the implementation of a reading corner to improve children's English literacy. It used a descriptive analysis with a case study technique. Data was obtained from observation. The result is that the implementation of a reading corner to improve children's English literacy is carried out with reading assistance and comprehension of English reading content for children aged 4-6 years and facilitating reading activities for children aged 7-11 years. At the end of the activity, children aged 7-11 years analyzed and criticized the content of the reading and reflected on the results of their reading by presenting. Reading corners can improve children's English literacy

Pendampingan Baca Tulis Al-Qur’an Menggunakan Metode Fatullah di Pondok Tahfizh Tazkiyah

The high interest of parents in directing children to study the Qur'an means that there needs to be important attention for a tahfizh teacher to teach the Qur'an comprehensively and continuously. with the applicable tajwid rules, special attention is needed from the tahfzih teacher to always upgrade learning so that learning in class is more active and innovative. So that a new method of learning is formed so that the students become more proficient in learning the Alquran. Because of the reality that occurs in the field, students find it difficult to understand the meaning and nature of letters correctly. There is also boredom among students in studying due to the long practice of reciting recitation material in the Alquran. The method that the author uses is the Participatory Action Research (PAR) approach, where this research is oriented towards empowerment and change in society. It is clear that this writing is oriented towards quality change. Based on the results and assistance above, it can be concluded that assistance in reading and writing the Alquran through the Fatullah Method at Pondok Tahfizh Tazkiyah has been carried out well and can indirectly improve the reading and writing skills of the Alquran for the students of Pondok Tahfizh Tazkiyah.

Pendampingan Baca Tulis AlQuran Anak melalui Metode Qiroati di Masjid Al-Barkah Kota Padang

The lack of public awareness of Alquran reading and writing education is marked by an imbalance between teachers and students in learning to read and write the Alquran at the Al-Barkah Mosque in Padang City so that learning outcomes do not go as desired, assistance in reading and writing Alquran -Qur'an aims to measure the extent to which Ustadz and Ustadzah provide understanding to Alquran educational park students in reading the Alquran and writing correct Alquranic verses according to the rules, from the way of reading, rhythm, and know the tajwid contained in the reading. The methods used in this assistance are interviews and documentation, the methods used in reading the Alquran are repetition, question and answer, deepening the material and writing verses. students who are taught at the Alquran educational park at primary school level, the aim of this assistance is to measure the extent of the ability of Alquran educational park children in reading the Alquran at the Al-Barkah Mosque in Padang City by applying the qiroati method, children know and understand how to read the Alquran correctly with tartil rhythm. The application of the Qiroati method has a significant role in learning to read and write the Alquran at the Al-Barkah Mosque in Padang City.

OCR Using Python and Its Application

Optical Character Recognition (OCR) of papers has tremendous practical value given the prevalence of handwritten documents in human exchanges. A discipline known as optical character recognition makes it possible to convert many kinds of texts or photos into editable, searchable, and analysable data. In the past ten years, academics have developed systems that automatically evaluate printed and handwritten documents to convert them to electronic format. In the modern era, as demand for computer systems arose, the demand to convert paper text and computer vision also erose. To interact the computer with capability to read text from images, videos and images have been arose rapidly and many software companies came in role to fulfil this need. One of the active and difficult study areas in the world of pattern recognition and image processing has been handwriting recognition. Among its many uses are bank checks, reading assistance for the blind, and the conversion of any handwritten document into structural text. The main aim of this paper is to create a searchable pdf from the image and bring the application to easy use and deployable on premises and cloud.&#x0D;

Effects of augmented reality on perceived motivation for struggling readers: Mix-method analysis

