<p>A decision support system is an interactive human–computer decision-making system that s... more <p>A decision support system is an interactive human–computer decision-making system that supports decision makers rather than replaces them, utilizing data and models. It solves unstructured and semi-structured problems with a focus on effectiveness rather than efficiency in decision processes. In the early 1970s, scholars in this field began to recognize the important roles that decision support systems (DSS) play in supporting managers in their semi-structured or unstructured decision-making activities. Over the past five decades, DSS has made progress toward becoming a solid academic field. Nevertheless, since the mid-1990s, the inability of DSS to fully satisfy a wide range of information needs of practitioners provided an impetus for a new breed of DSS called business intelligence systems (BIS). The academic discipline of DSS has undergone numerous changes in technological environments including the adoption of data warehouses. Until the late 1990s, most textbooks referred to "decision support systems." Nowadays, many of them have replaced "decision support systems" with "business intelligence." While DSS/BIS began in academia and were quickly adopted in business, in recent years these tools have moved into government and the academic field of public administration. In addition, modern political campaigns, especially at the national level, are based on data analytics and the use of big data analytics. The first part of this article reviews the development of DSS as an academic discipline. The second part discusses BIS and their components (the data warehousing environment and the analytical environment). The final part introduces two emerging topics in DSS/BI: big data analytics and cloud computing analytics. Before the era of big data, most data collected by business organizations could easily be managed by traditional relational database management systems with a serial processing system. Social networks, e-business networks, Internet of Things (IoT), and many other wireless sensor networks are generating huge volumes of data every day. The challenge of big data has demanded a new business intelligence infrastructure with new tools (Hadoop cluster, the data warehousing environment, and the business analytical environment).</p>
This paper proposes a Cloud based multiple criteria decision support system (DSS) for Selecting U... more This paper proposes a Cloud based multiple criteria decision support system (DSS) for Selecting Urban Housing Sustainable Development Projects in order to help the decision makers to choose the best urban project with conflicting criteria. The DSS is deployed on a platform Cloud (CloudBees) and managed by the OpenStack infrastructure. The Cloud based multiple criteria DSS we designed and implemented has significant advantages. It reduces the deployment and processing time, ameliorates the communication and the cooperation between the decision makers, facilitates the accessibility, and decrease the cost. The DSS is built on the Cloud Computing architecture with three layers and includes the multiple criteria decision making (MCDM) method PROMETHEE II as well as the procedure of negotiation Hare in order to help the decision makers to select the best urban project.
The past several decades of e-learning empirical research has advanced our understanding of the e... more The past several decades of e-learning empirical research has advanced our understanding of the effective management of critical success factors (CSF) of technology-mediated learning. Meanwhile, the proliferation of measures of dependent and independent variables has been overelaborated. A significant reduction in dependent and independent variables and their measures is necessary for building a technology-mediated learning success model, and that such a model should incorporate the interdependent (not independent) process nature of technology-mediated learning success. Structural equation modeling is to be applied to empirically validate a comprehensive model of technology-mediated learning success. Our research advances existing literature on CSF of technology-mediated learning success and provides a basis for guiding future empirical research to build robust technology-mediated learning theories. The model aims to satisfactorily explain and predict the interdependency of six CSFs...
This research identifies leading institutions and the most frequent contributors in the field of ... more This research identifies leading institutions and the most frequent contributors in the field of decision support systems tDSSI development research. Two hundred and three specific DSS were extracted from over 1100 English-language journals published worldwide in the last 18 years (1971-April 1988). From the bibliography, this survey identified 37 leading DSS development publishing institutions from the U .S.A., Canada, and European countries as well as 35 frequent contributors from academic institutions all over the world .
This study applies partial least squares (PLS) to examine the effects of interactions and instruc... more This study applies partial least squares (PLS) to examine the effects of interactions and instructor feedback and facilitation on the students' satisfaction and their perceived learning outcomes in the context of university online courses. Independent variables included in the study are course structure, self-motivation, learning style, and interaction. A total of 397 valid unduplicated responses from students who have completed at least one online course at a university in the Midwest U.S. are used to examine the structural model. Four of the five antecedent constructs hypothesized to directly affect student/instructor interaction are significant. This research makes a critical contribution in e-learning empirical research by identifying two critical human factors that make e-learning a superior mode of instruction.
