Empirical Restructuring of Planning Education Under Spatial Data Science Intervention

Bibliographic Data

ID22047910
AuthorsLixiang Zhai (0000-0001-8416-1749, Gansu Agricultural University, corresponding author), Xiaoqian Wang (0000-0002-3144-8903, Gansu Agricultural University), Jingjing Zhang (0000-0003-0408-374X, Gansu Agricultural University), Peng Qi (0000-0003-0514-9464, Gansu Agricultural University)
Year2026
Volume16
Issue6
Pages932
Publication date2026-06-11
Open AccessYes
TypeARTICLE
VenueEducation Sciences (JOURNAL)
Journal identifiersISSN: 2227-7102 • E-ISSN: 2227-7102
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/educsci16060932
OpenAlexW7165058975
LanguageEN
References cited43

Driven by the digital transformation of territorial spatial governance, traditional urban planning is irreversibly shifting towards a data-driven empirical paradigm. However, constrained by mimetic isomorphism and path dependence, many geography-based regional universities remain trapped in an educational dilemma: they overemphasize morphological representation while marginalizing quantitative decision-making, fostering a structural mismatch between graduate competencies and industry demands. To explore a systematic pathway out of this dilemma, this study chronicles a three-year pedagogical intervention utilizing a mixed-methods design with a historical control cohort (N = 275) within the urban planning program of Gansu Agricultural University—a regional institution situated in a less-developed frontier where territorial renewal demands macro-spatial synthesis over aesthetic forms. The intervention strategically redefined the graduate competency profile as “spatial data analysts”, constructing a pedagogical model comprising foundational algorithmic training, cross-disciplinary faculty collaboration, and real-world Project-Based Learning (PBL), coupled with a restructured, evidence-based evaluation system. Longitudinal tracking and quantitative analyses indicate a structural alignment with elevated educational efficacy. At the macro level of employment trajectories, the proportion of graduates securing knowledge-intensive data positions experienced a structural shift, rising from a baseline of 14.5% to 42.5%, reflecting an enhanced capacity to capitalize on expanding societal demands. At the meso level of practical competence, the award rate in high-level professional competitions increased by 35.4%. At the micro cognitive level, the new evaluation mechanism is associated with a successful redirection of students’ cognitive resources toward algorithmic logic and policy translation (p

Cognition · Decentralization · Empirical research · Frontier · Restructuring · Spatial planning · Digital Transformation in Industry · Geography Education and Pedagogy · Smart Cities and Technologies

Tools

Open DOIOpen Access