面向精准农业的Python编程教学改革：PBL驱动的课程开发与实践

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中图分类号：G640 文献标志码：A 文章编号：2096-9902（2025）16-0184-04

Abstract：Againstthebackdropofrapiditerationofsmartagriculturaltechnologyandexplosivegrowthofmulti-source agriculturaldataPythonprogrammingabilityhasbecomeacoreskillforprecisionagriculturepractitionersBasedonthecourse PythonandBiologicalDataProcessng，thisresearchproposesaProblem-basedLearing（PBL）AI-Pythoncollborativeteaching modelinresponsetotheprogrammingcognitiveanxietyandsubject transferobstaclesfacedbyzero-foundationlearnersmajoring inagriculture.Bybuildingathree-levelprogressveteachingframework：refiningrealbigdataprocessingneedsbasedon cuting-edgeliteratureonpreisionagiculture（askingquestions），usingAItolstostructuralldisassemblesolutions（disaeblig problems），andfinallycompletingPythoninanAI-asistedprogrammingenvironent.Codeimplementationanddebugging （problemsolving）.Comparedwithtraditionalgrammar-driventeaching，thisprogramrealizestheabiltytransitionfrom"code writing"to"intellgentsolution"，providesstrongsupportforcultivatinghighqualitysmartagricultualtalentshoadapttotheAI era，andprovides areplicable technical solution to thereform of programming coursesin agricultural coleges.

Keywords：precisionagriculture;Pythonprogramming teaching;A-asistedteaching;Problem-basedLeaing;interdisciplinary subjects

随着智慧农业技术的快速发展和多源农业数据的爆发式增长，Python编程已成为精准农业领域不可或缺的核心技能。（剩余5519字）