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Using Interactive Story Maps Enriched by Direct Knowledge Queries for the Development of E-Learning Modules on Climate Change
Abstract
Predicted precipitation and temperature development for the lee area of the Harz Mountains increase the requirements for climate adaptation. Particularly sensitive to the effects of climate change is the agricultural sector in Central Germany, as reported in the Vulnerability Study for the Federal Republic of Germany. The e-learning platforms introduced in this paper, therefore, focus on sensitizing different educational and agricultural stakeholder to the regional and local impacts of climate change and necessary adaptation strategies. The aim is to combine the possibilities of conventional classroom learning with web-based learning units. Regional case studies serve as training objects, presented in web-based learning modules as well as in lecture series or science camps. Additionally, virtual landscape models and interactive maps are generated for selected processes in the context of climate change, supplemented by simplified simulations. The educational concept focuses not only on the visualization of directly perceptible structures such as snow cover, but also on the representation of non-observable processes (e.g., soil water). The results of the project are implemented as a Rich Internet application in a modular e-learning platform, that combines semantic web technologies and cross media ESRI Story Maps with R-based models, scenarios, and database-supported long climate measurement series. In addition, numerous immediate self-examination applications are integrated. The web-based teaching and learning methods are developed for a usage within blended learning models and to support individual learning under the consideration of previous knowledge.
... Die Online-Tools sind für eine globale, freie Nutzung zugänglich und werden nach ihrer Evaluation im Rahmen von Blended-Learning-Szenarien an Partnerschulen und im Grundstudium von Universitäten eingesetzt. Eine ausführlichere Darstellung von Konzepten und Ergebnissen zu den Online-Lernmodulen erfolgt inThürkow et al. (2019). Eine umfassende Übersicht zum Gegenstand und zu den einhergehenden Kompetenzen der Wissensvermittlung sowie zum aktuellen Status der Lernmodule ist in dem zugehörigen Lernportal dargestellt (https://bit.ly/3fdBgjP). ...
Zusammenfassung: Die aktuellen und zukunftsrelevanten Themen des Klimawandels stellen global, regional und lokal eine hohe ökologische und wirtschaftliche Relevanz dar, weshalb die wachsenden Anforderungen an Landnutzungs-und Managementstrategien sowie an Maßnahmen zur Klimaanpas-sung zunehmend im Fokus der Aus-und Weiterbildung zugehöriger Berufsfelder stehen. Die vorge-stellten E-Learning-Formate kennzeichnen Geoinformationsmethoden, mediendidaktische Konzeptio-nen sowie deren Einsatz-und Evaluationsmöglichkeiten im Rahmen des Wissenstransfers von Schule und Hochschule. Im Fokus stehen crossmediale Storytelling-Lernmodule auf der Basis von Esri Story Maps, welche mit R-basierten Modellen, In-situ-Messreihen und H5P Modulen zur Selbstüberprüfung des Lernerfolgs kombiniert werden. Abstract: The current and future-relevant topics of climate change are of high ecological and economic relevance globally, regionally and locally. Therefore, the growing demands on land use and management strategies as well as on measures for climate adaptation are increasingly in the focus of education and training in related professional fields. The presented e-learning formats characterize geoinfor-mation methods, media-didactic concepts as well as application and evaluation possibilities in the context of knowledge transfer from school and university. The focus is on cross-media storytelling learning modules based on Esri Story Maps, which arecombined with R-based models, in situ measurement series and H5P modules for self-checking learning success.
This study examines digital story mapping as a pedagogical tool in the in the context of sustainability education with high school students and pre-service teachers. The study focuses on finding out how participants used geomedia as a source of geographic information and in presenting geographic information on story maps, comparing self- and teacher evaluations of story maps and describing experienced learning opportunities and limitations of story mapping. Research data consists of digital story maps, questionnaires and learning diaries which were analyzed with qualitative and quantitative content analysis supplemented by means of quantitative descriptive statistical figures. The findings revealed that the main criteria for choosing geomedia were reliability, easy access and use and teacher recommendations. High school students assessed their own story maps with higher grades compared to teacher evaluations, while pre-service teachers were more critical in assessing their own outputs. Participants experienced successes and difficulties in digital story mapping. These factors are referred to as educational opportunities, enablers of learning, barriers to learning and suggestions for improvements. Based on the results it can be concluded that story mapping has potential value for teaching and learning geography considering the limitations and needs for improvement in its implementation as identified in this study.
