Tool For Correction Research Articles

Improved motion correction in brain MRI using 3D radial trajectory and projection moment analysis.

To develop a generalized rigid body motion correction method in 3D radial brain MRI to deal with continuous motion pattern through projection moment analysis. An assumption was made that the multichannel coil moves with the head, which was achieved by using a flexible head coil. A two-step motion correction scheme was proposed to directly extract the motion parameters from the acquired k-space data using the analysis of center-of-mass with high noise robustness, which were used for retrospective motion correction. A recursive least-squares model was introduced to recursively estimate the motion parameters for every single spoke, which used the smoothness of motion and resulted in high temporal resolution and low computational cost. Five volunteers were scanned at 3 T using a 3D radial multidimensional golden-means trajectory with instructed motion patterns. The performance was tested through both simulation and in vivo experiments. Quantitative image quality metrics were calculated for comparison. The proposed method showed good accuracy and precision in both translation and rotation estimation. A better result was achieved using the proposed two-step correction compared to traditional one-step correction without significantly increasing computation time. Retrospective correction showed substantial improvements in image quality among all scans, even for stationary scans. The proposed method provides an easy, robust, and time-efficient tool for motion correction in brain MRI, which may benefit clinical diagnosis of uncooperative patients as well as scientific MRI researches.

Natural Language Processing of Grammar Checker Tools for Academic Writing: A Systematic Literature Review

Grammar correction is crucial for essential documents such as research, business articles, formal papers, but with language evolving every century, some rules for grammar correction are added or changed. There have been created grammar correction online, which has helped most students create academic writing. Some tools focus on correcting the paper by following specific rules; some run an algorithm based on what type of document you are writing. In this paper, we reviewed documents published from 2017 up to 2021 related to grammar correction and Grammar error detection, with numerous Natural Language Processing and models provided by past researchers, which may aid this paper towards a solution on creating a grammar correction tool.

Commissioning and first operation of East Japan Heavy Ion Center at Yamagata University

A world smallest carbon ion radiotherapy facility, East Japan Heavy Ion Center, Yamagata University, started treatment operations in February 2021. The treatment system consists of an ECR ion source, an RFQ and IH-type drift tube linac, a 430 MeV/u synchrotron and a spot-scanning irradiation system. It has two treatment rooms, one is a fixed horizontal beam port and the other is a rotating gantry beam port with superconducting magnets. The ECR ion source is the Kei2-type permanent magnet 10 GHz ECR ion source with a maximum field of 0.8 T. All the improvements of the previous facilities are applied to the ion source, such as helium gas-assisted operation and changes in the shape of an anode electrode and an extraction electrode to reduce the discharge. Owing to these improvements, the ion source has been operated stably during the commissioning and clinical operation. The irradiation system of Yamagata University eliminated the plastic block range shifter to realize a compact gantry, and has 600 energy levels to control the beam range in step of 0.5 mm. In order to optimize the beam transport parameters quickly, automation tools for orbit correction were developed. Machine commissioning and clinical commissioning were carried out in parallel to allow treatment to begin earlier. First, the horizontal fixed beam port was commissioned by verifying the dose distribution of the treatment planning system. Then, the gantry beam port was commissioned by full beam distribution measurement for representing beam angle of 90 degree, and other angles were sequentially released after the compatibility measurement of beam position, beam size, and two-dimensional uniformity. In September 2022, we were able to accept all treatment sites. By August 2023, 1151 cancer patients had been treated. Further improvements to increase available gantry angle and to increase beam efficiency are ongoing.

NextDenovo: an efficient error correction and accurate assembly tool for noisy long reads

Long-read sequencing data, particularly those derived from the Oxford Nanopore sequencing platform, tend to exhibit high error rates. Here, we present NextDenovo, an efficient error correction and assembly tool for noisy long reads, which achieves a high level of accuracy in genome assembly. We apply NextDenovo to assemble 35 diverse human genomes from around the world using Nanopore long-read data. These genomes allow us to identify the landscape of segmental duplication and gene copy number variation in modern human populations. The use of NextDenovo should pave the way for population-scale long-read assembly using Nanopore long-read data.

