ing WS1S Systems to Verify Parameterized Networks . . . . . . . . . . . . 188 Kai Baukus, Saddek Bensalem, Yassine Lakhnech and Karsten Stahl FMona: A Tool for Expressing Validation Techniques over Infinite State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 J.-P. Bodeveix and M. Filali Transitive Closures of Regular Relations for Verifying Infinite-State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Bengt Jonsson and Marcus Nilsson Diagnostic and Test Generation Using Static Analysis to Improve Automatic Test Generation . . . . . . . . . . . . . 235 Marius Bozga, Jean-Claude Fernandez and Lucian Ghirvu Efficient Diagnostic Generation for Boolean Equation Systems . . . . . . . . . . . . 251 Radu Mateescu Efficient Model-Checking Compositional State Space Generation with Partial Order Reductions for Asynchronous Communicating Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Jean-Pierre Krimm and Laurent Mounier Checking for CFFD-Preorder with Tester Processes . . . . . . . . . . . . . . . . . . . . . . . 283 Juhana Helovuo and Antti Valmari Fair Bisimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 Thomas A. Henzinger and Sriram K. Rajamani Integrating Low Level Symmetries into Reachability Analysis . . . . . . . . . . . . . 315 Karsten Schmidt Model-Checking Tools Model Checking Support for the ASM High-Level Language . . . . . . . . . . . . . . 331 Giuseppe Del Castillo and Kirsten Winter Table of

Tools and Algorithms for the Construction and Analysis of Systems. Proc. TACAS 2009

The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Model Driven Engineering

https://repository.tudelft.nl/islandora/object/uuid%3A7bdae86a-0209-4e53-83d0-c531dd3465ec/datastream/OBJ/download

Artificial Intelligence (AI) : Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy

The extent to which teachers adopt technology in their teaching practice has long been in the focus of research. Indeed, a plethora of models exist explaining influential factors and mechanisms of technology use in classrooms, one of which—the Technology Acceptance Model (TAM) and versions thereof—has dominated the field. Although consensus exists about which factors in the TAM might predict teachers’ technology adoption, the current field abounds in some controversies and inconsistent findings. This meta-analysis seeks to clarify some of these issues by combining meta-analysis with structural equation modeling approaches. Specifically, we synthesized 124 correlation matrices from 114 empirical TAM studies (N = 34,357 teachers) and tested the fit of the TAM and its versions. Overall, the TAM explains technology acceptance well; yet, the role of certain key constructs and the importance of external variables contrast some existing beliefs about the TAM. Implications for research and practice are discussed.

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The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education

Control Systems Engineering

Various review studies were conducted to provide valuable insights into the current research trend of the Technology Acceptance Model (TAM). Nevertheless, this issue still needs to be investigated from further directions. It has been noticed that research overlooks the investigation of TAM with regard to Mobile learning (M-learning) studies from the standpoint of different perspectives. The present study systematically reviews and synthesizes the TAM studies related to M-learning aiming to provide a comprehensive analysis of 87 research articles from 2006 to 2018. The main findings include that most of the TAM studies involving M-learning focused on extending the TAM with external variables, followed by the studies that extended the model by factors from other theories/models. In addition, the main research problem that was frequently tackled among all the analyzed studies was to examine the acceptance of M-learning among students. Moreover, questionnaire surveys were the primarily relied research methods for data collection. Additionally, most of the analyzed studies were undertaken in Taiwan, this is followed by Spain, China, and Malaysia, respectively among the other countries. Besides, most of the analyzed studies were frequently conducted in humanities and educational context, followed by IT and computer science context, respectively among the other contexts. Most of the analyzed studies were carried out in the higher educational settings. To that end, the findings of this review study provide an insight into the current trend of TAM research involving M-learning studies and form an essential reference for scholars in the M-learning context.

Technology Acceptance Model in M-learning context: A systematic review

The impact of knowledge management processes on information systems: A systematic review

Towards a conceptual model for examining the impact of knowledge management factors on mobile learning acceptance

The partial least squares-structural equation modelling (PLS-SEM) has become a key approach for validating the conceptual models across many disciplines in general, and the Information Systems (IS) in specific. This is guided through the assessment of the measurement and structural models. Several research articles were carried out to provide an extensive coverage of the usage and application of PLS-SEM. These articles were mainly concentrated on providing guidelines of how to use PLS-SEM in terms of reflective and formative measures, measurement and structural models, and the steps for analysing a particular conceptual model. Nevertheless, there are several steps and procedures that precede the evaluation of the measurement and structural models. The understanding of these steps and procedures is very important for many IS scholars, Ph.D. and Master students who are always struggling to find a comprehensive reference that could guide them through their research journey. Hence, the main contribution of this study is to a build a comprehensive methodological guideline of how the PLS-SEM approach can be employed in the context of IS adoption and acceptance, starting from the research design stage till the assessment of the measurement and structural models. This study may serve as a comprehensive reference for formulating the methodology in the IS adoption and acceptance related studies in the case of PLS-SEM employment.

PLS-SEM in Information Systems Research: A Comprehensive Methodological Reference

The wide spectrum use of mobile devices has brought numerous opportunities to develop and design Mobile Learning (M-learning) applications that will assist learners in their studies. From the M-learning perspective, in order to improve the learners' capabilities through the use of mobile devices, Knowledge Management (KM) processes (Knowledge Acquisition, Knowledge Sharing, Knowledge Application, and Knowledge Protection) should be incorporated in M-learning applications. The literature shows that several research studies were carried out with the aim of developing M-learning applications. Due to the lack of literature on examining the impact of KM processes on M-learning acceptance theoretically and practically, the main objective of this study is to develop a M-learning application that enables KM processes (Acquisition, Sharing, Application, and Protection). Moreover, the paper describes the M-learning application framework that was developed based on KM processes. In addition, the paper deliberates the implementation of the application in two different universities in two different regions, namely: Universiti Malaysia Pahang (UMP) in Malaysia, and Al Buraimi University College (BUC) in Oman. Other implications and discussions are also presented in the paper.

Vitaliy Mezhuyev

Papers

Technology Acceptance Model in M-learning context: A systematic review

The impact of knowledge management processes on information systems: A systematic review

Towards a conceptual model for examining the impact of knowledge management factors on mobile learning acceptance

PLS-SEM in Information Systems Research: A Comprehensive Methodological Reference

Development of M-learning Application based on Knowledge Management Processes