Knowledge Points Research Articles

Assessing dental student knowledge on cannabis and demonstrating the need for cannabis education.

The American Dental Association advocates for dentists' education on therapeutic and legal issues related to medical cannabis. It is important to understand current knowledge of cannabis and cannabinoids and to have a practical knowledge assessment instrument. This exploratory study is the first of its kind to assess dental students' knowledge of cannabis and aims to determine if there is a need for more instruction regarding cannabis in a dental school's curriculum. Predoctoral dental students at the University at Buffalo School of Dental Medicine were recruited to participate. A validated, anonymous 22-item online survey was adapted and administered to students in all 4 years of the dental program. There was a total of 56 knowledge points. The average knowledge score was 21.6 points (SD=5.2, range: 7-34), corresponding to 38.5% (SD=9.2) of the answers correct. There were no overall differences in knowledge by gender, years in dental school, or by any reported source of formal education on cannabis. Those who reported doing their own research had higher knowledge scores. Most participants knew that there is an endogenous cannabinoid system (72.3%) and that Tetrahydrocannabinol (THC) is responsible for the "high" experienced with cannabis (76.6%). Most participants reported that they did not know the effective doses of THC (58.2%) and Cannabidiol (CBD) (66.7%); few provided an answer for THC (34%) or CBD (17%) in the acceptable range of 2-10mg. Dental students did not have adequate knowledge on cannabis and cannabinoids. Given the rapid expansion of cannabis legalization, additional efforts are needed to integrate cannabis topics into coursework and learning experiences.

Online English writing teaching method that enhances teacher–student interaction

Abstract A significant component of the online learning platform is the online exercise assessment system, which has access to a wealth of past student exercise data that may be used for data mining research. However, the data from the present online exercise system is not efficiently used, making each exercise less relevant for students and decreasing their interest and interaction with the teacher as she explains the activities. In light of this, this research creates an exercise knowledge map based on the connections between workouts, knowledge points, and previous tournaments. The neural matrix was then improved using cross-feature sharing and feature augmentation units to deconstruct the workout recommendation model. The study also developed an interactive text sentiment analysis model based on the expansion of the self-associative word association network to assess how students interacted after the introduction of the personalized exercise advice teaching approach. The outcomes demonstrated that the suggested model’s mean diversity value at completion was 0.93, an increase of 0.14 and 0.23 over collaborative filtering algorithm and DeepFM (deep factor decompose modle), respectively, and that the proposed model’s final convergence value was 92.3%, an improvement of 2.3 and 4.1% over the latter two models. The extended model used in the study outperformed the support vector machine (SVM) and Random Forest models in terms of accuracy by 5.9 and 1.7%, respectively. In terms of F1 value indicator, the model proposed by the research has a value of 90.4%, which is 2.5 and 2.1% higher than the SVM model and Random Forest model; in terms of recall rate indicators, the model proposed by the research institute has a value of 94.3%, which is an increase of 6.2 and 9.8% compared to the latter two models. This suggests that the study’s methodology has some application potential and is advantageous in terms of customized recommendation and interactive sentiment recognition.

CK12: A Rounded K12 Knowledge Graph Based Benchmark for Chinese Holistic Cognition Evaluation

New NLP benchmarks are urgently needed to align with the rapid development of large language models (LLMs). We present a meticulously designed evaluation benchmark that leverages the knowledge graph. This evaluation comprises 584 level-1 knowledge points and 1,989 level-2 knowledge points, thereby encompassing a comprehensive spectrum of the K12 education domain knowledge. The primary objective is to comprehensively assess the high-level comprehension aptitude and reasoning capabilities of LLMs operating within the Chinese context. Our evaluation incorporates five distinct question types with 39,452 questions. We test the current mainstream LLMs by three distinct modes. Firstly, four prompt evaluation modes were employed to assess the fundamental capacity. Additionally, for choice questions, a result-oriented evaluation approach was designed through data augmentation to assess the model's proficiency in advanced knowledge and reasoning. Moreover, a subset with reasoning process is derived, and the process-oriented testing method is used to test the model's interpretability and higher-order reasoning capacity. We further show models' capability in our knowledge points, and anticipate the evaluation can assist in the assessment of the strengths and deficiencies of LLMs on knowledge points, thus fostering their development within the Chinese context. Our Dataset will be publicly available in https://github.com/tal-tech/chinese-k12-evaluation.

