Comparing Geoinformation and Geography Students’ Spatial Thinking Skills with a Human-Geography Pedagogical Approach in a Chinese Context

Abstract

We conducted a standardized spatial thinking ability test (STAT) to examine the spatial thinking abilities of a group of Chinese undergraduates with a focus on their spatial reasoning, which is a very important component of critical spatial thinking. The college subject of human geography in China is often geared toward the preparation of students for government consultancy and policy-making tasks, known as the “tasks leading disciplines” (renwu dai xueke), where the pedagogies are problem-solving based and sustainability centered. Geographic Information Systems (GIS) has become the universal tool for problem solving in geography and other areas, thus human geography in this situation gives us a context to test and investigate whether and to what extent GIS implementation is able to improve undergraduate spatial thinking levels. Our comparative analysis reported the marginally significant difference of STAT test scores between GIS application (geoinformation group) and its control group (geography group without GIS training). It was also found that the Chinese students performed the spatial reasoning better in this test than American participants as reported in prior study, displaying their higher spatial cognition in terms of problem solving and Boolean logics. Futhermore, a strong negative correlation was reported between STAT test scores and final exam rank. It is possible that the higher geography education in a context of China may not fully embrace the spatial thinking capacity as the strategic goal. The results can help us to better understand the Oriental and Western gaps in higher geography education. Policy suggestions are given in the conclusion.

1. Introduction

There has been a steady growth of interest in a series of geospatial technologies including Geographic Information Systems (GIS) learning and big data use in human geography pedagogy, which is essential to enhance the spatial thinking skills that uncover knowledge that is socially and spatially situated [1,2]. This research topic is derived from the substantial existing research on the importance of spatial thinking for geography learning and the various definitions, pedagogies as well as measurements of spatial thinking skills in relation to the geography education. The earliest study on spatial thinking can be dated back to the 1970s, when the researchers had proved the importance of map-use in enhancing the spatial ability in the geography education [3,4]. Considering the great potential to enrich GIS and other information technologies in geography education, the connections between information technologies (GIS, google map, smartphone and big data) and spatial thinking and the curriculum and student learning through information technology application became the foci in the geography education research during the 2000s and has continued until now [1,5,6,7]. The geographers Golledge et al. published a paper in the Annals of the Association of American Geographers in 2008 to display clearly the several essential spatial concepts that constitute spatial thinking and reasoning processes, for instance, distribution, distance, change, hierarchy and overlay [8]. The research by Golledge et al. and Lee and Bednarz has laid the foundation for a standardized test on spatial thinking ability, which is acknowledged by the Association of American Geographers and is now widely used in a context of geography teaching [8,9,10]. The studies on the application of information technologies in the different geography disciplines (e.g., geology, world geography and economic geography) have boomed in the past several years as a result [10,11]. In addition, the enhancing of higher-level spatial thinking (namely, critical spatial thinking) has attracted much attention since the 2010s [12].

However, little research has been conducted on the new technology application and its effects on the human geography teaching. More interestingly, relevant empirical studies on the Chinese cases were also rarely reported in the international research reports or journal publications. The concepts and tests of spatial thinking ability that are derived from the British and U.S. education system are now open to question in the light of our better knowledge of the various geography teaching across the different cultures and countries, particularly in the transitional China nowadays. As excerpted from the Advanced Placement Human Geography (also known as AP Human Geography) Course and Exam Description, the college human geography course has recognized the educational value of geospatial thinking skills and the importance of maps, GIS, quantitative models across geographic scales and other geospatial technologies in promoting the spatial thinking in the human geography curriculum development [13]. The 2019 AP Human Geography Course and Exam Description highlights the five categories of spatial thinking skills which are a recurring theme in the various topics in human geography textbooks (i.e., demographic geography, economic geography, cultural geography, political geography and urban geography) concerned with how humans interact with geographic and spatial concepts: a) the geographic concepts and processes in theoretical and applied contexts; b) spatial relationships in applied contexts; c) the quantitative geographic data analysis; d) qualitative geographic information analysis; and e) geographic multi-scalar analysis [13]. Human geographers have begun to build up the different pedagogical frameworks for spatial thinking training. Bednarz redefined the spatial thinking for specific suggestions in human geography teaching, and proposed that thinking through maps and in, about, and with space are all productive habits of mind for college human geography students [14]. While spatial thinking has been actively recognized and measured during the past two decades especially with respect to its relationships with the GIS teaching in the geography curriculum development [9,10,11], we still know little about the specific levels of spatial thinking performance within a particular human-geography pedagogical approach, and especially in the non-Anglo-Saxon geographical context like mainland China.

As argued by John R. Logan and Michael F. Goodchild, the last two decades have seen an explosion of interest in the application of spatial concepts and techniques in the social sciences and humanities [12,15]. Taking human geography as an example, the core concepts and GIS skills in geospatial thinking have been important forces to promote the cross-disciplinary analysis and the unified knowledge system in problem solving for purposes of sustainable development [16]. Unfortunately, there is a lack of quantitative studies reporting whether the spatial learning across the social science courses differ with respect to different instructional approaches. Among the social sciences and humanities, human geography is an interdisciplinary course that gives a context to test and investigate whether and to what extent the teaching with GIS skills would improve undergraduate spatial thinking levels. Human geography is one of the most basic compulsory geography courses in different countries, and a heavily enrolled elective course for problem-based learning among geoinformation students in mainland China. However, empirical studies are lacking as to whether and how human geography course can serve both geography and geoinformation students as a socio-economic problem-based venue to practice thinking spatially.

Our empirical study tries to fill this gap through the comparative assessment of a spatial thinking ability test (STAT) [9,10] in a human geography course with two sections at Capital Normal University (CNU) in Beijing, China, where the geography (Section 1) and geoinformation (Section 2) students participated in either a content-based (Section 1) or GIS-based (Section 2) instruction, and in either a local Chinese textbook (Section 1) or Anglo-Saxon (Section 2) textbook adoption. This kind of Chinese-English dual curriculum project in the undergraduate human geography courses is an important part in the Internationalization Demonstration School Plan in the College of Geospatial Information Science and Technology (CGIST) of CNU, which is managed and funded by the State Administration of Foreign Experts Affairs and the Ministry of Education of the People’s Republic of China. Based on such a local vs. international comparative human geography course, this paper examines whether and how an Anglo-Saxon human geography textbook integrated with GIS problem solving exercises can generate a better performance of students’ spatial thinking ability than a content-based Chinese teaching strategy. The college students’ perceptual and demographic variables such as gender, ethnicity, motivation and attitudes toward human geography are investigated, too, to search for the variance in spatial thinking skill acquisition among students under the two diverse human-geography pedagogical approaches. To be more concise, the research goal focuses on the following question: whether and how does teaching human geography with GIS (combined with an Anglo-Saxon human geography textbook) improve the undergraduate spatial thinking abilities as measured by the STAT in a context of China? Furthermore, what is the difference in students’ spatial thinking performance between Chinese and American college students?