This research examines the current state of multiple criteria decision making (MCDM) model-embedd... more This research examines the current state of multiple criteria decision making (MCDM) model-embedded decision support systems (MCDSS). A comprehensive bibliography of 203 specific DSS applications was extracted from over 1100 English-language journals published in the last 18 years (1971–April 1988). The survey identified 26 MCDM model-embedded DSS (13% of the 203 DSS applications). Approximately 30% of the MCDSS applications (8 out of 26 applications) were developed to support strategic decisions; about 70% support tactical and operational levels of decisions. The integration pattern over the last two decades was also analysed. During the 1970s only two MCDM model-embedded DSS were developed; however, the number of MCDSS models has increased proportionately during the 1980s.
A survey of specific DSS applications published between 1971 and April 1988 indicates the develop... more A survey of specific DSS applications published between 1971 and April 1988 indicates the development of a wide variety of DSS applications in many different fields. Despite two decades of cooperative efforts by practitioners and theoreticians to develop specific DSSs, many goals in the DSS field remain unfulfilled. The critical issue is to implement a system that integrates organizational decision making vertically (among strategic, tactical, and operational levels) and horizontally (among many functional fields at the same level) to coordinate and manage conflicts among the various subunits of the organization.
The purpose of this research is to develop a goal programming based decision support system (DSS)... more The purpose of this research is to develop a goal programming based decision support system (DSS) for global financing strategies of the multinational corporation. The global financing decision is characterized by the uncertain foreign exchange rates and uncertain political conditions of each operating host country. Because of the nature of the uncertainty involved in the decision process, operations research (OR)/management science (MS) models themselves do not always provide satisfactory solutions for the financing problems of an MNC. On the other hand, managerial judgement alone is also inadequate because of the complexity, size of the decision variables, and numerous and often conflicting objectives of global financing strategies. Therefore, the effectiveness of global financing decisions may only be improved by simultaneous use of managerial judgement and a well designed DSS. The proposed DSS can assist financial managers of the MNC in their strategic, financial planning process through broadening the focus of managers and extending limits on managers as information processors. The global financing decision requires three consecutive stages of interactions between managers and the proposed DSS. The first stage is primarily concerned with the adjustments of the cost of capital and the consolidated firm\u27s financial structure (selection of an appropriate adjusted cost of capital). In the second stage, the financing decision process is analyzed to identify and select a best priority structure. In the third and final stage, with the information derived about the fixed cost of financing and priority structure, managers can incorporate their what if types of managerial queries in their decision making process. The DSS allows MNC financial managers to choose an appropriate global financing strategy to satisfy multiple, and often conflicting management goals and to effectively analyze the trade-offs among costs, foreign exchange risks, political risks, and managerial motivation goals
Inter-Organizational Information Systems in the Internet Age
An IOS is an information and management system that transcends organizational boundaries via elec... more An IOS is an information and management system that transcends organizational boundaries via electronic linkages with its trading partners. The electronic linkage is established by information and communication technologies. Extranets1 are the core technology for building IOSs. There are a host of other technologies that serve as the infrastructure for managing IOSs. They include coordination technologies, monitoring technologies, filtering and negotiating technologies (intelligent agents), and decision-making and knowledge-management technologies. In this chapter, a brief overview of each of these technologies is presented.
Psychology is the study of the mental states and processes that give rise to behavior. It seeks t... more Psychology is the study of the mental states and processes that give rise to behavior. It seeks to understand the basic mechanisms and functions of perception, cognition, emotion, and attitudes in guiding behavior. Although it focuses on the level of the individual, individual behavior depends on the social relationships and structures in which people are embedded and the biological systems of which we are comprised. Thus, psychological study encompasses a broad set of topics that overlap with a number of disciplines across the social and biological sciences. The requirements of the major are designed to acquaint students with the research methods psychologists use and to provide a foundation of core knowledge covering the major areas of psychology. This broad foundation allows students to pursue a more advanced understanding of subfields related to their own particular interests and goals for the major. The program may serve as preparation for graduate work in psychology or related fields (e.g., neuroscience, education), as well as for students interested in careers in social work, public policy, business, or medicine. Students are encouraged to become actively engaged in research in the department and should consult with the director of undergraduate research about their interests as early as possible.
