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Integration of Artificial Intelligence in Geography Learning: Challenges and Opportunities
Abstract
This research discusses the potential and challenges of integrating Artificial Intelligence (AI) in geography learning. By considering the fundamentals of AI and the role of geography in the era of globalization, this research outlines the benefits of AI in geography learning through interactive visualization and personalization of learning. However, challenges such as equitable access to technology and teacher training are major concerns in the application of AI. The research uses descriptive method with literature review which involves collecting, analyzing, and explaining the information in the literature relevant to the integration of artificial intelligence (AI) in Geography learning. In addition, this study highlights the opportunities of AI in geographic data analysis and addressing global challenges such as climate change. The profound implications of AI integration in geography learning are also discussed, given its impact on education and society. This research provides a holistic picture of the intersection of AI and geography, encouraging a better understanding of its potential and limitations. It is hoped that this research will provide guidance for educational practitioners and researchers to optimize the potential of AI in geography teaching, taking into account the challenges to be overcome and the opportunities to be exploited.
... The effectiveness of AI algorithms relies heavily on the quality of the input data. Inaccurate, incomplete, or biased data can lead to flawed outputs and poor decision-making (Rakuasa, 2023). Addressing these data quality issues requires robust data governance frameworks and ongoing efforts to improve data collection and management practices. ...
The integration of Artificial Intelligence (AI) into Spatial Decision Support Systems (SDM) is a transformative advancement in improving decision-making processes in various fields, including urban planning, environmental management, and disaster response. This research uses a literature review methodology to systematically collect, analyze, and synthesize existing scientific articles, conference papers, and relevant reports related to AI applications in SDSS. The findings of this study reveal that AI technologies, such as machine learning and natural language processing, significantly enhance data processing capabilities, enabling the analysis of complex spatial data and the identification of hidden patterns that may be missed by traditional methods. Despite the great benefits, challenges related to data quality, ethical considerations, and the need for capacity building among stakeholders are critical to the successful implementation of AI in SDSS. It can be concluded that while AI has the potential to revolutionize spatial decision-making, ongoing research is essential to develop best practices, address ethical implications, and foster collaboration among various stakeholders to create a more sustainable and resilient society.
... Education in Indonesia has undergone significant changes in recent years, especially in terms of the integration of digital technology in the learning process (Rakuasa, 2023). This effort is driven by the rapid development of information and communication technology (ICT) that allows educators to access various online learning resources. ...
Training on the utilization of the Genially application as an innovative digital-based learning media for teachers at SMP Negeri 6 Inamosol, West Seram Regency, is an important initiative in improving the quality of education in the region. The training method consists of 3 steps, namely preparation (correspondence and coordination and needs analysis), implementation (socialization and training/practical and mentoring) and evaluation (testimony and post test). The training participants consisted of 10 people. The results showed that the training participants were very enthusiastic and able to create a variety of learning media with the Genelly application. This was also evident from the testimonials of 10 teachers who felt that the topics given were very interesting, and the training material for developing digital-based learning media with the Genelly application as a medium in the teaching and learning process was very useful. With this training, it is expected that teachers will become agents of change in improving the quality of education in West Seram Regency through the effective use of digital technology.
... The review revealed that parental conflict has a negative effect on student learning achievement in Indonesia. Students who experience parental conflict tend to have lower academic achievement and more behavioral problems compared to their peers from harmonious families (Santoso, 2019;Rakuasa 2023). The findings of this review have important implications for practice and policy in Indonesia. ...
By analyzing existing literature, this research identifies key factors such as parental involvement, socioeconomic status and family dynamics that influence student learning outcomes. The methods used include quantitative, qualitative and mixed research to provide a comprehensive understanding of this relationship. Findings show that a supportive family environment contributes positively to students' academic achievement and educational aspirations. This research provides important implications for parents, educators and policy makers in creating an environment conducive to learning.