2. Human Geography Teaching in China: A “Pseudo-Science” Education for Sustainability

In 1919, the climatologist and geographer Sir Chu Co-Ching founded the first department of geoscience in China in the Higher Normal College of Nanking (now the University of Nanking). Since the founding of the People’s Republic of China in 1949, geography in higher education in China has made great strides in improving the students’ thinking in terms of space and developing the problem-solving skills in various subject areas, especially in the sustainable development issues such as the urbanization, rural-urban migration, industrialization and tertiarization, and “Ecological Civilization” (shengtai wenming) and environment-related challenges [17,18]. Since the market-led reforms, teaching human geography outside the Anglo-American context still presents some outstanding pedagogical challenges, as the western concepts and theories might not be directly applicable in the particular institutional and development environments in China [19]. Human geography curriculum is developed and taught very locally, and its pedagogy in teaching human geography is institutionalized to a certain extent.

First, dated back to the late 1990s and early 2000s, Laurence J.C. Ma and other overseas Chinese scholars began to introduce a host of new human geography thoughts to mainland China, including the behavioralism, Marxism, humanism, feminism and the other postmodern perspectives for space- and place-based studies [20]. In many ways, as argued by Yeung Henry Wai-Chung [19], human geography is by its very nature a highly “localized” discipline in terms of its teaching languages, value systems, theoretical foundations and empirical examples. As a result, the western “cultural turn” and postmodernism have not become the core pedagogical approaches in teaching human geography in the transitional China. Some domestic scholars in China thought that the lagging behind of human geography teaching was attributable to a limited and regulated publication of translated books in human geography in the transitional period [21]. Human geography curriculum is criticized for being taught in as locally relevant and applicable a way as possible, and its pedagogy focuses too much on apparent forms rather than substantive contents [18,19,21]. It is thus difficult for Chinese students to understand the urban spatial structures around the post-modernist discussions of Los Angeles School, but they can map and explain it by the models of the Chicago School.

Second, the teaching of human geography is also influenced heavily by a unitary relation with physical sciences (including the physical geography, environmental sciences and ecology) because the Chinese government is calling for greater efforts in tackling sustainable development issues. This sustainable-development-oriented pedagogical approach in contemporary China is therefore different from the human geography teaching in the North America and Western Europe in their post-industrial periods. In this context, the fundamental pedagogical concern in human geography is to demonstrate the usefulness of a spatial- and place-based perspective towards sustainability. This interdisciplinary connection between human geography with the environmental and sustainable studies can be observable in the change of names among many prestigious geography departments in China to highlight its relevance for sustainability purposes [19,22]. Until now, the discipline of human geography in China has often focused on government consultancy and policy tasks, knowns as “tasks leading disciplines” (renwu dai xueke), inherited from the central-planning system. The preference for a wide range of planning theories and the related knowledge remains in the teaching of human geography for this reason. This problem-based and sustainability-centered teaching in the Chinese human geography curriculum was called a “pseudo-science” education in an introductory article by Sir Wu Chuan-jun about the progress of human geography in China [22].

This pedagogical approach in the Chinese human geography contrasts sharply with what may be considered a more theoretical and philosophical style of teaching human geography in an Anglo-Saxon context. The existing literature on the Chinese geography education rarely showed how such a sustainability-oriented and problem-based pedagogy has shaped the way of the production of geographical knowledge, and more importantly, how such a sustainable education orientation has impinged on the practice of teaching human geography and finally students’ spatial thinking. Although the spatial thinking ability in the Chinese colleges was rarely tested and reported, GIS learning has been advocated in China as a practical classroom-based pedagogy that can be used to develop spatial thinking and help students learn about the structure and operations of complex socio-economic system and environmental conditions [18]. To fill this research gap, the STAT developed by Lee and Bednarz [9,10] is adopted to measure the Chinese geography and geoinformation students’ spatial thinking skills taking different human geography courses: a local experience- and content-based pedagogy vs. the GIS-based Anglo-Saxon textbook adoption. Next, we will briefly review the literature in the spatial thinking together with the “critical” spatial thinking development through GIS tools, although its effects on the human geography courses were rarely recorded before.

3. A Rise of Critical Spatial Thinking: GIS Teaching on it and the Test on its Effects

Spatial thinking is acknowledged as a collection of three cognitive skills on the nature and concepts of space (such as distance, proximity, and distribution), on the representations of spatial information (such as maps and graphs), and on the processes of spatial reasoning (such as decision-making) [23]. GIS tools and other geospatial techniques, as a tool of spatial representation, have been proved an instructional approach to enhance students’ spatial thinking in numerous empirical studies since the early 1990s until now [24,25,26]. However, some other studies reported no significant variance between GIS application and its control group [25,27]. After three decades of debates on how to better define the complicated spatial thinking ability (beyond the simple recognition of spatial phenomena as advocated by psychologists), Lee and Bednarz and other geography educators have developed and verified the new types of assessment tools that can measure students’ higher spatial skills such as recognizing the spatial relations like spatial distributions, associations and hierarchies [9,10,28]. For instance, Question 4 of the STAT asked the students to choose the best site for a flood management facility based on the distance, elevation and land-use conditions [9,10]. In another test, the Google Earth skill was employed to assist students to manipulate the add-on overlays and see through what has changed in the superimposed layer into the base layer [29]. Similarly, in Kerski’s test, the students were asked to select the best location for the commercial purpose based on the given geographical data on the map [28].