This review article addresses the need for systematic in-depth reflection on how narratives are used in scholarly climate change literature and synthesizes ten years of research literature between 2009 and 2019. Firstly, the analysis results show that the research field of climate change narratives is scattered yet complementary, as scholarly literature addresses the content of all three working groups’ assessment reports of the IPCC’s Sixth Assessment Report (AR6). Secondly, the analysis of narrative conceptualizations identifies three themes on the whats, whens, and hows of narrative: transmission, perspectives, and practices, embodied and entangled. On the basis of the analysis, this article concludes with a discussion of the potential of climate change narratives to nuance the emergency rhetoric of climate change communication and simultaneously argues that a plurality of theoretical perspectives in research on climate change narratives has the power to create the transformative change needed to address the sustainability and climate challenges outlined in the 2030 Agenda for Sustainable Development.
This chapter provides an overview of the factors that will govern the rise in global mean surface temperature (GMST) over the rest of this century. We evaluate GMST using two approaches: analysis of archived output from atmospheric, oceanic general circulation models (GCMs) and calculations conducted using a computational framework developed by our group, termed the Empirical Model of Global Climate (EM-GC). Comparison of the observed rise in GMST over the past 32 years with GCM output reveals these models tend to warm too quickly, on average by about a factor of two. Most GCMs likely represent climate feedback in a manner that amplifies the radiative forcing of climate due to greenhouse gases (GHGs) too strongly. The GCM-based forecast of GMST over the rest of the century predicts neither the target (1.5 °C) nor upper limit (2.0 °C warming) of the Paris Climate Agreement will be achieved if GHGs follow the trajectories of either the Representative Concentration Pathway (RCP) 4.5 or 8.5 scenarios. Conversely, forecasts of GMST conducted in the EM-GC framework indicate that if GHGs follow the RCP 4.5 trajectory, there is a reasonably good probability (~75 %) the Paris target of 1.5 °C warming will be achieved, and an excellent probability (>95 %) global warming will remain below 2.0 °C. Uncertainty in the EM-GC forecast of GMST is primarily caused by the ability to simulate past climate for various combinations of parameters that represent climate feedback and radiative forcing due to aerosols, which provide disparate projections of future warming.
Es ist viel darüber bekannt, wie sich der Klimawandel auf verschiedene Komponenten des Erdsystems auswirkt. Wie die einzelnen Teilsysteme zusammenspielen, ist aber noch wenig verstanden. Gibt es Änderungen in einem System, kann sich dies direkt oder indirekt auch auf andere Systeme auswirken. So können sich örtliche Ereignisse durch komplexe Wirkungsketten und Rückkopplungen über verschiedene räumliche und zeitliche Skalen ausbreiten. Daher wird der Klimawandel auch als „Risikoverstärker“ und „Bedrohungsmultiplikator“ bezeichnet (EU 2008; WBGU 2007). Im Folgenden werden einige Aspekte dieser Risikoverstärkung beleuchtet.
Zunächst braucht es dafür grundsätzliche Überlegungen, wie kompliziert und wie stabil das Zusammenspiel von Mensch und Umwelt ist. Die komplexen Zusammenhänge in hoch vernetzten Systemen zeigen sich an verschiedenen Risikofeldern in Brennpunkten des Klimawandels. Hierzu gehören Wirtschafts- und Finanzkrisen, verwundbare Infrastrukturen und Netzwerke, Destabilisierung sozialer und politischer Strukturen, Migration und Flucht betroffener Menschen sowie Sicherheitsrisiken und Gewaltkonflikte. Beim Arabischen Frühling etwa wird deutlich, dass solche Prozesse auch primäre und sekundäre Konsequenzen für Deutschland haben, die über globale und regionale Mechanismen wirksam werden.