Design of Virtual Reality Based Game for Dual Enhancement of City Monuments and Brand Image

The increasing accessibility of Virtual reality (VR) technology presents an opportunity for enhancing human immersion in several domains (Industrial, Social, Media, Cultural heritage, etc.). Moreover, it has huge impact to leverage its interaction and engagement; to un-dominate person on live, work, and diversion. The development of innovative VR-driven method is a sign of evolvement witnessed by the interaction design industry. In this respect, the work presents a complete framework for the design of virtual reality-based game; offering features, mechanisms, and 3D models that facilitate the development of interactive scenes, which reveal of the city’s historic monuments reality. The main research question focuses on empirically establishing the impact of virtual reality on video game design, including its influence on in-game cultural placement and its potential to enhance the retention of legacy game experiences within players’ memories. The results show that the game experience is felt original, enjoyable, and appealing for the user’s target group. Also, participants appreciate the use of VR technologies to explore cultural scenes and product; and to enhance empathy within a virtual experience. Furthermore, our research extends recent studies, proposing a VR-based design methodology, as well as, an assessing process. It guides the creation of visual representation of monuments, artifacts, and culture. Moreover, it improves user’s point of view and knowledge of the place they visit, within playing the WallysCar Crash Team Racing (WCTR) game. Our project intended to achieve a twofold purpose related to the Tunisian context: discovering the popular “Sfax City” with historical and patrimonial monumental heritage, while promoting the local industry creation.

Multimodal prediction of student performance: A fusion of signed graph neural networks and large language models

In online education platforms, accurately predicting student performance is essential for timely dropout prevention and interventions for at-risk students. This task is made difficult by the prevalent use of Multiple-Choice Questions (MCQs) in learnersourcing platforms, where noise in student-generated content and the limitations of existing unsigned graph-based models, specifically their inability to distinguish the semantic meaning between correct and incorrect responses, hinder accurate performance predictions. To address these issues, we introduce the Large Language Model enhanced Signed Bipartite graph Contrastive Learning (LLM-SBCL) model—a novel Multimodal Model utilizing Signed Graph Neural Networks (SGNNs) and a Large Language Model (LLM). Our model uses a signed bipartite graph to represent students’ answers, with positive and negative edges denoting correct and incorrect responses, respectively. To mitigate noise impact, we apply contrastive learning to the signed graphs, combined with knowledge point embeddings from the LLM to further enhance our model’s predictive performance. Upon evaluating our model on five real-world datasets, it demonstrates superior accuracy and stability, exhibiting an average F1 improvement of 3.7% over the best baseline models.

A dataset without a code book: ethnography and open science.

This paper reflects upon calls for "open data" in ethnography, drawing on our experiences doing research on sexual violence. The core claim of this paper is not that open data is undesirable; it is that there is a lot we must know before we presume its benefits apply to ethnographic research. The epistemic and ontological foundation of open data is grounded in a logic that is not always consistent with that of ethnographic practice. We begin by identifying three logics of open data-epistemic, political-economic, and regulatory-which each address a perceived problem with knowledge production and point to open science as the solution. We then evaluate these logics in the context of the practice of ethnographic research. Claims that open data would improve data quality are, in our assessment, potentially reversed: in our own ethnographic work, open data practices would likely have compromised our data quality. And protecting subject identities would have meant creating accessible data that would not allow for replication. For ethnographic work, open data would be like having the data set without the codebook. Before we adopt open data to improve the quality of science, we need to answer a series of questions about what open data does to data quality. Rather than blindly make a normative commitment to a principle, we need empirical work on the impact of such practices - work which must be done with respect to the different epistemic cultures' modes of inquiry. Ethnographers, as well as the institutions that fund and regulate ethnographic research, should only embrace open data after the subject has been researched and evaluated within our own epistemic community.

Knowledge, attitudes, practices, and self-efficacy of the Chinese public regarding cardiopulmonary resuscitation: an online cross-sectional survey.

