1 Introduction
1.1 Research Backgrounds
1.1.1 National Policy Supports
The
Key Priorities of the Ministry of Education in 2022 proposed to implement the strategic action of education digitalization. In 2023, the
Opinions on Building a High-Quality and Balanced Basic Public Education Service System issued by the general offices of the Communist Party of China (CPC) Central Committee and a plan for the overall layout of the country’s digital development released by the CPC Central Committee and the State Council, proposed to vigorously promote national strategic action. In July 2024, the
Resolution on Further Deepening Reform Comprehensively to Advance Chinese Modernization passed by the third plenary session of the 20th Central Committee of the CPC, proposed to promote education digitalization (Editorial Board of
Primary and Secondary School Information Technology Education, 2024). Digital transformation of education has become an important strategic objective in the broader framework of national digital reform, representing a significant opportunity to forge new paths for educational development and create competitive advantages (
Zhang et al., 2024). In the global landscape of educational competition, Chinese students’ digital literacy enables them to stay at the frontiers of information, cultivate global competence, and enhance their international competitiveness and academic advantages in the future. Chinese teachers, grasping this opportunity, participate in digital literacy training, share distinctive teaching experiences in international exchanges, and enhance their professional competencies. China’s digital transformation in education is remarkable in both scale and speed. China, relying on its institutional advantages, can rapidly popularize new technologies, iterate and upgrade, and build a comprehensive digital ecosystem, covering preschool, elementary, higher, and vocational education. This showcases the vitality and resilience of the system, attracts international exchanges, and presents Chinese characteristics and wisdom.
1.1.2 New Curriculum Standards
The latest elementary school mathematics curriculum standards propose a clear requirement to focus on the integration of information technology with curriculum contents, prioritize outcomes, and fully consider the application and the impact of information technology in mathematics teaching (
Li, 2024).
1.1.3 School Education Reforms
Founded in 2011, Jinshan School in Liangjiang New Area, Chongqing, is located in China’s third state-level opening-up and development new area. Since its inception, the school has adhered to its philosophy of liberating minds and pursuing dreams, and its motto of pursuing utmost goodness. The school has consistently ranked among the top in the district’s education quality assessments. The school has explored smart education using iFLYTEK’s products to adapt to the evolving information technologies and educational reforms. These products include Changyan smart classroom platform, which creates a networked, data-driven, interactive, and intelligent learning environment supported by cloud computing architecture. The Changyan smart classroom platform integrates virtual reality, in-class and extracurricular activities, and online and offline scenarios (
Liu, 2019). The school designated the fourth grade at its Qixia Road campus as the pilot program, focusing on mathematics and information technology teachers’ collaborative exploration of tablet-based teaching in smart classrooms.
Although schools are well equipped with digital resources, personal observations reveal that mathematics teachers in smart classrooms often use technology in a rigid manner, failing to leverage its potential strengths. Digital education is both a policy-driven mandate and a technological inevitability. This research seeks to enhance learning outcomes and teaching efficiency, providing insights for elementary mathematics educators to update teaching models and methodologies. Furthermore, it offers data to support the digital transformation of elementary mathematics.
1.2 Technological Supports
1.2.1 Education Digitalization
Education digitalization refers to the application of digital technology to reform the teaching process, emphasizing networking and intelligence. This approach leverages information technology to transform educational services, management, and teaching, with the aim of enhancing quality and efficiency of teaching and learning.
1.2.2 Smart Classroom
The smart classrooms aim at developing students’ intellectual abilities through reformed teaching methods and information technologies. Liu et al. (
2019) described smart classrooms as constructivist environments that harnessed next-generation technology to create efficient, data-driven, and innovative learning spaces. These classrooms utilize data analytics and mobile applications to revolutionize teaching processes, classroom structures, and contents, and establish appropriate information-based teaching models for the era of Big Data (
Liu, 2019).
1.2.3 iFLYTEK Smart Classroom
The iFLYTEK’s smart classroom is an intelligent product that is widely implemented across schools in multiple administrative regions in China. It believes that in the future, smart classrooms should effectively achieve intelligence, precision, ubiquity, subject-specialization, autonomy, and ecological friendliness. The regional pilot projects have driven innovation and provided training for numerous district and county teachers.