These efforts for a standardized test of the students’ understanding of spatial relations are well acknowledged by the social studies educators including the human geography educators. As elaborated by John R. Logan, spatial thinking in the social science is the consideration of the relative locations of socio-economic phenomena, the causes and consequences of the locational pattern [15]. GIS and spatial statistics allow the visualization and insightfulness by making some associations between the spatial patterns and other extraneous information including: a) spatial variance like spatial clusters and outliers; b) distance as an indicator of access or exposure that is a basic for interpreting the inequality and clusters of related things; c) socio-spatial network proximity and connection; d) spatial dependence as an effect of neighborhoods; and e) multi-scalar effects [15,16]. The human geography and other social studies curriculums include many topics that involve an understanding of where people and places are located and why, spatial patterns and spatial relations of human settlement, migration, and conflicts over time, and the spatial distribution of economic activities and resources around the globe and at the local levels [14,15,30,31]. Students are also encouraged to conduct their own research using GIS tools on the empirical examples related to their everyday lives in these topics, such as community health, environmental exposure and inequality, residential segregation, neighborhood effects and land uses as elaborated by John R. Logan in his advocates for GIS applications in the social science [15,31]. However, the above “humanities disciplines most influenced by the linguistic and visual turns in scholarship over the past few decades have not given priority to critical spatial reasoning”, which is deemed crucial because the data manipulation, analysis, data mining, and modeling processes provoke and require critical thinking [32].

Since the early 2010s, the substantial research has focused on how to test reasonably a suite of critical spatial thinking and spatial reasoning ability that are essential to solve complex spatial problems in a real socio-economic world. Michael F. Goodchild used the word “critical” in the sense of a reflective, skeptical and analytic spatial thinking, “implying that the successful application of spatial perspectives can never be rote, but must always involve the mind of the researcher in an active questioning and examination of assumptions, techniques, and data if it is to meet the rigorous standards of good scholarship” [33]. Human geography that integrates the element that cuts across social sciences and humanity disciplines can provoke and require critical spatial thinking, concerning the comparatively profound issues such as multi-scales, tempo-spatial patterns, ambiguities and uncertainties, complexities, values and ethics.

After Goodchild’s emphasis on the critical spatial thinking in 2009 as a central education theme in the future digital world, especially in the field of humanities and social sciences [33,34], empirical studies have been conducted in the past decade on this critical spatial thinking issue across different fields, including undergraduate geology courses, economic geography course, GIS education, youth civic engagement pedagogies, as well as critical GIS in the design and planning [35,36,37,38,39]. As reviewed by Bearman in 2016, the critical spatial thinking skill is for students to be able to understand the spatial relationships, and to know how we can analyze these relationships, involving the following key set of skills: a) understanding the effect of scale and the role of assumptions in the use of spatial data; b) appreciating the difficulties of inferences in the multidimensional data; c) understanding the implication of problems and the uncertainty with spatial data; and d) applying geostatistical theory in the use of interpolation of spatial-temporal data [37]. Geography educators have tried to test this critical spatial thinking. Ormand tested the mental rotation, penetrative thinking and dis-embedding abilities of college geoscience students that were the well-acknowledged proxies for the spatial reasoning ability in analyzing a complex spatial relation within or between objects [35]. Kim and Bednarz used the STAT to test the relations between GIS learning and critical spatial thinking in the economic geography courses [36]. Huynh and Sharpe also tested students’ ability to reason about spatial relations, including identification of spatial patterns and spatial associations using GIS skills [40]. Similarly, Milson and Curtis proved that learning with GIS plays a positive role to enhance students’ critical spatial thinking by asking students to select the best location for a new business based on the given criteria [30].

To summarize, the prior studies have proved a positive role of GIS learning in developing the critical spatial thinking, especially in problem solving and a spatially integrative knowledge system for purposes of sustainable development. Nevertheless, the empirical studies in China were rarely reported to investigate the critical spatial thinking development in the geography or GIS courses. We will conduct an empirical study on the different pedagogies of human geography teaching in China, which is actually a “pseudo-science” education for sustainability as discussed earlier. This paper discusses different approaches of coping with the critical spatial thinking issue, one from the local content-based integrated human geography subject module and the other from a GIS skills-based module taught in an Anglo-American human geography textbook.

4. Methods

4.1. Participants

Prior research has pointed out that GIS learning in the curriculum of the social sciences and humanities is essential for fostering critical spatial thinking, but few empirical studies were reported [15,33]. In our study, human geography teaching in China is proved a “pseudo-science” education for sustainability. As reported in Liu’s empirical research on Singapore, the problem-based learning (known as PBL) together with GIS skills can develop the students’ higher-order spatial thinking including analytical and evaluation skills, rather than simply recalling the taught geographical information [41,42]. As a PBL pedagogy towards sustainability, human geography teaching in China can be seen as a good test for the effects of the well-known PBL-GIS pedagogy in the higher geography education. To be more specific, our research was conducted to investigate the pedagogical benefits of the enactment of GIS-enabled pedagogy in critical spatial thinking across the human geography teaching that would enable students to be competent problem solvers.

We employ the STAT [9,10] to compare and investigate the effects of the different human-geography pedagogical approaches: the local content-based module vs. the GIS learning module taught in an Anglo-American textbook. The English curriculum is derived from the Internationalization Demonstration School Plan in the CGIST of CNU. Two groups of participants were recruited for this comparative investigation: a) 51 geography students who took a compulsory human geography course in the local content-based module, without GIS enactment and b) 27 geoinformation students at the same grade level who were exposed to GIS courses and an intensive GIS training in visualizing and analyzing human geography problems. Although the sample sizes differed for the two groups, the t test procedure computed an approximate t test that did not assume that the population variances were equal or sample sizes were the same. In the reported results for the independent-samples t test, we selected the results on the conditions that equal variances or equal sample sizes were not assumed.

The human geography courses for geoinformation students were composed of two lectures on content parts and one laboratory session per week. The GIS practice was designed as a follow-up experiment using online database from the World Bank, UN and NASA’s websites, ArcGIS tools (such as table join, XY to line, overlay, clip and buffer) and Google map modules (such as satellite imagery, street maps, street view and historical view) to finish the mapping and spatial analysis on each related topic. To be more specific, this GIS learning material was derived from the widely accepted textbook, Exploring the Urban Community: A GIS Approach (second edition) written by Richard P. Greene and James B. Pick in 2012 [43]. The author Prof Richard P. Greene was the chief organizer of this course, who has made some modifications of the GIS learning material for the Chinese students. On the contrary, the human geography course for geography students was a content-based one using a Chinese textbook, which introduced the fundamental concepts, locational theories, and the knowledge about the cultural, political and behavior geographies, and especially the people-place relation and human geography practices in regional and urban planning towards sustainability in a Chinese context. The geography students did not take any GIS course before and were not exposed to the GIS learning environment this time. In this way, the geoinformation students (n = 27) acted as the treatment group, and the geography students (n = 51) as the control group. This relatively small sample of only 78 undergraduates was quite representative of a total of 320 undergraduates studying geography in all the relevant colleges in Beijing, involving those in Peking University, University of Chinese Academy of Sciences, Beijing Normal University, Capital Normal University and Beijing Union University.