Das Ziel der globalen Klimapolitik ist, die in der Klimarahmenkonvention (UN 1992) vereinbarte Stabilisierung des Klimasystems auf einem nicht gefährlichen Niveau zu erreichen. Dazu braucht es ein besseres wissenschaftliches Verständnis der zugrunde liegenden komplexen Wechselwirkungen, um eine vorausschauende, auf Anpassung ausgerichtete Politik zu ermöglichen, die riskante Pfade vermeidet und eine Stabilisierung ermöglicht.
Regional Adaptation on Climate Change –Supporting Land Management Decisions in the Middle German Dry Region by Geoecological Research
The Eastern Foothills of the Harz Mountains belongs to the driest regions of Germany with less than 500mm annual precipitation. The area is intensively used by agriculture based on the specific climate conditions and the fertile soils. One of the most former, current and future problems is the availability of water for plant growth and runoff in the small river systems.
Climate change prospections show that the situation will be more difficult in future because the inner annual precipitation dynamic changes to more snow in winter and less rain in summer. Another prediction for the region is, that the summer rain focuses increasingly on single storm events resulting in i) less infiltration, ii) increasing surface run of generation, iii) increasing sediment and nutrient input in river systems and iv) more flood events.
With different research projects the Geoecology Research Group at the Institute of Geosciences of Martin-Luther-University tries to generate basic knowledge for the development of regional adaptation strategies. This includes the investigation of effects of agricultural management practices on soil water balance and soil erosion and investigations on nutrient and sediment input in river systems. In addition to that methodical questions of the application of adapted monitoring strategies play an important role. All these research activities are carried out in collaboration with Regional Environmental Agencies, Water and Flood Management Department, Farmers and Agricultural Machinery Manufacturers.
Based on different examples the presentation focuses on the Generation of basic knowledge to support management and planning decision concerning the regional adaptation on climate change.
Geosciences deal with complex, interdependent landscape processes, of which hydrological processes are an important example. Understanding such processes in time and space is c rucial in geoscientific research and education. Add ressing and communicating hydrological processes using traditional teaching m ethods (e.g. blackboards in lectures, printed study books) is rather limited though. Hence, within the framework of the geoscientific e- learning platform, novel online learning modules ar e being developed to allow a better understanding of the aforementioned processe s. The integration of new photo-realistic geovisualisa tion and web-based approaches are effective means t o impart knowledge if designed accordingly, as the perception of a geovis ualisation and its contents vary strongly depending on various factors. Therefore, to make use of all advantages of geovisualisation, their methods and characteristics have to be chosen carefully. The departments of geosciences and computer science develop methods to visualise landscape processes b ased on precipitation- discharge-models that are directly integrated into e-learning environments. With the help of those onl ine learning modules, users have the possibility to visualise the effects of dy namic variances in the landscape balance on dischar ge behaviour in small and medium catchment areas interactively and on-the-fly.
Purpose
The purpose of this article is to highlight the factors that need to be considered when implementing a blended learning solution in a group environment.
Design/methodology/approach
The insights are based on the authors experience of delivering a blended learning module to successive cohorts of international Executive MBA candidates over a three year period. A range of post‐module evaluation mechanisms were utilized to collect quantitative and qualitative data and this was supported by face‐to‐face and online discussion with participants. In addition, the authors own reflections on the experience as faculty and e‐learning consultants has been taken account of in the interpretation of the results.
Findings
The importance of human behavioral factors over content and tool selection when implementing a blended learning solution cannot be ignored. The role of group dynamics in achieving the learning outcomes also needs to be considered, as does the perceived value of the approach to be taken by the participants. Findings relate to both the e‐learning experience and other learning methods experienced on the course, influenced partly by the students' expectations and preferences.
Practical implications
Key learning is shared with readers so that they can learn from the author's experiences such that anyone considering a blended learning approach in the future considers the three‐way partnership of the organization, the learner and the supplier.
Originality/value
This article will be of special interest to e‐learning developers or development specialists considering blended learning approaches as it draws their attention to the factors beyond the technological application itself which is where attention can become overly focused.
