Debbie Richards – författare

Augmented reality is a powerful tool that can help organizations achieve learning goals, but there are also a lot of misconceptions surrounding what it really is. In “Seeing the Possibilities With Augmented Reality,” Debbie Richards clarifies these misunderstandings. Further, in this issue of TD at Work, Richards:· details what AR is, what it can do, and when it is appropriate to use· provides a step-by-step process for designing successful AR learning· introduces the ADDEDD model, which is akin to ADDIE for AR· reviews tools and applications to consider· showcases how various industries currently use AR.

The study reported in this paper is an ongoing effort. We reported a preliminary analysis of the data in the paper. The current experiments varied the subjects to c- duct online group learning activities by the communication media such as email and threaded discussion. Although, we could have easily learned the impact of mobile devices in learning if we divided the subjects to use different hardware such as p- sonal computers, personal digital assistant, or mobile phones, we believe our findings will still be able to provide useful insights on the difficulties that the mobile learners will face in solving problems as a group. Our analysis result will also provide ba- line information on whether the traits of the successful or failed online groups are applicable to the mobile learners. For example, we expect the SMS will be a better medium to overcome the major problem of instant communication or the rapid propagation of the information as the mobile phones have built-in mechanism to remind the users of the incoming new messages and also the mobile phone users are expected to be interrupted for the incoming messages. However, we need further investigation of other problems, which hinder the optimum online group work. For example, ‘accuracy of the transferred information’ was identified as one of the pr- lems of using emails as the communication medium. Personal Digital Assistant (PDA) or SMS are more apt to deliver shorter messages than the typical emails.

The study reported in this paper is an ongoing effort. We reported a preliminary analysis of the data in the paper. The current experiments varied the subjects to c- duct online group learning activities by the communication media such as email and threaded discussion. Although, we could have easily learned the impact of mobile devices in learning if we divided the subjects to use different hardware such as p- sonal computers, personal digital assistant, or mobile phones, we believe our findings will still be able to provide useful insights on the difficulties that the mobile learners will face in solving problems as a group. Our analysis result will also provide ba- line information on whether the traits of the successful or failed online groups are applicable to the mobile learners. For example, we expect the SMS will be a better medium to overcome the major problem of instant communication or the rapid propagation of the information as the mobile phones have built-in mechanism to remind the users of the incoming new messages and also the mobile phone users are expected to be interrupted for the incoming messages. However, we need further investigation of other problems, which hinder the optimum online group work. For example, ‘accuracy of the transferred information’ was identified as one of the pr- lems of using emails as the communication medium. Personal Digital Assistant (PDA) or SMS are more apt to deliver shorter messages than the typical emails.

Since knowledge was recognized as a crucial part of intelligent systems in the 1970s and early 1980s, the problem of the systematic and efficient acquisition of knowledge was an important research problem. In the early days of expert systems, the focus of knowledge acquisition was to design a suitable knowledge base for the problem - main by eliciting the knowledge from available experts before the system was c- pleted and deployed. Over the years, alternative approaches were developed, such as incremental approaches which would build a provisional knowledge base initially and would improve the knowledge base while the system was used in practice. Other approaches sought to build knowledge bases fully automatically by employing machine-learning methods. In recent years, a significant interest developed regarding the problem of constructing ontologies. Of particular interest have been ontologies that could be re-used in a number of ways and could possibly be shared across diff- ent users as well as domains. The Pacific Knowledge Acquisition Workshops (PKAW) have a long tradition in providing a forum for researchers to exchange the latest ideas on the topic. Parti- pants come from all over the world but with a focus on the Pacific Rim region. PKAW is one of three international knowledge acquisition workshop series held in the Pacific-Rim, Canada and Europe over the last two decades. The previous Pacific Knowledge Acquisition Workshop, PKAW 2004, had a strong emphasis on inc- mental knowledge acquisition, machine learning, neural networks and data mining.