1.2.4 Integration Among Cloud, Edge, and Terminal
This framework integrates cloud computing and storage to manage teaching resources and data, platform-based hardware such as tablets for classroom interaction, and terminal software offering diverse learning and teaching tools. The iFLYTEK’s smart classroom is based on integration among cloud, edge, and terminal, allowing teachers to prepare in the cloud, display with hardware, and interact through software. Learning data are uploaded to the cloud in real time for analysis and evaluation, fostering a convenient and efficient teaching environment that enhances the quality and efficiency of education.
1.3 Theoretical Foundations
1.3.1 Constructivist Learning Theory
Constructivist learning theory posits that students connect with and activate relevant prior knowledge, analyzing and evaluating critically as they learn. Smart classroom, as a modern teaching model, leverages information technology to foster interactive and intelligent learning. This integration is evident in both teaching methodology and emphasis on respecting and stimulating learner agency. For example, constructivist methods utilize micro-lessons and other digital tools to organically integrate practical and theoretical coursework, creating a balanced and mutually reinforcing learning experience.
The development of the “3 + 5” teaching model exemplifies this integration. Beginning with the smart classroom 1.0 model rooted in constructivist principles, it has advanced to the 2.0 phase, incorporating teachers’ pedagogical expertise, and has reached the 3.0 stage now. This latest iteration integrates constructivist theory with personalized intellectual development, reflecting the ongoing synthesis of constructivist learning principles and smart classroom teaching innovations.
1.3.2 Cognitive Learning Theory
Cognitive learning theory categorizes the processes of human information acquisition into understanding, perception, memory, attention, and problem-solving. This theory emphasizes the learner’s competence to autonomously focus on, process, and comprehend external information, with higher accuracy in these processes correlated with improved learning outcomes.
In smart classrooms, tools, like Changyan smart classroom data system, allow teachers to monitor students’ learning progress and adjust their teaching methods and strategies based on real-time feedback. This function aligns with cognitive learning theory, promoting active student engagement while requiring educators to design lessons that coordinate with learners’ cognitive characteristics.
1.3.3 Optimal Learning Theory
Proposed by Soviet educator
Babanski (1973), optimal learning theory centers on the principle of optimization. Teachers must reflect on teaching tasks, principles, methods, modern teaching forms, internal and external conditions, and system characteristics to make deliberate and informed decisions that enhance instructional effectiveness (
Li, 2024). The “3 + 5” teaching model embodies the principle by utilizing Big Data to assess students’ academic performance and developmental needs. Teachers adapt their methods to guide students from surface-level learning to deeper cognitive engagement, ensuring that instructional strategies are informed by data and applied dynamically.
2 Research Methods
2.1 Literature Review Method
The literature review conducted in this research involved consulting relevant studies to contextualize the research within existing knowledge. Platforms like VIP Information and CNKI, we searched for keywords such as “digital education”, “smart classroom”, and “elementary school mathematics.” These searches yielded numerous articles that informed the study’s framework and provided valuable references for subsequent analysis.
2.2 Interview Survey Method
The interview survey method is a scientifically rigorous research approach in which relevant and effective information related to the study is gathered through in-depth communication with interviewees, guided by an interview outline. Fourth graders, representing a key developmental stage, are chosen as subjects due to their cognitive, learning, and feedback capabilities.
At the time of this research, other campuses are not mature, with some having few classes or lacking the fourth grade. Qixia Road campus, hence, is chosen as a pilot point. Stratified sampling has been employed to select 12 fourth-grade mathematics teachers across age groups—senior, middle-aged, and young groups. Fifty percent of the teachers in each category participated, including one district-level key teacher, one school-level key teacher, and four young teachers. Two classes per teacher are chosen by lot, with interviews conducted in two stages. The interviews consists of six questions, with answers recorded by hand at each stage.
To ensure privacy, participants’ names are anonymized, with teachers identified by numbers and students and parents by letters. Insights from these interviews illuminate teachers’ perceptions, suggestions, and actual application of the “3 + 5” smart classroom teaching model.
