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The purpose of this study is to verify the effect of smart pedagogy to facilitate the high order thinking skills of students and to provide the design suggestion of curriculum and intelligent tutoring systems in smart education.

A smart pedagogy framework was designed. The quasi-experiment was conducted in a junior high school. The experimental class used the smart pedagogy and smart learning environment. The control class adopted conventional teaching strategies. The math test scores of these two classes were compared to verify the effectiveness of smart pedagogy.

The smart pedagogy framework contains three sections including the situated learning (S), mastery learning (M), adaptive learning (A), reflective learning (R) and thinking tools (T) (SMART) key elements model, the curriculum design method and detailed teaching strategy. The SMART key elements model integrates the situated learning, mastery learning, adaptive learning, reflective learning and thinking tools to facilitate the high order thinking. The curriculum design method of smart pedagogy combines the first five principles of instruction and the SMART key elements model to design the curriculum. The detailed teaching strategies of smart pedagogy contain kinds of innovative learning methods. The results of the quasi-experiment proved that the learning outcome was significantly promoted by using smart pedagogy.

This research investigates a general framework that can be used to cultivate the high order thinking skills in different subjects and grades was one of the first to introduce high order thinking skills into smart education. The framework of smart pedagogy was innovative and effect in practice.

This paper aims to present a comprehensive review of the present state and trends of smart education research. It addresses the need to have a systematic review of smart education to depict its research landscape in view of the growing volume of related publications.

A bibliometric analysis of publications on smart education published in 2011 to 2020 was conducted, covering their patterns and trends in terms of collaboration, key publications, major topics and trends. A total of 1,317 publications with 29,317 cited references were collected from the Web of Science and Scopus for the bibliometric analysis.

Research on smart education has been widely published in various sources. The most frequently cited references are all theoretical or discussion articles. Researchers in the USA, China, South Korea, India and Russia have been most active in research collaborations. However, international collaborations have remained infrequent except for those involving the USA. The research on smart education broadly covered smart technologies as well as teaching and learning. The emerging topics have addressed areas such as the Internet of Things, big data, flipped learning and gamification.

This study depicts the intellectual landscape of smart education research, and illustrated the evolution and emerging trends in the field. The results highlight its latest developments and research needs, and suggest future work related to research collaborations on a larger scale and more studies on smart pedagogies.

Smart learning analytics (Smart LA) – i.e. the process of collecting, analyzing and interpreting data on how students learn – has great potentials to support opportunistic learning and offer better – and more personalized – learning experiences. The purpose of this paper is to provide an overview of the latest developments and features of Smart LA by reviewing relevant cases.

The paper studies several representative cases of Smart LA implementation, and highlights the key features of Smart LA. In addition, it discusses how instructors can use Smart LA to better understand the efforts their students make, and to improve learning experiences.

Ongoing research in Smart LA involves testing across various learning domains, learning sensors and LA platforms. Through the collection, analysis and visualization of learner data and performance, instructors and learners gain more accurate understandings of individual learning behavior and ways to effectively address learner needs. As a result, students can make better decisions when refining their study plans (either by themselves or in collaboration with others), and instructors obtain a convenient monitor of student progress. In summary, Smart LA promotes self-regulated and/or co-regulated learning by discovering opportunities for remediation, and by prescribing materials and pedagogy for remedial instruction.

Characteristically, Smart LA helps instructors give students effective and efficient learning experiences, by integrating the advanced learning analytics technology, fine-grained domain knowledge and locale-based information. This paper discusses notable cases illustrating the potential of Smart LA.

Higher education institutions are widely known both for their promotion to education for sustainable development (ESD) and for their contribution as living labs to urban management strategies. As for strategies, smart and learning campuses have recently gained significant attention. This paper aims to report an air quality monitoring experience with focus on the smart and learning campus and discuss its implications for the university context with regard to ESD and sustainable development goal (SDG) integration.

The air quality monitoring was held at the main campus of University of Passo Fundo and focused on three pollutants directly related to vehicle emissions. The air quality index (AQI) was presented on a website, along with information regarding health problems caused by air pollution, main sources of emissions and strategies to reduce it.

The results showed how the decrease in air quality is related to the traffic emissions and the fact that exposing students to a smart and learning environment could teach them about sustainability education.

This case study demonstrated how monitoring air quality in a smart environment could highlight and communicate the impact of urban mobility on air quality and alerted to the need for more sustainable choices, including transports.

This paper contributes to the literature by showing the potential of a smart-learning campus integration and its contribution towards the ESD and the UN SDGs.

The purpose of this study is to conduct a systematic review to understand state-of-art research related to learning preferences from the aspects of impacts, influential factors and evaluation methods.

This paper uses the systematic synthesis method to provide state-of-the-art knowledge on learning preference research by summarizing published studies in major databases and attempting to aggregate and reconcile the scientific results from the individual studies. The findings summarize aggregated research efforts and improve the quality of future research.

After analyzing existing literature, this study proposed three possible research directions in the future. First, researchers might focus on how to use the real-time tracking mechanism to further understand other impacts of learning preferences within the learning environments. Second, existing studies mainly focused on the influence of singular factors on learning preferences. The joint effects of multiple factors should be an important topic for future research. Finally, integrated algorithms might become the most popular evaluation method of learning preference in the era of smart learning environments.

This review used the search results generated by Google Scholar and Web of Science databases. There might be published papers available in other databases that have not been taken into account.

The research summarizes the state-of-art research related to learning preferences. This paper is one of the first to discuss the development of learning preference research in smart learning environments.