Since knowledge was recognized as a crucial part of intelligent systems in the 1970s and early 1980s, the problem of the systematic and efficient acquisition of knowledge was an important research problem. In the early days of expert systems, the focus of knowledge acquisition was to design a suitable knowledge base for the problem - main by eliciting the knowledge from available experts before the system was c- pleted and deployed. Over the years, alternative approaches were developed, such as incremental approaches which would build a provisional knowledge base initially and would improve the knowledge base while the system was used in practice. Other approaches sought to build knowledge bases fully automatically by employing machine-learning methods. In recent years, a significant interest developed regarding the problem of constructing ontologies. Of particular interest have been ontologies that could be re-used in a number of ways and could possibly be shared across diff- ent users as well as domains. The Pacific Knowledge Acquisition Workshops (PKAW) have a long tradition in providing a forum for researchers to exchange the latest ideas on the topic. Parti- pants come from all over the world but with a focus on the Pacific Rim region. PKAW is one of three international knowledge acquisition workshop series held in the Pacific-Rim, Canada and Europe over the last two decades. The previous Pacific Knowledge Acquisition Workshop, PKAW 2004, had a strong emphasis on inc- mental knowledge acquisition, machine learning, neural networks and data mining.

This book constitutes the thoroughly refereed post-workshop proceedings of the 2008 Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, held in Hanoi, Vietnam, in December 2008 as part of 10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008. The 20 revised papers presented were carefully reviewed and selected from 57 submissions and went through two rounds of reviewing and improvement. The papers are organized in topical sections on machine learning and data mining, incremental knowledge acquisition, web-based techniques and applications, as well as domain specific knowledge acquisition methods and applications.

This book constitutes the thoroughly refereed post-workshop proceedings of the 2008 Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, held in Hanoi, Vietnam, in December 2008 as part of 10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008. The 20 revised papers presented were carefully reviewed and selected from 57 submissions and went through two rounds of reviewing and improvement. The papers are organized in topical sections on machine learning and data mining, incremental knowledge acquisition, web-based techniques and applications, as well as domain specific knowledge acquisition methods and applications.

th The 11 International Workshop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010) has provided a forum for the past two decades for researchers and practitioners working in the area of machine intelligence. PKAW covers a spectrum of techniques and approaches to implement smartness in IT applications. As evidenced in the papers in this volume, machine intelligence solutions incorporate many areas of AI such as ontological engineering, agent-based techn- ogy, robotics, image recognition and the Semantic Web as well as many other fields of computing such as software engineering, security, databases, the Internet, information retrieval, language technology and game technology. PKAW has evolved to embrace and foster advances in theory, practice and te- nology not only in knowledge acquisition and capture but all aspects of knowledge management including reuse, sharing, maintenance, transfer, merging, reconciliation, creation and dissemination. As many nations strive to be knowledge economies and organizations seek to maximize their knowledge assets and usage, solutions to handle the complex task of knowledge management are more important than ever. This v- ume contributes towards this goal. This volume seeks to disseminate the latest solutions from the International Wo- shop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010) held in Daegu, Korea during August 30–31, 2010 in conjunction with the Pacific Rim International Conference on Artificial Intelligence (PRICAI 2010).

th The 11 International Workshop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010) has provided a forum for the past two decades for researchers and practitioners working in the area of machine intelligence. PKAW covers a spectrum of techniques and approaches to implement smartness in IT applications. As evidenced in the papers in this volume, machine intelligence solutions incorporate many areas of AI such as ontological engineering, agent-based techn- ogy, robotics, image recognition and the Semantic Web as well as many other fields of computing such as software engineering, security, databases, the Internet, information retrieval, language technology and game technology. PKAW has evolved to embrace and foster advances in theory, practice and te- nology not only in knowledge acquisition and capture but all aspects of knowledge management including reuse, sharing, maintenance, transfer, merging, reconciliation, creation and dissemination. As many nations strive to be knowledge economies and organizations seek to maximize their knowledge assets and usage, solutions to handle the complex task of knowledge management are more important than ever. This v- ume contributes towards this goal. This volume seeks to disseminate the latest solutions from the International Wo- shop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010) held in Daegu, Korea during August 30–31, 2010 in conjunction with the Pacific Rim International Conference on Artificial Intelligence (PRICAI 2010).