2.3 Survey Questionnaire Method
The questionnaire survey method is a research method that uses questionnaires to gather direct data reflecting study conditions. At Qixia Road campus, there are six mathematics teachers for the fourth grade, with each overseeing two pilot classes. Midway through the research, considering the actual conditions at the school, each teacher selects one of their two classes through a lottery to serve as the pilot class. These six pilot classes, comprising 51% of the total fourth-grade students at Qixia Road campus, have a gender distribution of 53% boys and 47% girls. The average final exam mathematics scores of these classes are close to the grade-level average score, and the gender and academic performance distributions in the pilot classes are closely resembled those of the overall student. Therefore, this research involves students from the six pilot classes at Qixia Road campus as survey subjects. Through the questionnaire, students’ views and feelings about the practical application of the “3 + 5” smart classroom teaching model are easy to be accurately captured.
3 Findings
3.1 Multiple Explorations to Establish the “3 + 5” Digital Teaching Model for Elementary Mathematics
3.1.1 The First Stage: Grappling with Uncertainty and Anxiety
At the start of the research, digital teaching model 1.0, an initial version of the elementary mathematics digital teaching model, is developed by reviewing relevant domestic and international literature. This initial model is depicted in Fig.1.
This teaching model is divided into three stages, including before, during, and after class system, each of them with corresponding activities. Pre-class data collection enables accurate identification of students’ current learning situations. As shown in Fig.2, teachers analyze learning situations, curriculum standards, and textbooks before class and pushing resource packs on the Changyan platform. Students then watch micro-lessons and complete guided assignments on the platform, facilitating to connect new and prior knowledge. Teachers adjust their instructional strategies based on the assessment data from the platform’s guided learning exercises. This process supports students in deepening their understanding of knowledge construction by reflecting on differences, fostering critical thinking, and providing multiple perspectives for deeper learning.
In-class multidimensional interaction enhances growth through information. As shown in Fig.3, teachers emphasize key points in the classroom using guided learning data from the Changyan smart classroom platform. Students are encouraged to rethink, discuss, and engage in group work on designated topics, drawing from their prior experiences and engaging in multidimensional interactive activities. This method allows students to actively construct knowledge in the context and work toward achieving learning objectives collaborative idea exchange.
Post-class data analysis informs personalized tutoring. As shown in Fig.4, in Liangjiang New Area in Chongqing, 55 schools, 2,192 classes, 6,083 teachers, and 92,883 students are using iFLYTEK’s Changyan smart classroom platform. The platform system utilizes Big Data to create student profiles, providing targeted supports based on individual differences during knowledge construction. Personalized learning plans and exercises are formulated for each student. Additionally, parents are allowed to log into the platform at any time to monitor students’ learning progress, ensuring timely communication between home and school.
3.1.2 The Second Stage: Finding Inspiration amid Tension Through Interview
After initially determining a digital teaching model, grade-level teachers trialed it in their respective classes but soon identified several issues with model 1.0 through interviews. One teacher answered the second question on the inquiry “What is the learning effect of the smart classroom teaching model on student?” The answer presents: I use it about four to ten times a month. Students are very engaged with interactive features like quick answers and voting. However, maintaining classroom discipline and pacing remains a challenge. Additionally, during group discussion sessions, only a few students actively participate, while others remain passive. (See Appendix D: Response of Teacher 4 to the Pre-test Interview Question 2, January 2022)
One teacher answered the fifth question on the inquiry “What difficulties have you encountered when using the smart classroom teaching model?” The answer presents: Some parents, such as those of students D, J, and Q do not support or cooperate with its use. They are concerned about the potential impact on students’ eyesight, as the rate of myopia among primary school students is gradually increasing. (See Appendix D: Response of Teacher 2 to the Pre-test Interview Question 5, January 2022)
Based on teacher interviews, the use of electronic screens was detrimental to students’ visual health, and certain teaching components were not effectively implemented. For parents, the need for constant supervision added to their burden, leading to a formalized pre-class guided learning structure and polarized student outcomes. From the teacher’s perspective, grading was burdensome. Some teachers, due to insufficient training, had an inadequate understanding of smart classroom, rendering teaching model superficial.