Higher education students who struggle with reading may find some relief via the use of technology, especially new and developing forms of technology. Even though augmented reality (AR) has been used in the classroom with great success to motivate and engage children who are difficult to teach, there hasn't been a lot of research done on how augmented print may help those who have trouble reading. The purpose of this study is to investigate the effect of augmented reality on perceived motivation for students currently enrolled in higher education, namely their engagement with and understanding of an upgraded design theory book, as well as their perceived motivation to read. This research was conducted using the mix method approach, supported with some different methodologies. The findings reveal that increased support for academic literature enhances motivation, engagement, and confidence in understanding, impacting both struggling and proficient readers. We concluded that students, regardless of their reading level, expressed a willingness to use AR reading assistance for future books. Further research is crucial given the heightened levels of motivation and confidence. This research aligns with technological advancements, and educators can influence the development of augmented reality apps for classroom use. Future studies should focus on students with reading difficulties, exploring the optimal design of AR experiences and learning games to enhance understanding and retention of art history lectures in higher education

CASES

The process of reading has attracted decades of scientific research. Work in this field primarily focuses on using eye gaze patterns to reveal cognitive processes while reading. However, eye gaze patterns suffer from limited resolution, jitter noise, and cognitive biases, resulting in limited accuracy in tracking cognitive reading states. Moreover, using sequential eye gaze data alone neglects the linguistic structure of text, undermining attempts to provide semantic explanations for cognitive states during reading. Motivated by the impact of the semantic context of text on the human cognitive reading process, this work uses both the semantic context of text and visual attention during reading to more accurately predict the temporal sequence of cognitive states. To this end, we present a Cognition-Aware Smart Eyewear System (CASES), which fuses semantic context and visual attention patterns during reading. The two feature modalities are time-aligned and fed to a temporal convolutional network based multi-task classification deep model to automatically estimate and further semantically explain the reading state timeseries. CASES is implemented in eyewear and its use does not interrupt the reading process, thus reducing subjective bias. Furthermore, the real-time association between visual and semantic information enables the interactions between visual attention and semantic context to be better interpreted and explained. Ablation studies with 25 subjects demonstrate that CASES improves multi-label reading state estimation accuracy by 20.90% for sentence compared to eye tracking alone. Using CASES, we develop an interactive reading assistance system. Three and a half months of deployment with 13 in-field studies enables several observations relevant to the study of reading. In particular, observed how individual visual history interacts with the semantic context at different text granularities. Furthermore, CASES enables just-in-time intervention when readers encounter processing difficulties, thus promoting self-awareness of the cognitive process involved in reading and helping to develop more effective reading habits.

Small bowel capsule endoscopy examination and open access database with artificial intelligence: The SEE-artificial intelligence project.

Artificial intelligence (AI) may be practical for image classification of small bowel capsule endoscopy (CE). However, creating a functional AI model is challenging. We attempted to create a dataset and an object detection CE AI model to explore modeling problems to assist in reading small bowel CE. We extracted 18,481 images from 523 small bowel CE procedures performed at Kyushu University Hospital from September 2014 to June 2021. We annotated 12,320 images with 23,033 disease lesions, combined them with 6161 normal images as the dataset, and examined the characteristics. Based on the dataset, we created an object detection AI model using YOLO v5 and we tested validation. We annotated the dataset with 12 types of annotations, and multiple annotation types were observed in the same image. We test validated our AI model with 1396 images, and sensitivity for all 12 types of annotations was about 91%, with 1375 true positives, 659 false positives, and 120 false negatives detected. The highest sensitivity for individual annotations was 97%, and the highest area under the receiver operating characteristic curve was 0.98, but the quality of detection varied depending on the specific annotation. Object detection AI model in small bowel CE using YOLO v5 may provide effective and easy-to-understand reading assistance. In this SEE-AI project, we open our dataset, the weights of the AI model, and a demonstration to experience our AI. We look forward to further improving the AI model in the future.