... Результати тестування систем зі штучним інтелектом для навчання різних шкільних дисциплін оцінюються педагогами досить оптимістично. Так, інтеграція ШІ у вивчення географії відкриває великі можливості для інтерактивної візуалізації, персоналізації навчання та поглибленого аналізу географічних даних [16]; захоплюючі перспективи підвищення якості освіти й підготовки учнів до дедалі складнішого світу [17]. ШІ може допомогти керувати текстовими аспектами підготовки польових робіт, допомогти в організації даних, зібраних на місцях, і навіть запропонувати способи представлення результатів [9]. ...
The involvement of artificial intelligence (AI) systems in the field of education/pedagogy is an irreversible process. The segment of general secondary education is promising for the introduction of AI services. Schools must provide students with basic skills and foster AI competence to prepare them for a high-tech future. UNESCO has developed a global regulatory framework for artificial intelligence. Some countries are already demonstrating successful initiatives to integrate new technology in schools. At the same time, the implementation of AI tools in the educational environment is a legitimate concern, because it is associated with high risks. In Ukraine, the study of various aspects of integrating AI technologies into secondary education is at an early stage. The purpose of the article is to study the advantages of implementing artificial intelligence tools in the segment of general secondary education, as well as some risks that teachers should be prepared for. The study is based on an in-depth analysis of numerous domestic and, particularly, foreign publications on the topic, and draws on the existing experience of testing various AI tools by educators and the author. Special attention is paid to the potential use of AI by students to improve learning outcomes through increased motivation, self-education and mentoring, personalized and interactive learning etc. Some challenges associated with the introduction of new technology, which is gaining momentum among students, are discussed, as well as suggestions on how to avoid the negative consequences of its incorrect use. In conclusion, it is noted that AI technology can help students develop creativity, innovation, creative abilities, providing a variety of tools and resources, as well as new opportunities for project and educational research activities. With the spread of new technology in general secondary education institutions, there is a need to change approaches to learning, including revising strategies for monitoring and correcting students' knowledge, skills, and abilities. It is timely to develop a methodology for teaching with AI in the context of various educational components of the school curriculum.
... Обмеженим є й коло наукових праць, в яких обґрунтовано механізми підвищення кваліфікації вчителів географії щодо використання ШІ в освітньому процесі. Підґрунтя для нашої наукової розвідки становлять переважно праці зарубіжних учених: T. Zhou (2023), G. Pang (2022), J. Gong (2018), H. Rakuasa (2023). ...
В оглядовій статті проаналізовано проблему розвитку цифрової компетентності вчителів географії засобами штучного інтелекту (ШІ). Акцентовано увагу на недостатньому розвитку в учителів-предметників, зокрема вчителів географії, цифрових навичок роботи з ШІ. Визначено шляхи підвищення рівня цифрової компетентності вчителів географії засобами ШІ в системі освіти дорослих, як-от: розроблення програм підвищення кваліфікації вчителів географії в умовах неформальної освіти, які передбачають набуття практичних умінь і навичок використання ШІ у процесі навчання географії. Акцентовано увагу на тому, що опанування вчителями географії інструментів ШІ дозволить підвищити рівень сформованості їх цифрової і методичної компетентностей. Розроблено дидактичний інструментарій і методичні рекомендації для вчителів щодо використання технології ШІ на уроках географії в закладах загальної середньої освіти. Запропоновано нейромережі та інструменти ШІ, які дозволяють створювати картинки до будь-якої теми уроку географії, асоціативні карти, малюнки до програмового матеріалу, 2d- та 3d-зображення, анімацію зображень, додавання звукового супроводу до фотографій, відео на основі текстових запитів, відеоуроки, презентації, навчальні мультфільми тощо. Охарактеризовано переваги і недоліки, пов'язані з упровадженням штучного інтелекту (ШІ) в шкільну практику. Наведено конкретні приклади використання ШІ у процесі навчання учнів географії та визначено алгоритм дій вчителя щодо роботи з цими інструментами. Рекомендовано включати пропонований дидактичний інструментарій і методичні рекомендації у процесі розроблення та впровадження програмам підвищення кваліфікації вчителів географії в умовах неформальної освіти. Ключові слова: штучний інтелект; учитель географії; цифрова компетентність; інструменти; нейромережі.
