Informatics Technology Research Articles

The application of naive bayes method for final project topic selection within the project-based learning framework in the data mining course

<p>This study aims to explore the potential application of the Naive Bayes Method in predicting the determination of final project topics for students within the context of project-based learning (PBL) in the Data Mining course. Adopting an observational quantitative approach, the research involved 34 students from the Educational Technology Informatics Study Program at Padang State University between 2013-2015 as research subjects. The sampling technique employed was stratified random sampling, aligning with the research findings. The study's results indicate that the Naive Bayes Method is proficient in providing accurate predictions concerning the determination of final project topics, with significant accuracy, precision, and recall values. Moreover, the integration with project-based learning (PjBL) approach effectively enhances the authenticity and relevance of the learning experience for students, further substantiating the effectiveness of Project-Based Learning (PjBL).</p>

Accelerating the construction of digital and intelligentialized pathology and the prospects

With the continuous development of informatization, digitalization and artificial intelligence technology, the working mode of the pathology department has gradually changed from the traditional manual check, paper circulation and physical carrier storage to the informatization process and digital storage. The traditional pathology discipline has ushered in unprecedented opportunities and challenges. Digital pathology department also emerge as the times require. Simultaneously, with the full integration of artificial intelligence technology in pathology department, the concept of "department of digital and intelligentialized pathology" was proposed. Based on information and digital technology, the digital intelligent pathology department integrates intelligent management system, optimizes the previous cumbersome management and workflow of the pathology department, develops advanced technologies such as intelligent material extraction, unmanned organization processing, artificial intelligence quality control, artificial intelligence diagnosis, and promotes the intelligent construction of the pathology department.

Assessment of Smallholder Poultry Farmers’ Use of Information and Communication Technologies (ICTs) in Kwali Area Council of Abuja, Nigeria

ICT can be regarded as the combination of "informatics communication" and other technologies, especially communications technology. Informatics refers to the study of information, computation, and communication. This can apply to artificial systems such as computers or natural systems such as brains, genes, and living cells. Informatics technology refers to the technological application of informatics in society and is the study of the behaviour and structure of any system that generates, stores, processes, and presents information. A simple random sampling technique was used. The total sample size was 100. The questionnaire method of data collection was adopted to elicit information on the socio-economic characteristics of the farmers, their perceptions of ICT, the accessibility of ICT, and factors that affect the use of ICT technology by poultry farmers. The collected data was subjected to descriptive statistics (such as frequency tables and percentages) for analysis. The result showed that 61% of the farmers are actively participating in poultry farming; it also showed that extension service delivery made it easier for the farmers to get ICT information; and it also showed that high costs (71% of the time) were the major constraint to the adoption of ICT by the smallholder poultry farmers in the study area.

Analysis of the Immunogenicity of African Swine Fever F317L Protein and Screening of T Cell Epitopes.

The African swine fever virus (ASFV) encodes numerous proteins characterized by complex immune escape mechanisms. At present, the structure and function of these proteins, including the F317L protein, have yet to be fully elucidated. In this study, we examined the immunogenicity of the F317L protein. Mice were subcutaneously immunized with the F317L protein using initial and subsequent booster doses, and, at the 28th day post-treatment, we assessed the humoral and cellular immune responses of mice. The F317L protein stimulated production of specific antibodies and activated humoral immune responses. In addition, F317L stimulated the production of large amounts of IFN-γ by splenic lymphocytes, thereby activating cellular immune responses. Using informatics technology, we predicted and synthesized 29 F317L protein T cell epitopes, which were screened using IFN-γ ELISpot. Among these, the F25 (246SRRSLVNPWT255) peptide was identified as having a stronger stimulatory effect than the full-length protein. Collectively, our findings revealed that the ASFV F317L protein can stimulate both strong humoral and cellular immunity in mice, and that the F25 (246SRRSLVNPWT255) peptide may be a potential active T cell epitope. These findings will provide a reference for further in-depth studies of the F317L protein and screening of antigenic epitopes.