Figure 1 shows one of the GIS practices in the urban geography topic that was designed by Prof Richard P. Greene. The GIS enactment provided students with tools for visualizing and basic spatial analysis in the geographic inquiry, such as demographic migration path, regional inequalities in GDP (known as gross domestic products) growth and import-export pattern, urban land use patterns and some other huge variety of human geography topics [44]. As shown in Figure 1, the geoinformation students were asked to download landcover imagery from website, symbolize different types of geographic data using points (such as sites of Forbidden City and CNU campus), lines (2nd to 6th Ring Roads in Beijing), and polygons (different land use patterns), and then use ArcGIS tools such as Clip, Buffer and Statistics Tools to create a map representing the land uses around the campus.

4.2. Research Design

This investigation covered all the second-year undergraduates of the participating human geography courses at CNU, Beijing, China. They were invited to complete the STAT test at the end of human geography courses in the early June of 2019 spring semester. The STAT test was modified to add in more personal information, compared with its original from Lee and Bednarz, dated back to 2009 [9,10]. This test consisted of 28 items, including STAT’s 16 standardized multiple choices, and 12 questions on their gender, major, ethnicity, parental educational levels, high school backgrounds (whether arts or science, which province, and the self-assessment of geography performance during the high school), a self-assessment of geography learning at the current college stage, their latest exam rank in class, the students’ assessment of the staff teaching, and their perceptions about the importance of GIS and English teaching as well as the local fieldwork for human geography learning. Another open question followed by asking for specific suggestions as to how to improve the human geography teaching in the college. We also invited several professors and PhD candidates in human geography and geography education fields to review this modified STAT test, and improve it based on comments.

Table 1. Students’ demographic and educational backgrounds, attitudes to geography & STAT results.

		Geography		Geoinformation		Total
		N	%	N	%	N	%
Gender	Male	5	9.8	12	44.4	17	21.8
	Female	46	90.2	15	55.6	61	78.2
	Total	51	100.0	27	100.0	78	100.0
Parental educational levels	College & above	30	58.8	17	63.0	47	60.3
	Senior/technical secondary	12	23.5	6	22.2	18	23.1
	Junior secondary	9	17.6	2	7.4	11	14.1
	Primary & below	0	0.0	2	7.4	2	2.6
	Total	51	100.0	27	100.0	78	100.0
Arts or science in senior high school	Arts	26	51.0	3	11.1	29	37.2
	Science	25	49.0	24	88.9	49	62.8
	Total	51	100.0	27	100.0	78	100.0
Which province do students come from	Beijing	43	84.3	14	51.9	57	73.1
	Others	8	15.7	13	48.1	21	26.9
	Total	51	100.0	27	100.0	78	100.0
Ethnicity	Han	45	88.2	21	77.8	66	84.6
	Others	6	11.8	6	22.2	12	15.4
	Total	51	100.0	27	100.0	78	100.0
Self-assessment of geography learning in high school	Excellent	7	13.7	4	14.8	11	14.1
	Good	27	52.9	11	40.7	38	48.7
	Medium	12	23.5	10	37.0	22	28.2
	Bad	3	5.9	1	3.7	4	5.1
	Awful	2	3.9	1	3.7	3	3.8
	Total	51	100.0	27	100.0	78	100.0
Self-assessment of geography learning in the college	Excellent	1	2.0	3	11.1	4	5.1
	Good	17	33.3	15	55.6	32	41.0
	Medium	30	58.8	8	29.6	38	48.7
	Bad	3	5.9	1	3.7	4	5.1
	Awful	0	0.0	0	0.0	0	0.0
	Total	51	100.0	27	100.0	78	100.0
The latest exam rank in the class (self-report)	1st quintile	9	17.6	8	29.6	17	21.8
	2nd quintile	7	13.7	6	22.2	13	16.7
	3rd quintile	18	35.3	10	37.0	28	35.9
	4th quintile	15	29.4	2	7.4	17	21.8
	5th quintile	2	3.9	1	3.7	3	3.8
	Total	51	100.0	27	100.0	78	100.0
Assessment of staff teaching in human geography	Excellent	21	41.2	14	51.9	35	44.9
	Good	26	51.0	11	40.7	37	47.4
	Medium	4	7.8	2	7.4	6	7.7
	Bad	0	0.0	0	0.0	0	0.0
	Awful	0	0.0	0	0.0	0	0.0
	Total	51	100.0	27	100.0	78	100.0
Is it necessary to keep or add the GIS learning?	Very important	6	11.8	13	48.1	19	24.4
	Important	26	51.0	11	40.7	37	47.4
	Neutral	17	33.3	1	3.7	18	23.1
	Not very important	2	3.9	2	7.4	4	5.1
	Not necessary at all	0	0.0	0	0.0	0	0.0
	Total	51	100.0	27	100.0	78	100.0
Is it necessary to keep or add the English teaching?	Very important	1	2.0	6	22.2	7	9.0
	Important	11	21.6	16	59.3	27	34.6
	Neutral	21	41.2	5	18.5	26	33.3
	Not very important	16	31.4	0	0.0	16	20.5
	Not necessary at all	2	3.9	0	0.0	2	2.6
	Total	51	100.0	27	100.0	78	100.0
Is it necessary to keep or add the fieldwork?	Very important	12	23.5	9	33.3	21	26.9
	Important	27	52.9	12	44.4	39	50.0
	Neutral	10	19.6	3	11.1	13	16.7
	Not very important	2	3.9	3	11.1	5	6.4
	Not necessary at all	0	0.0	0	0.0	0	0.0
	Total	51	100.0	27	100.0	78	100.0
STAT test (full score = 16)	< 10 (56.3% correct & below)	6	11.8	0	0.0	6	7.7
	10 ~ 12	11	21.6	5	18.5	16	20.5
	13	8	15.7	5	18.5	13	16.7
	14	9	17.6	7	25.9	16	20.5
	15	10	19.6	9	33.3	19	24.4
	16 (full score)	7	13.7	1	3.7	8	10.3
	Total	51	100.0	27	100.0	78	100.0

lists the students’ demographic and educational backgrounds, and their attitudes and performance toward human geography. Gender was unbalanced in the geography group (n = 51), with males only 9.8% but females as high as 90.2%. Such a gender imbalance is common in the Higher Normal College in China, as the female undergraduates display a much stronger preference to become geography teachers in secondary schools than their male cohorts. The GIS group (n = 27) displayed an almost equal proportion of males and females (44.4% vs. 55.6%). As a local college, 84.3% of its geography students were born and grown up in Beijing households. The local and non-local ratio of geoinformation students was more even, reported as 51.9% to 48.1%. A small handful of undergraduates were from the Uygur and Tibet Autonomous Regions, as a national plan to educate the new generation of ethnic minority students in the college periods (see Table 1). As demonstrated in Table 1, the geography and geoinformation students had a similar ratio of high score (33.3% vs. 37.0% in 15 ~ 16 range), but geoinformation students had an apparently much lower share in the low score (18.5% in the 0 ~ 12 range) than the geography students (33.4% in the 0 ~ 12 range). Next, we will look closer into the different items in STAT test, concerning their relevance to students’ critical spatial thinking ability in the human geography course. The quantitative analysis of the main findings will follow then in Section 5.