Digital classroom construction should align with the curriculum system and focus on supporting student comprehensive development, avoiding the blind pursuit of trends or technolatrialism. As shown in Fig.5, in response to these challenges, teachers and we participated in training and reviewed relevant literature to transform their educational concepts and methods, ultimately developing the elementary mathematics digital teaching model 2.0.
Before class, micro-lessons are set up with check-in tasks and guided exercises, featuring automatic grading of objective questions. This promotes independent learning and allows teachers to prepare lessons based on precise data while also experiencing the advantages of smart education. During class, diverse teaching methods, such as group presentation and collaborative learning, are used to engage students via smart classroom technologies. This helps teachers to understand and implement the advantages of smart classrooms in practical teaching and fosters an appreciation of constructivist learning theories that prioritize student-centered learning and emphasize process and interaction. After class, resources and differentiated exercises are tailored to individual learning needs, further enhancing the precision of personalized learning and teaching.
Adjustments have been made to the scope and approach of the pilot. After establishing the digital teaching model 2.0 and considering teachers’ varying levels of familiarity with smart classrooms, the grade team now organizes smart classroom training sessions. Moreover, through a lottery system, one class from each teacher’s two classes is selected as the pilot class, reducing the number of pilots from twelve to six classes in the overall grade. The frequency of smart classes has also shifted from daily to weekly. Teachers within the group are divided into two teams, including senior and young teachers. The senior teachers’ team is responsible for overseeing the overall teaching process, including pre-class preparation, optimization of teaching designs, and formulation of post-class exercises. The young teachers’ team, in collaboration with information technology teachers, is tasked with recording discussion contents, creating micro-lessons, exercises, and other resource packages, and continuing to experiment with digital teaching in their classrooms. This structure allows teachers to deepen their understanding of smart education principles through distinct roles and responsibilities.
3.1.3 The Third Stage: Insights and Realizations
From the educational perspective, although the smart classroom is deeply integrated with information technology, technology is not a prerequisite. The core of smart education lies in nurturing individuals and transforming knowledge into wisdom. Three months of practice has shown that the digital teaching model 2.0 is maturing, with students, parents, and teachers working in harmony, although some issues persist.
At the student level, a minority of students procrastinate, skim through exercises without supervision, neglect personalized learning plans, and choose only the easiest questions from tiered exercises. At the parent level, some students are unable to complete guided learning content due to family reasons, such as busy parents or children with digital illiteracy being cared by elderly relatives who are not adept. This leads to inefficiency and time-consuming collaboration between family and school. At the teacher level, some have suggested reorganizing teaching components using systematic design. This approach coordinates and arranges teaching tasks and activities supported by technology at every stage, conducting in phases to construct comprehensive framework for smart classrooms and ensuring the implementation of all components.
To swiftly establish a digital educational teaching model, the grade team holds seminars weekly and organizes smart classroom sessions and trainings monthly. Based on practical teaching experiences, young teachers, veteran teachers, and information technology teachers have repeatedly revised and refined teaching segments. Based on the digital teaching model 2.0 and model 3.0, “3 + 5” teaching model is developed for elementary mathematics, guided by constructivist theories and integrating teachers’ educational wisdom to promote personalized intellectual development among students as shown in the Fig.6.
In the model’s name, “3” refers to three phases of instruction, including pre-class data collection for precise targeting of learning performance, multidimensional interaction during class, with information aiding growth, and post-class data analysis to support personalized tutoring. Moreover, “5” represents five steps of digital teaching, namely, prediction, fine-tuning, detailed explanation, intensive support, and extension.
The first step is prediction. Before class, teachers draw on their experience to anticipate students’ performance and prepare lessons, distributing guided learning resource packs. After receiving the information and instructional resources, students compare new knowledge with their prior experiences, attempt to understand new concepts, memorize important points, and gain a preliminary understanding of learning contents.
The second step is fine-tuning. Based on students’ guided exercise data, the teaching plan is adjusted accordingly, and the teaching design is optimized synchronously. Teaching methods and contents are adapted based on a thorough consideration of students’ prior experiences and new knowledge acquisition, helping students focus on learning, enhancing their understanding, and encouraging them to reflect on their learning strategies to reinforce memory.
