In terms of outputs, INCLUDE begins with identifying the currently available online, distance learning strategies in DRR, their success factors and associated issues and problems (O1). In this context, O1 will help to understand exactly where the gaps in remote learning exist, and how educators are coping, and their predictions for the future, and whether or not there is gender equality and sensitivity and also in whether the current practices address the differences in relation to the access and use by underrepresented groups. O1 will be very useful for DRR educators and policy makers to understand the existing online and distance learning strategies, associated issues and their effectiveness, and will provide valuable lessons to deploy distance learning at scale across all levels of DRR education. To tackle the problems that will be identified as part of O1, a framework will then be developed to reimagine online distance learning education that can support the diverse DRR community, as O2. It will outline different strategies to remote learning which suit different types of content and community groups. These strategies are guided by a concern for equity and inclusion and the need to ensure the design and delivery of distance learning do not exacerbate existing educational and social inequalities. This framework will be beneficial for DRR educators and policy makers in designing and implementing online and distance learning education in DRR.
Adopting new digital communication tools will be a key driver of change for strengthening collaborations across greater distances, as remote working has now become the new ‘normal’. Based on the framework that will be developed as part of O2, INCLUDE will strengthen university-industry collaboration in DRR in each participant country through the development of a digital learning platform (O3). Because the platform will be designed to bring together a variety of stakeholders, such as University and Industry, it directly contributes to the objective of improving the quality of education and the relevance it has for society at large. Accordingly, INCLUDE will develop a sustainable digital learning platform for University-Industry collaboration based on MOOCs (Massive Open Online Courses) principle. Traditional MOOCs lack functions for participatory learning and network building. Therefore, in INCLUDE, a collaborative MOOCs architecture (called cMOOCs) will be built using traditional open source MOOCs technology, Moodle. Another priority of the INCLUDE project is to make the student-centred learning more personalised so as to enhance the quality of students’ experience, enabling interaction with a wider range of cultures, personal encounters, knowledge systems, and beliefs. Accordingly, as part of the O4, case studies will be conducted and developed to explore the opportunities of the use of disruptive technologies [AI, AR/VR, IoT, drones, big data, Robots, blockchain] in online distance learning education in DRR. Validated case studies will then be integrated into University-Industry digital learning platform developed, to provide high quality inclusive digital education to DRR community. Each case study will be supplemented by learning outcomes, content, student activities and assessment plan, open source readings and resources (literature, video and other multimedia content).
INCLUDE will also develop an online research repository with open educational resources (O5). Finally, a digital competence framework (O6) will be developed for DRR educators to help develop digital pedagogical competences which are responsive, adoptable and flexible, and this will reflect INCLUDE’s O1,O2,O3, O4 and O5.
All these outputs will be developed through a rigorous scientific process and will directly contribute to the scientific theory of the domain. These outputs will not only benefit theory but due to the importance of the discipline within Europe and beyond, it will provide an important contribution to the practice in providing high quality inclusive digital education to DRR community. It will further develop digital competences and build capacities of DRR educators to implement online and distance teaching and learning.
INCLUDE will achieve the above-mentioned objectives by delivering 06 intellectual outputs as follows.
A survey of online, distance learning strategies used in DRR education and their effectiveness to identify their success factors and associated issues and problems
|Output Title||A survey of online, distance learning strategies used in DRR education and their effectiveness to identify their success factors and associated issues and problems|
|Output Lead||University of Huddersfield|
|Output Duration||2021-06-30 – 2021-11-30 (5 Months)|
Establishing or scaling up online, distance learning strategies was a sector-wide response to sudden interruption of educational processes as a result of unexpected COVID-19. Accordingly, a number of different strategies are used by educators to continue their education, and a number of different tools and strategies emerged to enhance the existing portfolio of online, distance learning strategies in DRR education. While there are a number of ways to implement high-quality remote education, remote-access technology are also associated with many advantages which enable educators to continue a relatively normal programme of teaching across all or most curriculum subjects. As already emphasized, the aim of INCLUDE is to reimagine online distance learning education so that it better supports the diverse DRR community, and thereby to develop a University-Industry digital learning platform to provide high quality, innovative, inclusive digital education in DRR. Before developing the University-Industry digital learning platform, it is important to understand the currently available online, distance learning strategies, success factors and associated issues and problems in making sure the appropriate steps are taken to understand the current status. In other words, it is important to learn exactly where the gaps in remote learning exist, and how educators are coping, and their predictions for the future. Accordingly, based on the survey that will be carried out, O1 aims to identify and describe current practices associated with remote learning with online and digital tools and their effectiveness, whether or not these current practices consider gender equality and sensitivity and also whether they address any differences in relation to the access and use by underrepresented groups.
