Exploring the experiences of instructors teaching massive open online courses in tourism and hospitality: a mixed methods approach

Massive Open Online Courses (MOOCs) have existed as a disruptive educational phenomenon for nine years. Grounded in the roots of distance education, open education, Open Educational Resources, and OpenCourseWare, MOOCs have now survived various critics and have continued growing globally. Reports about MOOCs in both the press and scholarly publications began to grow significantly in 2013 (Sánchez-Vera, Leon Urrutia, & Davis, 2015; Zancanaro & Domingues, 2017) and, since then, more and more researchers have joined the discussions, developing them to explore various new topics. To contribute to the literature of MOOC studies, this doctoral thesis begins with an in-depth analysis of the background, history, growth, and vision, and proposes a tentative definition of MOOCs. Meanwhile, by conducting bibliometric research to review MOOC studies conducted between 2015 and 2017, this thesis fills in the gap that has existed due to a lack of systematic reviews of MOOC literature since 2015. The results of the bibliometric research summarised the relevant MOOC research into nine categories, including learner focused, commentary and concepts, case reports or evaluations, pedagogy, curriculum and design, course object focused, provider focused, technology, systematic review of literature, and learning analytics and big data. They also suggested a limited amount of provider focused research, which became the research interest and focus of this thesis. In the centre of the Europe, Swiss universities have marched forward in the MOOC movement, together with other over 550 universities (Shah, 2016) around the world. Università della Svizzera italiana (USI; Lugano, Switzerland), a Swiss public university, became a MOOC provider in 2015 and offered the first MOOC in the topic of eTourism: eTourism: Communication Perspectives. This doctoral thesis is closely related to this university-level initiative, which was dedicated to producing the first pilot MOOC at USI. Therefore, the cases chosen by this thesis are positioned in the discipline of tourism and hospitality. The first MOOC with a large audience taught artificial intelligence in 2011 (Zancanaro & Domingues, 2017). Nowadays, MOOCs have broken the barrier of space and time to educate the masses in a wide range of subjects. However, the provision of MOOCs in the subject of tourism and hospitality did not appear until 2013, when two MOOCs from two American universities became available. In the past four years since these MOOCs were launched, the number of tourism and hospitality MOOCs available in the market has remained limited (Tracey, Murphy, & Horton-Tognazzini, 2016). This scarcity contradicts the fact that tourism and hospitality is the field that contributes the most to the employment of the global workforce. Pressing problems, such as high turnover, seasonality, and new global challenges have urged for solutions to quickly training people working in this area to become available (Cantoni, Kalbaska, & Inversini, 2009). A call for more studies about tourism and hospitality MOOCs has emerged. The combined reality of the lack of studies regarding MOOC providers, opportunities for first-hand experience of producing a tourism MOOC in a university, and the deficiency in both the research and practises of tourism and hospitality MOOCs has inspired the direction of this thesis in regard to exploring MOOC instructors’ experiences, using cases in the field of tourism and hospitality. It cumulates six studies, using a mixed methods approach, to tackle the two main research objectives: to investigate at large the tourism and hospitality MOOC provisions between 2008 and 2015 and to report the experiences of Università della Svizzera italiana (USI) when producing the eTourism MOOC. In order, the first two studies in Chapter 3 of this thesis focus on tourism and hospitality MOOCs in general and produce a big picture context for the other four studies in Chapter 4. The first study proposes a conceptual framework through which to describe and analyse the course design of a MOOC and applies it to 18 tourism and hospitality MOOCs produced between 2008 and 2015. The second study then continues to interview six tourism and hospitality MOOC instructors, to describe their experiences and perspectives of teaching MOOCs. After exploring a holistic view of the overall development of MOOCs in tourism and hospitality and gaining a deep understanding of the instructors behind these offerings, this thesis introduces the experiences of one single MOOC provider: Università della Svizzera italiana (USI) in Chapter 4. It first introduces its overall implementation process (Study 3), and further elaborates three phases of this process: how it selected a suitable MOOC platform at the beginning (Study 4); how it assessed learner engagement in the MOOC (Study 5); and, eventually, how it evaluated the performance of the MOOC (Study 6). This thesis was written mainly from the perspective of eLearning, with the intention of benefiting its community of scholars and practitioners. It has contributed to the literature by developing a framework with which to review MOOCs (in Study 1), the implementation process of producing MOOCs (in Study 2), practical review schema of MOOC platforms (in Study 4), the MOOC Learner Engagement Online Survey (in Study 5), and how to use the Kirkpatrick model to evaluate MOOCs (in Study 6). These conceptual frameworks and experiential tools can benefit future researchers and practitioners. Meanwhile, due to its intimate connection with the field of tourism and hospitality, by directly using its cases, the research outputs of the six studies can also benefit the tourism and hospitality education and training sector as a reference for further action