Kolb's experiential learning theory is one of the best known educational theories in higher education. The theory presents a way of structuring a session or a whole course using a learning cycle. The different stages of the cycle are associated with distinct learning styles. Individuals differ in their preferred learning styles, and recognizing this is the first stage in raising students' awareness of the alternative approaches possible. This article presents some case studies of ways in which the theory can be applied in university geography.
A Geographic Information System (GIS) is a high performance computer-aided chain of software which enables us to understand, interpret, capture, update, map, and display na-tural and human-originated events on Earth and allows us to bring out such phenome-na in a form of synthesis. Th erefore, a GIS is an important information system in which graphical and non-graphical information, which are based upon spatial observations, are accumulated, saved, processed, and presented to the users in unity. A GIS is known to be one of the devices employed in the application of spatial analysis of geography, a scientific field that makes an analysis of the reciprocal interaction between human and the natural environment in a sustainable framework. It does not seem to be very easy to draw as much benefit as would be expected from a geography lesson in which no atmosphere of sharing and discussing is available for students, memorization is given a good deal of emphasis and only the descriptive aspect of geography is laid emphasis upon. However, a geography lesson supplied with a GIS appears to make it possible for students to access whatever in-formation is being sought at the desired level. It also off ers some very good advantages to not only students but also to teachers who may still be teaching geography in the conven-tional way. It is also possible to feed into a GIS every single device, numerical data, tech-nical knowledge, and equipment used in geography teaching, as well as analysis or app-lication of all this stuff . Th erefore, if functionality of a GIS can be increased through the incorporation of various programs into it, the teaching of geography may well be easier and more productive. Besides, the enthusiasm of students for learning geography could be furthered even more, thus maximizing the level of the benefit to be drawn from teac-hing geography. Th e present study aims to encourage teaching geography with the help of a GIS in not only secondary and high schools but also in universities. With this in mind, a sample lesson on "Internal Migration" was presented. Th e method used in this lesson was based upon the contributions that a GIS could make to the teaching of this geog-raphy lesson so that the eff iciency of a GIS in learning geography could be appreciated.
We propose a tree regularization framework, which enables many tree models to
perform feature selection efficiently. The key idea of the regularization
framework is to penalize selecting a new feature for splitting when its gain
(e.g. information gain) is similar to the features used in previous splits. The
regularization framework is applied on random forest and boosted trees here,
and can be easily applied to other tree models. Experimental studies show that
the regularized trees can select high-quality feature subsets with regard to
both strong and weak classifiers. Because tree models can naturally deal with
categorical and numerical variables, missing values, different scales between
variables, interactions and nonlinearities etc., the tree regularization
framework provides an effective and efficient feature selection solution for
many practical problems.
This article explores the use of Story Maps in a cultural geography field course that uses a place-based approach to understand the Delta Blue’s culture. In this study, Story Maps was used to capture and map student experiences as they engaged in a field study. Student experiences are captured by incorporating different data mediums such as narratives, personal reflections, digital photos, videos and website. Such a project has the potential to challenge students to work collectively and present a coherent story of their field experiences. This, in turn, can be used to improve the design and experience of a field course. The study demonstrates that the availability of simple web-based mapping platform such as Story maps provides students the ability to harness technology to create geocoded narratives, visual representations and spatial documentation to map their field course experience.
In the current technological context new forms of mapmaking emerge. An increasingly common one produces story maps, maps that are shown with synchronized explanatory text, to visualize events in a spatial context. Story maps could be defined as the explicit display of such spatial and temporal landmarks on the grounds that a story is constructed. In this paper we present a story map oriented to pedagogical purposes. We have compiled an atlas displaying the expansion of the Black Death in Europe between 1346 and 1347, when the largest epidemic outbreak in the History of Europe ravaged the continent. To depict this event, we have used CartoDB, Odyssey and some other Web interactive tools to create eight interactive story maps gathered in an online atlas. The work was made in the frame of an end-of-degree Project (Geomatics Engineering, in Universidad Politécnica de Madrid).