This chapter will benefit those who teach individuals using the synchronous virtual classroom (SV... more This chapter will benefit those who teach individuals using the synchronous virtual classroom (SVC). The SVC model will help instructors design online courses that incorporate the factors that students need to be successful. This model will also help virtual classroom instructors and managers develop a systematic way of identifying and addressing the external and internal factors that might impact the success of their instruction. The strategies for empirically researching the SVC, which range from qualitative inquiry to experimental design, are discussed along with practical examples. This information will benefit instructors, researchers, non-profit and profit organizations, and academia.
Decision Sciences Journal of Innovative Education, Apr 1, 2016
ABSTRACTA stream of research over the past decade that identifies predictors of e‐learning succes... more ABSTRACTA stream of research over the past decade that identifies predictors of e‐learning success suggests that there are several critical success factors (CSFs) that must be managed effectively to fully realize promise for e‐learning. Grounded in constructivist learning theories, this study advances previous work on CSFs in university online education. Structural equation modeling is applied to examine the determinants of students’ satisfaction and their perceived learning outcomes in the context of university online courses. The independent variables of motivation (intrinsic and extrinsic), student self‐regulation, dialogue (instructor‐student, and student‐student), instructor, and course design are examined as potential determinants of online learning outcomes. A total of 372 responses from students who have completed at least one online course at a university in the Midwestern United States were used to examine the structural model. Findings indicate that instructor‐student dialogue, student‐student dialogue, instructor, and course design significantly affect students’ satisfaction and learning outcomes. However, both extrinsic student motivation and student self‐regulation have no significant relationship with user satisfaction and learning outcomes. Finally, intrinsic student motivation affects learning outcomes but not user satisfaction. The findings suggest that course design, instructor, and dialogue are the strongest predictors of user satisfaction and learning outcomes.
International Journal of Information Management, 1990
Although group decision making (GDM) is an important research field in social psychology, group d... more Although group decision making (GDM) is an important research field in social psychology, group decision support systems (GDSS) only recently emerged as a field in the decision support systems (DSS) area. This paper analyses the different types of organizational conflict and suggests the use of GDSS as an essential tool for resolving these conflicts. The role of computer-based information systems (CBIS) has evolved from focusing on data (transaction processing systems) and information (management information systems) to focusing on decision (decision support systems) and coordination (distributed decision-making systems). This paper expands the role of GDSS as an essential tool for resolving organizational conflicts. The GDSS must play a role in integrating functional subunits horizontally, and in integrating long-range, medium-range and short-range planning to create a coordinated strategy. Group decision support systems 3~~~~~, L. (1956). The functions of social conflict. New York: The Free Press. "ZELENY, M. (1982). Multiple criteria decision making. New York: McGraw-Hill.
There is nothing novel about the idea of assembling a group to work toward the solution of a spec... more There is nothing novel about the idea of assembling a group to work toward the solution of a specific problem, then dismantling it when the task is completed. We introduce an evolving concept, virtual TFTs (Task Force Teams), as a subset of virtual organization not only to effectively deal with a specific task that cannot be performed either as efficiently or effectively through current organizational structures and policies, but also to overcome the limitations of the traditional TFT. This paper is intended to show both how the virtual TFT is different from the traditional one and how the former can overcome the limitations of the latter.
