Innovative Pathways for Interdisciplinary Integration Teaching in Big-Data Application Courses
Abstract
As big-data technology deeply penetrates finance, healthcare, education and other domains, society's demand for compound talent
who simultaneously master big-data technology and interdisciplinary application literacy has surged. At present, university big-data application courses suffer from single teaching concepts, content detached from interdisciplinary practice, and rigid pedagogies, all of which fail
to meet talent-training requirements. By analysing new talent needs in the big-data era, this paper identifies core problems and their roots in
interdisciplinary integration teaching, and proposes innovative pathways from the dimensions of teaching philosophy, content, methods and
faculty construction, so as to provide references for optimising curriculum systems and improving talent-training quality.
who simultaneously master big-data technology and interdisciplinary application literacy has surged. At present, university big-data application courses suffer from single teaching concepts, content detached from interdisciplinary practice, and rigid pedagogies, all of which fail
to meet talent-training requirements. By analysing new talent needs in the big-data era, this paper identifies core problems and their roots in
interdisciplinary integration teaching, and proposes innovative pathways from the dimensions of teaching philosophy, content, methods and
faculty construction, so as to provide references for optimising curriculum systems and improving talent-training quality.
Keywords
Big-data application course; Interdisciplinary integration; Teaching innovation; Compound talent; Teaching pathway
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PDFReferences
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DOI: http://dx.doi.org/10.70711/wef.v3i3.7930
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