The third step is detailed explanation. During class, teaching is precisely managed based on real-time data, concentrating only on what students do not know. The use of human–computer, student–student, and teacher–student interactions, along with diverse teaching and monitoring methods, enhances students’ perception and attention. In these interactions, students analyze and critique new information, ask questions, and express opinions to get help in overcoming difficulties.
The fourth step is intensive support. Personalized learning plans guide students both inside and outside school. Inside school, teachers provide one-on-one tutoring and group students into pairs to support the exchange of learning experiences and build knowledge connections. Outside school, micro-lessons are recorded and shared in class groups, and class data, varied problems, and learning suggestions are sent to parents, meeting individualized learning needs. This guides students to critically reflect on their learning and improve their learning strategies.
The fifth step is extension. Respecting individualized needs and various characteristics, tiered extension homework is assigned to integrate new and prior knowledge and expand students’ mathematical thinking. Simultaneously, evaluation scales and class reward and punishment mechanism are established. Students use these scales to assess their own learning outcomes, identify their advantages and disadvantages, and provide feedback on evaluation methods, stimulating their enthusiasm for learning.
3.2 Case Sharing: Learning About the “3 + 5” Elementary Mathematics Digital Teaching Model
The successful implementation of the “3 + 5” teaching model in pilot classes gave grade-level teachers confidence to begin expanding it across the entire grade in March 2022. It is mandated that each mathematics teacher conducts at least one smart class per month. In April 2022, the school held a competition based on the iFLYTEK smart classroom. In 2023, a high-quality lesson competition was held. Mathematics teachers from all grades actively participated, sharing valuable resources and advancing the deployment of this new digital teaching model. A deep understanding of the “3 + 5” digital teaching model for elementary mathematics is exemplified by the lesson set up and think from the newer People’s Education Press Edition of the first grade mathematics textbook.
3.3 Pre-Class Data Collection: Targeting Specific Learning Situations
Before class, micro-lessons and learning resource packs are distributed. Based on students’ completion of the guided exercise worksheets as shown in Fig.7 and 2022 curriculum standards, appropriate teaching objectives are identified along with key areas of difficulty.
The teaching objective is to use tablets on digital tables to arrange discs, enhancing students’ understanding of numbers up to 100 and reinforcing the concepts of digits and place value. By exploring the relationships among “number of discs”, “numbers arranged”, and “count of numbers arranged”, students will discover patterns and draw conclusions through the process of arrangement and reasoning (
Chen & Liu, 2016). This helps students apply their knowledge to solve practical problems, fostering their ability to reason abstractly and think critically. Students are encouraged to appreciate the importance of orderly thinking through both independent exploration and collaborative communication. The aim is to cultivate scientific spirit of inquiry, self-reflection, and bold exploration, making learning mathematics enjoyable and motivating students to engage and appreciate the subject.
The teaching focus is on deepening students’ understanding of numbers up to 100, emphasizing the concepts of digits and place value during activities. The teaching difficulty lies in guiding students through the full inquiry process, helping them realize the value of orderly thinking, and developing their initial inductive abilities.
3.4 Multidimensional Interaction During Class: Information Fosters Growth
During the lessons, real-time data are captured through digital devices, utilizing human–machine, student–student, and teacher–student interactions to monitor learning processes. As shown in Fig.8, the latest Changyan smart classroom teacher–student edition offers robust interactive features such as “group response” and “layered selection” for group participation, “quick response” and “random selection” for individual participation, and “discussion”, “voting”, and “in-class quizzes” for whole-class engagement. These features help students to efficiently understand ambiguous and obscure concepts.
During the lessons, teachers use macros in PowerPoint to create movable discs. Students log into Changyan smart classroom platform via tablets and use touchscreens to place discs in the units and tens positions as shown in Fig.9. This helps them to grasp the concepts of digits and place value, understand the relationship among numbers arranged in sequence, and learn to think in an organized manner.
3.5 Post-Class Data Analysis: Designing Personalized Tutoring
After class, students engage in group work to complete post-class tiered worksheets while sharing micro-lessons as shown in Fig.10. Using a class reward and punishment mechanism, group members evaluate each other based on the effectiveness of their completion as shown in Fig.11, filling out evaluation scales to earn corresponding scores in Fig.12.