Upaya Meningkatkan Literasi Membaca Melalui Pojok Baca Untuk Mengantisipasi Buta Huruf Bagi Anak-Anak Di Desa Doda

This community service was carried out by Tadulako University lecturers and students in Doda Village, Kinovaro District, Sigi Regency. There is one thing that is the focus of the community service work program in Doda Village, namely a culture of low community literacy. The high number of school-age children is not accompanied by adequate literacy facilities. So that the literacy movement in Doda Village only relies on facilities and support from schools. The creation of a reading corner aims to provide literacy facilities and form reading habits in order to increase interest in reading as part of the literacy movement in Indonesia. The implementation of community service activities begins with observation, then is carried out in stages, namely social reflection, program planning, program implementation and evaluation. As an effort to form reading habits in order to foster children's interest in reading, assistance is provided for reading activities at the reading corner of Doda Village, Kinovaro District, Sigi Regency. The result of this service is the growth of children's interest in reading in Doda Village, this can be seen from the high enthusiasm of the children during the reading assistance activities which are carried out every week. It is hoped that this community service activity will foster children's interest in reading as an effort to activate the literacy movement in Indonesia.

How Can IJDS Authors, Reviewers, and Editors Use (and Misuse) Generative AI?

How Can <i>IJDS</i> Authors, Reviewers, and Editors Use (and Misuse) Generative AI?

Automated lung cancer assessment on 18F-PET/CT using Retina U-Net and anatomical region segmentation

ObjectivesTo develop and test a Retina U-Net algorithm for the detection of primary lung tumors and associated metastases of all stages on FDG-PET/CT.MethodsA data set consisting of 364 FDG-PET/CTs of patients with histologically confirmed lung cancer was used for algorithm development and internal testing. The data set comprised tumors of all stages. All lung tumors (T), lymphatic metastases (N), and distant metastases (M) were manually segmented as 3D volumes using whole-body PET/CT series. The data set was split into a training (n = 216), validation (n = 74), and internal test data set (n = 74). Detection performance for all lesion types at multiple classifier thresholds was evaluated and false-positive-findings-per-case (FP/c) calculated. Next, detected lesions were assigned to categories T, N, or M using an automated anatomical region segmentation. Furthermore, reasons for FPs were visually assessed and analyzed. Finally, performance was tested on 20 PET/CTs from another institution.ResultsSensitivity for T lesions was 86.2% (95% CI: 77.2–92.7) at a FP/c of 2.0 on the internal test set. The anatomical correlate to most FPs was the physiological activity of bone marrow (16.8%). TNM categorization based on the anatomical region approach was correct in 94.3% of lesions. Performance on the external test set confirmed the good performance of the algorithm (overall detection rate = 88.8% (95% CI: 82.5–93.5%) and FP/c = 2.7).ConclusionsRetina U-Nets are a valuable tool for tumor detection tasks on PET/CT and can form the backbone of reading assistance tools in this field. FPs have anatomical correlates that can lead the way to further algorithm improvements. The code is publicly available.Key Points• Detection of malignant lesions in PET/CT with Retina U-Net is feasible.• All false-positive findings had anatomical correlates, physiological bone marrow activity being the most prevalent.• Retina U-Nets can build the backbone for tools assisting imaging professionals in lung tumor staging.

A Necessary Redefinition of Lexicography in the Digital Age: Glossography, Dictionography and Implications for the Future

his paper deals with developments in the field of lexicography that resulted in the need for a new definition of this term. The paper offers a brief look at the origin, use and develop­ment of the term lexicography and at the use of glosses in former and current times. It is shown how the digital era enables the use of certain lexicographical features in other sources than dictionaries. This leads to an expansion of the scope of the term lexicography. A strong focus is on the use of glosses, originally inserted by scribes as snippets into manuscripts to help with the understanding of difficult words and expressions. The use of glosses has increased, and they are currently com­monly used in a variety of environments. In digital products glosses play an innovative, productive and significant role to present new types of lexicographical data. This demands the recognition of glosses as lexicographical entries and leads to a redefinition of the term lexicography that includes two major sub-fields, namely dictionography and glossography. Keywords: artificial intelligence, digital era, gloss, glossography, lexi­co­graphical data, scribe, dictionography, interdisciplinary col­labo­ration, reading assistant, writing assistant

Dyslexic Reading Assistance with Language Processing Algorithms

Dyslexic Reading Assistance with Language Processing Algorithms