This workshop will explore how certain concepts guide the choice of spatial computations to answer domain questions, similar to how measurement scales (nominal, ordinal, interval, ratio) guide the choice of statistical computations to answer primarily non-spatial domain questions. This link between concepts and the choice of software commands is the key innovation to be pursued in the workshop.
The workshop emphasizes the teaching of geospatial technologies to all, regardless of the learners’ disciplinary backgrounds. Participants will be challenged to consider what conceptual basis could guide user choices of specific spatial computations - and consequently should be taught in introductory courses on GIS and geospatial technologies.
Submissions should be position papers that are approximately 1500 words in length. They should address the topic of improving the teaching of geospatial technologies, and how this benefits from explicit conceptual foundations. They could formulate a position on core concepts and computations of spatial information, or respond more generally to the position provided by the organizers (see the discussion paper below). We encourage submissions by participants from all disciplines including those who are outside the geography or education disciplines.
Submission link
Position papers due: April 15
Notification of acceptance: April 30
Revisions possible until: May 15
Workshop date: June 12
A discussion paper preparing the AGILE 2018 Workshop on
Teaching Geospatial Technologies to All
Werner Kuhn^{1}, Karen Kamp^{2}, Sara Lafia^{1}, Thomas Hervey^{1}, Behzad Vahedi^{1}, Jingyi Xiao^{1}
Why is it so challenging to teach GIS across a broader disciplinary spectrum? Why do even geography students spend up to a whole academic year learning how to use these systems productively? How can GIS be taught more efficiently, given that such extended learning times are not practical in, say, economics or biology? And how can GIS be taught more effectively, given that GIS learners today achieve rather limited understandings of what a GIS is and does?
Our workshop will discuss a novel way to address these questions. We posit that, in order to effectively learn to use information systems, learners need to understand what the information is about. This understanding is best taught as a set of concepts underlying the information and behavior of these systems. The Learning Sciences refer to such concepts as threshold concepts, as they are often “opening up a new and previously inaccessible way of thinking about something” (Meyer et al. 2006). We refer to them as core concepts of spatial information^{3}, emphasizing that GIS users need to understand the concepts underlying spatial information, in order to effectively learn how GIS deal with it.
Information answers questions (Zins 2007). Thus, Information Science should study what questions there are and how to compute answers to them. This goal has not yet been tackled for geographic questions, nor is there a consensus on the concepts the questions are about. While the GIS&T Body of Knowledge has put forth a set of “foundational concepts”^{4}, only some of these (e.g., the Basic Measures) could be used to structure user questions, while most are about the philosophical, mathematical, technical, and social foundations of the systems and of the science behind them.
Contrast this situation with that of statistics, which is taught across different disciplines on a well defined and universally understood conceptual basis. This basis includes such “core concepts” as probability distribution, confidence interval, and hypothesis testing. These concepts have formal definitions and any statistics software applies them in exactly the same way to problems in economics, biology, or any other field. Are there any obstacles that prevent GIS teaching to reach the same level of conceptual clarity and universality?
The idea of core concepts of spatial information has been proposed with the goal of making GIS easier to learn, understand, and apply across disciplines (Kuhn 2012). The GIS and Spatial Analysis literature contains relatively obvious candidates for such core concepts (field, object, …), which can be refined and combined. The core should be neither too small, as this would lead to overly abstract questions, nor too large, as this would not reduce complexity enough. For every core concept, there must exist data representing instances and computations to analyze them in today’s GIS. Following various simplifications of the originally proposed set, the current set of core concepts^{4} consists of:
The base concept combines with the content concepts to formulate “where questions” (e.g., about the location in space and time of objects or events). The content concepts describe views of geographic environments (e.g., the view of people as nodes in a social network). The quality concepts describe how “good” geographic information (e.g., how accurate the information about connections between people is). One can think of the content concepts as lenses on geographic environments and of the quality concepts as lenses on the information about these environments. For further details on the definitions of these concepts, we refer readers to our project’s webpage^{3}.
Each core concept is being further specified by the core questions it enables GIS users to ask. For example, using the FIELD concept, one can ask “what is the value at this location?”; the OBJECT concept supports questions about properties and relations of objects in space and time, and the NETWORK concept supports questions about paths or centrality in a network (among others). All core questions need to be answerable by computations in existing GIS or other geospatial technologies. We call a computation that answers a core question a core computation. The concepts are being evaluated based on how much they reduce the number of computations that need to be taught.
The main innovation in the core concepts approach to teaching is to shift the users’ (and teachers’) mindset from “what procedure should I select next?” to “what is the question I want the system to answer?” Figure 1 illustrates this vision, with a user forming a question about the real world that is answerable through the application of core concepts and computations in a GIS (respectively Field and ValueAt in this example). At the workshop we will discuss this idea in more detail and test specific concept choices and questions regarding their ease of learning and understanding. Workshop participants are invited to challenge any or all concepts in this discussion paper, to suggest alternative sets, and/or to contribute to the testing of concepts and questions through use cases.
Among the many open issues to address, completeness is key: how can one show that a proposed set of core concepts is complete, in the sense of covering all content questions? We have been translating documented practical GIS analyses into core concept questions and computations. We are also currently mining online bulletin board databases for questions that users are trying to answer with GIS. What are other approaches to test for completeness?
An issue that we have not yet addressed is the learnability of the concepts and of query and interaction languages based on them. Our unproven assumption is that any domain specialist (such as a biologist or economist) can express their domain questions in terms of the core concepts of spatial information.
