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  • e-book 
    Ethical use of technology in digital learning environments : graduate student perspectives

    Ethical use of technology in digital learning environments : graduate student perspectives

    "This book is the result of a co-design project in a class in the Masters of Education program at the University of Calgary. The course, and the resulting book, focus primarily on the safe and ethical use of technology in digital learning environments. The course was organized according to four topics based on Farrow's (2016) Framework for the Ethics of Open Education and discusses Artificial Intelligence (AI) , social networking services (SNS), 3D printing, resource sharing, adaptive learning systems, STEM, assistive technologies, admissions, and communications. In each of the nine chapters, the authors discuss the connection to the value of technology in education, and practical possibilities of learning technologies for inclusive, participatory, democratic, and pluralistic educational paradigms."--BCcampus website.

    Keywords:
    Educational technology Education -- Philosophy
    Resource Type:
    e-book
     
  • e-book 
    Writing Instruction Tips For Automated Essay Graders: How To Design an Essay for a Non-human Reader

    Writing Instruction Tips For Automated Essay Graders: How To Design an Essay for a Non-human Reader

    As schools, as well as the workplace, become more automated, and remote or distance learning/working becomes the “new normal,” understanding and leveraging artificial intelligence will become a critical skill.

    Keywords:
    Report writing Grading marking (Students) -- Computer programs Textbooks
    Resource Type:
    e-book
     
  • e-book 
    The Crystal Ball Instruction Manual Volume One: Introduction to Data Science

    The Crystal Ball Instruction Manual Volume One: Introduction to Data Science

    A perfect introduction to the exploding field of Data Science for the curious, first-time student. The author brings his trademark conversational tone to the important pillars of the discipline: exploratory data analysis, choices for structuring data, causality, machine learning principles, and introductory Python programming using open-source Jupyter Notebooks. This engaging read will allow any dedicated learner to build the skills necessary to contribute to the Data Science revolution, regardless of background.

    Subjects:
    Computing
    Keywords:
    Data mining Computer science Artificial intelligence Textbooks
    Resource Type:
    e-book