This will be very useful for DRR educators and policymakers to understand the existing online and distance learning strategies, associated issues and their effectiveness. The survey will provide valuable lessons to deploy distance learning at scale across all levels of DRR education.
|Output Title||A framework to reimagine online distance learning education|
|Output Lead||Lund University|
|Output Duration||2021/11/01- 2022/02/28 (4 Months)|
To tackle the problems that will be identified as part of O1, a framework will be developed to reimagine online distance learning education that can support the diverse DRR community. (This includes not only the education providers and the receivers but other stakeholders also, including the DRR industry sectors and associated stakeholders, which is one of the key innovations of INCLUDE). The framework will be guided by both immediate mitigation needs and long-term goals. It will outline different strategies for remote learning which suit different types of content and community groups. These strategies are guided by a concern for equity and inclusion and the need to ensure the design and delivery of distance learning do not exacerbate existing educational and social inequalities. Accordingly, ensuring access to technology is key, particularly for the disadvantaged community. The proposed framework will also provide guidance on how the students will be supported to work independently and how peer interactions will be facilitated. It is important to note that the effectiveness of distance learning strategies is conditioned by levels of preparedness from various perspectives. As such, the framework will also identify the levels of preparedness needed, in relation to technological readiness, content readiness, pedagogical and home-based learning support readiness, and monitoring and evaluation readiness. This framework will be beneficial for DRR educators and policymakers in designing and implementing online and distance learning education in DRR, by taking into consideration the unique features associated with DRR education. It will provide valuable lessons to deploy distance learning at scale across all levels of DRR education. This framework will facilitate promoting gender equality and sensitivity and addressing differences in relation to the access and use by underrepresented groups.
|Output Title||An inclusive University-Industry digital learning platform|
|Output Lead||University of Central Lancashire|
|Output Duration||2022-03-01- 2022-08-31 (6 Months)|
In order to reduce disaster risks, technology and innovation links between universities and industry are of critical importance more than ever before to carry out robust research and development activities. The close partnership between universities and industry related to DRR is essential to reduce community vulnerability. If not, the separate initiatives carried out by University and Industry on DRR could lead to inefficiencies, overlapping of efforts, and also the reinvention of the wheel. In the context of COVID-19, university-industry collaboration was highlighted as one of the positives to come out of the pandemic in a recent survey carried out at institutes in the UK, Europe, the US and South America (https://globaluniversityventuring.com/mobilising-uni-industry-covid/). However, adopting new digital communication tools will be a key driver of change for strengthening collaborations across greater distances, as remote working has now become the new ‘normal’. Thus, the objective of this O3 is to strengthen university-industry collaboration in DRR in each participant country through the development of a digital learning platform. Because the platform will be designed to bring together a variety of stakeholders (representing the industry), it directly contributes to the objective of improving the quality of education and the relevance it has for society at large.
In order to fulfil the aforementioned objective, O3 will build and maintain a robust and sustainable digital learning platform for University-Industry collaboration based on MOOCs (Massive Open Online Courses) principle. Traditional MOOCs such as Udacity and Coursera lack functions for participatory learning and network building. Therefore, a collaborative MOOCs architecture (cMOOCs) will be built using traditional open-source MOOCs technology such as Moodle but will be customized to include collaborative tools to support participatory interaction, network building and peer to peer learning. The proposed cMOOCs architecture is composed of 5 layers:
Layer 1 – Underpinning Principles: Layer 1 defines the three underpinning principles on which the platform will be built. They are; Improving Access & Connectivity, Sustainability, and Emerging Technologies (ISE). Improving Access & Connectivity highlights the need for providing learning material free and in local languages to underrepresented communities. Improved connectivity promotes university-industry alliance and collective innovation. Sustainability is achieved through changing perspectives towards digital learning and participatory engagement. Emerging Technologies such as Drone Technology, Virtual Reality etc. (Identified in Output 4), and their application in DRR to improve disaster resilience is promoted.
Layer 2 – Computing & Middleware: Layer 2 defines the required computing resources for the cMOOCs platform. System Scalability (ability to add computing resources), Concurrency (ability to run multiple web applications), and fast access from across the globe are required for the proposed platform. Therefore, cloud computing and storage technology is envisaged. Server technologies required to implement cMOOCs such as Nginx or AMP (Apache, MySQL, PHP) would also be defined in this layer.
Layer 3 – Resource Management: Data used in cMOOCs such as instructional videos, course material, user data, corpus services for multilingual support will be implemented in Layer 3. It will also be possible to access teaching resources stored in this layer by the research repository implemented in O5.