We look forward to discussing the ideas set forth in this discussion paper in greater detail at the AGILE 2018 workshop. Generating feedback from the greater GI community will advance interdisciplinary thinking on GIS education, which can be put into practice in the classroom.
References
Kuhn, Werner (2012). Core concepts of spatial information for transdisciplinary research. International Journal of Geographical Information Science, 26, 2267–2276. https://doi.org/10.1080/13658816.2012.722637
Meyer, Jan H.F. and Ray Land (2006). Overcoming Barriers to Student Learning. London: Routledge.
Zins, Chaim (2007). Conceptual Approaches for Defining Data, Information, and Knowledge. Journal of the American Society for Information Science and Technology, 58(4), 479–493. https://doi.org/10.1002/asi.20508
3 See http://spatial.ucsb.edu/core-concepts-of-spatial-information/ and the references given there.
4 http://gistbok.ucgis.org/knowledge-area/foundational-concepts
Ann Johnson: Geospatial Technologies For All – What Does Everyone Need to Know?
Sanjeev Kumar Srivastava: Using the Threshold Concepts Framework: A Way to Enhance Students’ Conceptual Understanding and Promote Disciplinary Discourse in Geographical Information Systems (GIS)
Anne Schleicher and Diedrich Wolter: Natural Language Question Understanding Requires Concept-Level Reasoning for Resolving Reference Ambiguities
Carsten Keßler, Henning Sten Hansen, Lise Schrøder, and Jamal Jokar Arsanjani: Teaching Geospatial Technologies with Problem-Based Learning
Thomas Hervey: A Spatial Analytical Methods-First Approach to Teaching Core Concepts
Jingyi Xiao: GIS Interactive Web App on Core Concepts
We intend for this workshop to last a full day with a four-hour morning session and a three-hour afternoon session. The morning session will start with introductory presentations by the organizers, followed by presentations from participants and organizers on proposed conceptual foundations and then an open discussion on what to teach. The afternoon session will be breakout group discussions on the classification of concepts and rationale on why and how these concepts should be taught . The workshop will conclude with a discussion of group work findings, and how the workshop inputs and findings will be organized for an archival publication. Program modifications are possible, based on participant suggestions before and during the workshop.
Given the presumption of a science (GIScience) behind the systems (GIS), and behind geospatial technologies in general, this workshop will challenge participants to consider what conceptual basis could guide users from any discipline in their choices and uses of specific spatial computations - and consequently should be taught in introductory courses to GIS and geospatial technologies.
Participants will envision how to use an explicit conceptual basis to transform how and to whom geospatial technologies are taught in higher education. We seek to answer the questions: What would it take to make learning geospatial technologies and GIS as commonplace in higher education as learning statistics (and statistics software) is today? In other words, what are possible “core concepts” behind geospatial technologies that could or should be imparted to any willing learner, regardless of discipline? And, more daringly, what concepts would help learners understand how to use GIS or other geospatial technologies to answer spatial questions?
GIS are commonly presented as sets of tools for analyzing, “capturing, storing, checking, and displaying data related to positions on Earth's surface”. However, these descriptions do not explain what types of questions can be answered with a GIS, nor how users should translate these questions into software commands. A teaching emphasis on data models (such as raster or vector models) narrows that gap, but remains too concerned with representations and procedures, and not enough with conceptualizations nor with questions themselves.
Determining how to teach geospatial technologies to all requires agreeing on a conceptual foundation that is meaningful and engaging for learners across disciplines. Unlike attempts to define a canonical form of geographic information or to reorganize GIS commands bottom-up, core concepts of spatial information can relate user questions directly to information system contents. For example, the field or network concepts each come with relatively well-defined “core computations” that make sense on them (say, map algebra and routing). One set of such core concepts has been gradually adopted into the undergraduate GIS curriculum at the University of California, Santa Barbara (UCSB) and is beginning to transform and simplify the dominant image of GIS and spatial computing on campus and beyond.
The aspiration behind this workshop is to start a conversation among scientists from multiple disciplines about how advances in the theory of geographic (or, more generally, spatial) information can be used to bridge the gap between users and systems at a conceptual level.
This workshop will explore core concepts to teach when introducing geospatial technologies, regardless of the learners’ disciplinary backgrounds. Striving for a set of core concepts is motivated by the observation that statistics is taught successfully across academia using a solid conceptual foundation (measurement scales, probability distributions and their parameters, confidence intervals, statistical tests).
Can spatial computing be taught with a similarly strong conceptual foundation, rather than mainly as software training? And if so, what concepts would likely make geospatial technologies more accessible across academia? The workshop will specifically explore how certain concepts guide the choice of spatial computations to answer domain questions, similar to how measurement scales (nominal, ordinal, interval, ratio) guide the choice of statistical computations to answer primarily non-spatial domain questions. This link between concepts and, ultimately, the choice of software commands, is the key innovation to be pursued in the workshop.
We propose to produce a special issue of an international journal, with papers resulting from the workshop, and in response to a pre-workshop manifesto to be written by the workshop organizers. The journal will be selected from those covering geography or geosciences education (e.g., Journal of Geography in Higher Education) or those addressing IT/software education (e.g., IEEE Transactions on Learning Technologies). The journal and other specific outcomes of the workshop deliberations will be decided with all participants in the last session of the workshop.
Thomas Hervey^{1}
Werner Kuhn^{1}, Karen Kemp^{2}, Sara Lafia^{1}, Thomas Hervey^{1}, Behzad Vahedi^{1}, Jingyi Xiao^{1}
1 Department of Geography, University of California, Santa Barbara, USA
2 Spatial Sciences Institute, University of Southern California, USA