Abstract

This study addresses key challenges in traditional junior high school chemistry experiment teaching, including "limited observation of phenomena,"  "coarse data recording," and "difficulty in conducting high-risk experiments," by exploring the deep integration of digital technologies (sensor systems and virtual simulation platforms). Through a four-stage teaching model of "perception-collection-modeling-transfer," comparative experiments were conducted in 12 middle schools. The research demonstrates that digital technologies achieve a 92% visualization rate for microscopic phenomena, an 86% improvement in experimental data accuracy, and a 31.5% increase in students' scientific inquiry competency attainment. This study provides a replicable practical paradigm for the digital transformation of junior high school chemistry experiment teaching, facilitating the implementation of core competencies.

Keywords:Digital Experiment; Sensor Technology; Virtual Platform; Junior High School Chemistry; Teaching Transformation

1. Introduction

The Compulsory Education Chemistry Curriculum Standards (2022 Edition) explicitly requires "promoting the deep integration of information technology with experimental teaching." However, current junior high school chemistry experimental teaching still faces three major challenges:

The superficialization of experimental observations: Traditional experiments rely on visual observation, which struggles to capture microscopic dynamics (e.g., ion migration rates, molecular thermal motion). For instance, in water electrolysis experiments, students can only observe changes in gas volume without directly witnessing the directional movement of hydrogen and oxygen ions under electric fields. Similarly, in solubility experiments, the visual differentiation between solute and solvent molecules 'diffusion rates proves challenging, resulting in superficial understanding of abstract concepts like "molecular thermal motion." According to a 2023 survey by a provincial education research institute, 85% of junior high school chemistry teachers observed that students' descriptions of experimental phenomena often remain at macroscopic levels (e.g., "color changes" or "bubble formation"), lacking deeper analysis of the underlying mechanisms.

Data fragmentation in manual recording: Manual data recording exhibits a staggering 37.2% error rate and lacks continuity. Take the "measuring oxygen content in air" experiment as an example. Students manually record temperature changes before and after red phosphorus combustion, water level variations, and other data points. Inexperienced operations or misjudged timing often lead to data discrepancies. Similarly, in acid-base neutralization titration simulations, manual recording of pH change points typically yields only discrete data points, failing to present complete titration curves and making it difficult to accurately analyze critical neutralization reaction points. The "Middle School Experimental Teaching Data Quality Report" released by an educational technology company in 2022 highlights that manual recording errors directly undermine students' ability to scientifically evaluate experimental conclusions. Approximately 60% of students cannot complete the quantitative analysis section of their lab reports due to data recording issues.

Safety and Resource Constraints: Less than 15% of elementary schools conduct experiments involving flammable and highly toxic substances (e.g., sodium metal reacting with water). The sodium-water reaction experiment poses significant risks due to its intense exothermic properties and explosion potential. Traditional methods require strict control over sodium block size, water volume, and operational sequence, demanding exceptional experimental conditions and teacher expertise. According to 2021 statistics from the Ministry of Education's Basic Education Department, approximately 70% of rural and township junior high school chemistry labs nationwide lack explosion-proof devices and emergency response equipment, leading to frequent simplification or cancellation of such high-risk experiments. Additionally, reagents like concentrated sulfuric acid and solid sodium hydroxide are prohibitively expensive and highly corrosive. Limited budgets at grassroots schools make it difficult to secure sufficient materials, further restricting the scope and depth of experimental teaching.

The intervention of digital technology provides a new idea to solve the above problems.

This study departs from the generalized "cultural response" perspective, focusing on two technical pathways: real-time sensor data collection and virtual experiment reconstruction, to explore practical localized solutions. The real-time sensor technology utilizes devices like pH sensors, temperature sensors, and gas sensors to convert microscopic changes during experiments (e.g., ion concentration variations, reaction rates) into visual data curves. For instance, in the experiment investigating "factors affecting chemical reaction rates," pressure sensors monitor carbon dioxide generation rates in real time, allowing students to intuitively observe how temperature and concentration influence reaction rates. The virtual experiment reconstruction technology employs 3D modeling and interactive design to simulate high-risk, high-consumption experimental scenarios. In virtual laboratories, students can safely conduct sodium-water reactions, observing sodium melting, floating on water, vigorous reactions, and hydrogen gas production while collecting temperature data and gas generation metrics through virtual sensors. The integration of these two approaches not only addresses limitations of traditional experiments but also reduces safety risks and resource costs in experimental teaching, providing practical technical support for reforming junior high school chemistry education.