ОГЛЯД ТА АНАЛІЗ ІНФОРМАТИКИ ТА ІНФОРМАЦІЙНИХ ТЕХНОЛОГІЙ ЯК ОСНОВ СУЧАСНОГО ПРОГРАМУВАННЯ

The article focuses on the review and analysis of computer science and information technology as the foundations of modern programming, and the article presents theoretical aspects and concepts of their development that have a significant impact on technological progress and social development, which, in turn, contribute to innovations in various fields, from medicine to finance, making life easier and improving working conditions, creating new business sectors and labor markets that meet the requirements of the digital economy, changing the way of communication, education and interaction in society, including h The article analyzes software, which plays an important role in modern life, helping to solve various tasks and facilitating daily activities of users in various spheres of life. Accordingly, understanding its role and diversity is key to the effective use of technology in the modern world. In this article, we use the concept of logic in programming: decision-making (logic allows programs to make decisions based on conditions and circumstances), error avoidance (logical programming helps to avoid errors and wrong decisions in programs); code efficiency (the use of conditional statements and logical operations helps to make the code more efficient and readable); algorithms (developing effective algorithms requires logical thinking and the ability to make the right decisions at every step). In this article, we have also provided examples of programming languages. A programming language is a formal language construct designed to write computer programs. It defines the syntax and semantics that programmers use to create programs and interact with a computer. Today, there are many different programming languages, each of which has its own features and purpose. This article describes some of the most popular programming languages. Informatics and information technology have become not only the basis of modern programming, but also key determinants of technological progress and social development. Understanding their role and interconnection helps to unlock the potential of these industries for further development and achievement of new heights in technology and innovation.

Discovering the importance of health informatics education competencies in healthcare practice. A focus group interview

BackgroundAs healthcare and especially health technology evolve rapidly, new challenges require healthcare professionals to take on new roles. Consequently, the demand for health informatics competencies is increasing, and achieving these competencies using frameworks, such as Technology Informatics Guiding Reform (TIGER), is crucial for future healthcare. AimThe study examines essential health informatics and educational competencies and health informatics challenges based on TIGER Core Competency Areas. Rather than examine each country independently, the focus is on uncovering commonalities and shared experiences across diverse contexts. MethodsSix focus group interviews were conducted with twenty-one respondents from three different countries (Germany (n = 7), Portugal (n = 6), and Finland (n = 8)). These interviews took place online in respondents’ native languages. All interviews were transcribed and then summarized by each country. Braun and Clarke’s thematic analysis framework was applied, which included familiarization with the data, generating initial subcategories, identifying, and refining themes, and conducting a final analysis to uncover patterns within the data. ResultsAgreed upon by all three countries, competencies in project management, communication, application in direct patient care, digital literacy, ethics in health IT, education, and information and knowledge management were identified as challenges in healthcare. Competencies such as communication, information and communication technology, project management, and education were identified as crucial for inclusion in educational programs, emphasizing their critical role in healthcare education. ConclusionsDespite working with digital tools daily, there is an urgent need to include health informatics competencies in the education of healthcare professionals. Competencies related to application in direct patient care, IT-background knowledge, IT-supported and IT-related management are critical in educational and professional settings are seen as challenging but critical in healthcare.

The Role of Technology In Combating Fake and Malicious Contents

Technology presents a double-edged sword in the fight against fake content online This paper investigates the multifaceted roles of technology in the dissemination of fake content online. It explores how advancements like automation, social media algorithms, and deep fakes facilitate the spread of misinformation. Conversely, it examines how technologies like AI, fact-checking tools, and content moderation can be harnessed to mitigate this challenge Conversely, the paper examines how technologies like artificial intelligence (AI), fact-checking tools, and content moderation can be harnessed to mitigate this challenge. Finally, the discussion goes into policy considerations and potential future technological solutions for fostering a more trustworthy online environment (Shu et al., 2017; Tandoc et al., 2018). Keywords: Fake Content, Misinformation, Disinformation, Technology, AI, Fact-Checking, Content Moderation, Online Trust. Journal Reference Format: Omoyeni, O.E. Enyinnaya, C.V., Bardi, P., Ogbaini, C.A. & Ajayi, J.O. (2024): The Role of Technology In Combating Fake and Malicious Contents Social Informatics, Business, Politics, Law, Environmental Sciences & Technology Journal. Vol. 10, No. 1. Pp 17-24 www.isteams/socialinformaticsjournal. dx.doi.org/10.22624/AIMS/SIJ/V10N1P4

The Assessment of the Maturity of Informatization in Assembly-Building Projects Utilizing the CMM-CME Methodology, Taking a Project in China as an Illustration

