Analisis Faktor yang Memengaruhi Implementasi Pendidikan Cerdas dalam Sistem Pemerintahan Berbasis Elektronik

The improvement of education in an area is determined by the government's method of managing its education system. Smart education is an implementation of e-Government in a learning system that uses 21st century skills with the support of IT infrastructure and implementing the latest technological innovations. The implementation of smart education is required, especially during the pandemic and post-pandemic to improve the quality of education which has declined since the beginning of covid-19 pandemic, but not all regions in Indonesia are able and ready to implement the concept. City/district governments, especially those that have implemented smart cities, need a reference regarding the factors that considered in implementing smart education to avoid the risk of failure. Based on these problems, the purpose of this study is to create a summary of the factors that need to be considered to increase the success of smart education implementation. This study uses a systematic literature review method to identify factors that are considered in implementing smart education based on previous studies. The research produces five main aspects which are a summary of all the factors found in previous studies, which consist of technological aspects, data aspects, human resources aspects, governance aspects, and financial aspects. All factors from these five aspects can be a reference for the government and related parties to increase the success rate of implementing smart educatio

BIG DATA IN SMART CITIES: A SYSTEMATIC MAPPING REVIEW

Big data is an emerging area of research and its prospective applications in smart cities are extensively recognized. In this study, we provide a breadth-first review of the domain “Big Data in Smart Cities” by applying the formal research method of systematic mapping. We investigated the primary sources of publication, research growth, maturity level of the research area, prominent research themes, type of analytics applied, and the areas of smart cities where big data research is produced. Consequently, we identified that empirical research in the domain has been progressing since 2013. The IEEE Access journal and IEEE Smart Cities Conference are the leading sources of literature containing 10.34% and 13.88% of the publications, respectively. The current state of the research is semi-matured where research type of 46.15% of the publications is solution and experience, and contribution type of 60% of the publications is architecture, platform, and framework. Prescriptive is least whereas predictive is the most applied type of analytics in smart cities as it has been stated in 43.08% of the publications. Overall, 33.85%, 21.54%, 13.85%, 12.31%, 7.69%, 6.15%, and 4.61% of the research produced in the domain focused on smart transportation, smart environment, smart governance, smart healthcare, smart energy, smart education, and smart safety, respectively. Besides the requirement for producing validation and evaluation research in the areas of smart transportation and smart environment, there is a need for more research efforts in the areas of smart healthcare, smart governance, smart safety, smart education, and smart energy. Furthermore, the potential of prescriptive analytics in smart cities is also an area of research that needs to be explored

Непрерывное обучение в качестве инструмента для развития умных городов: технологии, способствующие обучению

This paper considers the ubiquity of technology as an enabler for lifelong learning in modern society and the impact this dependence on technology has on the strategic design of learning systems. The role of lifelong learning in modern economies and the diversity of activities associated with lifelong learning requires targeted resourcing and understanding of the meaning of lifelong learning. The dominance of technology enhanced learning in modern education is accepted as a de-facto component in the design of any learning programme. The literature on the technology enhanced learning – smart city nexus explores the technology in depth with a strong focus on learning analytics and big data applications. Evidence of the pedagogical paradigm requirements is not quite so visible and this lack of understanding of the complete model creates tensions in the design of lifelong learning systems. The agency of active learning is considered in the sense of the triune of human, education and economic, systems for the sustainable growth of a knowledge economy. Structured approaches to learning are demonstrated and comparison is drawn with smart city projects in Ireland and the United Kingdom.В статье рассматривается повсеместное распространение технологий в качестве инструмента для непрерывного обучения в современном обществе, а также влияние их связи на технологии для стратегического проектирования систем обучения. Роль непрерывного обучения в современной экономике и разнообразие видов деятельности, связанных с ним, требуют целенаправленного выделения ресурсов и понимания смысла непрерывного обучения. Доминирование технологии улучшенного обучения в современном образовании признается де-факто компонентом в разработке любой учебной программы. Литература о технологиях, развивающих взаимосвязь между обучением и умным городом, подробно исследует эту технологию, уделяя особое внимание обучающей аналитике и приложениям для работы с большими данными. Доказательства требований педагогической парадигмы не так очевидны, и это непонимание полной модели создает напряженность в разработке систем непрерывного обучения. Учреждение активного обучения рассматривается в смысле триединства человека, образования и экономики, систем устойчивого роста экономики знаний. Показаны структурированные подходы к обучению и проведено сравнение с проектами «умный город» в Ирландии и Великобритании.The authors would like to express their deepest gratitude to the Russian Foundation for Basic Research (RFBR) for the support of the research within the project No. 17-22-07001 The Complex Algorithm of Culture-Based Regeneration of Minor Industrial Cities in the Context of Agglomeration Processes in Russia and Europe.Авторы выражают глубокую благодарность Российскому фонду фундаментальных исследований (РФФИ) за поддержку исследований в рамках проекта № 17-22-07001 «Комплексный алгоритм культурной регенерации малых промышленных городов в контексте агломерационных процессов в России и Европе»