Layer 4 – Functional Services: Functions required for delivering effective learning is implemented in this layer. These may include; site management, user management, course management, groups/forums, chat rooms, assessment, feedback, questionnaires etc.
Layer 5 – User Interface: Portability (ability to use with multiple operating systems) is an important requirement in improving accessibility. Thus, the platform is designed to support multiple user devices (PCs, Smart Phones and Tabs.) and operating systems (Linux, iOS, Android, Windows).
The impact and the transferability skills/tools that will be achieved from this output include:
- A global learning platform for the DRR community – Having a common platform for all participant countries to facilitate knowledge exchange between partner countries as well as within them, will help to create a broader knowledge base and a skilled DRR talent pool.
- University-Industry collaboration – The platform allows learners to gain industry-relevant skills and be up to date with industry practices. The synergy with HEIs allows industries to learn and apply new research and technology to their practices. HEI will garner new pathways to integrate industry knowledge into curricula.
- Application of Emerging Technology – This empowers learners to tackle DRR challenges using new technology more efficiently and successfully.
|Output Title||Case studies with the use of disruptive technologies for disaster risk reduction|
|Output Lead||Keio University|
|Output Duration||2022-04-01 – 2023-06-29 (15 Months)|
Technological advancement and innovation have created new opportunities for enhancing DRR education. Developments in disruptive technologies, such as artificial intelligence (AI), the Internet of Things (IoT), and Big Data, and innovations in such areas as robotics and drone technology are transforming many fields, including disaster risk reduction and management. As already identified, one of the priorities of the INCLUDE project is to make the student-centred learning more personalized so as to enhance the quality of students’ experience, enabling interaction with a wider range of cultures, personal encounters, knowledge systems, and beliefs, during these difficult times where online delivery is becoming the “new normal”. Accordingly, O4 aims to explore the opportunities of using these disruptive technologies [AI, AR/VR, IoT, drones, big data, Robots, blockchain] in online distance learning education in DRR via case studies.
- DRR specific Artificial Intelligence (AI) education includes joint work between teachers and AI, learning that is both differentiated and individualized, student access on a universal basis, fully automated admin tasks and out-of-class tutoring and support. Grading and other rote tasks can also be automated by artificial intelligence and accordingly, adaptations of educational software to meet student needs become possible and the areas that are needed for learning programmes delivery upgrades can be pinpointed. AI provides the facility for the tutors to provide students with supplemental assistance and also the provisions of feedback for assisting students and educators. Discovering information and then interacting with it is a shifting process, becoming role-change to teachers. Trial-and-error learning loses its frightening aspects when AI is involved. When AI powers data, educators are able to change in their manners of finding, teaching and supporting students.
- The use of AR/VR (Augmented, Virtual Reality) in the DRR classroom is useful in DRR education in various ways. This will make abstract and difficult concepts understandable by engaging persons and interacting with them. The main idea involves discovery and learning, where as modelling of ideas and objects provide assistance for pertinent training.
- Internet of Things (IoT) education in DRR , resolves issues prevalent throughout the entire industry of education. These include curriculum that is out-of-date, standards needed for testing and quizzing, addressing below standard capacities of teachers and professors, lack of sufficient interest in classroom work and security within the campus territory. Employing IoT in DRR education offers several other advantages. These include: upgrade efficiencies in education and learning management, gathering data in real-time, upgrades in resource management, interrelationships on a worldwide basis and focus on safety. There are several instances of applying IoT in education that will be related to DRR within INDLUDE: EdModo (a communication platform with connections), C-Pen (cultivating engagements by students), LocoRobo (upgrading efficiency in educating), Magicard (collections of pertinent data on students), University of New South Wales Platform (well-organized resource management), Carnegie Mellon University (bettering student life by IoT), and VT Alerts (upgrading security within campus territory and Illuminated escort drones).
- DRR big data education will be employed for upgrading the education provision. For example, it will help to customize courses, better grading means for accuracy, develop unique fields of DRR education, provides immediate feedback with efficiency, and it matches education with technology. Accordingly, the entire experience of DRR education can be customized for personal needs. Furthermore, it is capable of developing unique courses also, a feature of which will be explored during INCLUDE.
- Robots, a field of robotics, will inspire students to unearth their inner passions and follow them. Excellence in robotics provides learners with education in communicating between various technology platforms. Communities benefit from robotics by its learner involvement. Additionally robotics will provide DRR education in teamwork capabilities.