3.6 The Transformation Brought About by the “3 + 5” Teaching Model
3.6.1 Enhancing Teachers’ Digital Literacy
The implementation of the “3 + 5” digital teaching model has resulted in a significant shift in educational perspectives, notably enhancing teachers’ digital literacy. Digital literacy refers to teachers’ awareness, ability, and responsibility in appropriately using digital technology to acquire, process, use, manage, and evaluate mathematical information and resources. It also includes their ability to identify, analyze, and solve problems in education as well as to optimize, innovate, and transform educational activities (
Ma & Yang, 2024). With the rapid development of information technology, the integration of digital technology and education is increasing. Additionally, policies like double reduction, educational evaluation reform are driving the demand for higher digital literacy among teachers. Enhancing teachers’ digital literacy is crucial for advancing the digital transformation of education.
3.6.2 Enhancing Students’ Comprehensive Literacy
The “3 + 5” digital teaching model fosters students’ curiosity through pre-class micro-lessons. The process of autonomous learning and inquiry further enhances students’ self-learning and problem-solving abilities. In-class group collaboration strengthens communication skills, while personalized learning consolidation plans and tiered extension exercises after class respect students’ individuality and diversity.
This research employs a questionnaire to gather statistics on the use of the “3 + 5” smart classroom teaching model in mathematics with students from 6 pilot classes in the fourth grade at Qixia Road campus. The anonymous survey was administered by school management staff who were not directly involved in teaching. During the questionnaire design phase, 50% of students from each of the 6 pilot classes are randomly selected for a preliminary survey. Based on the results from 139 students, the content and wording of the questionnaire are adjusted to eliminate misunderstandings, followed by the formal survey. A total of 285 questionnaires were collected, with 6 invalid questionnaires excluded and 279 valid questionnaires remaining. The data were processed by SPSS software, yielding positive results.
As shown in Tab.1, all reliability coefficients are greater than 0.8, indicating that the questionnaire is reliable.
The Kaiser-Meyer-Olkin (KMO) is a statistic used to measure the partial correlation between variables. The KMO value is 0.851, above the threshold of 0.8, and Bartlett’s test of sphericity yields an approximate chi-square value of 2199.740, with 21 degrees of freedom and a p-value less than 0.01. The p-value provides evidence in hypothesis testing. This indicates that the data are suitable for factor analysis, demonstrating excellent structural validity and scientificity.
As shown in Tab.2 and Tab.3, 87.10% of students use smart classroom for learning five or more times per week. The “3 + 5” teaching model has been widely adopted in the fourth grade mathematics instruction. Feedback from students indicates that this model positively impacts their learning, particularly by enhancing learning support, boosting confidence, and fostering interest in mathematics.
4 Conclusions
Based on iFLYTEK’s smart classroom, the “3 + 5” teaching model targets learning performances with precision, improves classroom efficiency, and offers personalized learning consolidation plans and tiered exercises. These features actively support digital transformation of elementary mathematics education. With continued exploration, the grade team has accumulated extensive practical experience, allowing this innovative teaching model to evolve and mature.
Inside the school, to enrich case studies, promote personalized teaching, and enhance educational quality, the school launched six cloud classes across four campuses in September 2024. Guided by the information technology team, this initiative aims at popularizing the “3 + 5” mathematics teaching model. In November 2024, the school established a smart education center to further these efforts. The center focuses on constructing and managing cloud classes and hopes to provide robust data support for the ongoing digital transformation of elementary mathematics.
Outside the school, the Jinshan Education Group has formed a mathematics master teachers’ studio and frequently organizes multi-district joint educational research activities. These efforts aim at promoting the “3 + 5” teaching model through collaboration and exchange, advancing elementary mathematics education. In December 2024, the group hosted an information technology educational research event in the Liangjiang New Area, Chongqing. During this event, the author delivered a lesson titled Efficient book borrowing and returning for the first semester of sixth-grade elementary information technology, extending the principles of the “3 + 5” model to other subjects.
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