International Journal of Decision Support System Technology
To increase healthcare quality, early illness prediction helps patients prevent potentially life-... more To increase healthcare quality, early illness prediction helps patients prevent potentially life-threatening health issues before it is too late. Artificial intelligence is a rapidly evolving area, and its applications to diabetes, a worldwide epidemic, have the potential to revolutionize the way diabetes is diagnosed and managed. A total of six supervised machine learning algorithms based on patient data were used and compared to predict the diagnosis of diabetes mellitus. For experiments, the Pima Indians Diabetes Database was used, and their missing values were carefully handled by different techniques. For random train-test splits, the Random Forest classification algorithm achieved an accuracy rate of 92 percent. This model outperforms other state-of-the-art approaches due to the application of a combination of techniques for dealing with missing values (the mixture of imputing missing values techniques) that is proposed. With this approach, the models of this manuscript achiev...
This paper examines the impact of using mobile devices, the pivotal element of a student-centered... more This paper examines the impact of using mobile devices, the pivotal element of a student-centered ecosystem, on the learning process and learning outcomes from a system’s view in which mobile technologies are considered a critical success factor to facilitate the dialogue and self-regulatory learning processes, thereby enhancing e-learning outcomes. We synthesize the disparate literature to develop an elevated model. A total of 323 valid and unduplicated responses from students who have completed at least one online course at a Midwestern university in the U.S. were used to examine the structural model, using SmartPLS v. 3.3.2. The results of this study show that the use of mobile devices positively affects student-instructor and student-student dialogues. It also facilitates the self-regulation process, which in turn positively affects the learning outcomes. Integrating mobile technology enables educational institutions to design and build distance learning systems that allow stude...
2019 IEEE 21st Conference on Business Informatics (CBI)
There are few empirical studies that directly investigate the relationships between mobile device... more There are few empirical studies that directly investigate the relationships between mobile device usage and four constructs (student-student dialogue, student-instructor dialogue, self-regulation, and learning outcomes) in university online education. Structural equation modeling is applied to examine the effects of mobile device usage on students' perceived learning outcomes. A total of 350 valid unduplicated responses from students who have completed at least one online course at a university in the Midwest USA were used to examine the structural model. The results of this study showed that mobile device usage affect student-instructor dialogue positively and facilitate the self-regulation process, which in turn positively affect the learning outcomes.
<p>A decision support system is an interactive human–computer decision-making system that s... more <p>A decision support system is an interactive human–computer decision-making system that supports decision makers rather than replaces them, utilizing data and models. It solves unstructured and semi-structured problems with a focus on effectiveness rather than efficiency in decision processes. In the early 1970s, scholars in this field began to recognize the important roles that decision support systems (DSS) play in supporting managers in their semi-structured or unstructured decision-making activities. Over the past five decades, DSS has made progress toward becoming a solid academic field. Nevertheless, since the mid-1990s, the inability of DSS to fully satisfy a wide range of information needs of practitioners provided an impetus for a new breed of DSS called business intelligence systems (BIS). The academic discipline of DSS has undergone numerous changes in technological environments including the adoption of data warehouses. Until the late 1990s, most textbooks referred to "decision support systems." Nowadays, many of them have replaced "decision support systems" with "business intelligence." While DSS/BIS began in academia and were quickly adopted in business, in recent years these tools have moved into government and the academic field of public administration. In addition, modern political campaigns, especially at the national level, are based on data analytics and the use of big data analytics. The first part of this article reviews the development of DSS as an academic discipline. The second part discusses BIS and their components (the data warehousing environment and the analytical environment). The final part introduces two emerging topics in DSS/BI: big data analytics and cloud computing analytics. Before the era of big data, most data collected by business organizations could easily be managed by traditional relational database management systems with a serial processing system. Social networks, e-business networks, Internet of Things (IoT), and many other wireless sensor networks are generating huge volumes of data every day. The challenge of big data has demanded a new business intelligence infrastructure with new tools (Hadoop cluster, the data warehousing environment, and the business analytical environment).</p>
This paper proposes a Cloud based multiple criteria decision support system (DSS) for Selecting U... more This paper proposes a Cloud based multiple criteria decision support system (DSS) for Selecting Urban Housing Sustainable Development Projects in order to help the decision makers to choose the best urban project with conflicting criteria. The DSS is deployed on a platform Cloud (CloudBees) and managed by the OpenStack infrastructure. The Cloud based multiple criteria DSS we designed and implemented has significant advantages. It reduces the deployment and processing time, ameliorates the communication and the cooperation between the decision makers, facilitates the accessibility, and decrease the cost. The DSS is built on the Cloud Computing architecture with three layers and includes the multiple criteria decision making (MCDM) method PROMETHEE II as well as the procedure of negotiation Hare in order to help the decision makers to select the best urban project.