4.3. STAT Used for a Quasi-Critical Spatial Thinking Test in the Human Geography Courses

Kim and Bednarz employed the critical spatial thinking oral test (CSTOT) in the economic geography teaching through GIS learning to investigate the three components of critical spatial thinking when the students solve problems: a) evaluating data reliability; b) exercising spatial reasoning; and c) accessing problem solving validity [36]. The semi-structured interview in the CSTOT allowed the participants to unfold flexible and reflective replies, but the assessment is not ideally comparative from one case to another. For this reason, we choose to use the standard multiple choices in the STAT, based on a comprehensive review of its relevance to the critical spatial thinking test in the curriculum of social sciences and humanities including human geography.

Table 2. Eight types of multiple-choice question items in STAT and the critical spatial thinking item to measure.

Item	Item Description	Geospatial Terms to Measure	Critical Spatial Thinking to Measure
I (#1, #2)	Visually navigate road maps	Direction, orientation, distance, navigation, general use of map	Using tools of spatial representation for navigation to places
II (#3)	Recognize spatial pattern and represent in a plot of function	Discerning spatial patterns, graphing spatial relations	Discerning, reasoning and graphing the positive and negative spatial relations of a certain univariable
III (#4)	Choose an ideal location based on the given criteria	Mentally overlying and dissolving maps to solve the location choice problem (involving the overlay, buffer, region, and Boolean logic in conditions A, B and C)	Spatial reasoning to mentally visualize, overlay and manipulate spatial objects, which are however not physically over-layable on the map
IV (#5)	Create 3-D topography profile from a 2-D map in a certain orientation	Contour, orientation, recognizing the 3-D spatial form based on 2-D topography map	Spatial reasoning, orientating and graphing of the 3-D spatial information based on a 2-D topography map
V (#6, #7)	Identify and graph the spatial correlations between sets of maps	Comprehending and graphing the positive and negative spatial associations on two maps	Recognizing and reasoning the spatial relations between sets of maps, including associating, correlating, estimating and then graphing spatially the distributed phenomena
VI (#8)	Visualize a real-world 3-D topography from a 2-D map in a certain orientation	Spatial orientation in a real-world situation, 2-D to 3-D conversion, visualization of real-world images	Spatial reasoning, orientating in real-world situations, and visualizing mentally the real-world 3-D topography based on the 2-D topography map.
VII (#9, #10, #11, #12)	Verify the overlay and select the appropriate layers in the overlay	Boolean logic such as overlaying and dissolving maps	Spatial reasoning about the Boolean logic for map layers
VIII (#13, #14, #15, #16)	Visually extract the types of spatial data based on the verbally expressed spatial relations	Comprehending the spatial shapes and patterns, and the integration of geographic features such as points, lines, networks and regions	Imagination and recognition of spatial data types (e.g. point, line and polygon) and their spatial patterns from the visually or verbally expressed spatial information
Source: Modified from Lee and Bednarz’s validity of STAT, and Kim and Bednarz’s validity of CSTOT [9,10,36].

provides a brief analysis of the 16 items used in the STAT, combined with Lee and Bednarz’s prior validity analysis on it [9,10] as well as its wide range of application in the recent several years, including its modified version in Kim and Bednarz’s critical spatial thinking test [36].

As analyzed in Table 2, the 16 items in STAT conduct a very comprehensive test on students’ spatial thinking ability, including their critical spatial thinking, especially pertaining to the exercising of spatial reasoning that is the 2nd component of critical spatial thinking in Kim and Bednarz’s validity of CSTOT [36]. Kim and Bednarz’s test on the other abilities as to the understanding of data reliability and problem-solving validity is an interview-based oral test fundamentally based on the STAT. For instance, the critical questions 1 to 3 were deprived from STAT (Items #4 and #7) but improved in the semi-structured interviews for qualitative analysis [36].

In this empirical study, our focus is on the spatial reasoning abilities that are important for the problem-based pedagogy in the human geography teaching in China. In this sense, the STAT was used here for a quasi-critical spatial thinking test in the human geography courses. The quantitative assessment on the geography students and geoinformation students is conducted using the 16 items in STAT. For each item listed in Table 2, students’ performance would be compared across the different human geography pedagogies. Anonymity and confidentiality were assured during the assessment. The test results are reported in the next section. Figure 2 gives an example Type V (#7) in STAT, assessing students’ spatial reasoning ability to decipher and graph the positive and negative spatial associations on two maps.

The following statistical analysis consists of three steps. Firstly, Cronbach’s Alpha as a popular tool to assess the reliability of scales and determine the internal consistency or average correlation of items in a survey instrument was reported. We conducted an independent-samples t test to examine the between-group variance of the total scoring, which was a calculation of the number of questions answered correctly. The t test results between geography and geoinformation groups regarding the respective scores of the 16 items of the STAT test were reported, too, including the mean, standard deviation (SD), standard error (SE), t, p, lower and upper limit for the 95% confidence interval (CI), and Cohen’s d. Here, Cohen’s d is an effect size used to indicate the standardized difference between two means, as reported in the t test. Levene’s test was also adopted here, to evaluate the assumption that the population variances for the two groups were equal. If Levene’s test was significant, the variances for the two groups were different and the sample sizes were unequal, and we cannot report the standard t value but rather the t value that did not assume equal variances. Secondly, we compared the scores with Lee and Bednarz’s study, including the mean score difference and the respective score variance for each item between CNU and the American universities. Finally, the correlation and regression analysis were adopted to explain the STAT test variance in CNU. To be more specific, the students’ perceptual and demographic variables such as gender, ethnicity, the motivation and attitudes toward human geography were investigated, too, to search for the variance in spatial thinking skill acquisition between geography and geoinformation groups.

