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Chapter 9 closes the loop with Chapter 2 to demonstrate the methods and techniques that can achieve the goals and objectives presented in Chapter 2. The attributes of the total system are summarized and supported with research that has examined its effectiveness in real-world applications. The attributes of the learning engagement, experience, and environment are discussed and supported with available practical and action research. As in the construction of cognition, this chapter is constructed in a matrixed model where the interactions across categories are explicit from multiple perspectives, which reveals the interactions across the categories of content.

Contends that effective e‐learning requires that the education content be written and delivered very differently than in the past. Proposes to cut through the complexity associated with adopting an e‐learning approach by highlighting 13 key questions that need to be asked in assessing the strengths, weaknesses, and applicability of different e‐learning offerings. Asserts that when properly answered, the 13 questions provide a solid basis for evaluating on‐line learning and education products, and for positioning a company’s approach to e‐learning with an eye on the future instead of the past. Includes definitions that illustrate how e‐learning products are evolving.

Chapter 2 discusses the relevance and potential benefits of the text to the realities of learning system design and configuration. The chapter is presented as an argument in support of the relevance of the work and its perspective on learning. It presents a continuous flow (implicate order), which reflects the structure of the discipline (argumentation). The three-part model of collection, discrimination, and integration into practice is configured into a continuous flow in the argument. This chapter creates interest and expectations in the subsequent discussions, which are reexamined in Chapter 9 to connect expectations with outcomes for the work.

Creating a BIM-enabled learning space that spans both higher education and industry offers the possibility of immersive and integrated learning on the basis of real, up-to-date project data for a new generation of students who will be “BIM natives” and can “think in BIM”. This paper aims to elaborate the concept of BIM as a learning environment so that it can be produced for Architecture Engineering Construction (AEC) educational purposes.

The complementary theoretical lenses of Experiential Learning, Structuration Theory and Systems Theory are adopted for conceptualising a BIM-enabled Learning Environment (BLE).

The BLE is proposed in the form of a social system embedded within both the education system and the industry system. The BLE is described in terms of its structures and component subsystems, inputs, outputs and flows at different scales.

In this initial paper, the BLE is merely outlined and its constituent structures alluded to. Further investigation is required to fully detail the BLE.

By describing the identified structures in still more detail, the BLE can be understood to the extent that it can be reproduced in practice for actual learning. This is the goal and expectation going forward.

The derived BLE is described in social terms and this reflects the centrality of social activity to both building and learning. Technology, processes and traditional industry roles are subordinated into supporting functions. This potentially offers opportunities for learners to reflect on all of these and to consider ways of improving them.

Chapter 6 synthesizes the psychophysics of sensation into a plausible model for the design and configuration of the learning engagement dimension of a learning system. In sensation, the task is to collect and review stochastic information collected from an external stimulus. In learning systems design, the task is the opposite: to design learning objects and activities that communicate the intended learning to the learner effectively and efficiently. The sensation systems focus their attention on the structure of the stimulus. Likewise, a psychophysical learning system emphasizes the interconnections within categories of content to configure the learning experiences. The curriculum embeds this information into a learning plan.

Students of organizations are beginning to recognize the importance of continuous learning in organizations, but to date the concept is not well understood, particularly in terms of how the learning of individuals is related to the learning that takes place in groups, which is related to the learning that occurs in organizations (and all other combinations). To further our understanding, we offer the idea of continuous learning in organizations from a living system's perspective. We view individuals, groups, and organizations as living systems nested in a hierarchy. We propose that living systems can learn in three ways: they can adapt, they can generate, and they can transform. Learning triggers from the environment spark learning, and this relationship is moderated by the system's readiness to learn. Readiness to learn is a function of the permeability of the system's boundaries, the system's stage of development, and the system's meta-systems perspective. Additional research questions are presented to explore learning flow between levels and to determine how the match between one system's pressure for change and another system's readiness to learn affects the emergence of adaptive, generative, and transformative learning. In addition, research questions are offered as a means to test these ideas and build grounded theory. Finally, using this model, the chapter presents three case studies and suggests diagnostic questions to analyze and facilitate continuous learning from a multi-level perspective.

In this response to Day and Tate (this volume) and Markham, Groesbeck, and Swan (this volume), we clarify the concept of continuous learning from a living system's perspective and address the evolution of adaptive, generative, and transformative learning. Further, we assert that a system's drive for homeostasis is actually a fluid, continuous learning process that may vary in the rate and direction of change. Environmental triggers, readiness for learning, and feedback provide leverage points for change and learning within and across individual, group, and organizational systems. Future research is needed to identify and study the effects of these leverage points on systems’ adaptive, generative, and transformative learning.

Chapter 7 synthesizes the perception research into plausible design and configuration strategies for the learning experience dimension of a psychophysical learning system. The processes used in all five senses to reduce information into a perception are again used to create learning activities and processes, which facilitate the learning and discriminate meaning from the learning objects and activities. This process attends to the interactions across the categories of content to determine the critical components of the discipline to include in the learning experience. Once again, the focus of the psychophysical learning experience is placed on the structure of the (external) discipline, which is used to configure the learning experiences.

Establishes our perspective for shared organizational learning processes, cycles, and systems. These learning phenomena are usually tacit, i.e. the organization is only dimly aware of them. These tacit phenomena drive both decision and action and, because they are tacit, they are self‐organizing and are normally not analysed. In order to develop effective learning systems, the organization must explicitly articulate and design these learning processes, cycles, and systems. The “learning unit” is introduced as the essential element where learning development must focus for improved organizational performance. Begins to develop the implications of this perspective for organization theory, organizational practice, and the art of management. Organizational learning can drive organizational transformation if these phenomena are properly planned, designed, and facilitated.

This paper aims to present a comprehensive overview of the patterns and trends of publications on artificial intelligence (AI) in personalised learning. It addresses the need to investigate the intellectual structure and development of this area in view of the growing amount of related research and practices.

A bibliometric analysis was conducted to cover publications on AI in personalised learning published from 2000 to 2022, including a total of 1,005 publications collected from the Web of Science and Scopus. The patterns and trends in terms of sources of publications, intellectual structure and major topics were analysed.

Research on AI in personalised learning has been widely published in various sources. The intellectual bases of related work were mostly on studies on the application of AI technologies in education and personalised learning. The relevant research covered mainly AI technologies and techniques, as well as the design and development of AI systems to support personalised learning. The emerging topics have addressed areas such as big data, learning analytics and deep learning.

This study depicted the research hotspots of personalisation in learning with the support of AI and illustrated the evolution and emerging trends in the field. The results highlight its latest developments and the need for future work on diverse means to support personalised learning with AI, the pedagogical issues, as well as teachers’ roles and teaching strategies.