- DRR blockchain education contributes to education by upgrading records, diplomas and badges; providing facilities for upkeeping files and certificates; making ongoing business processes more efficient; developing new market outlets for digital assets; modelling disruptive business as well as offering learning coursework and publishing at less expense and with greater rewards.
|Output Title||Online research repository with open educational resources|
|Output Lead||Vilnius Gediminas Technical University, Lithuania|
|Output Duration||2022-04-01 – 2023-06-29 (15 Months)|
High-level exposure to world-leading research is a significant barrier in empowering the DRR community in underrepresented countries and communities. The high cost of subscriptions and lack of participation in research activities are some of the reasons for this. In addition, limited research visibility and open access research are common issues faced by the wider DRR community.
In a comprehensive research done by UK academics (https://doi.org/10.1038/s41591-020-1011-4), it has been identified that sharing of virus sequencing data using open repositories during COVID-19 has increased the speed of data sharing not seen in previous global outbreaks. As such, quick and open access to research data is vital to developing preparedness for future disasters and in tackling COVID-19 and other biological hazards related shocks. In this context, the research repository that is planned as O5 will have number of objectives;
- Encourage research among underrepresented communities (in the EU and also elsewhere) by providing access to world class DRR research through an open access repository.
- Medium to share, showcase DRR research and educational material easily, and increase stakeholder visibility.
- Enable and promote lifelong learning within the DRR community by strengthening research capacity.
- A platform to share unpublished work such as datasets, dissertations, reports, case studies, multimedia content in DRR etc.
- Maintain long-term preservation and accessibility to DRR related research outputs.
O5 differentiates from O3. O5 focuses on building a data sharing platform for research outputs, whilst O3 focuses on building a collaborative digital teaching and learning platform. The technical requirements and the user interfaces required for the two systems are significantly different. However, teaching and research complement each other, and as a result, the ability to share data between the two platforms will be promoted. Therefore, O5 will be designed in such a wat that it will have the facility to share data with O3 at Layer 3.
In order to achieve the above mentioned objectives, the envisaged repository will be built with following features;
- Full stack web solution with a database, management tools and a front-end web user interface. Open source repository technology such as Fedora, DSpace, Eprints will be considered to ensure the repository is free and accessible to all DRR community.
- Simplified workflow for submitting datasets, with suitable gate keeper and curator functions.
- Ability to support widely known metadata schemes such as QDC (Qualified Dublin Core), MARC (Machine-Readable Cataloguing) etc. This ensures the transfer of existing data from other repositories.
- Facility to both search and browse content.
- Ability to upload a wide variety of file types including PDFs, images, videos and other multimedia file types.
- Security services such as authentication, setting user permissions, setting administrative rights etc.
- Security of data such as the ability to back up and recover data.
- Ability include features (but not limited to) such as; Quizzes for collecting data, and Blogs
The proposed repository will also have numerous impacts and transferable outputs, especially in the areas of research, knowledge creation and dissemination to the wider DRR community.
- Going beyond the concept of traditional university directional knowledge flow, (from the repository to the beneficiaries), feedback knowledge flow (from beneficiaries to the repository), is also envisaged via the incorporation of features such as Blogs, where other stakeholders and interested parties are allowed to contribute to knowledge dissemination. It is expected that a spiral effect will be created for the continuous improvement of the online repository.
- The repository will function as an important digital archival facility for the DRR community, ensuring continuous access to past research and past training material such as; datasets, thesis, webinars, material from workshops etc.
- The repository will also function as a knowledge creation and dissemination tool for EU and like-minded international researchers from the DRR community. The system will be updated frequently with new research publications, case studies, new scientific advancements and emerging technologies related to DRR etc. This will especially be beneficial to researchers from underrepresented countries or communities, because access to world leading research will improve their own research skills and practices. EU researchers will benefit from improved access to DRR research problems and datasets that were previously hard to access, whereby they can broaden their research experience further and develop research infrastructures within their own institutions as well as for EU funded research programmes.
|Output Title||Digital competence framework for DRR educators to develop digital pedagogical competences|
|Output Lead||University of Huddersfield|
|Output Duration||1/6/2023 – 29/06/2023 (1 Month)|
As part of Output 6, a digital competence framework will be developed for DRR educators. The framework will describe what it means for DRR educators to be digitally competent. In other words, it will provide a set of knowledge, skills and attitudes that enable the use of the digital technologies and systems ethically, safely and productively in DRR education. The framework will have three main virtues, responsive, adaptable and flexible. It will be responsive to the needs of the DRR education and the diverse DRR community and be developed in such a way that it can be adaptable to different educational contexts in Europe and the global setting. It will be flexible enough for the prospective users to make necessary adjustments to suit their institutional and country specific requirements. Accordingly, it will provide a reference frame to develop the digital pedagogical competence of DRR educators. The framework will include the mandatory and optional competencies under different themes. The framework will also incorporate an interim self-assessment tool to evaluate the progress.