Socrates Digital for learning and problem solving [electronic resource] / by Mark Salisbury.
- 作者： Salisbury, Mark, 1955-
- 出版： Hershey PA : Engineering Science Reference 2021
- 主題： Expert systems (Computer science) , Problem solving--Data processing. , Knowledge, Theory of--Data processing. , Questioning--Data processing.
- ISBN： 9781799879572 (ebk.) 、 9781799879558 (hbk.) 、 9781799879565 (pbk.)
- URL：
點擊此處查看電子書
點擊此處查看電子書
- 一般註：Includes bibliographical references and index. A data-driven world : the opportunity and challenge for human learning and problem-solving -- Problem-solving with data and information : accelerating learning with technology -- Critical thinking and the Socratic method : automating Socratic questioning for problem-solving -- A dialog with Socrates digital : Socratic problem-solving for investment opportunities -- System design and development : understand, explore, materialize, and realize -- Socrates digital system architecture : overview of the Socrates digital module -- Problem definition : specifying the problem and solution requirements -- Information, assumptions, & concepts : forming the basis for conclusions -- Conclusions, implications, & viewpoints : creating a point of view for solving a problem -- Dialog development manager : managing the system design and development process -- Problem-solving manager : creating an innovative learning organization -- The road ahead : enhancing Socrates digital. 111年度臺灣學術電子書暨資料庫聯盟採購
-
讀者標籤：
- 系統號： 000299006 | 機讀編目格式
館藏資訊
There is a tremendous need for computer scientists, data scientists, and software developers to learn how to develop Socratic problem-solving applications. While the amount of data and information processing has been accelerating, our ability to learn and problem-solve with that data has fallen behind. Meanwhile, problems have become too complex to solve in the workplace without a concerted effort to follow a problem-solving process. This problem-solving process must be able to deal with big and disparate data. Furthermore, it must solve problems that do not have a “rule” to apply in solving them. Moreover, it must deal with ambiguity and help humans use informed judgment to build on previous steps and create new understanding. Computer-based Socratic problem-solving systems answer this need for a problem-solving process using big and disparate data. Furthermore, computer scientists, data scientists, and software developers need the knowledge to develop these systems. Socrates Digital™ for Learning and Problem Solving presents the rationale for developing a Socratic problem-solving application. It describes how a computer-based Socratic problem-solving system called Socrates Digital™ can keep problem-solvers on track, document the outcome of a problem-solving session, and share those results with problem-solvers and larger audiences. In addition, Socrates Digital™ assists problem-solvers in combining evidence about their quality of reasoning for individual problem-solving steps and their overall confidence in the solution. Socrates Digital™ also captures, manages, and distributes this knowledge across organizations to improve problem-solving. This book also presents how to build a Socrates Digital™ system by detailing the four phases of design and development: understand, explore, materialize, and realize. The details include flow charts and pseudo-code for readers to implement Socrates Digital™ in a general-purpose programming language. The completion of the design and development process results in a Socrates Digital™ system that leverages artificial intelligence services from providers that include Apple, Microsoft, Google, IBM, and Amazon. In addition, an appendix provides a demonstration of a no-code implementation of Socrates Digital™ in Microsoft Power Virtual Agent.
摘要註
"Readers of this book will learn how to build intelligent digital advisors that discern and provide the knowledge human users seek in fulfilling their responsibilities in the workplace through the aid of a new knowledge representation, called expert advice, that builds upon research in artificial intelligence, instructional design, cognitive psychology, and the learning sciences"--