An intelligent error correction model for English grammar with hybrid attention mechanism and RNN algorithm

Abstract This article proposes an English grammar intelligent error correction model based on the attention mechanism and Recurrent Neural Network (RNN) algorithm. It aims to improve the accuracy and effectiveness of error correction by combining the powerful context-capturing ability of the attention mechanism with the sequential modeling ability of RNN. First, based on the improvement of recurrent neural networks, a bidirectional gated recurrent network is added to form a dual encoder structure. The encoder is responsible for reading and understanding the input text, while the decoder is responsible for generating the corrected text. Second, the attention mechanism is introduced into the decoder to convert the output of the encoder into the attention probability distribution for integration. This allows the model to focus on the relevant input word as it generates each corrected word. The results of the study showed that the model was 2.35% points higher than statistical machine translation–neural machine translation in the CoNLL-2014 test set, and only 1.24 points lower than the human assessment score, almost close to the human assessment level. The model proposed in this study not only created a new way of English grammar error correction based on the attention mechanism and RNN algorithm in theory but also effectively improved the accuracy and efficiency of English grammar error correction in practice. It further provides English learners with higher-quality intelligent error correction tools, which can help them learn and improve their English level more effectively.

De novo diploid genome assembly using long noisy reads

The high sequencing error rate has impeded the application of long noisy reads for diploid genome assembly. Most existing assemblers failed to generate high-quality phased assemblies using long noisy reads. Here, we present PECAT, a Phased Error Correction and Assembly Tool, for reconstructing diploid genomes from long noisy reads. We design a haplotype-aware error correction method that can retain heterozygote alleles while correcting sequencing errors. We combine a corrected read SNP caller and a raw read SNP caller to further improve the identification of inconsistent overlaps in the string graph. We use a grouping method to assign reads to different haplotype groups. PECAT efficiently assembles diploid genomes using Nanopore R9, PacBio CLR or Nanopore R10 reads only. PECAT generates more contiguous haplotype-specific contigs compared to other assemblers. Especially, PECAT achieves nearly haplotype-resolved assembly on B. taurus (Bison×Simmental) using Nanopore R9 reads and phase block NG50 with 59.4/58.0 Mb for HG002 using Nanopore R10 reads.

Визуализация в задачах реконструкции данных

Many application tasks of multidimensional data analysis which describe the state of real physical or other systems face with difficulties. This is a consequence of the low-quality source data, including missing values, the probability of errors or unreliability of measurements. Incomplete data can become an obstacle for research using many modern informational methods. The current work examines the potential and capabilities of visual analytics tools for preliminary preparation, correction or complete analysis of primary data volumes. A promising area of application of the approach discussed in the study is the targeted use of visualization capabilities as a data analysis tool. The implementation of specialized visual metaphors is used to solve problems of processing and interpreting data, the sources of which are cyberphysical systems of different complexity levels. Such systems operate in an autonomous or partially controlled mode. A characteristic feature of these systems is the presence of a large number of sensors that collect various types of data. Such data differ in the capacity of the corresponding information channels, their speed and reliability. Examples of such cyberphysical systems are unmanned aerial vehicles (UAVs), robotic stations, and multimodal monitoring systems. These systems can function in conditions where it is difficult to obtain objective observation experience (deep-sea robots). The effective use of data collected by cyberphysical monitoring systems is a condition for solving a large number of application and research tasks.

Riddling Substitution of "hsa" to "has" in the Enigmatic MicroRNA Nomenclature.

This concise review and analysis offers an initial unpacking of a previously under-recognized issue within the microRNA research and communications field regarding the inadvertent use of "has" instead of "hsa" in article titles in the microRNA nomenclature. This subtle change, often the result of grammar auto correction tools, introduces considerable ambiguity and confusion among readers and researchers in reporting of microRNA-related discoveries. The impact of this issue cannot be underestimated, as precise and consistent nomenclature is vital for science communication and computational retrieval of relevant scientific literature and to advance science and innovation. We suggest that the recognition and correction of these often inadvertent "hsa" to "has" substitution errors are timely and important so as to ensure a higher level of accuracy throughout the writing and publication process in the microRNA field in particular. Doing so will also contribute to clarity and consistency in the field of microRNA research, ultimately improving scientific veracity, communication, and progress.