... Furthermore, the condition of geography learning in the classroom is also not as expected. Many problems are encountered such as low student engagement , basic learning activities , cognitive activity tends to be at low and partial levels (ahyuni, 2022), limited use of technology (silaban et al, 2023), low access to internet-based learning resources (Rakuasa, 2023), and learning activities are less varied and lack collaboration . Next is teachers are less prepared to teach (Sari et al, 2019), teaching methods are less varied (Pramudarmo, 2000;Harris dkk, 2015). ...
The development of human life in the 21st century requires teachers to be more creative in designing learning that is more interesting, challenging and impressive. Interesting learning is learning that is presented with the teacher's brilliant ideas in the form of methods, media and learning resources. Challenging learning can be defined as learning that is able to develop students' reasoning, critical thinking and analytical skills. Meanwhile, impressive learning is learning that is framed by example, character and universal human values. The GEOSMART approach was developed as an alternative solution to the problem of Geography learning which is still teacher-centred, has minimal student involvement and limited use of technology. There are five elements in the GEOSMART approach, namely, 1) scientific, 2) measurable, 3) applicable, 4) reasoning and 5) technology. Development is carried out using the Plomp model. The results of validation by experts show that the development product is in the very valid category. Meanwhile, the practicality test results show that the development product is in the very practical category. The results of effectiveness tests based on the results of experimental research in seven schools in West Sumatra show that the GeoSMART approach can improve student learning outcomes, especially student involvement in learning and critical thinking abilities.
This study used data from observations of first-grade primary school pupils at SDN Srengseng Sawah 04 South Jakarta in the 2017–2018 academic year who still had learning outcomes in the mathematics topic of addition material that fell short of the KKM norm. This study aimed to improve the learning outcomes of grade I children in math addition material. This study employs a cycle approach of classroom planning, implementation, observation, and reflection as its methodology. Thirteen class I B students, sixteen of whom were male and fifteen of whom were female, made up the subjects of this study. Their backgrounds varied concerning place of residence, social standing, and academic accomplishment. Pre-cycle findings showed 48.4% completeness, while cycle one completeness of student scores was 64.52%; cycle 2 data showed an average score of 96.77%. We can conclude that bettering student learning outcomes through a cooperative learning approach is possible.
This research is a literature review that aims to explore the significant role of Geography Education in increasing environmental awareness. This research uses a descriptive Qualitative Method by conducting a literature study related to this research. The results of the literature analysis show that geography education provides an important foundation for students to understand the complex relationship between humans and the natural environment, as well as its impact on the sustainability of the Earth. In addition, it helps students identify global and local environmental problems, provides insight into workable solutions, and encourages an environmentally responsible attitude. This study confirms that geography education has great potential in shaping a generation that is environmentally conscious, ready to participate in nature conservation efforts, and address the increasingly pressing environmental challenges of the future.
Suhu permukaan daratan di Kecamatan Ternate Tengah mengalami peningkatan dari tahun 2013-2023, salah satu faktor penyebabnya yaitu terjadinya perkembangan lahan terbangun yang semakin meningkat setiap tahunnya. Penelitian ini menggunakan data citra Landsat 8 Collection 1 Tier 2 TOA Reflectance pada google earth engine berbasis cloud computing. Hasil penelitian menunjukan bahwa nilai suhu permukaan daratan tertinggi di tahun 2013 yaitu 24,41ᵒ C dan mengalami peningkatan di tahun 2023 menjadi 28,63ᵒ C. Hasil peneltian diharapkan dapat memberikan manfaat yang besar bagi Pemerintah setempat dalam merencanakan dan mengambil keputusan dalam berbagai sector diantaranya pengembangan sektor pertanian, pengelolaan sumber daya air, dan penanggulangan bencana.