Adaptive Multi-Armed Bandit Learning for Task Offloading in Edge Computing

The widespread adoption of edge computing has emerged as a prominent trend for alleviating task processing delays and reducing energy consumption. However, the dynamic nature of network conditions and the varying computation capacities of edge servers (ESs) can introduce disparities between computation loads and available computing resources in edge computing networks, potentially leading to inadequate service quality. To address this challenge, this paper investigates a practical scenario characterized by dynamic task offloading. Initially, we examine traditional Multi-armed Bandit (MAB) algorithms, namely the $\varepsilon$-greedy algorithm and the UCB1-based algorithm. However, both algorithms exhibit certain weaknesses in effectively addressing the tidal data traffic patterns. Consequently, based on MAB, we propose an adaptive task offloading algorithm (ATOA) that overcomes these limitations. By conducting extensive simulations, we demonstrate the superiority of our ATOA solution in reducing task processing latency compared to conventional MAB methods. This substantiates the effectiveness of our approach in enhancing the performance of edge computing networks and improving overall service quality.Comment: 5 pages,6 figure

Constructing a Non-Negative Low Rank and Sparse Graph with Data-Adaptive Features

This paper aims at constructing a good graph for discovering intrinsic data structures in a semi-supervised learning setting. Firstly, we propose to build a non-negative low-rank and sparse (referred to as NNLRS) graph for the given data representation. Specifically, the weights of edges in the graph are obtained by seeking a nonnegative low-rank and sparse matrix that represents each data sample as a linear combination of others. The so-obtained NNLRS-graph can capture both the global mixture of subspaces structure (by the low rankness) and the locally linear structure (by the sparseness) of the data, hence is both generative and discriminative. Secondly, as good features are extremely important for constructing a good graph, we propose to learn the data embedding matrix and construct the graph jointly within one framework, which is termed as NNLRS with embedded features (referred to as NNLRS-EF). Extensive experiments on three publicly available datasets demonstrate that the proposed method outperforms the state-of-the-art graph construction method by a large margin for both semi-supervised classification and discriminative analysis, which verifies the effectiveness of our proposed method

Sustaining Urban Public Spaces through Everyday Aesthetic Cosmopolitanism: The Case of the Art Center Recyclart

This article explores how social artistic interventions provide forms of everyday aesthetic cosmopolitanism – an intellectual and aesthetic openness towards objects, places, experiences, activities that relates to the everyday life of people regardless of identity, occupation, social class, cultural/racial background, and lifestyle – in transforming urban voids into inclusive urban public spaces. Through socially engaged art, artists and artistic institutions do not play a leading role but act as facilitators to provide space and context for events to emerge. Through participant observations and interviews for the period 2015-2018 and using concepts of everyday aesthetic cosmopolitanism, we demonstrate how the art center Recyclart, through socially informed artistic interventions, practices, and performances, contributed to transforming urban voids into inclusive urban public spaces. Our results indicate that local life, enacted by so-called marginalized residents and their everyday practices in urban central neighborhoods, is critical in city-making and contributes to everyday aesthetic cosmopolitanism