To evaluate the current status of Chinese public's knowledge, attitudes, practices (KAP) and self-efficacy regarding cardiopulmonary resuscitation (CPR), and to analyze the factors that influence KAP and self-efficacy. An online cross-sectional survey was conducted from February to June 2022 in Mainland China via a self-designed self-filled questionnaire. Potential participants were recruited through WeChat by convenience sampling and snowball sampling methods. Descriptive and quantitative analyses were used for statistical analysis. The survey included 4,450 participants from 31 provinces, autonomous regions, or municipalities across Mainland China, aged 18 or above. The public's average understanding (clear and very clear) of the knowledge regarding CPR was 67.4% (3,000/4,450), with an average proportion of positive attitudes at 96.8% (4,308/4,450). In practice, the average proportion of good practices was 92.8% (4,130/4,450), while the percentage of good self-efficacy averaged at 58.9% (2,621/4,450), only 42.4% (1,885/4,450) of the participants had confidence in the correct use of automated external defibrillator (AED). Pearson correlation analysis showed a significantly positive correlation among knowledge, attitude, practice, and self-efficacy (p < 0.01). Multiple linear regression analysis revealed that several factors have a significant influence on the public's CPR KAP and self-efficacy, including ever having received CPR training (p < 0.001), hearing about AED (p < 0.001), performing CPR on others (p < 0.001), hearing about CPR (p < 0.001), occupation (p < 0.001), personal health status (p < 0.001), education level (p < 0.001), gender (p < 0.001), and encountering someone in need of CPR (p = 0.021). The Chinese public demonstrates good knowledge of CPR, positive attitude, and high willingness to perform CPR. However, there is still room for improvement in the mastery of some professional knowledge points related to CPR and AED. It should be noted that knowledge, attitude, practice, and self-efficacy are interrelated and influence each other. Factors such as prior CPR training, hearing about AED, having performed CPR before, hearing about CPR, occupation, personal health status, education level, gender, and having encountered someone in need of CPR have a significant impact on the public's KAP and self-efficacy.

Development of an integrated and project-based laboratory course in upper-level biochemistry and molecular biology.

An integrated and projected-based laboratory course was described, integrating interconnected knowledge points and biochemistry and molecular biology techniques on a research project-based system. The program, which served as an essential extension of theoretical courses to practice, was conducted with a sophomore of basic medical science who had completed the course in medical biochemistry and molecular biology. This course engaged students in learning "genetic manipulation" and "recombinant DNA technology" to understand the target gene's role in disease mechanics, thus altering evaluation and treatment for clinical disease. Students could master applied and advanced techniques, such as cell culture, transfection, inducing exogenous fusion protein expression, purifying protein and its concentration assay, quantitative polymerase chain reaction, and western bot analysis. This laboratory exercise links laboratory practices with the methods of current basic research. Students need to complete the experimental design report and laboratory report, which could be advantageous for improving their ability to write lab summaries and scientific papers in the future. The reliability and validity analyses were conducted on the questionnaire, and we examined students' satisfaction with the course and their gains from the course. The student feedback was generally positive, indicating that the exercise helped consolidate theoretical knowledge, increase scientific research enthusiasm, and provide a powerful tool to be a better person and make informed decisions.

Educational intervention to improve management of totally implanted vascular access device

Objective: To evaluate the effect of an educational intervention for nurses to increase knowledge and practical skills of management of totally implanted vascular access devices. Methods: A quasi-experimental study conducted in a teaching hospital. The intervention included exposure to a manual of procedures followed by a theoretical-practical training seven days later. Eighty-one nurses were evaluated at baseline, after self-exposure to the manual, and after receiving the theoretical-practical training. Participants were evaluated on their knowledge and practical skills of totally implanted vascular access device management. Descriptive statistics were performed for all variables. Paired t test was used to examine whether the mean score changed from the baseline to first and second assessments of knowledge, access, de-access and maintenance of catheter. Significance level was set to 0.05. Results: Mean increases in scores after nurses were exposed to the manual were: 18.2 points for knowledge, 16.5 points for access technique, 15.5 for de-access technique, and 24.2 for catheter maintenance technique. After the theoretical-practical training, we observed a mean increase of 4.2 points for access, 3.9 for deaccess and 4.2 for catheter maintenance. Conclusion: The educational intervention for nurses increased mean scores of knowledge and practical skills. At the end of the intervention, 75% of the nurses reached at least 33 points out of 38 for knowledge, and 77%, 77%, and 78% had perfect scores for access, de-access, and maintenance, respectively. The educational intervention was effective in improving knowledge and practical skills for management of totally implanted vascular access devices.

