Supporting Adult Learners\u27 Metacognitive Development with a Sociotechnical System

Metacognition is defined as thinking about and reflecting on one\u27s cognitive processes. In learning contexts, strong metacognition leads to retention, academic success, and deep learning. While we know a lot about the metacognition of learners in grades K-12 and college, there are limited studies on adult learners\u27 (24 and older) metacognitive awareness, how to support it, or the role technology can play, particularly since e-learning is quickly becoming the central mode of learning for adult learners. Thus, I have the following motivating research question: How can we support adult learners\u27 metacognitive development in e-learning environments? To better understand adult learners\u27 needs, I conducted a content analysis of adults\u27 learning ePortfolios and surveyed a cross-section of adult learners to determine their metacognitive awareness. Based on those findings and the literature on designing learning technologies for adult learners, I iteratively designed and developed a web-based application with adult learning, social learning, and persuasive design elements. During two sections of an online course, a treatment group used the intervention and a control group did not. Both groups completed a pre-/post-self report of their metacognitive awareness, developed a learning portfolio that was rated by two raters for evidence of metacognition, and participated in interviews. This research shows that (a) adult learners are adept at planning and monitoring their learning but need more support in managing information and evaluating their learning; (b) a web-based intervention with social-persuasive design elements supports adult learners in metacognitive development; and (c) social and persuasive design elements, when aligned with adult learning principles, support adult learners\u27 narrative identity, which I argue is a key factor in supporting their metacognitive development. This research aims to provide designers, educators, and learners with a better understanding of adult learners needs and offers design principles and guidelines for development of sociotechnical systems that can promote their metacognitive development in e-learning environments

The use of computer science practices and methods for developing social simulations to stimulate changes in travellers’ mode choice

In this thesis, Computer Science practices and methods including Software Engineering and Artificial Intelligence techniques are explored to incorporate Human Factors and Psychology knowledge in a structured way into agent-based models to model modal shift in a social system. Observations of peoples’ behaviours in social systems regarding choice-making suggest that they tend to have preferences among the available alternatives in many situations. Experts in the domain of Psychology have been interested in the relationships that exist between the psychological processes (factors) and peoples’ behaviours. Human Factors’ experts are concerned with, among other things, the study of factors and development of tools that improve users’ experiences. The findings from the literature suggest that the two groups have been working from the perspective of their domains without much collaboration. Also, no known framework or methodology offers the required collaborative modelling support and techniques to model people’s emotion as they traverse the system. The aim of this thesis is, therefore, to provide modelling techniques that better support the use of Human Factors and Psychology knowledge in understanding factors that influence travellers’ decision-making in travel mode choice so as to stimulate changes in their behaviours. The support also provides collaboration among relevant stakeholders to work on modal shift project in the transport system. The method adopted in carrying out the research reported in this thesis is informed by the descriptive, developmental, and exploratory nature of the objectives of the research. Our novel methodology which includes a framework is named MOdal SHift (MOSH) methodology. Its development process involves the use of design principles that include encapsulation, data abstraction, inheritance, and polymorphism in defining and integrating the Human Factors and Psychology practices into the methodology. The structures and behaviours of the system components are described and documented using the Unified Modelling Language (UML) as a standard specification language to promote uniform communication among a group of experts. The decision variable decomposition module and techniques for deriving travellers’ emotions that correspond to their context involved the use of the Fuzzy sets system. The methodology contains guides that include the process map diagram showing the major stages in the methodology as well as the step-by-step development guidelines. To verify and to validate the methodology, two case studies in the transport domain are selected. The first case study aims at demonstrating the use of the framework included in the methodology for policy formulation. The second case study has the goal of demonstrating the use of the methodology for understanding individuals’ abilities to satisfy travel requirements. Data Science methods including both supervised and unsupervised learning algorithms are applied at relevant stages of the case studies. The reflection from the cases investigated with the MOSH methodology reveals its novelty in modelling interdependencies among the transport system’s constraints and in modelling travellers’ emotional state as they traverse the transport system’s environment. In addition, the adoption of the standard specification language in the design of the methodology provides the means for easy communication and transfer of knowledge among stakeholders. The use of Software Engineering tools and methods in conjunction with the agent-based modelling paradigm in the MOSH methodology design and development phases promotes the separation of concerns for the interrelated and non-linear levels of organisation within a sociotechnical system. It also promotes extensibility of various aspect of the methodology as a result of the independence among the components and makes reusability of relevant aspects possible when there are needs to use the same functionality in a new project. The agent-based modelling paradigm provides opportunities for investigating the interactions among the agents and the environment as well as providing insights into the various complex interrelated behaviours

The use of computer science practices and methods for developing social simulations to stimulate changes in travellers’ mode choice

In this thesis, Computer Science practices and methods including Software Engineering and Artificial Intelligence techniques are explored to incorporate Human Factors and Psychology knowledge in a structured way into agent-based models to model modal shift in a social system. Observations of peoples’ behaviours in social systems regarding choice-making suggest that they tend to have preferences among the available alternatives in many situations. Experts in the domain of Psychology have been interested in the relationships that exist between the psychological processes (factors) and peoples’ behaviours. Human Factors’ experts are concerned with, among other things, the study of factors and development of tools that improve users’ experiences. The findings from the literature suggest that the two groups have been working from the perspective of their domains without much collaboration. Also, no known framework or methodology offers the required collaborative modelling support and techniques to model people’s emotion as they traverse the system. The aim of this thesis is, therefore, to provide modelling techniques that better support the use of Human Factors and Psychology knowledge in understanding factors that influence travellers’ decision-making in travel mode choice so as to stimulate changes in their behaviours. The support also provides collaboration among relevant stakeholders to work on modal shift project in the transport system. The method adopted in carrying out the research reported in this thesis is informed by the descriptive, developmental, and exploratory nature of the objectives of the research. Our novel methodology which includes a framework is named MOdal SHift (MOSH) methodology. Its development process involves the use of design principles that include encapsulation, data abstraction, inheritance, and polymorphism in defining and integrating the Human Factors and Psychology practices into the methodology. The structures and behaviours of the system components are described and documented using the Unified Modelling Language (UML) as a standard specification language to promote uniform communication among a group of experts. The decision variable decomposition module and techniques for deriving travellers’ emotions that correspond to their context involved the use of the Fuzzy sets system. The methodology contains guides that include the process map diagram showing the major stages in the methodology as well as the step-by-step development guidelines. To verify and to validate the methodology, two case studies in the transport domain are selected. The first case study aims at demonstrating the use of the framework included in the methodology for policy formulation. The second case study has the goal of demonstrating the use of the methodology for understanding individuals’ abilities to satisfy travel requirements. Data Science methods including both supervised and unsupervised learning algorithms are applied at relevant stages of the case studies. The reflection from the cases investigated with the MOSH methodology reveals its novelty in modelling interdependencies among the transport system’s constraints and in modelling travellers’ emotional state as they traverse the transport system’s environment. In addition, the adoption of the standard specification language in the design of the methodology provides the means for easy communication and transfer of knowledge among stakeholders. The use of Software Engineering tools and methods in conjunction with the agent-based modelling paradigm in the MOSH methodology design and development phases promotes the separation of concerns for the interrelated and non-linear levels of organisation within a sociotechnical system. It also promotes extensibility of various aspect of the methodology as a result of the independence among the components and makes reusability of relevant aspects possible when there are needs to use the same functionality in a new project. The agent-based modelling paradigm provides opportunities for investigating the interactions among the agents and the environment as well as providing insights into the various complex interrelated behaviours