GeoAI, or geospatial artificial intelligence, has become a trending topic and the frontier for spatial analytics in Geography. Although much progress has been made in exploring the integration of AI and Geography, there is yet no clear definition of GeoAI, its scope of research, or a broad discussion of how it enables new ways of problem solving across social and environmental sciences. This paper provides a comprehensive overview of GeoAI research used in large-scale image analysis, and its methodological foundation, most recent progress in geospatial applications, and comparative advantages over traditional methods. We organize this review of GeoAI research according to different kinds of image or structured data, including satellite and drone images, street views, and geo-scientific data, as well as their applications in a variety of image analysis and machine vision tasks. While different applications tend to use diverse types of data and models, we summarized six major strengths of GeoAI research, including (1) enablement of large-scale analytics; (2) automation; (3) high accuracy; (4) sensitivity in detecting subtle changes; (5) tolerance of noise in data; and (6) rapid technological advancement. As GeoAI remains a rapidly evolving field, we also describe current knowledge gaps and discuss future research directions.
The emergence of innovative technologies has an impact on the methods of teaching and learning. With the rapid development of artificial intelligence (AI) technology in recent years, using AI in education has become more and more apparent. This article first outlines the application of AI in the field of education, such as adaptive learning, teaching evaluation, virtual classroom, etc. And then analyzes its impact on teaching and learning, which has a positive meaning for improving teachers' teaching level and students' learning quality. Finally, it puts forward the challenges that AI applications may face in education in the future and provides references for AI to promote education reform. Received: 16 January 2021 / Accepted: 24 March 2021 / Published: 10 May 2021
This study provided a content analysis of studies aiming to disclose how artificial intelligence (AI) has been applied to the education sector and explore the potential research trends and challenges of AI in education. A total of 100 papers including 63 empirical papers (74 studies) and 37 analytic papers were selected from the education and educational research category of Social Sciences Citation Index database from 2010 to 2020. The content analysis showed that the research questions could be classified into development layer (classification, matching, recommendation, and deep learning), application layer (feedback, reasoning, and adaptive learning), and integration layer (affection computing, role-playing, immersive learning, and gamification). Moreover, four research trends, including Internet of Things, swarm intelligence, deep learning, and neuroscience, as well as an assessment of AI in education, were suggested for further investigation. However, we also proposed the challenges in education may be caused by AI with regard to inappropriate use of AI techniques, changing roles of teachers and students, as well as social and ethical issues. The results provide insights into an overview of the AI used for education domain, which helps to strengthen the theoretical foundation of AI in education and provides a promising channel for educators and AI engineers to carry out further collaborative research.
According to various international reports, Artificial Intelligence in Education (AIEd) is one of the currently emerging fields in educational technology. Whilst it has been around for about 30 years, it is still unclear for educators how to make pedagogical advantage of it on a broader scale, and how it can actually impact meaningfully on teaching and learning in higher education. This paper seeks to provide an overview of research on AI applications in higher education through a systematic review. Out of 2656 initially identified publications for the period between 2007 and 2018, 146 articles were included for final synthesis, according to explicit inclusion and exclusion criteria. The descriptive results show that most of the disciplines involved in AIEd papers come from Computer Science and STEM, and that quantitative methods were the most frequently used in empirical studies. The synthesis of results presents four areas of AIEd applications in academic support services, and institutional and administrative services: 1. profiling and prediction, 2. assessment and evaluation, 3. adaptive systems and personalisation, and 4. intelligent tutoring systems. The conclusions reflect on the almost lack of critical reflection of challenges and risks of AIEd, the weak connection to theoretical pedagogical perspectives, and the need for further exploration of ethical and educational approaches in the application of AIEd in higher education.
What is the current state-of-the-art in integrating results from artificial intelligence research into geographic information science and the earth sciences more broadly? Does GeoAI research contribute to the broader field of AI, or does it merely apply existing results? What are the historical roots of GeoAI? Are there core topics and maybe even moonshots that jointly drive this emerging community forward? In this editorial, we answer these questions by providing an overview of past and present work, explain how a change in data culture is fueling the rapid growth of GeoAI work, and point to future research directions that may serve as common measures of success.