The past several decades of e-learning empirical research has advanced our understanding of the e... more The past several decades of e-learning empirical research has advanced our understanding of the effective management of critical success factors (CSF) of technology-mediated learning. Meanwhile, the proliferation of measures of dependent and independent variables has been overelaborated. A significant reduction in dependent and independent variables and their measures is necessary for building a technology-mediated learning success model, and that such a model should incorporate the interdependent (not independent) process nature of technology-mediated learning success. Structural equation modeling is to be applied to empirically validate a comprehensive model of technology-mediated learning success. Our research advances existing literature on CSF of technology-mediated learning success and provides a basis for guiding future empirical research to build robust technology-mediated learning theories. The model aims to satisfactorily explain and predict the interdependency of six CSFs...
This research identifies leading institutions and the most frequent contributors in the field of ... more This research identifies leading institutions and the most frequent contributors in the field of decision support systems tDSSI development research. Two hundred and three specific DSS were extracted from over 1100 English-language journals published worldwide in the last 18 years (1971-April 1988). From the bibliography, this survey identified 37 leading DSS development publishing institutions from the U .S.A., Canada, and European countries as well as 35 frequent contributors from academic institutions all over the world .
This study applies partial least squares (PLS) to examine the effects of interactions and instruc... more This study applies partial least squares (PLS) to examine the effects of interactions and instructor feedback and facilitation on the students' satisfaction and their perceived learning outcomes in the context of university online courses. Independent variables included in the study are course structure, self-motivation, learning style, and interaction. A total of 397 valid unduplicated responses from students who have completed at least one online course at a university in the Midwest U.S. are used to examine the structural model. Four of the five antecedent constructs hypothesized to directly affect student/instructor interaction are significant. This research makes a critical contribution in e-learning empirical research by identifying two critical human factors that make e-learning a superior mode of instruction.
This research examines the current state of multiple criteria decision making (MCDM) model-embedd... more This research examines the current state of multiple criteria decision making (MCDM) model-embedded decision support systems (MCDSS). A comprehensive bibliography of 203 specific DSS applications was extracted from over 1100 English-language journals published in the last 18 years (1971–April 1988). The survey identified 26 MCDM model-embedded DSS (13% of the 203 DSS applications). Approximately 30% of the MCDSS applications (8 out of 26 applications) were developed to support strategic decisions; about 70% support tactical and operational levels of decisions. The integration pattern over the last two decades was also analysed. During the 1970s only two MCDM model-embedded DSS were developed; however, the number of MCDSS models has increased proportionately during the 1980s.
A survey of specific DSS applications published between 1971 and April 1988 indicates the develop... more A survey of specific DSS applications published between 1971 and April 1988 indicates the development of a wide variety of DSS applications in many different fields. Despite two decades of cooperative efforts by practitioners and theoreticians to develop specific DSSs, many goals in the DSS field remain unfulfilled. The critical issue is to implement a system that integrates organizational decision making vertically (among strategic, tactical, and operational levels) and horizontally (among many functional fields at the same level) to coordinate and manage conflicts among the various subunits of the organization.