Owing to its rapid advancement, information technology has emerged as a critical tool in assembly construction for addressing market demands, improving project quality, and reducing costs. However, the absence of unified informatization standards within the assembly construction industry has led to the adoption of different technologies and systems by various businesses during the development of informatization systems; this has generated issues such as unbalanced development and mutual incompatibility. While researchers have examined these issues, a comprehensive assessment of the maturity of informatization in assembly-building projects is lacking. Assessment of the maturity of informatization can provide evaluation standards and methods for the development of informatization of assembly buildings, explore the important and difficult points of applying informatization technology to assembly buildings, and put forward corresponding countermeasures and suggestions to promote the benign development of informatization of assembly buildings. Therefore, this study strives to develop a model for assessing the maturity of informatization of assembly-building projects. This study begins by determining the level of the maturity level of informatization, key process areas, and key practices for assembly-building projects using the capability maturity model (CMM). On this basis, the maturity evaluation index system was constructed through expert interviews and questionnaires. Furthermore, in order to assign weights to the indicators comprehensively, the ordinal relationship method and entropy weight method were implemented. The evaluation criteria were determined by consulting the relevant literature and expert opinions. Followingly, an evaluation model was established based on the cloud matter element (CME) theory. Finally, a case study demonstrates that the methodology can be utilized to quantify the maturity of project informatization. In conclusion, this study unearths a system for assessing the level of maturity of informatization of assembly-building projects, which provides a valuable reference for promoting the continuous development of the maturity of informatization in assembly-building projects.

Abstract 879: The AVERON Notebook to discover druggable cancer dependencies through the mutant-directed protein-protein interactions

Abstract Cancer is a devastating disease that takes more than 10 million lives every year. The genomic alterations, such as mutations in cancer driver genes, can disrupt the essential networks of protein-protein interactions (PPIs), dysregulating major oncogenic pathways and inducing the transformation. While some mutations can disrupt existing PPIs, others can create neomorph PPIs (neoPPIs), which are unnatural for wild-type counterparts. Discovery of such mutant-created neoPPIs is vital for understanding the molecular mechanisms of mutant-driven tumorigenesis and developing new personalized clinical strategies in cancer. However, systematic experimental interrogation of the clinical significance and biological functions of neoPPIs is highly challenging. To address this critical challenge, we develop a novel computational platform called AVERON Notebook for identifying new Actionable Vulnerabilities Enabled by Rewired Oncogenic Networks. The AVERON employs specially designed algorithms and statistical techniques to i) Assess and compare the levels of neoPPIs in cancer patients; ii) Examine their impact on clinical outcomes; iii) Identify distinctive sets of signature genes and oncogenic pathways regulated by individual neomorph PPIs; and iv) Discover clinically significant neoPPI-regulated genes with available clinical compounds and approved drugs. Together, the AVERON Notebook provides a powerful tool for exploring the functional consequences of tumor-driving mutations mediated through the neoPPI networks and sheds new light on previously unexplored clinically actionable dependencies enabled by neomorph PPIs in cancer patients. The AVERON Notebook is freely available onGitHub: https://github.com/aivanovlab/averon_notebook and Code Ocean: https://doi.org/10.24433/CO.7986101.v1 Acknowledgments: This work was supported in part by NCI’s Informatics Technology for Cancer Research (ITCR) Program (R21CA274620, A.A.I.), Mary Kay Foundation Grant for Cancer Research (A.A.I), NCI Emory Lung Cancer SPORE (P50CA217691, H.F.), NCI P01CA257906 (H.F.), Career Enhancement Program (A.A.I., P50CA217691), Winship Cancer Institute (NIH 5P30CA138292). Citation Format: Hongyue (Nicole) Chen, Sean Yeung, Brian Revennaugh, Haian Fu, Andrey A. Ivanov. The AVERON Notebook to discover druggable cancer dependencies through the mutant-directed protein-protein interactions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 879.

Latest developments, obstacles, and upcoming patterns in the realm of eHealth informatics: Review

The fusion of healthcare and information technology in eHealth informatics has rapidly evolved in recent years, presenting transformative possibilities for healthcare delivery. This article explores advancements, challenges, and emerging trends in this dynamic field, including telemedicine, wearable devices, Artificial intelligence, and data analytics. Despite promising developments such as predictive healthcare and personalized medicine, challenges like data security, interoperability, and ethical concerns must be addressed. Looking forward, the integration of genomics, Virtual Reality, and Argumented Reality is expected to reshape healthcare practices, emphasizing the importance of understanding and navigating these dynamics for an efficient, accessible, and patient-focused healthcare landscape.