The purpose of this review article is to present state-of-the-art approaches and examples of virtual reality/augmented reality (VR/AR) systems, applications and experiences which improve student learning and the generalization of skills to the real world. Thus, we provide a brief, representative and non-exhaustive review of the current research studies, in order to examine the effects, as well as the impact of VR/AR technologies on K-12, higher and tertiary education students’ twenty-first century skills and their overall learning. According to the literature, there are promising results indicating that VR/AR environments improve learning outcomes and present numerous advantages of investing time and financial resources in K-12, higher and tertiary educational settings. Technological tools such as VR/AR improve digital-age literacy, creative thinking, communication, collaboration and problem solving ability, which constitute the so-called twenty-first century skills, necessary to transform information rather than just receive it. VR/AR enhances traditional curricula in order to enable diverse learning needs of students. Research and development relative to VR/AR technology is focused on a whole ecosystem around smart phones, including applications and educational content, games and social networks, creating immersive three-dimensional spatial experiences addressing new ways of human–computer interaction. Raising the level of engagement, promoting self-learning, enabling multi-sensory learning, enhancing spatial ability, confidence and enjoyment, promoting student-centered technology, combination of virtual and real objects in a real setting and decreasing cognitive load are some of the pedagogical advantages discussed. Additionally, implications of a growing VR/AR industry investment in educational sector are provided. It can be concluded that despite the fact that there are various barriers and challenges in front of the adoption of virtual reality on educational practices, VR/AR applications provide an effective tool to enhance learning and memory, as they provide immersed multimodal environments enriched by multiple sensory features.
This study discusses the significant role of geographic research in supporting sustainable development efforts in Ambon City, Indonesia. Through the analysis of urban growth patterns, natural resource management, spatial planning, and identification of environmental and social impacts, geographic research provides insights that guide urban planners and decision-makers. This research. This research uses a descriptive qualitative approach. The type of research used is a literature study which is research that has been done before by collecting books, journals, magazines, and scientific papers that are related to how the utilization of geography research in the fields of disaster, regional and urban planning, health, tourism, agriculture and forestry and climate change is applied to realize an environmentally sound and sustainable Ambon City. The results show that Geography research plays an important role in supporting sustainable development in Ambon City, Indonesia, revealing that geography research is not just an analytical tool, but also a valuable guide for policy makers, urban planners, and communities in designing and implementing sustainable development. Through collaboration and application of research findings, Ambon City can grow into a city that not only develops economically, but also preserves the environment and the welfare of its people.
Penelitian ini bertujuan untuk menerapkan Geographic Artificial Intelligence (Geo-AI) dalam identifikasi daerah rawan banjir di Kota Ambon. Geo-AI merupakan kombinasi teknologi kecerdasan buatan dengan data geospasial, termasuk citra satelit dan data cuaca, yang memungkinkan analisis yang lebih akurat dan efisien dalam mengidentifikasi daerah rawan banjir. Melalui Google Earth Engine, data citra satelit dan data geospasial lainnya diolah dan dianalisis menggunakan algoritma kecerdasan buatan untuk mengidentifikasi pola banjir dan daerah yang rentan tergenang air. Penelitian menggunakan data JRC Global Surface Water Mapping Layers, v1.4, data NASA SRTM Digital Elevation 30m, data USGS Landsat 8 Level 2, Collection 2, Tier 1. Pegolahan dan analisis data penelitian sepenuhnya di lakukan di Geogle Earth Engine. Hasil penelitian menunjukan bahwa daerah berpontensi banjir memiliki luas 12.991.33 ha dan daerah yang tidak berpotensi banjir yaitu seluas 18.924,24 ha. Daerah potensi rawan banjir kemudian diklasifikasi berdasarkan batas administrasi dimana Kecamatan Teluk Ambon memiliki daerah yang berpotensi tergenang banjir seluas 5.149.37 ha, Kecamatan Nusaniwe seluas 2.034.23 ha, Kecamatan Serimau seluas 1.914.18 ha, Kecamatan Leitimur Selatan seluas 1.180.13 ha dan Kecamatan Teluk Ambon Baguala seluas 2.713.42 ha. Peta daerah potensi banjir di Kota Ambon kemudian dioverlay dengan data sebaran permukiman di Kota Ambon dan diketahui bahwa permukiman penduduk yang diprediksi berada pada daerah yang berpotensi banjir seluas 3.400.65 ha. Dengan analisis yang lebih akurat, sistem peringatan dini yang efektif, dan pengetahuan yang ditingkatkan, penelitian ini dapat berkontribusi dalam mitigasi risiko banjir, melindungi masyarakat dan lingkungan dari dampak banjir, serta menciptakan kota yang lebih aman dan berkelanjutan