5. Analysis of STAT Test Results

5.1. Between-Group Variance

The test results from 78 undergraduates in the CNU in Beijing, China, were calculated to examine the reliability of this STAT test in a context of the Chinese higher geography education. A relatively high value of Cronbach’s Alpha at 0.71 was considered to be a reliable set of items in this survey instrument.

The scoring for each participant was a calculation of the number of questions answered correctly, thus ranging from 0 to 16. An independent-samples t test was conducted to look into whether the geography and geoinformation students’ STAT test scores differed significantly from each other. The mean scores of STAT tests of the two pedagogy groups in our study were 12.88 (the geography group without GIS enactment) and 13.70 (the geoinformation group with an intense GIS learning), respectively. Apparently, the geography group scored lower than the geoinformation group, and their mean difference (−0.82) was statistically marginally significant (p < 0.10, t = −1.68, SE = 0.49, 95% CI = −1.79 ~ 0.15). This finding supported our presumption that the GIS learning would prominently improve the spatial reasoning abilities in the human geography courses.

Table 3. STAT test mean scores for each item and the variance between geography and geoinformation groups.

Item	Geography Group		Geoinformation Group		Variance (Geography vs. Geoinformation Groups)
	Mean	SD	Mean	SD	Levene’s Test for Equality of Variances (p)	Mean	SE	t	p	95% CI		Cohen’s d
										Lower	Upper
#1	0.92	0.27	0.96	0.19	0.15	−0.04	0.05	−0.78	0.44	−0.15	0.06	0.17
#2	0.88	0.33	0.93	0.27	0.23	−0.04	0.07	−0.64	0.53	−0.18	0.09	0.17
#3	0.96	0.20	0.89	0.32	0.02	0.07	0.07	1.07	0.29	−0.07	0.21	0.26
#4	0.82	0.39	0.85	0.36	0.52	−0.03	0.09	−0.32	0.75	−0.21	0.15	0.08
#5	0.80	0.40	0.81	0.40	0.82	−0.01	0.10	−0.12	0.91	−0.20	0.18	0.03
#6	0.92	0.27	0.93	0.27	0.89	−0.00	0.06	−0.07	0.95	−0.13	0.12	0.04
#7	0.69	0.47	0.85	0.36	0.00	−0.17	0.10	−1.73	0.09	−0.36	0.03	0.38
#8	0.65	0.48	0.44	0.51	0.20	0.20	0.12	1.71	0.09	−0.04	0.44	0.42
#9	0.90	0.30	1.00	0.00	0.00	−0.10	0.04	−2.33	0.02	−0.18	−0.01	0.47
#10	0.96	0.20	0.96	0.19	0.93	−0.00	0.05	−0.05	0.96	−0.09	0.09	0.01
#11	0.76	0.43	0.85	0.36	0.06	−0.09	0.09	−0.95	0.35	−0.27	0.10	0.23
#12	0.76	0.43	0.81	0.40	0.30	−0.05	0.10	−0.52	0.61	−0.24	0.14	0.12
#13	0.61	0.49	0.96	0.19	0.00	−0.36	0.08	−4.53	0.00	−0.51	−0.20	0.94
#14	0.82	0.39	0.96	0.19	0.00	−0.14	0.07	−2.13	0.04	−0.27	−0.01	0.46
#15	0.94	0.24	1.00	0.00	0.01	−0.06	0.03	−1.77	0.08	−0.13	0.01	0.35
#16	0.47	0.50	0.48	0.51	0.87	−0.01	0.12	−0.09	0.93	−0.25	0.23	0.02
Total	12.88	2.83	13.70	1.49	0.02	−0.82	0.49	−1.68	0.09	−1.79	0.15	0.36

Note: Standard deviation (SD), standard error (SE), confidence interval (CI).

represents the t test results between geography and geoinformation groups regarding the respective scores of the 16 items of STAT test. Percentages of students correctly answering each of the 16 items of the STAT were calculated and tabulated in Table 3, ranging from 0 to 1. As verified by Lee and Bednarz, the STAT test is able to investigate how completely the students can understand the core concepts of the spatial thinking suggested by Gersmehl et al. [45,46,47]. As elaborated in Table 2, we also analyze the detailed critical spatial thinking to measure in STAT test. Combined with Table 2 and Table 3, we can see the particular variance between the two human geography pedagogy groups in these various aspects of spatial reasoning. Levene’s test evaluates the assumption that the variances for the two pedagogy groups are equal. Levene’s tests are significant for total, #3, #7, #9, #11, #13, #14 and #15, and thus the equality-of-variance assumption is violated and we should report the t value that does not assume equal variances. In our investigation among the eight item types in STAT identified from I to VIII in Table 2, it was found that only the latter four types (V, VI, VII and VIII) showed statistically significant mean differences between geography and geoinformation groups. Apparently, GIS learning was exerting very different influences on the different components of spatial reasoning ability, and this standardized and comprehensive STAT test allowed us to look into the different skill sets and GIS training’s differential effects on them. Such an item-by-item analysis was also adopted in Lee and Bednarz’s validity of their STAT test, and another empirical study on the effects of web-based GIS learning in a world geography context in 2016 [10,11].

The mean score difference between the geography and geoinformation groups in #7 that is the second item of Type V, which requires comprehending and graphing the positive and negative spatial associations on two maps, was reported to be marginally significant (mean difference = −0.17, p = 0.09, Cohen’s d = 0.38, small to medium effect size). However, their mean scores on #6 (also Type V) were insignificantly different, because #6 requires a simpler comparison of different layers of spatial information pertaining to the same area in the map, and #7 asks to critically interpret and graph the spatial information that is a higher-order critical thinking.

What is beyond the expectation is that the geography students had a marginally significantly better performance on Type VI (#8), which requires spatial orientation in the real-world situation, 2-D to 3-D conversion and visualization of real-world images (mean difference = 0.20, p = 0.09, Cohen’s d = 0.42, medium effect size). It is thus proved that the GIS enactment failed to effectively improve this spatial reasoning type compared with traditional geography teaching. Extensive fieldwork in a human geography course has strengthened geography students’ imagination and orientation in a real-world 3-D situation, including how to associate and estimate spatial information from an unannotated 2-D topography map with a real world. Types VI (#8) and IV (#5) are seemingly quite similar; but very different from #5, #8 asks to estimate the elevation of places having no labelled data points and thus demonstrate a higher-order spatial cognitive ability as to mentally visualize, imagine and orientate in the real-world 3-D situation. Therefore, it is probable that students can improve this type of spatial thinking as a result of fieldwork in a real world rather than GIS enactment.