Research on SPAD Estimation Model for Spring Wheat Booting Stage Based on Hyperspectral Analysis.

With the rapid progression of agricultural informatization technology, the methodologies of crop monitoring based on spectral technology are constantly upgraded. In order to carry out the efficient, precise and nondestructive detection of relative chlorophyll (SPAD) during the booting stage, we acquired hyperspectral reflectance data about spring wheat vertical distribution and adopted the fractional-order differential to transform the raw spectral data. After that, based on correlation analysis, fractional differential spectra and fractional differential spectral indices with strong correlation with SPAD were screened and fused. Then, the least-squares support vector machine (LSSSVM) and the least-squares support vector machine (SMA-LSSSVM) optimized on the slime mold algorithm were applied to construct the estimation models of SPAD, and the model accuracy was assessed to screen the optimal estimation models. The results showed that the 0.4 order fractional-order differential spectra had the highest correlation with SPAD, which was 9.3% higher than the maximum correlation coefficient of the original spectra; the constructed two-band differential spectral indices were more sensitive to SPAD than the single differential spectra, in which the correlation reached the highest level of 0.724. The SMA-LSSSVM model constructed based on the two-band fractional-order differential spectral indices was better than the single differential spectra and the integration of both, which realized the assessment of wheat SPAD.

Reduction of NIFTI files storage and compression to facilitate telemedicine services based on quantization hiding of downsampling approach

Magnetic resonance imaging is a medical imaging technique to create comprehensive images of the tissues and organs in the body. This study presents an advanced approach for storing and compressing neuroimaging informatics technology initiative files, a standard format in magnetic resonance imaging. It is designed to enhance telemedicine services by facilitating efficient and high-quality communication between healthcare practitioners and patients. The proposed downsampling approach begins by opening the neuroimaging informatics technology initiative file as volumetric data and then planning it into several slice images. Then, the quantization hiding technique will be applied to each of the two consecutive slice images to generate the stego slice with the same size. This involves the following major steps: normalization, microblock generation, and discrete cosine transformation. Finally, it assembles the resultant stego slice images to produce the final neuroimaging informatics technology initiative file as volumetric data. The upsampling process, designed to be completely blind, reverses the downsampling steps to reconstruct the subsequent image slice accurately. The efficacy of the proposed method was evaluated using a magnetic resonance imaging dataset, focusing on peak signal-to-noise ratio, signal-to-noise ratio, structural similarity index, and Entropy as key performance metrics. The results demonstrate that the proposed approach not only significantly reduces file sizes but also maintains high image quality.

Innovative Learning Strategies:Project-Based Learning Model for Excelling in Visual Programming

Modern education demands innovative approaches to engage students effectively and enhance learning outcomes. This article explores the implementation of an innovative pedagogical approach, namely Project-Based Learning (PjBL), in the context of the Visual Programming course. The study aims to investigate the impact of this approach on students’ participation and learning achievements. Using a Classroom Action Research (CAR) design, the research was conducted in two cycles. The participants were 30 students enrolled in the Educational Technology Informatics program at Universitas Negeri Padang. The study used a descriptive comparative method to assess the outcomes, comparing pre-cycle to Cycle II results. The findings reveal remarkable improvements in student’s cognitive growth (53.33%), affective development (46.66%), and psychomotor skills (56.66%) following the application of the PjBL approach. Furthermore, there was a noticeable increase of 43.44% in the active participation of students during the learning process after incorporating the PjBL approach. In conclusion, this study underscores the effectiveness of PjBL in fostering active participation and elevating learning achievements in the Visual Programming course. The article contributes to the discourse on innovative pedagogical strategies. It highlights the potential of PjBL to revolutionize traditional educational methods, equipping students with skills engagingly and effectively.