Full text can be found in: https://www.researchgate.net/profile/Temenoujka_Bandrova/publication/309772611_6th_International_Conference_on_Cartography_and_GIS/links/582312cf08aeebc4f89844d4.pdf#page=221
Die Analyse von Natur- und Kulturräumen sowie die Steigerung des Erkenntnis-gewinns durch Geländemethoden hat eine wesentliche Bedeutung im Bildungs-bereich (DGFG 2014, S. 13ff. u. 20). Auch aus Sicht der Schulen nimmt die “Out-door-Education” traditionell und fächerbezogen einen hohen Stellenwert ein (HEYNOLDT 2014). Bisher fehlt jedoch ein umfassendes Bildungsangebot, das eine Vielzahl von Ideen zu Outdoor-Education-Settings bereitstellt. Ein großes Poten-tial liegt dabei in der Gestaltung von Exkursionen, um das Lehren und Lernen ortsbezogen zu ergänzen. In einem Gemeinschaftsprojekt des Instituts für Geo-wissenschaften und Geographie sowie des Zentrums für multimediales Lehren und Lernen der Martin-Luther-Universität Halle-Wittenberg wurde dafür eine Outdoor-Methoden-Datenbank entwickelt. Die fachlichen Inhalte in Form von Methodenerläuterungen, Video- und Informationsmaterialien sind in der Daten-bank räumlich verknüpft sowie Standorten und Exkursionsrouten zugeordnet. Die einzelnen Module der Datenbank können separat genutzt und/oder zu eige-nen Exkursionen zusammengestellt werden.
Both scientists and policy-makers emphasize the importance of education for influencing pro-environmental behavior and minimizing the effects of climate change on biological and physical systems. Education has the potential to impact students’ system knowledge – their understanding of the variables that affect the climate system – and action knowledge – their understanding of behaviors that can impact the system. Research on climate change education has largely focused on system and action knowledge that address mitigation while overlooking equally necessary adaptive responses. This study used a pre/post-test format to identify aspects of middle and high school students’ climate system knowledge and action knowledge of both mitigation of and adaptation to climate change. Results indicate that adolescents currently conflate climate change mitigation strategies with unrelated environmental problems far less than in previous surveys. However, students demonstrated limited understanding of adaptive responses to climate change. After engaging in an instructional unit on climate change, students expressed stronger system and action knowledge, but significant misconceptions remained that conflated mitigation of and adaptation to climate change.
AbstrAct Doering, J.: The climate conditions in the eastern foreland of the Harz mountains. -Hercynia N.F. 37 (2004): 137 – 154. The climate conditions in the eastern foreland of the Harz mountains have decisive influence on the type and distribution of its ecosystems, the development of the cultivated landscape and its actual way of usability. The determining climatic characteristics of this area (annual average values of air temperature above 9 °C, annual precipitation below 500 mm) are enabling the cultivation of wine in its northernmost area of Europe. Furthermore data are presented and interpreted regarding the role of air humidity, radia-tion and wind conditions, characterizing together with the above named parameters the climate condi-tions in the eastern foreland of the Harz mountains, measured for the station Halle/S.
Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them. Using a random selection of features to split each node yields error rates that compare favorably to Adaboost (Y. Freund & R. Schapire, Machine Learning: Proceedings of the Thirteenth International conference, ***, 148–156), but are more robust with respect to noise. Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the splitting. Internal estimates are also used to measure variable importance. These ideas are also applicable to regression.
The spatial sign is a multivariate extension of the concept of sign. Recently multivariate estimators of covariance structures based on spatial signs have been examined by various authors. These new estimators are found to be robust to outlying observations. From a computational point of view, estimators based on spatial sign are very easy to implement as they boil down to a transformation of the data to their spatial signs, from which the classical estimator is then computed. Hence, one can also consider the transformation to spatial signs to be a preprocessing technique, which ensures that the calibration procedure as a whole is robust. In this paper, we examine the special case of spatial sign preprocessing in combination with partial least squares regression as the latter technique is frequently applied in the context of chemical data analysis. In a simulation study, we compare the performance of the spatial sign transformation to nontransformed data as well as to two robust counterparts of partial least squares regression. It turns out that the spatial sign transform is fairly efficient but has some undesirable bias properties. The method is applied to a recently published data set in the field of quantitative structure-activity relationships, where it is seen to perform equally well as the previously described best linear model for these data.
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