Fostering students' geographical synthetic thinking using geographic subject mind maps

The paper situates systems thinking as a foundation for understanding complex phenomena and argues that geography, dealing with the Earth as a complex system, naturally aligns with systems thinking. However, generic systems thinking lacks explicit geospatial embeddedness, limiting understanding of geographic phenomena. The authors define geographical synthetic thinking as systems thinking enriched with spatial (regional) cognition and temporal dynamics—comprehensive, systematic, spatial, and dynamic analysis of geographic phenomena—aligned with China’s Geography Curriculum Standards. Building on prior work that divides geographical synthetic thinking into six dimensions (geographical factors system thinking, geographical factors interaction thinking, temporal changes thinking, regional differentiation thinking, intraregional synthetic thinking, interregional synthetic thinking), the study proposes a geographic subject mind map (GSMM) as a visualization and problem-solving tool to cultivate these dimensions. Research questions: (1) How are geographic subject mind maps drawn? (2) How are the teaching application standards for GSMM established? (3) Can GSMM use effectively cultivate students’ geographical synthetic thinking? The study hypothesizes that standardized GSMM use will significantly improve students’ geographical synthetic thinking and that teachers’ GSMM application level will positively relate to student gains.

Theoretical background: Sustainability challenges (e.g., climate change, urbanization) require competencies to recognize system interconnections; systems thinking has been recognized internationally as a core educational competence. Yet, systems thinking often lacks geospatial embeddedness, prompting enriched conceptions that integrate spatial scales and regional variation. Geography uniquely emphasizes spatial change and human–environment interactions; thus, enriched systems thinking in geography—termed here geographical synthetic thinking—focuses on factor systems, interrelations, temporal dynamics, and regional differentiation and connections. Measurement: The study employs the Geographical Synthetic Thinking Measurement Scale (Lu et al., 2022), a 32-item instrument (24 items measuring six dimensions; 5 validity check items; 3 objective recognition items). Reliability is high (Cronbach’s alpha = 0.928 overall; subscales 0.631–0.786); items use a 5-point Likert scale; scores are converted to a 100-point scale. Empirical evidence: Prior research shows students need scaffolded guidance and visualization tools to develop systems thinking. Tools such as concept maps, causal loop diagrams, system diagrams, and computer modeling support systems reasoning, but disciplinary distinctions matter. In geography, traditional mind maps may not represent spatial differentiation or interregional synthesis well. This motivates the design of the GSMM, explicitly aligned to the six dimensions of geographical synthetic thinking with drawing/application standards.

Design: Quasi-experimental pretest–posttest study without a separate control group, using GSMM as the intervention. Teachers received training on GSMM drawing standards and teaching application standards, then implemented 4–5 experimental lessons using GSMM with their classes. Pretests of students’ geographical synthetic thinking (GST) were conducted before the intervention; posttests after. Hypotheses tested: standardized GSMM use improves GST; teacher GSMM application level correlates with student GST gains. Participants and sampling: Seven high school geography teachers across seven provinces/cities representing six major regions in China (Shandong, Shanxi, Guangdong, Shanghai, Heilongjiang, Xinjiang, Chongqing) taught eight class sections (T01–T08). Recruitment ensured teachers had been continuously teaching their classes (to avoid novelty effects). Initially 301 students consented; 267 provided valid pre/post data (ages ~16–18; 98 male/169 female). Ethics approval: ECNU Human Research Protection Committee (HR226-2022); informed consent from students, parents, and schools. Intervention: GSMM development and standards. Drawing standards (13 indicators) operationalize factor (F1–F5), time (T1–T2), space (S1–S5), and question (Q1):

• Q1: state the geographic question.
• F1: analyze from factor perspective; F2: include natural and human factors; F3: identify dominant factors; F4: link factors to regions; F5: show factor interactions.
• T1: specify time points/periods; T2: express temporal changes.
• S1: name regions; S2: indicate multiple regions; S3: analyze regional differentiation; S4: represent intraregional synthesis; S5: represent interregional synthesis (connections). Teaching application standards comprised two primary indicators with weights: A) involvement of GST dimensions (0.65) and B) standardization of mind map application (0.35). Subindicators:
• A1 Frequency of dimensions, A2 Coverage of six dimensions, A3 Implementation degree of dimension-specific objectives.
• B1 Introduction of GSMM drawing standards, B2 Analysis based on GSMM, B3 Guiding students to draw GSMM, B4 Showing teacher-drawn GSMM, B5 Guiding revisions and improvements. Procedures and implementation timeline: Pilot (June 2022) confirmed feasibility. Teacher training (Sept 5, 2022) on drawing/application standards and experimental procedures. Student recruitment followed. Pretests occurred Sept 14–Oct 20, 2022. Teachers designed five experimental lessons (four in one site) with GSMM and submitted plans for feedback/approval by the research team. Teaching ran Sept–Dec 2022 (amid COVID-19 disruptions: online, offline, hybrid modes). Posttests Dec 17, 2022–Jan 6, 2023. Across 38 lessons, 54 GSMMs were used (some lessons used multiple maps). The research team extracted GSMMs from lesson recordings for evaluation. Evaluation of implementation fidelity: Indicator A (dimension involvement) was judged by a panel (core authors plus two experienced teachers) identifying which GST dimensions each GSMM addressed; consensus reached after discussion. Indicator B (standardization) was rated by the three core team members from lesson videos. Weighted application levels per teacher were computed from A and B per preassigned weights. Measurement: GST measured by Lu et al. (2022) scale. The first 24 items form six 4-item subscales (max 20 each), converted to 100-point scale for dimensions and total. Data analysis: Normality of pre–post differences assessed (histograms, Q–Q plots, W-tests). Paired-sample t-tests evaluated pre–post changes overall and by dimension. Pearson correlation analyzed the relation between teacher GSMM application level and class-average GST improvement (both variables passed normality tests; W-test P teaching application = 0.326; W-test P improvement = 0.809). Additional case analyses examined classes with differing implementation (e.g., T06) and a retest for T06 to verify posttest reliability (retest ~50 days later; r = 0.671, p < 0.01). Context and materials: GSMM exemplars (Figs. 4–6) varied in conformity to drawing standards (12/13, 9/13, 7/13 respectively). Table-based standards guided design and application. COVID-19 conditions complicated delivery but all required lessons were completed (five teachers completed five lessons; one site completed four).