Pemantauan suhu permukaan daratan dengan di Kabupaten Seram Bagian Barat menggunakan teknologi geospasial berbasis cloud computing Google Earth Engine dapat membantu dalam memahami perubahan iklim dan cuaca, serta memberikan informasi penting bagi para akademisi,masyarakat,pemerintah, dan organisasi non-pemerintah dalam mengambil keputusan terkait mitigasi perubahan iklim dan penanganan bencana alam. Penelitian ini menggunakan data citra Moderate Resolution Imaging Spectroradiometer (MODIS) Terra Land Surface Temperature and Emissivity 8-Day Global yang dianalisis di Google Earth Engine. Hasil penelitian menujukan bahwa nilai nilai suhu permukaan daratan di Kabupaten Seram Bagian Barat pada tahun 2012 yaitu 21,15ᵒ-32,88 ᵒCdan mengalami kenaikan ditahun 2022 menjadi 12,73 ᵒ-40,43ᵒC. Suhu permukaan daratan di Kabupaten Seram Bagian Barat mengalami peningkatan setiap tahunnya.Hasil penelitin inisangat bermanfaat untukpemantauan kualitas udara, pemantauan resiko kebakaran hutan, pada bidang pertanian dan lingkungan serta pada bidang kebencanan.
This paper concentrates on the different meanings of machine learning (ML) from its origins to the present and potential future, focusing on contributions within the discipline of geography. Understanding the history of ML is important both for understanding current trends and predicting future applications. The 1950s saw the first idea of ML with the Turing Test, which was described as a ‘learning machine’ that could acquire information and become artificially intelligent. This thought prevailed until the 1960s with the release of Perceptron I, which caused a shift to attempt to code computers to learn from input data in order to run like a human brain. The 1980s and 1990s saw the advancement of computing technologies which enabled ML within artificial intelligence to prosper. The development of artificial neural networks during this time shifted ML from a knowledge‐driven approach to a data‐driven one. The 2000s saw ML becoming more widespread within geography and other disciplines as unsupervised methods enabled the analysis of large data sets. More recently, deep learning emerged to enable processes to be integrated into many software services and applications. Present day ML has been defined by Stanford University (2017) as “the science of getting computers to act without being explicitly programmed”. Academic research alongside industry and government investments in ML now account for some of the most important technological advancements. The use of ML within geography has been increasing at a rapid rate paving the way for future advancements in the discipline.
This paper examines the political economy of artificial intelligence (AI) and education in China, through an analysis of government policy and private sector enterprise. While media and policy discourse often portray China’s AI development in terms of a unified national strategy, and a burgeoning geopolitical contestation for future global dominance, this analysis will suggest a more nuanced internal complexity, involving differing regional networks and international corporate activity. The first section considers two key policy documents published by the central Chinese government, which are shown to implicate educational institutions as influential actors in national and regional strategies for AI development, with a significant role in plans to train domestic expertise. The second section outlines three prominent private education companies: New Oriental Group, Tomorrow Advancing Life (TAL), and Squirrel AI. These companies are selected to represent important aspects of China’s development of educational AI applications, including the influence of a well-established private education sector, and a growing interest in international corporate activity. The paper concludes with the suggestion that while central government policy reserves a significant role for education in the national AI strategy, the private sector is utilising favourable political conditions to rapidly develop educational applications and markets.