Factors Influencing the Use of the MPDN Application by Midwives at RSU Boven Digoel Regency, Papua Province in 2023

Background:Maternal Perinatal Death Notification (MPDN) is a fast and structured maternal death reporting application, utilizing the latest information technology and has been used for 15 years in Indonesia. Purpose of Writing: to determine the factors that influence the use of the MPDN application by midwives. Research Methods: This type of quantitative research uses a cross sectional study design, the sample in this study is 35 people, test the chi square analysis. Research Results: There is a relationship between knowledge (p value=0.012) and training (p value=0.002) with the use of the MPDN application by midwives, there is no relationship between attitude (p value=0.849) and the availability of smart phones and internet connection (p value=0.656) with the use of the MPDN application by midwives. Conclusions and Suggestions: It is hoped that the results of this study will serve as material for consideration and evaluation of improving the quality of human resources and quality of hospital services, one of which is by using the latest informatics technology for reporting maternal and infant mortality / Maternal Perinatal Death Notification.

ИНФОРМАТИКА И ВЫЧИСЛИТЕЛЬНАЯ ТЕХНИКА: ПРОБЛЕМЫ И ОСОБЕННОСТИ НАПРАВЛЕНИЙ ПОДГОТОВКИ

The article discusses the areas of training included in the enlarged group “Computer Science and Computer Engineering”. The relevance of the study is due to the approach to increasing the control figures for admission to training areas related to information technology, which does not solve the personnel problem in this area. The paper examines 140 higher educational institutions, which in 2022 announced enrollment for higher education programs in the enlarged group 09.00.00. “Informatics and computer technology.” Information was collected on the structure of open training areas at two levels of higher education in the context of higher educational institutions. Through an additional indicator, the demand for the implementation of a specific direction of training of an enlarged group within one university is determined. The format of enrollment within the framework of the powers granted to the admissions committees of higher educational institutions is investigated. The correlation between the distribution of budget places by the university and the popularity of specific areas of training of the enlarged group is determined. The leading universities in the federal districts, in terms of budget and commercial recruitment for the group under consideration are recorded. The proposals on system work with the enlarged group of directions of training of IT specialists are formulated: 1) adjust the system of distribution of admission control figures for the enlarged group “Computer Science, Computer Technology and Artificial Intelligence”, providing all applicants who have coped with the minimum requirements of higher education institutions with a budget place; 2) fix the combination of subjects of the unified state exam for admission to bachelor’s degree programs – Russian, mathematics, computer science and information technology communication technologies (ICT); 3) abandon five bachelor’s degree courses within the framework of a new enlarged group in favor of one that will form the universal competencies of an IT specialist; 4) implement a narrow-profile master’s degree program together with professional market partners through a project approach, limiting admission only with basic IT education; 5) implement a master’s program as a scientific program only within higher educational institutions institutions with current dissertation councils.

Information Technology Integration and Teaching Effectiveness Enhancement Strategies in Public Physical Education Programs

Abstract By integrating a heart rate monitoring module and a step frequency monitoring module, this study aims to use informatization technology to monitor the exercise level of students in public physical education courses and to adjust the teaching methods of public physical education courses based on informatization feedback. A school had 332 students divided into an experimental and control group for comparative experiments. Based on the results of students’ exercise data monitoring by heart rate oximetry module and acceleration sensor, it was found that the exercise density of students in the experimental group (73.3%) was much higher than that of students in the control group (54.4%), which means that the students’ exercise status was better under the informatization teaching mode. During the experimental period, there were significant differences in the average heart rate and MVPA percentage time between the experimental group and the control group students (p<0.05). The results of the physical fitness test showed that the informatization teaching mode significantly improved the student’s performance in body weight, pull-up, and standing long jump events (p<0.05) and significantly improved the student’s performance in lung capacity, sitting and lying forward bends, 50-meter run, and 1000-meter run events (p<0.01).

ОБЛАСТЬ СТАНДАРТОВ ОБРАЗОВАТЕЛЬНЫХ ИНФОРМАЦИОННЫХ ТЕХНОЛОГИЙ

The research, formulation, promotion and application of educational informatization technology standards are of great importance for promoting the standardized and coordinated development of educational informatization, as well as the implementation of the sharing of educational informatization resources and system compatibility. Therefore, the International Organization for Standardization and relevant international industry associations are paying more attention to this. Governments and enterprises from different countries have also invested in the development and application of educational information technology standards. This article briefly presents the current main international organizations for the standardization of educational information technologies and their main standards or specifications, as well as the work of our country in the field of international standards of educational information technology.

Analysis of Hybrid Feature Optimization Techniques Based on the Classification Accuracy of Brain Tumor Regions Using Machine Learning and Further Evaluation Based on the Institute Test Data.