Research on the application of knowledge mapping and knowledge structure construction based on adaptive learning model

This project has developed a geometry learning software that integrates multiple computer technologies to address the challenges of deep analysis of knowledge points and establishing connections in learning software. The software combines Long Short-Term Memory (LSTM) and Residual Neural Network (ResNet101) to encode text and image features. A self-attention mechanism is used to fuse information from both modalities, enabling decoding of geometric models and classification of corresponding knowledge points.This project uses LSTM and ResNet101 models to extract text and visual features for problem-solving using the Multi Mode Thinking Chain (CoT) method. Classification labels are utilized to generate text responses for problem-solving ideas. Furthermore, a recommendation module is proposed, which combines knowledge tracking and neural collaborative filtering algorithms to capture student behavior and knowledge point vectors. Implicit factors representing students' mastery of different knowledge points are used as inputs in neural collaborative filtering for personalized recommendations. The results demonstrate improvements in accuracy using the ResNet + LSTM multimodal algorithm, achieving a 13 % increase compared to single-modal classification. The multimodal CoT approach also outperforms language models like GPT3.5 and VisualBert by 10 %. Additionally, the combined algorithm of knowledge tracking and neural collaborative filtering shows a 13.3 % higher F1 value compared to ordinary algorithms, confirming the superiority of the adopted method in this project.

Knowledge of ocular infections among the dental practitioners across India: a cross sectional survey

BackgroundOcular issues such as impaired vision, ophthalmia, orbital cellulitis, and blindness are not common with dental infections. However, there is absence of set guidelines in prevention and management of ocular issues arising from dental infections. Hence the knowledge and vantage point of the dentists with respect to ocular complications arising from dental infections was evaluated.ObjectiveThis study reviews the knowledge of dentists with association of eye infection due to dental contamination.MethodA cross sectional survey using standardized questionnaires were sent suing social media platform among the academicians and practicing dental clinicians. All the questionnaires were content validated by three ophthalmologists. Descriptive statistics was scrutinized and tabulated by employing the Statistical Package for Social Sciences (SPSS), version 17 (SPSS Inc., Chicago IL). Chi square tests was used.ResultsAbout 69.1%(65) and 30.9%( 29) of BDS and MDS grduates have experienced ocular complications because of dental contamination. This distribution showed no statistical significance (p = 0.25). 73.8% (183) and 28.2%( 65) had compliance with the eye protection, 77.7% (160) of BDS graduates and 22.3% (46) of MDS graduates preferred safety eye wear. This distribution showed statistical significance (p = 0.00). About 76.2% (279) of BDS graduates and 23.8%( 67) of MDS graduates faced ocular infections because of different types of splashes which included water, blood and saliva. (p = 0.23)ConclusionThis study puts an emphasis on the knowledge assessment among the dental practitioners on the importance of preventive barriers, and how special protective gear is required for doing cases undergoing dental treatment.

Effect of Selected Antioxidants on the In Vitro Aging of Human Fibroblasts.

The modification of the replicative lifespan (RLS) of fibroblasts is of interest both from a knowledge point of view and for the attenuation of skin aging. The effect of six antioxidants at a concentration of 1 μM on the replicative lifespan of human dermal fibroblasts was studied. The nitroxide 4-hydroxy-TEMPO (TEMPOL), ergothioneine, and Trolox extended the replicative lifespan (RLS) (40 ± 1 population doublings (PD)) by 7 ± 2, 4 ± 1, and 3 ± 1 PD and lowered the expression of p21 at late passages. Coumaric acid, curcumin and resveratrol did not affect the RLS . The level of reactive oxygen species (ROS) was decreased or not affected by the antioxidants although TEMPOL and coumaric acid decreased the level of glutathione. Only ergothioneine and resveratrol decreased the level of protein carbonylation. The antioxidants that could prolong the RLS elevated the mitochondrial membrane potential. Protecting the activity of mitochondria seems to be important for maintaining the replicative capacity of fibroblasts.

Construction of Innovative Comprehensive Training Platform Based on Internet of Things Intelligent Hardware

The traditional training platform carries out experimental teaching for a specific course. The main content of experimental teaching is for each single knowledge point, not all experiments can be covered. Students can not rise from individual knowledge points to a systematic understanding of the course.This thesis addresses the problems of the traditional training platform and proposes that the construction of an innovative training platform based on Internet of Things intelligent hardware ,which covering multi-specialty courses is proposed.

Adapting an Environmental Scan for 'Insights Reporting': Learnings from an Online Brain Cancer Peer Support Platform.