The Regime as a primary means of correction for convicts: theory and practice

The article discusses the specifics of a correctional tool, such as the regime, which is part of the system of correctional measures for prisoners and is intended by the legislator to contribute to the achievement of the declared goals of the criminal and penal enforcement legislation of the Republic of Kazakhstan. It is empha-sized that the regime, being the main means of correcting convicts, is in fact not such, but has turned into a total means of controlling convicts and what is especially worth noting, taking into account the penetration of modern means of technical control into places of deprivation of liberty, provokes a contingent of criminal en-vironment to resist this type of supervision from which you cannot escape, which leads to this type of viola-tion of the established procedure for serving a sentence, such as damage to technical equipment (video cam-eras). The work makes an attempt to compare the regime with other means of correction in institutions of var-ious security and as a result, the authors offer their proposals for inclusion in Kazakhstan’s criminal and pris-on legislation, along the way, an understanding of the role and place of the regime among other main means of correction of convicts and its purpose is proposed and voiced, and also proposals were formulated for criminal legislation in the form of a separate article draft.

Improved data assimilation for algal bloom dynamics simulation in the Three Gorges Reservoir using particle filter

Algal blooms have been increasingly prevalent in recent years, especially in lakes and reservoirs; their accurate prediction is essential for preserving water quality. In this study, the observed chlorophyll a (chl-a) levels were assimilated into the Environmental Fluid Dynamics Code (EFDC) of algal bloom dynamics by using a particle filter (PF), and the state variables of water quality and model parameters were simultaneously updated to achieve enhanced algal bloom predictive performance. The developed data assimilation system for algal blooms was applied to Xiangxi Bay (XXB) in the Three Gorges Reservoir (TGR). The results show that the ensemble mean accuracy and reliability of the confidence intervals of the predicted state variables, including chl-a and indirectly updated phosphate (PO4), ammonium (NH4), and nitrate (NO3) levels, were considerably improved after PF assimilation. Thus, PF assimilation is an effective tool for the dynamic correction of parameters to represent their inherent variations. Increased assimilation frequency can effectively suppress the accumulation of model errors; therefore, the use of high-frequency water quality data for assimilation is recommended to ensure more accurate and reliable algal bloom prediction.

Ways to Protect Creditors’ Rights When Presenting Property Claims to the Debtor’s Managers in the Bankruptcy Procedure

The article defines the main mechanisms for attracting persons who lead (managed) a legal entity to civil and public liability. The concepts of a person influencing the actions of a legal entity (Article 53.1 of the Civil Code of the Russian Federation), a person controlling the debtor (Article 61.10 of the Bankruptcy Law) and a civil defendant in criminal proceedings (Article 54 of the Code of Criminal Procedure of the Russian Federation) are revealed. Due to the variety of mechanisms established by the legislator for the restoration of creditors’ property rights, the article analyzes the advantages and disadvantages of each separately. Using examples from judicial practice, the author proves that there is no dispositivity in choosing the method of replenishing the bankruptcy estate at will, and the opinion that the difference in methods is insignificant, that it is not the rule of law that you refer to that is important, but the fact of restoration of rights after harm by the debtor is incorrect. The author makes an assertion that the choice of the appropriate method is justified by the individuality of the dispute, the conditions of treatment, the person applying and the result desired by creditors, depending on the chosen method of protecting creditors’ rights. The legislator distinguishes between ways to protect the rights of creditors, where each case has its own goals, objectives and results. The paper raises the question of finding criteria for the correct and most profitable tool for restoring creditors’ property rights in a bankruptcy case, taking into account procedural and legal features. The article is aimed at developing the theory and judicial practice in bankruptcy cases and ensuring the stability of the already formed practice, maintaining a balance of interests, as well as resolving conflicts.

Oblique anterior column realignment with a mini-open posterior column osteotomy for minimally invasive adult spinal deformity correction: illustrative case.

Adult spinal deformity (ASD) occurs from progressive anterior column collapse due to disc space desiccation, compression fractures, and autofusion across disc spaces. Anterior column realignment (ACR) is increasingly recognized as a powerful tool to address ASD by progressively lengthening the anterior column through the release of the anterior longitudinal ligament during lateral interbody approaches. Here, we describe the application of minimally invasive ACR through an oblique antepsoas corridor for deformity correction in a patient with adult degenerative scoliosis and significant sagittal imbalance. A 65-year-old female with a prior history of L4-5 transforaminal lumbar interbody fusion and morbid obesity presented with refractory, severe low-back and lower-extremity pain. Preoperative radiographs showed significant sagittal imbalance. Computed tomography showed a healed L4-5 fusion and a vacuum disc at L3-4 and L5-S1, whereas magnetic resonance imaging was notable for central canal stenosis at L3-4. The patient was treated with a first-stage L5-S1 lateral anterior lumbar interbody fusion with oblique L2-4 ACR. The second-stage posterior approach consisted of a robot-guided minimally invasive T10-ilium posterior instrumented fusion with a mini-open L2-4 posterior column osteotomy (PCO). Postoperative radiographs showed the restoration of her sagittal balance. There were no complications. Oblique ACR is a powerful minimally invasive tool for sagittal plane correction. When combined with a mini-open PCO, substantial segmental lordosis can be achieved while eliminating the need for multilevel PCO or invasive three-column osteotomies.