Long Short-Term Memory with Dynamic Skip Connections

In recent years, long short-term memory (LSTM) has been successfully used to model sequential data of variable length. However, LSTM can still experience difficulty in capturing long-term dependencies. In this work, we tried to alleviate this problem by introducing a dynamic skip connection, which can learn to directly connect two dependent words. Since there is no dependency information in the training data, we propose a novel reinforcement learning-based method to model the dependency relationship and connect dependent words. The proposed model computes the recurrent transition functions based on the skip connections, which provides a dynamic skipping advantage over RNNs that always tackle entire sentences sequentially. Our experimental results on three natural language processing tasks demonstrate that the proposed method can achieve better performance than existing methods. In the number prediction experiment, the proposed model outperformed LSTM with respect to accuracy by nearly 20%

An Empirical Study on the Evolution of Employment Structure of Transport, Storage and Post Industry of Beijing During Economic Transition in China

Employment structure of transport, storage and post industry is in continuous evolution along with the economic transition, and this paper makes an empirical study on it. This paper analyzes the change in employed laborers, employment structure and industry structure in transport, storage and post industry in Beijing, and makes a comparison with the employment proportion in third industry. Based on the above analysis, this paper gives some policy suggestions to both promote the healthy development of transport, storage and post industry in Beijing and further enhance the industry to absorb laborers

New insulin-like growth factor 1 (IGF-1) analogs for receptor studies and therapeutic applications

The insulin/IGF system is an evolutionary conserved network that includes three closely related peptide hormones (insulin, IGF-1 and IGF-2), three homologous tyrosine kinase receptors (IR-A, IR-B and IGF-1R), a distinct IGF-2 receptor (IGF-2R), and six IGF-binding proteins. While insulin signals mainly via IR, playing a key role in glucose homeostasis, IGFs mainly signal via IGF-1R to mediate normal human growth. A tight control of ligands and receptors expression is crucial for the proper functioning of the organism. Aberrant signaling by these receptors is manifested in many pathological conditions, including cancer, growth disorders, neurodegenerative diseases and diabetes. Hence, the insulin/IGF axis represents a promising therapeutic target. In view of the multiple unsuccessful clinical anticancer trials performed either with tyrosine kinase inhibitors or antibodies targeted against IGF-1R, the development of novel selective and receptor-specific insulin and IGF analogs with minimized side effects would be of interest. Our study began with the recombinant preparation of IGF-1 dimers in which IGF-1 monomers are interlinked between their C- and N-termini with Ser-Gly linkers (length of 8, 15 or 25 residues). The goal was to investigate whether the binding of two covalently linked IGF-1 molecules...Systém insulin/IGF je evolučně konzervovaný systém, který zahrnuje tři blízce příbuzné peptidové hormony (insulin, IGF-1 a IGF-2), tři homologní tyrozin-kinázové receptory (IR-A, IR- B a IGF-1R), odlišný receptor IGF-2R a šest proteinů vážících IGF. Zatímco insulin signalizuje hlavně prostřednictvím IR a hraje klíčovou roli v homeostázi glukózy, IGF signalizují hlavně prostřednictvím IGF-1R a zprostředkovávají normální lidský růst. Pro správné fungování organismu je klíčová přísná kontrola exprese ligandů i receptorů. Aberantní signalizace prostřednictvím těchto receptorů se projevuje u mnoha patologických stavů, včetně rakoviny, poruch růstu, neurodegenerativních onemocnění a diabetu. Osa insulin/IGF proto představuje slibný terapeutický cíl. Vzhledem k četným neúspěšným klinickým protinádorovým studiím prováděným buď s inhibitory tyrosin-kináz, nebo s protilátkami namířenými proti IGF-1R, by byl zajímavý vývoj nových receptorově specifických analogů insulinu a IGF s minimalizovanými vedlejšími účinky. Naše studie začala rekombinantní přípravou dimerů IGF-1, v nichž jsou monomery IGF-1 propojeny mezi svými C- a N-konci Ser-Gly linkery (délka 8, 15 nebo 25 zbytků). Cílem bylo zjistit, zda vazba dvou kovalentně spojených molekul IGF-1 na receptor může tento receptor inhibovat nebo aktivovat. Dále...Katedra biochemieDepartment of BiochemistryFaculty of SciencePřírodovědecká fakult