The purpose of this research is to develop a goal programming based decision support system (DSS)... more The purpose of this research is to develop a goal programming based decision support system (DSS) for global financing strategies of the multinational corporation. The global financing decision is characterized by the uncertain foreign exchange rates and uncertain political conditions of each operating host country. Because of the nature of the uncertainty involved in the decision process, operations research (OR)/management science (MS) models themselves do not always provide satisfactory solutions for the financing problems of an MNC. On the other hand, managerial judgement alone is also inadequate because of the complexity, size of the decision variables, and numerous and often conflicting objectives of global financing strategies. Therefore, the effectiveness of global financing decisions may only be improved by simultaneous use of managerial judgement and a well designed DSS. The proposed DSS can assist financial managers of the MNC in their strategic, financial planning process through broadening the focus of managers and extending limits on managers as information processors. The global financing decision requires three consecutive stages of interactions between managers and the proposed DSS. The first stage is primarily concerned with the adjustments of the cost of capital and the consolidated firm\u27s financial structure (selection of an appropriate adjusted cost of capital). In the second stage, the financing decision process is analyzed to identify and select a best priority structure. In the third and final stage, with the information derived about the fixed cost of financing and priority structure, managers can incorporate their what if types of managerial queries in their decision making process. The DSS allows MNC financial managers to choose an appropriate global financing strategy to satisfy multiple, and often conflicting management goals and to effectively analyze the trade-offs among costs, foreign exchange risks, political risks, and managerial motivation goals
Inter-Organizational Information Systems in the Internet Age
An IOS is an information and management system that transcends organizational boundaries via elec... more An IOS is an information and management system that transcends organizational boundaries via electronic linkages with its trading partners. The electronic linkage is established by information and communication technologies. Extranets1 are the core technology for building IOSs. There are a host of other technologies that serve as the infrastructure for managing IOSs. They include coordination technologies, monitoring technologies, filtering and negotiating technologies (intelligent agents), and decision-making and knowledge-management technologies. In this chapter, a brief overview of each of these technologies is presented.
Psychology is the study of the mental states and processes that give rise to behavior. It seeks t... more Psychology is the study of the mental states and processes that give rise to behavior. It seeks to understand the basic mechanisms and functions of perception, cognition, emotion, and attitudes in guiding behavior. Although it focuses on the level of the individual, individual behavior depends on the social relationships and structures in which people are embedded and the biological systems of which we are comprised. Thus, psychological study encompasses a broad set of topics that overlap with a number of disciplines across the social and biological sciences. The requirements of the major are designed to acquaint students with the research methods psychologists use and to provide a foundation of core knowledge covering the major areas of psychology. This broad foundation allows students to pursue a more advanced understanding of subfields related to their own particular interests and goals for the major. The program may serve as preparation for graduate work in psychology or related fields (e.g., neuroscience, education), as well as for students interested in careers in social work, public policy, business, or medicine. Students are encouraged to become actively engaged in research in the department and should consult with the director of undergraduate research about their interests as early as possible.
This chapter will benefit those who teach individuals using the synchronous virtual classroom (SV... more This chapter will benefit those who teach individuals using the synchronous virtual classroom (SVC). The SVC model will help instructors design online courses that incorporate the factors that students need to be successful. This model will also help virtual classroom instructors and managers develop a systematic way of identifying and addressing the external and internal factors that might impact the success of their instruction. The strategies for empirically researching the SVC, which range from qualitative inquiry to experimental design, are discussed along with practical examples. This information will benefit instructors, researchers, non-profit and profit organizations, and academia.
Decision Sciences Journal of Innovative Education, Apr 1, 2016
ABSTRACTA stream of research over the past decade that identifies predictors of e‐learning succes... more ABSTRACTA stream of research over the past decade that identifies predictors of e‐learning success suggests that there are several critical success factors (CSFs) that must be managed effectively to fully realize promise for e‐learning. Grounded in constructivist learning theories, this study advances previous work on CSFs in university online education. Structural equation modeling is applied to examine the determinants of students’ satisfaction and their perceived learning outcomes in the context of university online courses. The independent variables of motivation (intrinsic and extrinsic), student self‐regulation, dialogue (instructor‐student, and student‐student), instructor, and course design are examined as potential determinants of online learning outcomes. A total of 372 responses from students who have completed at least one online course at a university in the Midwestern United States were used to examine the structural model. Findings indicate that instructor‐student dialogue, student‐student dialogue, instructor, and course design significantly affect students’ satisfaction and learning outcomes. However, both extrinsic student motivation and student self‐regulation have no significant relationship with user satisfaction and learning outcomes. Finally, intrinsic student motivation affects learning outcomes but not user satisfaction. The findings suggest that course design, instructor, and dialogue are the strongest predictors of user satisfaction and learning outcomes.