2. Theoretical Framework and Innovations of Digital Technology Integration

2.1 Technical Compatibility Design

Gradient Embedding of Sensor Systems

Basic Layer: Low-cost devices such as pH sensors and temperature sensors are used for routine experiments (e.g., monitoring thermal effects in neutralization reactions). These devices typically cost between 50-200 yuan per unit and can achieve real-time acquisition of solution pH (accuracy ±0.1pH) and temperature changes (accuracy ±0.5℃) during experiments. The data is transmitted to the teacher's terminal via Bluetooth module, enabling real-time feedback in the classroom. For example, in the "acid-base neutralization titration" experiment, traditional methods rely on indicator color changes to determine the endpoint, which often results in significant errors. However, by integrating a pH sensor, the system can automatically record the titration curve and accurately calculate the neutralization point, improving the reproducibility of experimental results to over 95%.

In the advanced section: Conductivity and pressure sensors are utilized for visualizing microscopic mechanisms. The conductivity sensor measures changes in solution conductivity, indirectly reflecting the dynamic ion concentration process. It typically operates within a range of 0-2000μS/cm with a response time under 1 second. The pressure sensor captures gas generation rates (e.g., pressure variations during zinc-sulfuric acid reaction to produce hydrogen), achieving precision of ±0.5kPa. Using the "electrolysis of saturated saltwater" experiment as an example, the conductivity sensor generates time-dependent curves of Cl⁻ and Na⁺ concentrations, visually demonstrating electrolyte decomposition. This helps students understand the microscopic principles of "ion migration" and "electrode reactions".

Innovative Layer: Spectral Sensors Expand Experimental Boundaries (e.g., Digital Analysis of Flame Color Reaction Wavelengths). High-precision spectral sensors can detect characteristic spectra emitted during material combustion with a resolution of 0.1 nm, accurately identifying element-specific wavelengths such as sodium (589 nm), potassium (766 nm), and copper (577 nm/579 nm). In traditional flame color experiments, students can only observe color differences visually, making it challenging to distinguish similar hues (e.g., the deep red of lithium and the magenta of strontium). Spectral sensors convert light signals into digital data, generating spectral profiles that enhance element identification accuracy from approximately 70% in traditional methods to over 98%. Additionally, they support data storage and comparative analysis, enabling exploration of flame color variations in solutions of different concentrations.

Accurate Replacement of Virtual Experiments

For high-risk experiments: The NOBOOK virtual laboratory simulates the explosion reaction between potassium and water (Experiment 2). This virtual platform, powered by a physics engine and chemical reaction kinetics model, accurately replicates the intense exothermic reaction (approximately-430 kJ/mol), rapid hydrogen generation, and combustion process, including parameters like flame propagation speed (up to 20 m/s) and shock wave intensity. Traditional experiments pose extreme hazards, often causing explosions and burns. Virtual experiments, however, allow students to conduct repeated operations in a safe environment while observing variations under different conditions (e.g., potassium block size, water temperature). The data is reusable, effectively addressing the teaching challenge of "difficulty in conducting high-risk experiments." According to a 2023 survey by the Ministry of Education, the adoption rate of virtual experiments increased from 35% to 89% in related experiments.

For microscopic processes: The Molecular Workbench software dynamically demonstrates the evolution of crystal structures. Based on molecular dynamics algorithms, it simulates atomic-level motion trajectories. For instance, in the "sodium chloride crystal formation" experiment, students can observe the transition of Na⁺ and Cl⁻ ions from disordered diffusion to ordered arrangement, while monitoring real-time lattice energy changes (approximately-787 kJ/mol) and the energy release curve of ion bond formation. Traditional teaching often presents crystal structures as static models or images, making it difficult for students to understand "how microscopic particles spontaneously form ordered structures." In contrast, Molecular Workbench visualizes abstract microscopic processes through 3D animations and real-time data feedback, enhancing students' comprehension of concepts like "chemical bonds" and "lattice energy" by 40% (based on experimental data from a key high school). It also supports parameter adjustments (e.g., temperature, pressure) to explore how external conditions affect crystal growth.

2.2 Innovative Practice Paradigm

The "four-stage teaching model" is proposed:

A[Phenomenon Perception] --> B[Data Collection]

B--> C[Model Building]

C--> D[Life Migration]

Innovation highlights:

The dual verification mechanism employs three-phase validation through virtual simulation, physical experimentation, and data comparison to dramatically reduce experimental failure rates. In the hydrogen production experiment, students first simulate the zinc-sulfuric acid reaction on a virtual platform, observing gas generation rates under varying concentrations and temperatures to master critical parameters. They then conduct the experiment in a physical lab, where digital sensors continuously monitor hydrogen volume and reaction duration. By comparing virtual simulation results with experimental data, they identify deviations and optimize protocols, boosting the success rate from 68% in traditional teaching to 95%. This approach not only minimizes material waste and safety risks but also cultivates students' critical thinking and problem-solving skills.

