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Personalized or precision education (PE) considers the integration of multimodal technologies to tailor individuals’ learning experiences based on their preferences and needs. To identify the impact that emerging multimodal technologies have on personalized education, we reviewed recent implementations and applications of systems (e.g., MOOCs, serious games, artificial intelligence, learning management systems, mobile applications, augmented/virtual reality, classroom technologies) that integrate such features. Our findings revealed that PE techniques could leverage the instructional potential of educational platforms and tools by facilitating students’ knowledge acquisition and skill development. The added value of PE is also extended beyond the online digital learning context, as positive outcomes were also identified in blended/face-to-face learning scenarios, with multiple connections being discussed between the impact of PE on student efficacy, achievement, and well-being. In line with the recommendations and suggestions that supporters of PE make, we provide implications for research and practice as well as ground for policy formulation and reformation on how multimodal technologies can be integrated into the educational context.

This paper firstly proposes a precise vocal music teaching model based on information technology. Through the collection and in-depth mining of educational big data such as class attendance, after-class singing training, students’ performance, etc., and the use of precise mathematical model for processing and analysis, students can all explore deeply according to their own learning rhythm and interest points, and enhance the effect of vocal music learning. Then, precision teaching is applied to Z University, using a questionnaire survey and comparative analysis to discuss its application effect. Finally, the optimization strategy for precision teaching reform in the age of information technology is presented. The study shows that there is a significant linear relationship between class attendance, after-class training, and performance (P=0.001). The precise teaching method can significantly promote students’ development and improve their performance. There is a significant difference between the performance of the experimental and control classes with Sig. value equal to 0.03. Most students think that precision teaching is better than traditional teaching and that it is becoming a big trend.

This paper utilizes the methods of effectiveness prediction and teaching decision-making to construct a precise teaching management framework based on artificial intelligence, and gives a specific plan for carrying out precise teaching interventions in educational practice. This paper investigates the cognition and demand of students in Z province for precise education in college civics and politics through a questionnaire survey. It also researches and verifies precision education through practical research to present its effectiveness. The results show that in terms of the needs and preferences of various aspects of ideological and political education, the majority of students accounted for between 40 and 60%, which is a relatively even distribution, reflecting the diversity of needs. The p-values of the entrance examination and the final examination of the second semester, the final examination of the first semester and the final examination of the second semester are 0.046, 0.004 and 0.18 respectively.Precision teaching can significantly improve students’ Civic and Political Learning Effect.

This paper analyzes the technical and educational aspects of English teaching informatization, explores the impact of university English teaching reform on traditional English teaching in the informatization era, and designs an information technology-assisted precise English teaching model in three stages: before, during and after class. To realize accurate teaching, the FCE_DFM teaching resource recommendation model is constructed by the fuzzy C-mean clustering method in combination with the recommendation model based on self-encoder and FM. The RMSE and MAE values of this paper were reduced by about 0.12 and 0.2, respectively, compared with traditional recommended teaching, the attendance rate was increased by 22%, and about 2.0 points improved the emotional attitude toward learning through English teaching reform practice.

The article analyzes the precise teaching reform by applying artificial intelligence technology in English teaching in colleges and universities to improve teaching efficiency and student learning effect. The study establishes an English teaching model based on learner profiling, using artificial intelligence technology for student data analysis to achieve personalized customization of teaching content. Through empirical analysis, this study found that the experimental class adopting this teaching model significantly improved classroom interaction, learner class profile, and English performance. The average score of English assessment of students in the practical class increased from 55.5465 to 78.7267, and the passing rate also increased significantly. In addition, the teaching mode can effectively reduce the degree of dispersion of students’ performance and reduce the performance differences among students. The application of artificial intelligence technology in English teaching in colleges and universities can effectively promote students’ learning interest and performance improvement, providing a new direction for reforming English teaching in colleges and universities.

The present quantitative study aims to explore how students perceived the incorporation of precision teaching with Pinpoint, Record, Change, and Evaluation (PRCE) in a blended English course. This study surveyed 80 non-English majors at a Chinese university and utilised a questionnaire that focused on online learning experience, interaction, teaching quality, and evaluation, and overall satisfaction. The analysis of students’ responses showed that the blended design based on precision teaching gained positive learner perceptions due to its greater spatial and temporal flexibility, accessibility, targeted classroom instruction, increased learning autonomy, and more learner-instructor interaction. This study also established that learners’ positive attitudes towards blended learning featuring precision teaching were significantly linked to teaching quality and evaluation. The findings are discussed in alignment with those of earlier research, and practical implications for foreign teaching and learning in Chinese universities are also provided.