International Journal of Information Management, 1990
Although group decision making (GDM) is an important research field in social psychology, group d... more Although group decision making (GDM) is an important research field in social psychology, group decision support systems (GDSS) only recently emerged as a field in the decision support systems (DSS) area. This paper analyses the different types of organizational conflict and suggests the use of GDSS as an essential tool for resolving these conflicts. The role of computer-based information systems (CBIS) has evolved from focusing on data (transaction processing systems) and information (management information systems) to focusing on decision (decision support systems) and coordination (distributed decision-making systems). This paper expands the role of GDSS as an essential tool for resolving organizational conflicts. The GDSS must play a role in integrating functional subunits horizontally, and in integrating long-range, medium-range and short-range planning to create a coordinated strategy. Group decision support systems 3~~~~~, L. (1956). The functions of social conflict. New York: The Free Press. "ZELENY, M. (1982). Multiple criteria decision making. New York: McGraw-Hill.
There is nothing novel about the idea of assembling a group to work toward the solution of a spec... more There is nothing novel about the idea of assembling a group to work toward the solution of a specific problem, then dismantling it when the task is completed. We introduce an evolving concept, virtual TFTs (Task Force Teams), as a subset of virtual organization not only to effectively deal with a specific task that cannot be performed either as efficiently or effectively through current organizational structures and policies, but also to overcome the limitations of the traditional TFT. This paper is intended to show both how the virtual TFT is different from the traditional one and how the former can overcome the limitations of the latter.
International Journal of Decision Support System Technology
To increase healthcare quality, early illness prediction helps patients prevent potentially life-... more To increase healthcare quality, early illness prediction helps patients prevent potentially life-threatening health issues before it is too late. Artificial intelligence is a rapidly evolving area, and its applications to diabetes, a worldwide epidemic, have the potential to revolutionize the way diabetes is diagnosed and managed. A total of six supervised machine learning algorithms based on patient data were used and compared to predict the diagnosis of diabetes mellitus. For experiments, the Pima Indians Diabetes Database was used, and their missing values were carefully handled by different techniques. For random train-test splits, the Random Forest classification algorithm achieved an accuracy rate of 92 percent. This model outperforms other state-of-the-art approaches due to the application of a combination of techniques for dealing with missing values (the mixture of imputing missing values techniques) that is proposed. With this approach, the models of this manuscript achiev...
This paper examines the impact of using mobile devices, the pivotal element of a student-centered... more This paper examines the impact of using mobile devices, the pivotal element of a student-centered ecosystem, on the learning process and learning outcomes from a system’s view in which mobile technologies are considered a critical success factor to facilitate the dialogue and self-regulatory learning processes, thereby enhancing e-learning outcomes. We synthesize the disparate literature to develop an elevated model. A total of 323 valid and unduplicated responses from students who have completed at least one online course at a Midwestern university in the U.S. were used to examine the structural model, using SmartPLS v. 3.3.2. The results of this study show that the use of mobile devices positively affects student-instructor and student-student dialogues. It also facilitates the self-regulation process, which in turn positively affects the learning outcomes. Integrating mobile technology enables educational institutions to design and build distance learning systems that allow stude...
2019 IEEE 21st Conference on Business Informatics (CBI)
There are few empirical studies that directly investigate the relationships between mobile device... more There are few empirical studies that directly investigate the relationships between mobile device usage and four constructs (student-student dialogue, student-instructor dialogue, self-regulation, and learning outcomes) in university online education. Structural equation modeling is applied to examine the effects of mobile device usage on students' perceived learning outcomes. A total of 350 valid unduplicated responses from students who have completed at least one online course at a university in the Midwest USA were used to examine the structural model. The results of this study showed that mobile device usage affect student-instructor dialogue positively and facilitate the self-regulation process, which in turn positively affect the learning outcomes.
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