A reinforcement learning recommender system using bi-clustering and Markov Decision Process

Collaborative filtering (CF) recommender systems are static in nature and does not adapt well with changing user preferences. User preferences may change after interaction with a system or after buying a product. Conventional CF clustering algorithms only identifies the distribution of patterns and hidden correlations globally. However, the impossibility of discovering local patterns by these algorithms, headed to the popularization of bi-clustering algorithms. Bi-clustering algorithms can analyze all dataset dimensions simultaneously and consequently, discover local patterns that deliver a better understanding of the underlying hidden correlations. In this paper, we modelled the recommendation problem as a sequential decision-making problem using Markov Decision Processes (MDP). To perform state representation for MDP, we first converted user-item votings matrix to a binary matrix. Then we performed bi-clustering on this binary matrix to determine a subset of similar rows and columns. A bi-cluster merging algorithm is designed to merge similar and overlapping bi-clusters. These bi-clusters are then mapped to a squared grid (SG). RL is applied on this SG to determine best policy to give recommendation to users. Start state is determined using Improved Triangle Similarity (ITR similarity measure. Reward function is computed as grid state overlapping in terms of users and items in current and prospective next state. A thorough comparative analysis was conducted, encompassing a diverse array of methodologies, including RL-based, pure Collaborative Filtering (CF), and clustering methods. The results demonstrate that our proposed method outperforms its competitors in terms of precision, recall, and optimal policy learning

Lifelong learning as a tool for the development of smart cities: technology enhanced learning as an enabler

This paper considers the ubiquity of technology as an enabler for lifelong learning in modern society and the impact this dependence on technology has on the strategic design of learning systems. The role of lifelong learning in modern economies and the diversity of activities associated with lifelong learning requires targeted resourcing and understanding of the meaning of lifelong learning. The dominance of technology enhanced learning in modern education is accepted as a de-facto component in the design of any learning programme. The literature on the technology enhanced learning – smart city nexus explores the technology in depth with a strong focus on learning analytics and big data applications. Evidence of the pedagogical paradigm requirements is not quite so visible and this lack of understanding of the complete model creates tensions in the design of lifelong learning systems. The agency of active learning is considered in the sense of the triune of human, education and economic, systems for the sustainable growth of a knowledge economy. Structured approaches to learning are demonstrated and comparison is drawn with smart city projects in Ireland and the United Kingdom

Scrutinizing the Smart City Index: a multivariate statistical approach

Koncept pametnog grada često se obrađuje, ali još nije postignuta konzistentna definicija. Ipak, svaki je opis gotovo uvijek usmjeren na njegovu tehnološku komponentu, politike održivog razvoja i omogućavanje visokih kapaciteta za učenje i inovacije. Osim toga, pametni grad ima za cilj povezivanje ljudi, informacija i drugih gradskih elemenata koristeći najsuvremenije tehnologije. Kao rezultat, stvara se održivi, zeleniji grad, potiče konkurentna i inovativna trgovina i povećava opća kvaliteta života.Integriranim prikazom pametnog grada ističe se da ne djeluje izolirano, te stoga, svaki podsustav grada treba razvijati svoju pametnu komponentu. Širok raspon rangiranja koristi se za određivanje pametnosti gradova mapiranjem prednosti i nedostataka svakog analiziranog grada. Kao način integriranja različitih pokazatelja u jednu vrijednost koja će predstavljati rang, najčešće se koristi složeni indeksni pristup.Ipak, složeni indeksi najčešće se formiraju primjenom pristupa jednakih pondera, što se u trenutnoj literaturi žestoko kritizira. U ovom radu pokušavamo pružiti dodanu vrijednost indeksu Smart City primjenom statističkog post-hoc I-distance pristupa. Postupak nam omogućuje osvjetljavanje pitanja osjetljivosti ranga gradova. Primjena post-hoc I-distance definira pokazatelje koji su najvažniji za postupak rangiranja što gradskim donositeljima odluka omogućava da poboljšaju svoje poslovanje, s naglaskom na upravo te pokazatelje.The smart city represents a frequently elaborated concept which however comes short in delivering a consistent definition. Nevertheless, almost every description has always been oriented to its technological component, sustainable development policies, and enabling high capacities for learning and innovation. Moreover, the smart city aims at connecting people, information and other city elements using state-of-the-art technologies. As a result, it creates a sustainable, greener city, pushes forward competitive and innovative commerce, and increases overall life quality. The integrated view of a smart city underlines it does not operate in isolation, which is why every subsystem of a city needs to develop its smart component. A wide range of rankings is used to determine the smartness of cities by mapping out the pros and cons of each analysed city. As the way to integrate various indicators into one value which will represent the rank, a composite index approach is most frequently used. Still, composite indexes are usually formed using the equal weight approach, which is heavily criticised in current literature. In this paper, we try to provide added value to the Smart City Index by implementing the statistical post hoc I-distance approach. The procedure enables us to shed some additional light on the issue of sensitivity of cities’ rank. The application of post hoc I-distance defines indicators which are most significant for the ranking process. It consequently empowers city decision-makers to improve their performance, with a focus on those particular indicators