AI Application in Foreign Language Literature: ChatGPT's Impact and Skill Enhancement

This study investigates the prospective of incorporating input hypothesis, output hypothesis, interaction hypothesis and metacognitive theory into the best practices of ChatGPT in foreign literature. The study used an online survey involving 146 Chinese internet users to examine opinions on the use of ChatGPT for foreign literature analysis and tasks. Specific skills enhanced by AI integration, such as critical thinking, nuanced comprehension, and advanced linguistic proficiency in foreign languages are discussed in the research. However, there were concerns about its ethical implications when used for literary purposes because it may lead to biases, wrong information and risks which include plagiarism. During the application of ChatGPT, it was emphasized that comprehensible input is crucial to ensure that AI provided content is both understandable and suitable to learners’ current proficiency level. Moreover, learners are encouraged to actively utilize ChatGPT as feedback as well as correction tool. Furthermore, this research allowed learners to engage in live communication through using ChatGPT as a speaking partner thereby negotiating meaning and getting instant feedback to support interaction hypothesis (IH). Underpinned by metacognitive theory, instructing learners to reflect on their learning process with the help of ChatGPT involves identifying areas of difficulty and seeking specific assistance, for example, learners may ask about linguistic doubts from chat GTP or test their understanding about certain concepts or vocabulary using it. In order to effectively integrate these hypotheses with metacognitive theories, interactive chat GPTs were designed which required learners’ involvement in comprehensible input generation of language, output meaningful interactions and reflection on learning process; reading or listening to foreign language content (input), responding or creating content (output), engaging in conversation (interaction) tasks are assessed for their comprehension and performance levels (metacognition).

LATCH score: a tool for identification and correction of breastfeeding problems in a tertiary care hospital of North Karnataka

Background: Breastfeeding, a vital childhood intervention, faces challenges despite being a natural process. Factors such as maternal confidence, latching issues, breast pain, perceived milk insufficiency, and inadequate encouragement contribute to early discontinuation. Assessing breastfeeding in postpartum mothers prior to discharge is important for successful breastfeeding. The LATCH charting system designed by Jensen et al was used to assess the score. Objectives were to determine early breastfeeding problems using LATCH score and to study the impact of breastfeeding supportive measures on LATCH score. Methods: Hospital-based prospective observational study was conducted among 100 mothers who delivered in hospitals attached to Mahadevappa Rampure Medical College, Kalaburagi. The LATCH score was assessed twice, first within 24 hrs after birth and second 48 hrs after intervention. Results: Good LATCH score was found among the rural mothers, multiparous mothers and those who had a normal vaginal delivery. After providing breastfeeding support, a majority (81%) of the mothers transitioned from poor or moderate to a good LATCH score group. The overall mean LATCH score increased from 5.83±1.64 to 9.31±1.5 following intervention. Improvement was seen in all the individual components of LATCH. Conclusions: This LATCH assessment tool can identify mothers and infants who are at risk of early breastfeeding cessation and serve as a guide to initiate appropriate intervention.

NeuroEditor: a tool to edit and visualize neuronal morphologies.