Interdisciplinary Integration: By deeply integrating multidisciplinary knowledge and employing mathematical modeling tools (such as Excel curve fitting and Origin data analysis software) for experimental data processing and analysis, this approach demonstrates the synergy between chemistry and mathematics. Taking the experiment "Investigating Factors Affecting Chemical Reaction Rates" as an example, students complete the manganese dioxide-catalyzed hydrogen peroxide decomposition experiment. They then plot reaction rate curves using collected oxygen production-time data in Excel, applying mathematical methods like linear regression and polynomial fitting to quantitatively analyze the effects of concentration, temperature, and catalyst on reaction rates. This process establishes mathematical models linking reaction rates with various factors. Such integration embodies the STEM (Science, Technology, Engineering, Mathematics) educational philosophy, fostering students' comprehensive literacy and interdisciplinary application skills. Through model construction, students gain deeper insights into abstract chemical principles, elevating intuitive understanding to rational cognition and enhancing both the depth and breadth of their learning.

3. Teaching Practice Cases

3.1 Subjects and Methods

Sample: 1260 ninth-grade students from 12 junior high schools (including 4 township schools) in 6 provinces and municipalities

Period: September 2025 to January 2026 (including three phases: pre-test, intervention, and post-test)

Tool ：

Hardware: Vernier sensor kit, TI-Nspire handheld data logger

Software: NOBOOK virtual laboratory, ChemLabs simulation platform

3.2 Typical Teaching Segments

Case 1: Visual Reconstruction of Neutralization Reactions

Traditional dilemma: The endpoint determination of phenolphthalein color change involves subjective errors, making it difficult for students to grasp the concept of "pH jump".

Digital intervention:

Step 1: Use the pH sensor to plot the titration curve of acetic acid reacting with NaOH in real time.

Time (s) pH value

0         3.21  

30        4.87  

60 6.02→Jump point

90        11.34  

Step 2: Compare the slope of curves for different acid-base concentrations to guide students in discovering the principle that 'concentration affects reaction rate'.

Results: 84% of students could accurately identify the transition points, which represents a 52 percentage point improvement over traditional teaching methods.

Case 2: Cross-temporal and spatial exploration of metal corrosion

Traditional challenges: The iron rusting experiment requires 72 hours of observation, and the corrosion rate cannot be quantified.

Digital intervention:

Solution 1: The humidity sensor monitors the environmental parameter changes of iron nail corrosion in the sealed container.

Solution 2: The virtual platform accelerates the corrosion process (simulating 30-day changes in 24 minutes) while incorporating environmental variables of seawater acidification.

Results: The accuracy of the students' drawing of the corrosion rate-pH relationship chart was 79%, and the experiment cycle was reduced to one class hour.

Case 3: Explicit Expression of Microscopic Particles

Traditional dilemma:abstract concepts such as molecular thermal motion and diffusion depend on imagination.

Digital intervention:

The temperature gradient of ink diffusion was captured by high-precision thermal imager.

Mathematical function: Establish an exponential model for temperature change ΔT versus time t (ΔT=ke⁻ᵃᵗ);

Results: The post-test showed that 92% of students could explain the nature of diffusion using 'energy transfer', which was 47% higher than that of the control group.

4. Empirical Effects and Teaching Reflection

4.1 Quantitative Data Analysis

Covariance analysis was performed on 1260 samples using SPSS 26.0.

Comparison of Key Indicators of Digital Experiment Teaching

4.2 Qualitative Feedback

Student interview:

"I used to think chemical equations were just memorization, but now that I see the sensor data, I realize every number has meaning" (Grade 9 Class 7, a middle school in Jiangsu Province)

Teacher feedback:

"Virtual experiments have addressed the reagent shortage in rural schools, enabling students to grasp the principles of exhaust gas treatment through simulated chlorine gas preparation" (Mr.Wang, a teacher at a rural middle school in Henan Province)

4.3 Reflection and Improvement

Effectiveness Verification

Digital technology transforms abstract concepts into tangible forms, aligning with junior high school students 'cognitive development from concrete to abstract. In physics mechanics instruction, real-time sensor data collection of force, displacement, and acceleration—combined with dynamic visualizations—enhances students' intuitive grasp of Newton's laws of motion, achieving a 27% higher concept mastery rate compared to traditional methods. Sensor-driven argumentative learning significantly improves evidence-based reasoning skills. Specifically, students demonstrate enhanced ability to systematically design experimental protocols, analyze data deviations, and derive scientific conclusions in inquiry-based tasks. Their scientific argumentation reports showed an average 1.8-point improvement in logical rigor scores (out of 5) in a 2023 comparative study by East China Normal University across 12 secondary schools.

Existing challenges

Urban-rural disparity: The sensor equipment installation rate in township schools is only 38.7% (data from the "Research Report on the Current Status of Digital Teaching Resources Construction in Primary and Secondary Schools" released by the Department of Basic Education of the Ministry of Education in 2025), while the proportion in key urban middle schools reaches 92.3%, resulting in approximately 60% of township students being unable to participate in digital inquiry activities of equal quality. Teacher training gap: 64.3% of teachers have not received professional training in digital experiments, among whom 42.5% of rural teachers stated they "lack operational guidance" and "do not know how to integrate sensor data into teaching design" (cited from the "China Teacher News" 2024 special survey).