A hybrid e-learning framework: Process-based, semantically-enriched and service-oriented

Despite the recent innovations in e-Learning, much development is needed to ensure better learning experience for everyone and bridge the research gap in the current state of the art e-Learning artefacts. Contemporary e-learning artefacts possess various limitations as follows. First, they offer inadequate variations of adaptivity, since their recommendations are limited to e-learning resources, peers or communities. Second, they are often overwhelmed with technology at the expense of proper pedagogy and learning theories underpinning e-learning practices. Third, they do not comprehensively capture the e-learning experiences as their focus shifts to e-learning activities instead of e-learning processes. In reality, learning is a complex process that includes various activities and interactions between different roles to achieve certain gaols in a continuously evolving environment. Fourth, they tend more towards legacy systems and lack the agility and flexibility in their structure and design. To respond to the above limitations, this research aims at investigating the effectiveness of combining three advanced technologies (i.e., Business Process Modelling and Enactment, Semantics and Service Oriented Computing – SOC–) with learning pedagogy in order to enhance the e-learner experience. The key design artefact of this research is the development of the HeLPS e-Learning Framework – Hybrid e-Learning Framework that is Process-based, Semantically-enriched and Service Oriented-enabled. In this framework, a generic e-learning process has been developed bottom-up based on surveying a wide range of e-learning models (i.e., practical artefacts) and their underpinning pedagogies/concepts (i.e., theories); and then forming a generic e-learning process. Furthermore, an e-Learning Meta-Model has been developed in order to capture the semantics of e-learning domain and its processes. Such processes have been formally modelled and dynamically enacted using a service-oriented enabled architecture. This framework has been evaluated using a concern-based evaluation employing both static and dynamic approaches. The HeLPS e-Learning Framework along with its components have been evaluated by applying a data-driven approach and artificially-constructed case study to check its effectiveness in capturing the semantics, enriching e-learning processes and deriving services that can enhance the e-learner experience. Results revealed the effectiveness of combining the above-mentioned technologies in order to enhance the e-learner experience. Also, further research directions have been suggested.This research contributes to enhancing the e-learner experience by making the e-learning artefacts driven by pedagogy and informed by the latest technologies. One major novel contribution of this research is the introduction of a layered architectural framework (i.e., HeLPS) that combines business process modelling and enactment, semantics and SOC together. Another novel contribution is adopting the process-based approach in e-learning domain through: identifying these processes and developing a generic business process model from a set of related e-learning business process models that have the same goals and associated objectives. A third key contribution is the development of the e-Learning Meta-Model, which captures a high-abstract view of learning domain and encapsulates various domain rules using the Semantic Web Rule Language. Additional contribution is promoting the utilisation of Service-Orientation in e-learning through developing a semantically-enriched approach to identify and discover web services from e-learning business process models. Fifth, e-Learner Experience Model (eLEM) and e-Learning Capability Maturity Model (eLCMM) have been developed, where the former aims at identifying and quantifying the e-learner experience and the latter represents a well-defined evolutionary plateau towards achieving a mature e-learning process from a technological perspective. Both models have been combined with a new developed data-driven Validation and Verification Model to develop a Concern-based Evaluation Approach for e-Learning artefacts, which is considered as another contribution

Law in the present future : approaching the legal imaginary of smart cities with science (and) fiction