The research presents precision education that aims to regulate students’ behaviors through the learning analytics dashboard (LAD) in the AI-supported smart learning environment (SLE). The LAD basically tracks and visualizes traces of learning actions to make students aware of their learning behaviors and reflect these against the agreed goals. This research aims to realize the digital transformation of the learning space, thereby improving students’ learning outcomes with the assistance of the learning dashboard. To examine whether there was a close relationship between the frequency of using the whole platform and academic results, the data was collected from 50 first-year university students who registered with the innovative thinking course. Based on the data, we constructed the Technology Acceptance Model (TAM) questionnaire and interview guide to realize the students’ acceptance and feedback towards the SLE. Students were clustered into high-mark and low-mark groups based on their final results. The Wilcoxon rank-sum test is used to identify a significant difference between the two groups using the precision education platform. Subsequently, the partial least squares structural equation modeling (PLS-SEM) is further utilized to analyze the relationship between system quality, perceived ease of use, and perceived usefulness on behavioral intention and learning transfer.

According to the cultivation goal of vocational education, this paper analyzes the ontological connotation of digital transformation of vocational education from four aspects, namely, precise teaching, embodied learning experience, intelligent management mode, and visualization of evaluation path, and points out the direction of reform of “three-teaching” in higher vocational mathematics. The research subjects were selected and questionnaires were distributed to analyze the current situation of the “Three Teaching Reforms” of higher vocational mathematics under the perspective of digital education. The results summarize that 8 teachers believe that their ability to basically meet the needs of the “Three Teachings” reform, and the number of teachers who say that their ability is not quite able to meet the “Three Teachings” reform is the same, both accounting for 26.67%, while 53.33% of the teachers are still adopting traditional teaching methods and means. Teaching methods and methods. Based on the results of the current situation analysis, we propose a path for the reform of the three aspects of higher vocational mathematics under the perspective of digital education from the three dimensions of teacher cultivation, textbook innovation and teaching methods.

Leveraging the unique capabilities of intelligent technologies, this study presents an advanced approach to Civics and Politics education, emphasizing personalized and multimodal teaching strategies suitable for various educational stages. We establish an Integrated Civics and Political Teaching Platform using multimodal feature fusion algorithms coupled with personalized recommendation techniques. This platform incorporates genetic algorithm-based analysis of students’ learning behaviors, facilitating a Precision Teaching Service Model that tailors education to individual needs. A comparative study of semester scores highlights the model’s effectiveness: notably, a substantial 19.89 point increase in declarative knowledge scores and a significant reduction in the variability of strategic knowledge scores by 5.28 points. These results affirm the benefits of personalized teaching in enhancing student outcomes in Civics education.

Critical thinking is identified as a key educational outcome in higher education curricula; however, it is not trivial to support students in building this multifaceted skill. In this study, we evaluated a brief online learning intervention focusing on informal fallacy identification, a hallmark critical-thinking skill. The intervention used a bite-sized video learning approach, which has been shown to promote student engagement. Video-based learning was implemented within a precision teaching (PT) framework, which modulates the exposure of individual learners to the learning material to enable them to build ‘fluency’ in the targeted skills. In one of the learning conditions, PT was applied synergistically with domain-general problem-based training to support generalisation. The intervention consisted of two learning episodes and was administered to three groups (learning conditions) of 19 participants each: a PT fluency-based training group; a PT + group, where PT was combined with problem-based training; and a self-directed learning control group. All three groups showed comparable improvements in fallacy identification on taught (post-episode tests) and unseen materials (post-intervention assessment), with lower-scoring participants showing higher gains than high-scoring participants. The results of the knowledge retention tests a week later were also comparable between groups. Importantly, in the domain-general fallacy-identification assessment (post-intervention), the two PT groups showed higher improvements than the control group. These findings suggest that the integration of bite-sized video learning technologies with PT can improve students’ critical-thinking skills. Furthermore, PT, on its own or combined with problem-based training, can improve their skill to generalise learning to novel contexts. We discuss the educational implications of our findings.