When developing a digital health solution, product owners, healthcare professionals, researchers, IT teams, and consumers require timely, accurate contextual information to inform solution development. Insights Reporting can rapidly draw together information from literature, end users and existing technology to inform the development process. This was the case when creating an online brain cancer peer support platform where solution development was conducted in parallel with contextual information synthesis. This paper discusses the novel adaptation of an environmental scan methodology using codesign and multiple layers of qualitative rigor, to create Insights Reporting. This seven-step process can be completed in two months and results in salient points of knowledge that can rapidly inform the design of a solution, creating a shared understanding of a digital health phenomenon. Project members noted that Insights Reporting surfaces previously inaccessible knowledge, catalyzes decision-making and allows all stakeholders to influence the report agenda, affirming principles of digital health equity.

Knowledge, Attitude, and Practice Toward Dietary Salt Intake Among Medical Students at King Abdulaziz University.

Background Since the beginning of the century, dietary patterns have been changing rapidly due to evolving lifestyles, restaurants that cater to dietary restrictions, etc. As a result, populations started consuming a large amount of salt in their diets. Years of research have found that high salt intake is strongly related to many serious health problems like hypertension and cardiovascular diseases. This study's objective is to evaluate knowledge, attitudes, and practices regarding dietary salt intake among medical students at King Abdulaziz University (KAU) in Jeddah, Saudi Arabia, and to identify barriers and concerns related to optimum dietary sodium intake. Method A cross-sectional study done at KAU among 310 students using an online questionnaire included items to assess their knowledge, attitudes, and practices related to dietary salt intake. There were 24 questions to assess knowledge, six questions to assess attitude, and eight questions to assess practice. Results The mean age of the participants was 21.52 ± 1.94 years; 180 of the 57.5% were female. A score of "1" was given to the right answer for knowledge, positive attitude, and correct practice. The mean knowledge, attitudes, and practices scores were 16.99 ± 3.8, 3.03 ± 1.46, and 2.13 ± 1.34, respectively. The percentage of poor, fair, and good knowledge levels regarding dietary salt intake among studied students was 72:23%, 210:67.1%, and 31:9.9%. While the prevalence of negative, fair, and positive attitudes was 111:35.5%, 141:45%, and 161:9.5%. As for practice level, none of the students had good practice, while 263:84% and 50:16% had poor and fair practice, respectively. Conclusion In conclusion, the majority of students were aware that a high-salt diet can result in serious health issues. They were also uncertain of whether their salt intake was extremely high or not, which is consistent with thefact that they were ignorant of the daily salt intake guidelines. The findings in our study can stand as a reference point for salt-related knowledge, attitude, and practice (KAP) studies to help further future research in Saudi Arabia and other countries. Multi-sector coordination between the food suppliers, health agencies, and government is necessary to increase public awareness, decrease the salt content of food, and lower individual salt consumption in Saudi Arabia.

Construction and Application of Physical Education Classroom Teaching Model Integrating MOOC and Flipped Classroom

In terms of sports itself, mastering certain skills is a reliable way to avoid injury and futile training, and the teaching process needs to focus on imparting skills. Therefore, in order to optimize the teaching mode of physical education courses, this study explores the current improvement achievements and draws on the advancement of curriculum reform. The study proposes a recommendation method based on knowledge points and student characteristics by studying the characteristics and importance of sports techniques, in order to achieve high-quality customized content recommendations. Through validation experiments, the effectiveness of this recommendation method and optimization path is demonstrated. This study adopts an empirical research design to explore the impact of recommendation methods based on knowledge points and student characteristics on the teaching effectiveness of physical education courses. The effectiveness of this recommendation method is evaluated by collecting and analyzing students' learning data. Statistical analysis methods are used to analyze experimental data, including calculating the percentage of improvement in students' technical movements under different teaching modes. The research results indicated that recommendation methods based on knowledge points and student characteristics were of great significance for optimizing the teaching mode of physical education courses. The improvement of subjects' technical movements such as hitting and swinging in the new teaching mode was significantly better than that in the traditional teaching mode, with an increase of 10-20 technical movements per unit time, with a growth rate of over 20%. Compared with traditional teaching models, this teaching model has been subjectively recognized by students and has positive reference significance for the current physical education teaching model.