This doctoral research concerns smart cities, describing digital solutions and social issues related to their innovative technologies, adopted models, and major projects around the world. The many perspectives mentioned in it were identified by online tools used for the textual analysis of two databases that were built from relevant publications on the main subject by authors coming from media and academia. Expected legal elements emerged from the applied process, such as privacy, security, transparency, participation, accountability, and governance. A general review was produced on the information available about the public policies of Big Data in the two municipal cases of Rio de Janeiro and Montréal, and their regulation in the Brazilian and Canadian contexts. The combined approaches from science and literature were explored to reflect on the normative concerns represented by the global challenges and local risks brought by urban surveillance, climate change, and other neoliberal conditions. Cyberpunk Science Fiction reveals itself useful for engaging with the shared problems that need to be faced in the present time, all involving democracy. The results achieved reveal that this work was, in fact, about the complex network of practices and senses between (post)modern law and the imaginary of the future.Cette recherche doctorale centrée sur les villes intelligentes met en évidence les solutions numériques et les questionnements sociétaux qui ont trait aux technologies innovantes, ainsi qu’aux principaux modèles et projets développés autour d’elles à travers le monde. Des perspectives multiples en lien avec ces développements ont été identifiées à l’aide d’outils en ligne qui ont permis l’analyse textuelle de deux bases de données comprenant des publications scientifiques et des écrits médiatiques. De ce processus analytique ont émergé des éléments juridiques relatifs aux questions de vie privée, de sécurité, de transparence, de participation, d’imputabilité et de gouvernance. De plus, à partir de ces informations a été réalisée une revue des politiques publiques relatives aux mégadonnées dans les villes de Rio de Janeiro et de Montréal, ainsi que des réglementations nationales du Canada et du Brésil en lien avec ce sujet. Finalement, à travers l’exploration d’écrits scientifiques et fictionnels de la littérature, les principaux enjeux normatifs soulevés localement et mondialement par la surveillance urbaine, les changements climatiques et les politiques néolibérales ont pu être mis à jour. Le courant cyberpunk de la science-fiction s’est avéré particulièrement utile pour révéler les principaux problèmes politiques, en lien avec la préservation de la démocratie, auxquelles sont confrontées nos sociétés présentement. Les résultats de la recherche démontrent finalement la présence d’un réseau de pratiques et de significations entre le droit (post)moderne et les représentations imaginaires du futur

Supporting student experience management with learning analytics in the UK higher education sector

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyWhile some UK Higher Education Institutes (HEIs) are very successful at harnessing the benefits of Learning Analytics, many others are not actually engaged in making effective use of it. There is a knowledge gap concerning understanding how Learning Analytics is being used and what the impacts are in UK HEIs. This study addresses this gap. More specifically, this study attempts to understand the challenges in utilising data effectively for student experience management (SEM) in the era of Big Data and Learning Analytics; to examine how Learning Analytics is being used for SEM; to identify the key factors affecting the use and impact of Learning Analytics; and to provide a systematic overview on the use and impact of Learning Analytics on SEM in HEIs by developing a conceptual framework. To achieve the research objectives, a qualitative research method is used. The data collection process firstly involves an exploratory case study in a UK university to gain a preliminary insight into the current status on the use of Big Data and Learning Analytics and their impact, and to determine the main focuses for the main study. The research then undertakes an extensive main study involving 30 semi-structured interviews with participants in different UK universities to develop more in-depth knowledge and to present systematically the key findings using a theoretical framework underpinned by relevant theories. Based on the evidence collected from the exploratory case study and interviews, the study identifies the key challenges in utilising data and Learning Analytics in the era of Big Data. These include issues related to data quality, data consistency, data reliability, data analysis, data integration, data and information overload, lack of data, information availability and problems with systems. A series of critical factors affecting the use of Learning Analytics is emerged and mapped out from a technology-organisation-environment-people (TOE+P) perspective. The technology-related factors include Usability, Affordability, Complexity and System integration. The organisation-related factors cover Resource, Data Driven Culture, Senior management support and Strategic IT alignment. The environment-related factors include Competitive pressure, Regulatory environment and External support. Most importantly, the findings emphasise the importance of the people-related factor in addition to TOE factors. The people-related factors include People’s engagement with using data and Learning Analytics, People’s awareness of Data Protection and Privacy and Digital Literacy. The impacts of the Learning Analytics are also identified and analysed using organisational absorptive capacity theory. The findings are integrated in the final theoretical framework and demonstrate that the HEIs’ capabilities in terms of data acquisition, assimilation, transformation and exploitation supported by Learning Analytics enable them to improve student experience management. This study makes new contributions to research and theory by providing a theoretical framework on understanding the use and impact of Learning Analytics in UK HEIs. It also makes important practical contributions by offering valuable guidelines to HEI managers and policy makers on understanding the value of Learning Analytics and know how to maximise the impact of Big Data and Learning Analytics in their organisations