This chapter examines the teaching practice of the author in the Faculty of Education, University of Malta, taking sessions in smart learning as part of technology-enhanced learning (TEL) study units in Bachelors of Education and Masters in Teaching and Learning degree programs between 2017 and 2019. My teaching sessions ran concurrent with undertaking separate doctoral research investigating how participants experience “smart learning journeys.” Smart learning journeys in the research were conceptualized as real-world journeys, with geo-spatially relevant points of interest forming a journey of locations related to a topic of learning, providing context-aware content via digital interactions. Research was not connected to teaching practice, though students who took TEL units also participated in the same smart learning journey activity as part of their syllabus.

Though teaching sessions were not part of my research, my classroom practice modified as a result of emerging research findings, and my teaching benefited as I gained deeper understanding about smart learning activities and the role of the learner in them. Using dialogic learning methods and techniques inspired from my research interview methodology, class sessions became noticeably more effective as students engaged directly in discovering their own learning from having participated in the smart learning journey.

This research study aims to evaluate the capacity and sustainability of an accessible society as a smart society and services with the help of MOOCs and assistive technologies within the learning analytics framework.

Qualitative research was employed in this research that interview forms were conducted to get data from 60 participants. Thematic analysis was used to analyze data.

Research results revealed that MOOCs and assertive technologies are crucial for smart society and opens a map for open pedagogy. Accessible media, services and applications in smart societies are key elements for disabled people lives.

Research is limited to numbers of research participants in northern part of Cyprus.

Establishing strategies and policies for the smart and accessible society and services are intensified need for the disabled people within the framework of learning analytics.

Assistive technologies become medium of facilitating accessible and smart society and services for everyone.

Education plays a great role to enrich services of societies in order to create inclusive efforts to the life of disabled people. United Nations Educational Scientific and Cultural Organizations (UNESCO) underline the main theme of making inclusive and equitable quality education and promoting lifelong learning opportunities for all. In this respect, accessibility, inclusiveness, equity, equality, quality for lifelong learning are main components to foster accessible and smart society for everyone. Integrating the importance of learning analytics creates a value for understanding of being smart society.

The primary objective of this study is to examine how students' technological factors affect remote access (RA) in smart learning (SL) environments. Additionally, the paper explores the moderating effect of students' technical skills (TS) on RA and SL.

The study applied a quantitative research approach and collected 125 valid questionnaires from students in Oman's higher education institutions (HEIs). A structural equation model (SEM) was employed for data analysis using the Smart PLS 4 version to examine the influence of technological factors on RA in SL environments.

It was found that the use of cloud-based RA in SL is influenced by students' use of technology, technology competitiveness and the availability of institutional software (IS). Moreover, students' TS were found to play a crucial role in moderating RA and SL, as well as technical knowledge (TK) and SL. These findings highlight the importance of technical competencies and software availability in shaping students' RA experiences.

The study's findings should be interpreted with caution due to the limited sample size, which may restrict the generalizability of the results.

The study suggests the technological learning capabilities of HEIs, which significantly improved by prioritizing critical technical factors, including knowledge and use of technology, availability of institutional software and RA antecedents in SL environments.

This paper offers practical and actionable directions for HEIs, universities, colleges and educators looking to incorporate technology into their practices in the dynamic and ever-evolving Fourth Industrial Era.

This study aimed to investigate learning behaviors deeply in flipped classrooms. In addition, it is worth considering how to help learners through recognition technology with natural language processing (NLP) when learners have question and answer (Q&A). In addition, the Internet of Things (IoT) can be utilized to make the physical learning environment more comfortable and smarter.

The authors developed smart learning environment (SLE) with smart mechanisms supported by recognition technology, NLP and IoT to help learners and employed scaffolding to facilitate their group discussions. This study is an explanatory research to investigate graduate learners' learning behavior when they are collaborating with group members and interacting with the environment in flipped classroom using the proposed SLE.

The results revealed that learners who collaborated more while coediting had significant learning achievement, and NLP sufficiently addressed their questions. Physical conditions of the SLE were comfortable for learners. They perceived that SLE could facilitate group discussions with scaffolding.

This study suggests to utilize flipped classrooms with technologies, e.g. Google Slides integration, to help learners to do more collaboration and use smart mechanisms, e.g. Q&A with NLP, to make learners more interacting during the discussion process.

The proposed SLE can record and analyze smartly their collaboration meaningfully with group members and interact with the environment. Accordingly, researchers found that collaboration in flipped classrooms can help their learning achievement, and it is worth being widely promoted.

This study explores the factors that promote university teachers' switching intention from a traditional classroom to a smart classroom based on the push–pull–mooring (PPM) framework to enrich the theoretical research on the smart classroom and provide a reference for smart classroom promotion.

The proposed conceptual framework was developed from a comprehensive review of the related literature. This study tested and validated the proposed framework using a partial least square structural equation model based on 269 valid questionnaires.

(1) Perceived inefficiency, inquiry-based learning, future expectation and technical self-efficacy had significant effects on switching intention, while low participation, perceived usefulness and habit had no significant effects on university teachers’ switching intention in the smart classroom. (2) In the process of decision-making, the course category significantly moderates the impact of perceived inefficiency and technical self-efficacy on switching intention, while the user experience of smart classrooms significantly moderates the impact of perceived inefficiency on switching intention.

This study explains university teachers' switching intention from a traditional classroom to the smart classroom, which enriches the application area of the PPM framework.