• Implementation fidelity: The weighted overall GSMM teaching application score across eight classes was 4.30 (>4.0 target). Subscores: A (involvement of GST dimensions) = 4.07; B (standardization) = 4.72.
• Overall learning gains: Mean GST increased from 64.87 (SD 10.64) pretest to 75.38 (SD 10.01) posttest; mean gain = +10.51 points, improvement rate 16.20%; paired t-test p = 0.000 (<0.001), indicating highly significant improvement.
• Dimension-level gains (all p = 0.000): • Geographical factors system: 70.02 → 82.68 (+18.08%). • Geographical factors interaction: 64.76 → 76.42 (+18.00%). • Regional differentiation: 67.34 → 76.61 (+13.77%). • Temporal changes: 64.19 → 73.15 (+13.96%). • Intraregional synthetic thinking: 58.31 → 69.36 (+18.95%). • Interregional synthetic thinking: 64.61 → 74.06 (+14.63%).
• Correlation between implementation and gains: Teacher GSMM application level positively correlated with class-average GST improvement (Pearson r = 0.722, p = 0.043), supporting the hypothesis that higher-quality, standardized GSMM use yields larger student gains.
• Class-level outcomes (illustrative): T03 (application 4.50) had the largest gain (+20.86). T06 (application 3.35; below the 4.0 standard) showed no improvement (−0.49), with limited dimension coverage (A2 = 2.50; only 3/6 dimensions covered) and lower target implementation (A3 = 2.92). Retest for T06 confirmed posttest reliability (r = 0.671, p < 0.01).
• Usage statistics: 38 lessons delivered, 54 GSMMs used across eight classes.

The standardized GSMM approach improved geographical synthetic thinking because it functions as: (1) a visualization tool that externalizes analytical reasoning and supports meaningful learning; (2) a structured thinking framework organizing factor, spatial, and temporal dimensions essential to geographic analysis; (3) a scaffolded instructional routine where teachers guide the drawing, analysis, and iterative refinement of maps; and (4) a metacognitive tool whose repeated use helps students internalize a habit of integrated, geographical problem-solving. The positive correlation between GSMM application level and student gains indicates the importance of both dimension involvement (coverage, frequency, and objective implementation) and standardized classroom practices (introducing standards, analyzing with GSMMs, guiding student drawings, presenting teacher exemplars, and revision activities). Case analyses reinforce this: high-fidelity implementations (e.g., T03) yielded strong gains, whereas limited dimension coverage and target implementation (e.g., T06) blunted impact despite high initial ability. Differences in indicator weights suggest some practices (e.g., hands-on analysis, guidance, and revision) may be more consequential than formal introductions of standards (B1). Teacher training likely enhanced awareness and consistent use of GSMMs, enabling scaffolding aligned to students’ zones of proximal development, particularly benefiting classes starting from lower baseline GST.

Standardized use of geographic subject mind maps significantly improves students’ geographical synthetic thinking overall and across all six component dimensions. Moreover, the level of GSMM application in teaching shows a significant positive relationship with student improvement. Effective implementation involves both (1) ensuring broad and frequent involvement of GST dimensions with clear objective realization, and (2) adhering to standardized GSMM teaching practices (introducing standards, guided analysis, student construction, teacher exemplars, and iterative refinement). The developed drawing and teaching application standards provide practical guidance to help teachers systematically cultivate GST. Recommendations include selecting integrative geographic issues, ensuring high coverage and frequency of GST dimensions in lesson design, and consistently applying GSMM standards to embed metacognitive strategies. Future work should expand samples, include control groups, and refine understanding of how specific GSMM practices and teacher/student characteristics mediate outcomes.

• No randomized control group; quasi-experimental design limits causal inference despite significant pre–post gains and correlational evidence.
• Small number of classes (n=8) and context variability (mixed online/offline delivery due to COVID-19) may affect generalizability.
• Potential confounds include differences in teachers’ understanding of GSMM, prior experience with synthetic thinking, and students’ prior knowledge and learning abilities.
• Implementation variability (e.g., uneven coverage of GST dimensions) influenced outcomes; fidelity measurement relied on expert ratings.
• Further research should add control groups, increase sample size, control additional variables, and disentangle direct and indirect effects of GSMM.