Integration of Smart Teaching Technologies inCatalyst Skills Instruction for VocationalEducation an Empirical Study
Journal: Region - Educational Research and Reviews DOI: 10.32629/rerr.v7i8.4466
Abstract
Vocational education cultivates catalyst-skill chemical talents, but traditional instruction faces three issues: abstract microscale concepts (e.g., catalytic active sites), high equipment costs (XRD: 50k–200k), and limited hands-on training (8–10 students/share device, <5 min individual operation). This study proposes an integrated smart framework (VR/AR + virtual simulation + big data) and validates it via a quasi-experiment with 98 vocational chemical students (experimental: 50; control: 48). Results: (1) Experimental group’s theoretical score (82.5 ± 6.3) > control (75.3 ± 7.1, p < 0.01), 20% higher catalytic mechanism accuracy; (2) 25% faster Ni/Al₂O₃ preparation (45 ± 5 min vs. 60 ± 8 min), 30% higher parameter precision (pH: ±0.2 vs. ±0.5), 21.7% higher BET (185 ± 12 m²/g vs. 152 ± 15 m²/g, meeting Sinopec's ≥180 m²/g); (3) 85% experimental group reported high interest vs. 52% control (p < 0.001). This framework bridges theory-practice gaps, offering a replicable model for vocational chemical education.
Keywords
Vocational Education, Catalyst Instruction, VR/AR, Virtual Simulation, Big Data Analytics
Funding
the Youth Fund Project of Jiangsu Vocational College of Electronics and Information (grant number JSEIZYB202403), the General Project of Philosophy and Social Science Research in Jiangsu Universities in 2025 (grant number 2025SJYB1436)
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