The geoinformation group improved significantly on Type VII (#9) requiring Boolean operations such as overlaying and dissolving maps. Among all the four items in Type VII (#9, #10, #11, #12), only #9 that requires choosing Boolean logics showed a significant score difference (mean difference = −0.10, p = 0.02, Cohen’s d = 0.47, medium effect size); but the other three items (#10, #11, #12) in Type VII requiring a unidirectional Boolean operation did not show a statistically significant mean difference between geography and geoinformation groups.

The geoinformation group with GIS enactment reported a significantly higher score in Type VIII items (#13, #14, #15), associated with the imagination and recognition of spatial data types and map symbols (e.g. point, line and polygon) and their spatial patterns from visually or verbally expressed spatial information. The mean score differences between geography and geoinformation groups were reported −0.36 for item #13 (p = 0.00, Cohen’s d = 0.94, large effect size), −0.14 for item #14 (p = 0.04, Cohen’s d = 0.46, medium effect size), and −0.06 for item #15 (p = 0.08, Cohen’s d = 0.35, small to medium effect size). Although no significant difference was reported for item #16, it is interesting that both geography and geoinformation groups performed badly in answering item #16, with over half of them wrongly comprehending and constructing the data types and symbols.

5.2. Comparison with Lee and Bednarz’s Study

Our test using STAT has examined the Chinese undergraduate students’ spatial thinking ability in the human geography teaching in China today, which is a problem-based pedagogy towards sustainability. CNU is a “Double First-Class” university in China (sorted by discipline), and its geography discipline was ranked B⁺ on the 2017 lists of universities and disciplines to be developed under China’s “Double First-Class” (Shuang yiliu) initiative, which was released by the Chinese Ministry of Education, Ministry of Finance and National Development and Reform Commission in September 2017 [48]. CNU and its geography discipline are therefore representative of a medium to upper level of the higher geography education in a context of China.

We thus continue with another analysis of the Chinese college students’ spatial thinking ability in comparison with the existing STAT reports from the different American Universities located in Texas, Ohio, Illinois and Oregon in Lee and Bednarz’s 2012 STAT test, and the Texas State University and the University of West Georgia (UWG) in Jo Injeong, Hong Jung Eun and Verma Kanika’s 2016 STAT test [10,11].

Table 4. Comparison of the mean scores on the STAT test between the Chinese and American undergraduates.

Country	China		USA
STAT test	This study (2019)		Lee and Bednarz (2012) [10]				Jo et al. (2016) [11]
University	Geo in CNU	GIS in CNU	Univ. A	Univ. B	Univ. C	Univ. D	Texas State	UWG
N	51	27	29	11	59	146	183	123
Mean	12.88	13.70	11.93	7.64	9.07	11.32	9.40	7.85
SD	2.83	1.49	2.64	3.67	2.79	2.82	2.90	2.89
% Geography majors	100.00	100.00	41.38	9.09	16.95	26.03	12.02	2.40

summarizes and compares the STAT test results from a total of the seven different universities in China and the USA. According to Lee and Bednarz’s analysis on the possible correlation between the STAT scores and the percentage of geography majors, the better performance of Chinese students in the STAT can be partially attributable to the apparent gap in percentage of geography majors in each group [10]. Jo et al. explained the difference between Texas State and UWG using the same reasoning [11]. Some other reasons, such as the large difference in geography textbooks and pedagogies and in social and cultural capital for the STEM (known as an interdisciplinary and applied curriculum in science, technology, engineering and mathematics), critical thinking and spatial cognition abilities in the Oriental and Western cultures are worthy of more investigation [49,50,51].

Figure 3 shows the percentage of participants correctly answering each of the 16 items of the standardized STAT test as reported in Lee and Bednarz’s 2012 STAT test and this study [10]. The horizontal axis and vertical axis in Figure 3 show the 16 items in the STAT test and the percentage of correctly answering each of the item, respectively. The detailed scores for each item in the Texas State and UWG were not given in the published paper [11], and thus were not compared here in Figure 3. Univ. A had the highest percentage of geography majors and also the highest mean scores on STAT test in these American samples. For this reason, the comparative examination would be focused on the mean score difference between CNU in China and Univ. A in the USA. As shown in Figure 3, the Chinese students can better solve the ideal location choice problem based on given criteria in Type III (#4). More than 80% of the Chinese participants can perform spatial reasoning to visualize, overlay and manipulate spatial objects that are not physically over-layable on map, but only about 70% of the American participants chose the right location. Furthermore, Chinese students can successfully execute the complex Boolean operations among all the four items in Type VII (#9, #10, #11, #12), displaying a higher spatial cognition than their American peers in this aspect. The different comparative performance between Chinese and American students seems to show the great advantage in adopting the standardized STAT test which can embrace a multi-facet examination of spatial thinking that is composed of more than one different skill. It is true that the participants from different pedagogies or demographic and cultural contexts would be good at very different skills of spatial thinking. Next, we will look into the correlation between the reported STAT scores and exam ranks.

5.3. Statistics Explaining the Applicability of the STAT Test in the Chinese Context

In Lee and Bednarz’s 2009 STAT test, it was found that the exam grade could explain quite well the students’ STAT test scores, but this presumption was not held in our empirical study.

Table 5. Correlations among STAT score, exam rank and self-assessments of geography learning.

		STAT Score	Exam Rank	Self-Assessment in College
Total (n = 78)	Exam rank	−0.31 ***
	Self-assessment in college	−0.19	0.31 ***
	Self-assessment in high school	−0.19	0.13	0.41 ***
Geography group (n = 51)	Exam rank	−0.37 ***
	Self-assessment in college	−0.26 *	0.43 ***
	Self-assessment in high school	−0.27 *	0.30 **	0.36 ***
Geoinformation group (n = 27)	Exam rank	−0.01
	Self-assessment in college	0.18	−0.02
	Self-assessment in high school	0.04	−0.17	0.59 ***

Note: * p < 0.1, ** p < 0.05, *** p < 0.01.

presents the correlations between STAT test scores, final exam rank in the class and the students’ self-assessments of geography learning in the college and high school periods. It was expected that the positive correlations between students’ STAT test scores and their final exam rank as well as their self-assessments on geography learning would exist in our empirical study. This research assumption, however, was not supported by empirical findings listed in Table 5. A strong negative correlation was reported between STAT test scores and final exam rank (r = −0.31, p = 0.006), and the weak and negative correlations between the students’ STAT test scores and self-assessments on geography learning (r = −0.19, p = 0.10; r = −0.19, p = 0.10) were also found.

