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This work describes the application of management theories in STEM
(Science, Technology, Engineering and Mathematics) education
systems. Two chapters examine STEM education on the K-12 national
level and one chapter focuses on the higher education institutional
level. All chapters are based on comprehensive research. Thus, it
will appeal to teachers, school principals, researchers, graduate
students, government policymakers, and all practitioners who care
about STEM education in schools, academia and government. In each
chapter, SWOT (Strengths, Weaknesses, Opportunities, and Threats)
analysis is used as a managerial strategic tool for the examination
of factors that focus either on internal circumstances (strengths
and weaknesses), or external ones (opportunities and threats).
This work illustrates how risk management can be applied to
educational systems in general, and STEM (Science, Technology,
Engineering and Mathematics) education in particular. The rationale
for this approach stems from the increased awareness of the
importance and contribution of STEM education to nations' economic
growth and development. The coverage begins with the challenges of
STEM education systems, and concludes with a thorough strategic
risk response plan. The text outlines a risk-management
plan/program for STEM education in Israel, based on the conceptions
of five stakeholders groups: educators, academics, industry
professionals, military and philanthropic actors. All of whom have
expressed interest in promoting STEM education in the high
school/secondary education system. The result, ultimately, presents
an impressive, meaningful, and practical understanding of the
difficulties and challenges, together with applicable modes of
action, and a new horizon towards which STEM Education should
march.
This Brief presents a new model for business development-MERge-to
be implemented in practitioners' professional development in
general and in the context of STEM (Science, Technology,
Engineering and Mathematics) initiatives, particularly, in
industry, educational institutions and public sector organizations.
The authors aim to contribute to the field of innovation and
entrepreneurship by merging and consolidating different
methodologies and insights borrowed from the "meta-professions"
(referring to skills that can be expressed meaningfully after one
has gained disciplinary and professional knowledge) of management,
education, and research. Targeting three key groups-practitioners
in industry, academic institutions and public sector
organizations-this model proposes that all practitioners can
further develop their unique expertise, as well as new skills,
while acknowledging and applying the three meta-professions in
their initiatives, on-going work and personal lives. The authors
acknowledge that in the postmodern era, where barriers between
disciplines are falling in every aspect of professional life,
managerial, educational and research skills are becoming
increasingly essential and interdependent. Featuring case studies
that illustrate how the MERge model is implemented in practice,
this volume presents practical tools for integrating these key
skills in a wide variety of initiatives in business, teaching and
research contexts.
The message conveyed in this work is that agility can be
implemented anywhere. Accordingly, ten guidelines are presented for
the adoption of agility to enable us to cope with changes in our
lives, in our teams, and in our organizations. Since the authors
advocate agility, the content is presented in the form of concise
standalone chapters, allowing the reader to focus on the specific
topic they wish to adopt in order to become agile.
This guide presents both a conceptual framework and detailed
implementation guidelines for general computer science (CS)
teaching. The content is clearly written and structured to be
applicable to all levels of CS education and for any teaching
organization, without limiting its focus to instruction for any
specific curriculum, programming language or paradigm. Features:
presents an overview of research in CS education; examines
strategies for teaching problem-solving, evaluating pupils, and for
dealing with pupils' misunderstandings; provides learning
activities throughout the book; proposes active-learning-based
classroom teaching methods, as well as methods specifically for
lab-based teaching; discusses various types of questions that a CS
instructor, tutor, or trainer can use for a range of different
teaching situations; investigates thoroughly issues of lesson
planning and course design; describes frameworks by which
prospective CS teachers gain their first teaching experience.
Data science is a new field that touches on almost every domain of
our lives, and thus it is taught in a variety of environments.
Accordingly, the book is suitable for teachers and lecturers in all
educational frameworks: K-12, academia and industry. This book aims
at closing a significant gap in the literature on
the pedagogy of data science. While there are many
articles and white papers dealing with the curriculum of data
science (i.e., what to teach?), the pedagogical aspect of the field
(i.e., how to teach?) is almost neglected. At the same time, the
importance of the pedagogical aspects of data science increases as
more and more programs are currently open to a variety of people.
This book provides a variety of pedagogical discussions and
specific teaching methods and frameworks, as well as includes
exercises, and guidelines related to many data science concepts
(e.g., data thinking and the data science workflow), main machine
learning algorithms and concepts (e.g., KNN, SVM, Neural Networks,
performance metrics, confusion matrix, and biases) and data science
professional topics (e.g., ethics, skills and research approach).
Professor Orit Hazzan is a faculty member at the
Technion’s Department of Education in Science and Technology
since October 2000. Her research focuses on computer science,
software engineering and data science education. Within this
framework, she studies the cognitive and social processes on the
individual, the team and the organization levels, in all kinds of
organizations. Dr. Koby Mike is a Ph.D. graduate from
the Technion's Department of Education in Science and Technology
under the supervision of Professor Orit Hazzan. He continued his
post-doc research on data science education at the Bar-Ilan
University, and obtained a B.Sc. and an M.Sc. in Electrical
Engineering from Tel Aviv University.
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Agile Processes in Software Engineering and Extreme Programming - 12th International Conference, XP 2011, Madrid, Spain, May 10-13, 2011, Proceedings (Paperback, 2011)
Alberto Sillitti, Orit Hazzan, Emily Bache, Xavier Albaladejo
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R1,574
Discovery Miles 15 740
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Ships in 10 - 15 working days
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This book contains the refereed proceedings of the 12th
International Conference on Agile Software Development, XP 2011,
held in Madrid, Spain, in May 2011.The year 2011 marked the 10th
anniversary of the Agile Manifesto. In this spirit, the XP
conference continued its fine tradition of promoting agility by
disseminating new research results in a timely manner and by
bringing together researchers and practitioners for a fruitful
mutual exchange of experiences. As introduced for XP 2010, there
were again two different program committees, one for research
papers and one for experience reports. Regarding the research
papers, 11 out of 56 submissions were accepted as full papers; and
as far as the experience reports were concerned, the respective
number was 4 out of 17 submissions. In addition to these papers,
this volume also includes the short research papers, the abstracts
of the posters, the position papers of the PhD symposium, and the
abstracts of the workshops.
This concise yet thorough textbook presents an active-learning
model for the teaching of computer science. Offering both a
conceptual framework and detailed implementation guidelines, the
work is designed to support a Methods of Teaching Computer Science
(MTCS) course, but may be applied to the teaching of any area of
computer science at any level, from elementary school to
university. This text is not limited to any specific curriculum or
programming language, but instead suggests various options for
lesson and syllabus organization. Fully updated and revised, the
third edition features more than 40 new activities, bringing the
total to more than 150, together with new chapters on computational
thinking, data science, and soft concepts and soft skills. This
edition also introduces new conceptual frameworks for teaching such
as the MERge model, and new formats for the professional
development of computer science educators. Topics and features:
includes an extensive set of activities, to further support the
pedagogical principles outlined in each chapter; discusses
educational approaches to computational thinking, how to address
soft concepts and skills in a MTCS course, and the pedagogy of data
science (NEW); focuses on teaching methods, lab-based teaching, and
research in computer science education, as well as on
problem-solving strategies; examines how to recognize and address
learners' misconceptions, and the different types of questions
teachers can use to vary their teaching methods; provides coverage
of assessment, teaching planning, and designing a MTCS course;
reviews high school teacher preparation programs, and how
prospective teachers can gain experience in teaching computer
science. This easy-to-follow textbook and teaching guide will prove
invaluable to computer science educators within all frameworks,
including university instructors and high school teachers, as well
as to instructors of computer science teacher preparation programs.
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