The goal of this study was to get optimal brain tumor features from magnetic resonance imaging (MRI) images and classify them based on the three groups of the tumor region: Peritumoral edema, enhancing-core, and necrotic tumor core, using machine learning classification models. This study's dataset was obtained from the multimodal brain tumor segmentation challenge. A total of 599 brain MRI studies were employed, all in neuroimaging informatics technology initiative format. The dataset was divided into training, validation, and testing subsets online test dataset (OTD). The dataset includes four types of MRI series, which were combined together and processed for intensity normalization using contrast limited adaptive histogram equalization methodology. To extract radiomics features, a python-based library called pyRadiomics was employed. Particle-swarm optimization (PSO) with varying inertia weights was used for feature optimization. Inertia weight with a linearly decreasing strategy (W1), inertia weight with a nonlinear coefficient decreasing strategy (W2), and inertia weight with a logarithmic strategy (W3) were different strategies used to vary the inertia weight for feature optimization in PSO. These selected features were further optimized using the principal component analysis (PCA) method to further reducing the dimensionality and removing the noise and improve the performance and efficiency of subsequent algorithms. Support vector machine (SVM), light gradient boosting (LGB), and extreme gradient boosting (XGB) machine learning classification algorithms were utilized for the classification of images into different tumor regions using optimized features. The proposed method was also tested on institute test data (ITD) for a total of 30 patient images. For OTD test dataset, the classification accuracy of SVM was 0.989, for the LGB model (LGBM) was 0.992, and for the XGB model (XGBM) was 0.994, using the varying inertia weight-PSO optimization method and the classification accuracy of SVM was 0.996 for the LGBM was 0.998, and for the XGBM was 0.994, using PSO and PCA-a hybrid optimization technique. For ITD test dataset, the classification accuracy of SVM was 0.994 for the LGBM was 0.993, and for the XGBM was 0.997, using the hybrid optimization technique. The results suggest that the proposed method can be used to classify a brain tumor as used in this study to classify the tumor region into three groups: Peritumoral edema, enhancing-core, and necrotic tumor core. This was done by extracting the different features of the tumor, such as its shape, grey level, gray-level co-occurrence matrix, etc., and then choosing the best features using hybrid optimal feature selection techniques. This was done without much human expertise and in much less time than it would take a person.

A Scenario for a Model of Excellence in Comprehensive Cancer Care.

Cancer is the leading cause of death in Thailand, and the incidence of cancer is increasing substantially. The aim of the research was to develop a scenario for a model of excellence in comprehensive cancer care. Using Ethnographic Delphi Futures Research (EDFR), 30 expert informants in the field of cancer care were selected using the snowball sampling technique. The research tools were an interview guide and questionnaires. Data were transcribed, analyzed, and synthesized to yield a proposed scenario of the model, which was validated by seven qualified persons. The generated scenario for a model of excellence in comprehensive cancer care consisted of seven dimensions. The first five dimensions described excellence in service systems and comprised proactive prevention, early detection, rapid and accurate diagnosis, effective treatment from multidisciplinary teams, and palliative care to improve quality of life. The last two dimensions described supporting systems and comprised informatics technology and continuous research and innovation. The scenario for a model of excellence in comprehensive cancer care can be summarized according to the "3 Ts": transformation of cancer care, team and capacity building, and total quality management.

Research on the Influence of Modern Informatization Technology on English Education and Teaching in Colleges and Universities

Abstract With the development of modern informatization technology, how to combine modern informatization technology with English education and teaching in colleges and universities has become a key research direction in the current education sector. This paper proposes English information literacy education and teaching based on linear regression. The research problem and object are identified based on the current situation of English education and teaching in colleges and universities, and then a research design program is developed. Using a combination of linear regression algorithms and statistical analysis software, the mechanism of the influence of modern information technology on English education and teaching is analyzed by example. The results show that the average pre-test score of students at the intermediate level is 83.854 points. In comparison, the post-test score is 89.789 points, and the post-test score is about 5.935 points higher than the pre-test score, which indicates that there is a significant improvement in the English scores of students at the intermediate level after English informatization teaching. Taking English informatization teaching as the dependent variable and “teaching equipment” and “class size” as the independent variables, the regression equation of English informatization teaching = 0.215×teaching equipment+0.144×class size. This study has a far-reaching and positive impact on improving the quality and level of university English teaching, making teaching methods richer and the teaching effect more significant.