The digital extraction of detailed neuronal morphologies from microscopy data is an essential step in the study of neurons. Ever since Cajal's work, the acquisition and analysis of neuron anatomy has yielded invaluable insight into the nervous system, which has led to our present understanding of many structural and functional aspects of the brain and the nervous system, well beyond the anatomical perspective. Obtaining detailed anatomical data, though, is not a simple task. Despite recent progress, acquiring neuron details still involves using labor-intensive, error prone methods that facilitate the introduction of inaccuracies and mistakes. In consequence, getting reliable morphological tracings usually needs the completion of post-processing steps that require user intervention to ensure the extracted data accuracy. Within this framework, this paper presents NeuroEditor, a new software tool for visualization, editing and correction of previously reconstructed neuronal tracings. This tool has been developed specifically for alleviating the burden associated with the acquisition of detailed morphologies. NeuroEditor offers a set of algorithms that can automatically detect the presence of potential errors in tracings. The tool facilitates users to explore an error with a simple mouse click so that it can be corrected manually or, where applicable, automatically. In some cases, this tool can also propose a set of actions to automatically correct a particular type of error. Additionally, this tool allows users to visualize and compare the original and modified tracings, also providing a 3D mesh that approximates the neuronal membrane. The approximation of this mesh is computed and recomputed on-the-fly, reflecting any instantaneous changes during the tracing process. Moreover, NeuroEditor can be easily extended by users, who can program their own algorithms in Python and run them within the tool. Last, this paper includes an example showing how users can easily define a customized workflow by applying a sequence of editing operations. The edited morphology can then be stored, together with the corresponding 3D mesh that approximates the neuronal membrane.

Classical Cepheid pulsation properties in the Rubin-LSST filters

ABSTRACT Homogeneous multiwavelength observations of classical Cepheids from the forthcoming Rubin-LSST have the potential to significantly contribute to our understanding of the evolutionary and pulsation properties of these pulsating stars. Updated pulsation models for classical Cepheid stars have been computed under various assumptions about chemical compositions, including relatively low metallicity (Z = 0.004 with Y = 0.25 and Z = 0.008 with Y = 0.25), solar metallicity (Z = 0.02 with Y = 0.28), and supersolar metallicity environments (Z = 0.03 with Y = 0.28). From the predicted periods, intensity-weighted mean magnitudes, and colours, we have derived the first theoretical pulsation relations in the Rubin-LSST filters (ugrizy), including period–luminosity–colour, period–Wesenheit, and period–age–colour relations. We find that the coefficients of these relations are almost insensitive to the efficiency of superadiabatic convection but are significantly affected by the assumption of the mass–luminosity relation and the adopted chemical composition. Metal-dependent versions of these relations are also derived, representing valuable tools for individual distance determinations and correction for metallicity effects on the cosmic distance scale.

MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads.

The rapid advancement of next-generation sequencing (NGS) machines in terms of speed and affordability has led to the generation of a massive amount of biological data at the expense of data quality as errors become more prevalent. This introduces the need to utilize different approaches to detect and filtrate errors, and data quality assurance is moved from the hardware space to the software preprocessing stages. We introduce MAC-ErrorReads, a novel Machine learning-Assisted Classifier designed for filtering Erroneous NGS Reads. MAC-ErrorReads transforms the erroneous NGS read filtration process into a robust binary classification task, employing five supervised machine learning algorithms. These models are trained on features extracted through the computation of Term Frequency-Inverse Document Frequency (TF_IDF) values from various datasets such as E. coli, GAGE S. aureus, H. Chr14, Arabidopsis thaliana Chr1 and Metriaclima zebra. Notably, Naive Bayes demonstrated robust performance across various datasets, displaying high accuracy, precision, recall, F1-score, MCC, and ROC values. The MAC-ErrorReads NB model accurately classified S. aureus reads, surpassing most error correction tools with a 38.69% alignment rate. For H. Chr14, tools like Lighter, Karect, CARE, Pollux, and MAC-ErrorReads showed rates above 99%. BFC and RECKONER exceeded 98%, while Fiona had 95.78%. For the Arabidopsis thaliana Chr1, Pollux, Karect, RECKONER, and MAC-ErrorReads demonstrated good alignment rates of 92.62%, 91.80%, 91.78%, and 90.87%, respectively. For the Metriaclima zebra, Pollux achieved a high alignment rate of 91.23%, despite having the lowest number of mapped reads. MAC-ErrorReads, Karect, and RECKONER demonstrated good alignment rates of 83.76%, 83.71%, and 83.67%, respectively, while also producing reasonable numbers of mapped reads to the reference genome. This study demonstrates that machine learning approaches for filtering NGS reads effectively identify and retain the most accurate reads, significantly enhancing assembly quality and genomic coverage. The integration of genomics and artificial intelligence through machine learning algorithms holds promise for enhancing NGS data quality, advancing downstream data analysis accuracy, and opening new opportunities in genetics, genomics, and personalized medicine research.