English Distance Teaching Based on SPOC Classroom and Online Mixed Teaching Mode

At present, the English Small Private Online Course (SPOC) online mixed teaching model has problems in evaluating students' learning and organizing teaching papers. For example, the evaluation is chaotic and unable to meet the key points of organizing the paper. Starting from the thinking chain that accepting learning outcomes can promote learning behavior, a score prediction method and test paper generation algorithm (TPGA) based on a learning evaluation diagnostic model are designed. Among them, the performance prediction algorithm is designed by combining multiple linear regression (MLR) and random forest (RF). The TPGA is based on students' learning status. The research results show that most of the predicted values output by the performance prediction model are not significantly different from the actual values. They are within a reasonable range. Meanwhile, under the influence of TPGA, the number of students in the experimental group is higher in the 70-80 and 80-90 segments, with 27 and 6, respectively. The experimental group has a higher average score rate on each type of question and knowledge point. Both models have high student satisfaction, indicating that the results oriented online mixed learning strategy designed in the study can effectively improve students' learning outcomes.

Research on the reform of the modularized curriculum of “Cultivation Technology of Northern Taoist Medicinal Herbs” in the context of the new version of GAP

Abstract This study explores the reform of the modularized course “Cultivation Technology of Northern Daoji Medicinal Herbs” in the context of the new version of the “Good Agricultural Practice for the Production of Chinese Medicinal Herbs” (GAP). The research methods include skill mapping and knowledge structure analysis, formal context theory, ensemble and analytic models, and learning path planning algorithms based on KL dispersion and matrix eigenvector similarity. These methods aim to construct course knowledge structures, clarify teaching and learning priorities, and generate personalized learning paths. RESULTS SURFACE: The established course knowledge network reveals the relationship between knowledge points through skill mapping and knowledge structure analysis. The network density is 0.0624, indicating fewer connections between knowledge points. The course contains 68 knowledge and skill points, among which the Degree of centrality of the skill node “Dewhead Cultivation” is the largest. Based on the analyzed knowledge networks and learning paths, the course was divided into several modules, each tailored to specific teaching objectives and students’ learning needs. Through the effective integration of skill mapping and knowledge structure, the modularized curriculum reform of “Cultivation Technology of Northern Medicinal Herbs” in the context of the new GAP not only improves the quality of teaching, but also meets the personalized learning needs of the students, and provides a new direction for future education.

Research on the Application of Knowledge Mapping Technology in Vocational Skills Training Demand Forecasting and Curriculum Designing

Abstract Due to the differences in individual qualifications, training duration, etc., the current vocational skills training is less efficient and cannot rationally arrange the training process and course content design etc. In this paper, we have constructed a model for predicting vocational skills training demand using knowledge mapping and knowledge tracking technology. First, a matrix is constructed to obtain the implicit relationship between knowledge. Reduce the influence weights with time intervals according to the theory of the forgetting curve. Modify the alignment scores of the attention mechanism to pay more attention to the relevant knowledge interactions in the sequence determined by the relationship coefficient g. Comparative analysis of the model and practical application reveals that the model in this paper has a better classification effect and better reflects the deeper recursive relationship and structure between knowledge points. When the professional teacher recommends the knowledge point C, the SVD model predicts the training demand of the trainees only 72.33%, while the model of this paper predicts 94.17% accuracy, which is highly compatible with the judgment of the professional teacher and more accurately identifies the training demand of the majority of trainees for the knowledge point C. The model provides a more scientific and reasonable curriculum and also provides a better classification of knowledge points. The model provides a more scientific and reasonable course design idea. Under the gradual course arrangement, the mastery of the knowledge points of the 20 trainees all shows a steady improvement trend. From the highest score of no more than 17 points in the first week to the 16th week at the end of the semester, all the trainees scored more than 70 points, which maximized the training efficiency. This study develops a reasonable course design based on the relationship between knowledge points, which can ensure gradual and interrelated progress and improve training efficiency and quality.

Correlation Analysis and Teaching Optimization of University English Lecture Mode Preferences

Abstract The article first discusses the categorization and difficulty of learning resources and proposes a method to quantify the difficulty of teaching resources. Then, the article recommends appropriate learning resources through similarity matching and student knowledge level diagnosis. This includes analyzing students’ test answers and modeling students’ knowledge level based on this. Data analysis and model building were employed to propose four key indicators: knowledge point density, knowledge point depth, evaluation index and correctness rate. In addition, cosine distance was employed to measure the similarity between resources and Hidden Markov Models were used to predict students’ knowledge point mastery. Four key indicators were effectively applied to construct a vector of resource difficulty indicators in quantifying learning resource difficulty. A vector representation of students’ knowledge mastery was successfully built in diagnosing students’ knowledge level. In addition, the article discusses the construction of a personalized learner preference model and a personalized English teaching model based on collaborative filtering algorithms. The effect of college English teaching can be effectively improved through the detailed Analysis of learning resources and the application of personalized recommendation model.