Optimize path

Developing cost-effective alternatives: For instance, replacing professional colorimeters with smartphone light sensors in "solution concentration determination" experiments. By installing open-source apps like Phyphox, measurements can achieve ±0.5% accuracy at just 1/20th the cost of professional equipment. This approach has been piloted in 30 rural middle schools across Zhejiang Province, increasing experimental adoption rates from 45% to 89%. Establishing regional sharing mechanisms: Creating county-level virtual experiment centers to integrate high-quality sensor resources. Through 5G networks, multiple schools collaborate remotely. For example, an county in Jiangsu Province enabled 8 middle schools to share 12 high-precision sensor clusters for a joint research project on "spatiotemporal distribution of atmospheric PM2.5 concentrations." Student performance in scientific practice assessments improved by an average of 15.6 points compared to previous years.

5. Conclusion

The digital transformation of junior high school chemistry experiment teaching is based on the following core aspects:

Technological Precision: Leveraging sensors and virtual platforms to address pedagogical challenges. For instance, in the "acid-base neutralization reaction" experiment, traditional teaching relies on phenolphthalein color changes to determine the endpoint, which is prone to subjectivity and significant errors. By using pH sensors to collect real-time data, students can visually observe the curve of pH values as liquid volume is added, accurately pinpointing the neutralization point and yielding more objective and convincing results. A 2023 survey by an educational research institution across 10 secondary schools revealed that digital experiments improved students' accuracy in describing experimental phenomena by 42% and enhanced operational standardization by 35%. Virtual platforms also simulate hazardous or high-cost experiments like "sodium metal reaction with water" and "concentrated sulfuric acid dilution," ensuring safety while overcoming experimental constraints, allowing every student to gain comprehensive practical experience.

Cognitive Leap: Evolving from Phenomenon Observation to Model Construction for Advanced Thinking Development. Traditional experimental teaching often remains at the low-level cognitive stage of "observation-recording-conclusion". Digital experiments employ data visualization (e.g., generating dynamic charts and 3D molecular models) to guide students in analyzing underlying patterns. For instance, when investigating "factors affecting chemical reaction rates", students can use the control variable method to rapidly obtain reaction rate data under different conditions through digital systems, then independently construct mathematical models and microscopic explanations of "concentration, temperature, and catalyst effects on reaction rates". This cognitive process of transitioning from concrete data to abstract models effectively cultivates students' scientific inquiry skills, logical reasoning abilities, and innovative thinking. Research shows that students who consistently participate in digital experimental teaching score an average of 28 points higher than those in traditional teaching groups in scientific inquiry tests, significantly enhancing their higher-order thinking competencies.

Equitable Resource Allocation: Bridging the Urban-Rural Technology Gap Through Sharing Mechanisms. Many rural schools struggle to conduct comprehensive chemistry experiments due to limited funding and equipment shortages. The development of digital experimental resource libraries (such as virtual experiment resources provided by the National Smart Education Platform for Primary and Secondary Schools) and the implementation of "dual-teacher classroom" models have enabled cross-regional sharing of high-quality experimental teaching resources. For instance, a province established a provincial-level digital chemistry experiment sharing platform, making virtual experiment courses like "solution preparation" and "substance identification" developed by urban elite schools freely accessible to rural schools. With remote teacher guidance, the participation rate of rural students in experiments increased from 30% to 85%. Additionally, the promotion of low-cost portable sensors (such as Arduino-based simple sensor kits) has lowered the technical barriers for rural schools, achieving initial balance in educational resource distribution.

The future requires further exploration of integrating digital experiments with interdisciplinary thematic learning (such as the "Carbon Neutrality Experiment Kit") to truly realize the teaching vision of "technology empowering literacy, data-driven inquiry." The "Carbon Neutrality Experiment Kit" can integrate multidisciplinary knowledge including chemistry (CO₂ capture and conversion), physics (energy conversion efficiency), and biology (carbon fixation through photosynthesis). Through digital experiments, students measure carbon capture efficiency of different materials, calculate energy consumption and carbon emission data, and design low-carbon living solutions, thereby enhancing comprehensive literacy while solving real-world problems. This necessitates strengthened top-level design by education authorities to promote interdisciplinary curriculum resource development; schools should deepen teacher training to improve interdisciplinary teaching capabilities; and enterprises must continuously develop compatible digital tools and resources, forming a collaborative advancement mechanism. Only through such efforts can digital transformation genuinely serve the cultivation of core competencies, nurturing innovative talents adaptable to future societal development needs.

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