Comparison of the accuracy of commercial two-point and multi-echo Dixon MRI for quantification of fat in liver, paravertebral muscles, and vertebral bone marrow

PurposeExcess fat accumulation contributes significantly to metabolic dysfunction and diseases. This study aims to systematically compare the accuracy of commercially available Dixon techniques for quantification of fat fraction in liver, skeletal musculature, and vertebral bone marrow (BM) of healthy individuals, investigating biases and sex-specific influences. Method100 healthy White individuals (50 women) underwent abdominal MRI using two-point and multi-echo Dixon sequences. Fat fraction (FF), proton density fat fraction (PDFF) and T2* values were calculated for liver, paravertebral muscles (PVM) and vertebral BM (Th8–L5). Agreement and systematic deviations were assessed using linear correlation and Bland-Altman plots. ResultsHigh correlations between FF and PDFF were observed in liver (r = 0.98 for women; r = 0.96 for men), PVM (r = 0.92 for women; r = 0.93 for men) and BM (r = 0.97 for women; r = 0.95 for men). Relative deviations between FF and PDFF in liver (18.92 % for women; 13.32 % for men) and PVM (1.96 % for women; 11.62 % for men) were not significant. Relative deviations in BM were significant (38.13 % for women; 27.62 % for men). Bias correction using linear models reduced discrepancies. T2* times were significantly shorter in BM (8.72 ms for women; 7.26 ms for men) compared to PVM (13.45 ms for women; 13.62 ms for men) and liver (29.47 ms for women; 26.35 ms for men). ConclusionWhile no significant differences were observed for liver and PVM, systematic errors in BM FF estimation using two-point Dixon imaging were observed. These discrepancies – mainly resulting from organ-specific T2* times – have to be considered when applying two-point Dixon approaches for assessment of fat content. As suitable correction tools, linear models could provide added value in large-scale epidemiological cohort studies. Sex-specific differences in T2* should be considered.

Use of comprehensive psychodiagnostics of applicants for the position of sales manager

The subject of the study is the features of the process of psychodiagnostics of candidates for the position of sales manager. The object of the study is the process of psychodiagnostics of candidates for the position of sales manager. The author examines in detail such aspects of the topic as the correct selection of psychodiagnostic tools for the purpose of assessing a potential candidate, the difficulties in conducting psychodiagnostics of a potential sales manager, and provides instructions for identifying diagnostic needs and selecting the correct psychodiagnostic tools. This article used methods of analysis, synthesis and classification. The author of this article conducted a comprehensive diagnosis of job subjects using various psychodiagnostic techniques. The main conclusions of the research are: a list of difficulties was compiled when conducting psychodiagnostics of an applicant for the position of sales manager; Step-by-step instructions are provided on how to correctly classify the main qualities and properties of a sales manager, taking into account the specifics of the company’s work, a request from the owner or manager of the company, and taking into account the knowledge and skills of a psychologist who deals with psychodiagnostics in this company. The author’s special contribution to the study of the topic is the systematization of the most sought-after qualities and properties of a sales manager and the proposal of psychodiagnostic and other practical tools for diagnostics. This article expands the knowledge base on the use of various diagnostic tools for a comprehensive diagnosis of sales managers and projective techniques for the purpose of diagnosing employees, and helps to identify the personal characteristics of employees in the private and public sector.

Use of ICT in Teaching Islamic Studies in Higher Education Schools

Information and Communication Technology is currently recognized as a viable and correct educational tool. The application of ICT makes the teaching and learning process simpler, closer, and easier to do anytime and anywhere. The availability and use of ICT tools in the teaching and learning arena is said to be one of the main determinants of the effectiveness of teaching and learning at all levels of education. Islamic Studies is one of the study programs offered in colleges of education in Nigeria that can be taught using ICT. Therefore, this study aims to examine the influence of ICT on the teaching of Islamic studies in universities of education. Three study objectives and research questions were formulated in this research. Descriptive survey research was adopted in this study. The population of this study were all Islamic Studies lecturers in all colleges of education in Kwara State and purposive sampling technique was used to sample respondents in this study. An adapted questionnaire entitled Uses of ICT in Teaching Islamic Studies was used. The main results of the study show that ICT has a significant positive impact on the effectiveness of teaching and learning. This research reveals that the use of ICT, such as computers, the internet, and educational software, has increased student participation and their understanding of Islamic study material. The implication of this research is that these findings highlight the urgent need to strengthen ICT infrastructure and provide adequate access to digital resources to improve the quality of teaching and learning.