This study investigated student teachers’ (N = 82) learning of action-oriented knowledge (AOK), triggering incidents in teaching practice, and the relationships between these two. Student teacher’s action-oriented knowledge is understood as core capability for the practice of teaching, and learning of action-oriented knowledge needs to be facilitated during teacher education. Action-oriented knowledge integrates theoretical and practical aspects of teaching, and it needs to be investigated in the context of teaching practice in teacher education. The results showed that student teachers identified critical incidents related to didactical relation (57%), pedagogical relation (39%) and content relation (4%) meaningful for their learning. Within the relations, student teachers showed descriptive (43%), inferential (24%) and justified (33%) AOK in their reflections. The incidents related to pedagogical and didactical relation especially triggered descriptive and justified AOK. The results showed that teacher candidates AOK reflection started with evaluative descriptions of their teaching, and moved on to practical justifications. The study confirms that teacher candidates’ videos can extend their focus of teaching and afford more attention to student learning.
Purpose
This paper aims to clarify the notion of artificial intelligence (AI), reviewing the present scope of the phenomenon through its main applications. It aims at describing the various applications while assessing the markets, highlighting some of the leading industrial sectors in the field. Therefore, it identifies pioneering companies and the geographical distribution of AI companies.
Design/methodology/approach
The paper builds upon an in-depth investigation of public initiatives focusing mostly on the EU. It is based on desk research, a comprehensive review of the main grey and scientific literature in this field.
Findings
The paper notes that there is no real consensus on any definition for this umbrella term, that the definition does fluctuate over time but highlights some of the main changes and advances that took place over the past 60 years. It stresses that, in spite of the hype, on both the business and consumer sides, the demand appears uncertain. The scope of the announced disruptions is not easy to assess, technological innovation associated with AI may be modest or take some time to be fully deployed. However, some companies and regions are leading already in the field.
Research limitations/implications
The paper, based on desk research, does not consider any expert opinions. Besides, the scientific literature on the phenomenon is still scarce (but not the technical one in the specific research sectors of AI). Most of the data come from consultancies or government publications which may introduce some bias, although the paper gathered various, often conflicting viewpoints.
Originality/value
The paper gives a thorough review of the available literature (consultancies, governments) stressing the limitations of the available research on economic and social aspects. It aims at providing a comprehensive overview of the major trends in the field. It gives a global overview of companies and regions.
This piece provides an overview of decolonising approaches for geographers unfamiliar with the field, first by examining some of the ways in which decolonial scholarship seeks to build on – and go beyond – postcolonialism. Developing these points, it turns to discuss what it means to think about decolonising geography at this particular political, institutional and historical conjuncture, examining the urgencies and challenges associated in this moment particularly for British geography. The introductory intervention then moves to examine how the remaining intervention pieces understand and address the theme of decolonial scholarship and geography.
This article provides the theoretical underpinnings for an innovative international collaborative project in the field of geography education named GeoCapabilities. The project attempts to respond in new ways to enduring challenges facing geography teachers in schools. These include the need to find convincing expression of geography's contribution to the education of all young people and coping with the apparent divergence of geography in educational settings and its highly disparate expression as a research discipline in university departments. The project also hopes to contribute to the development of a framework for communicating the aims and purposes of geography in schools internationally, because here, too, there is great variety in definitions of national standards and even of disciplinary allegiances (including, e.g., the social studies, humanities, and biological sciences). GeoCapabilities does not seek to flatten such divergences, for one of geography's great strengths is its breadth. The long-term goal is to establish a secure platform for the international development of teachers’ capacities as creative and disciplined innovators. The project encourages teachers to think beyond program delivery and implementation and to embrace their role as the curriculum makers.
Flood Risk Modeling in Buru Island
- S E Manakane
- P C Latue
- G Somae
- H Rakuasa
Manakane, S. E., Latue, P. C., Somae, G., & Rakuasa, H. (2023). Flood Risk Modeling in Buru
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