Such a mismatch between the STAT test and final test in geography teaching needs more attention, because it is possible that the higher geography education in a context of China may not fully embrace the spatial thinking capacity as a strategic goal. We can see the very different outline in the Chinese and American geography education systems when probing into China’s 2017 version of the compulsory geography education curriculum criteria in secondary school. In this national curriculum criteria released during new curriculum reforms in contemporary China, four different types of geographic abilities have been highlighted as the very core of geography education in China also including that in higher education: a) the sustainability ideal of People-Place Harmony; b) the spatially integrative knowledge system for purposes of the sustainable development; c) the regional cognition towards sustainability; and d) the newly proposed concepts on geographic practice ability [52]. Apparently, the Chinese students’ spatial cognition is not taught and tested independently from the problem solving for purposes of the sustainable development.

The standardized STAT test can report a better performance of Chinese students in solving the location choice problems and practicing Boolean operations (see Figure 3), but this test was actually NOT quite consistent with the geography teaching pedagogies towards sustainability in real world situations in contemporary China, such as an extraordinary fast urbanization and industrialization process and the very challenging pollution issues. Interestingly, the mismatch between STAT test scores and Chinese geography pedagogies was apparently more prominent in the geography group (without any GIS enactment) than geoinformation peers who were exposed to intensive GIS practices (see Table 5), but self-assessments of the geoinformation group in geography learning displayed a weak but negative correlation with their exam rank in the class, implying that higher student motivation in geography learning would not produce higher achievement. This result can be attributable to geoinformation students’ stronger identity to be an IT (information technology) professional rather than a geography teacher in secondary schools in the near future.

Table 6. Regression results testing for significance of STAT score variability sources.

Independent Variable	Beta	t	p
Gender	−0.07	−0.66	0.51
Pedagogical approach	0.23	2.03	0.05 **
Arts or science in senior high school	0.01	0.05	0.96
Hometown (Beijing or not)	−0.28	−2.21	0.03 **
Ethnicity (Han or not)	0.37	2.78	0.01 ***
Self-assessment of geography learning in high school	−0.16	−1.51	0.14
Self-assessment of geography learning in the college	−0.05	−0.39	0.70
Assessment of staff teaching in human geography	−0.12	−1.25	0.22
Latest exam rank in the class	−0.13	−1.19	0.24
Parental educational levels	−0.05	−0.46	0.65
Constant		3.88	0.00 ***

Note: * p < 0.1, ** p < 0.05, *** p < 0.01.

lists the results of a regression taking into account the STAT test score variability. It is demonstrated that the human-geography pedagogical approaches (GIS enactment or not), local-nonlocal divide, and ethnical difference (Han or not) were significant (R Square = 0.47, adjusted R Square = 0.40, F = 6.07, p < 0.01 for regression model). It is therefore revealed that the GIS teaching, Beijing local students, and Han ethnicity would enhance the students’ performance in a standardized STAT test. However, the other independent variables were reported not significant, indicating that the quite important findings in the educational fields (such as the role of the gender gap, student motivation and parental social capital) were not highlighted in this STAT test here. The limitation of the STAT test application in the context of China would explain partially the results in regression analysis. Despite these limitations, our preliminary assumption on the different effects of the two different human-geography pedagogical approaches (GIS enactment or not) was supported quite well in this test. More comparative experimental research on the Oriental and Western gaps and other socio-cultural backgrounds is worthy of attention for a more solid explanation in further research.

6. Conclusions

This research has answered an interesting question concerned with the critical spatial thinking in a human-geography pedagogical approach in a Chinese context: whether and how does teaching human geography with GIS (combined with an Anglo-Saxon human geography textbook) improve undergraduate spatial thinking as measured by the STAT in a context of China? The comparative STAT test on the ways that students learn to think spatially using geospatial technologies would be quite helpful to develop curriculum and content standards, pedagogical approach, support materials, and assessment guides to improve human geography teaching and student learning. Since 2015, the CGIST of CNU in Beijing has launched the Internationalization Demonstration School Plan, which is managed and funded by the State Administration of Foreign Experts Affairs and the Ministry of Education of the People’s Republic of China. Two groups of participants were recruited for this comparative investigation: a) 51 geography students who took a compulsory human geography course in the local content-based module, without GIS enactment and b) 27 geoinformation students at the same grade level who were exposed to GIS courses and an intensive GIS training in visualizing and analyzing human geography problems. This seemingly small sample has covered one quarter of a total of 320 undergraduates studying geography in all the relevant colleges in a whole Beijing. Our comparative analysis reported the marginally significant higher STAT test scores of GIS application (geoinformation group) than its control group (geography group without GIS training). The students’ subjective assessment on quality and teaching skills of lecturers were reported to be an insignificant and negative factor in explaining the STAT test variance, possibly due to the incomparability between different student groups’ attitudes towards quality and teaching skills. Besides, in examining into the geography students’ marginally significantly better performance on Type VI (#8), it was also proved the importance of traditional geography teaching (such as fieldwork) without GIS in enhancing their spatial thinking.

This paper reveals a profound gap in human geography teaching between China and the USA. First, the human geography teaching in China is a problem-based pedagogy towards sustainability, quite different from the mainstream postmodern perspectives in the human geography teaching in the North America and Western Europe at their post-industrial periods. Second, the Chinese students’ spatial cognition is not taught and tested independently from the problem-solving skills towards the sustainability. Partially due to this reason, higher geography education in a context of China may not fully embrace the spatial thinking capacity as a strategic goal in the curriculum and content standards. We also found a weak but negative correlation between STAT test scores and exam rank. Apparently, we need to grapple with how to examine systematically this human geography pedagogy that is very pragmatic in China’s current developmental stage. What we need would be a modified test that can examine the Chinese students’ abilities to analyze, explain, graph and visualize the interconnected nature of the various and complex human and environmental systems, both human and physical (e.g. congregation, dispersion, driving and resisting forces, equilibrium, threshold, multi-scalar effect, and heterogeneity). As elaborated by Bednarz [14], it is better to offer students the “tool” of maps, GIS and other geospatial techniques to assist in their spatial ability to understand the complex and ill-defined problems and situations. The complexities, uncertainties and ambiguities should become the main components throughout the human geography course to examine a range of human systems [53,54].

Further research should be carried out to assess the Oriental and Western gaps and other socio-cultural effects in explaining the different performances of the Chinese and American students in the standardized STAT test [19,49]. In follow-up research, we will design a more convincing pre- and post-test in each group that can measure the improvements brought about by GIS training. In sum, our empirical study provides insights into the progress of China’s pedagogical approaches in college human geography teaching, which is a more sustainability-oriented education in nature.