|
Showing 1 - 7 of
7 matches in All Departments
As technology continues to advance, it is critical for businesses
to implement systems that can support the transformation of data
into information that is crucial for the success of the company.
Without the integration of data (both structured and unstructured)
mining in business intelligence systems, invaluable knowledge is
lost. However, there are currently many different models and
approaches that must be explored to determine the best method of
integration. Integration Challenges for Analytics, Business
Intelligence, and Data Mining is a relevant academic book that
provides empirical research findings on increasing the
understanding of using data mining in the context of business
intelligence and analytics systems. Covering topics that include
big data, artificial intelligence, and decision making, this book
is an ideal reference source for professionals working in the areas
of data mining, business intelligence, and analytics; data
scientists; IT specialists; managers; researchers; academicians;
practitioners; and graduate students.
The term learning analytics is used in the context of the use of
analytics in e-learning environments. Learning analytics is used to
improve quality. It uses data about students and their activities
to provide better understanding and to improve student learning.
The use of learning management systems, where the activity of the
students can be easily accessed, potentiated the use of learning
analytics to understand their route during the learning process,
help students be aware of their progress, and detect situations
where students can give up the course before its completion, which
is a growing problem in e-learning environments. Advancing the
Power of Learning Analytics and Big Data in Education provides
insights concerning the use of learning analytics, the role and
impact of analytics on education, and how learning analytics are
designed, employed, and assessed. The chapters will discuss factors
affecting learning analytics such as human factors, geographical
factors, technological factors, and ethical and legal factors. This
book is ideal for teachers, administrators, teacher educators,
practitioners, stakeholders, researchers, academicians, and
students interested in the use of big data and learning analytics
for improved student success and educational environments.
As technology continues to advance, it is critical for businesses
to implement systems that can support the transformation of data
into information that is crucial for the success of the company.
Without the integration of data (both structured and unstructured)
mining in business intelligence systems, invaluable knowledge is
lost. However, there are currently many different models and
approaches that must be explored to determine the best method of
integration. Integration Challenges for Analytics, Business
Intelligence, and Data Mining is a relevant academic book that
provides empirical research findings on increasing the
understanding of using data mining in the context of business
intelligence and analytics systems. Covering topics that include
big data, artificial intelligence, and decision making, this book
is an ideal reference source for professionals working in the areas
of data mining, business intelligence, and analytics; data
scientists; IT specialists; managers; researchers; academicians;
practitioners; and graduate students.
The term learning analytics is used in the context of the use of
analytics in e-learning environments. Learning analytics is used to
improve quality. It uses data about students and their activities
to provide better understanding and to improve student learning.
The use of learning management systems, where the activity of the
students can be easily accessed, potentiated the use of learning
analytics to understand their route during the learning process,
help students be aware of their progress, and detect situations
where students can give up the course before its completion, which
is a growing problem in e-learning environments. Advancing the
Power of Learning Analytics and Big Data in Education provides
insights concerning the use of learning analytics, the role and
impact of analytics on education, and how learning analytics are
designed, employed, and assessed. The chapters will discuss factors
affecting learning analytics such as human factors, geographical
factors, technological factors, and ethical and legal factors. This
book is ideal for teachers, administrators, teacher educators,
practitioners, stakeholders, researchers, academicians, and
students interested in the use of big data and learning analytics
for improved student success and educational environments.
E-assessments of students profoundly influence their motivation and
play a key role in the educational process. Adapting assessment
techniques to current technological advancements allows for
effective pedagogical practices, learning processes, and student
engagement. The Handbook of Research on E-Assessment in Higher
Education provides emerging perspectives on the theoretical and
practical aspects of digital assessment techniques and applications
within educational settings. Featuring coverage on a broad range of
topics such as competency assessment, adaptive courseware, and
learning performance, this publication is ideally designed for
educational administrators, educational professionals, teachers and
professors, researchers, and graduate-level students seeking
current research on comparative studies and the pedagogical issues
of online assessment in academic institutions.
Uncovering and analyzing data associated with the current business
environment is essential in maintaining a competitive edge. As
such, making informed decisions based on this data is crucial to
managers across industries. Integration of Data Mining in Business
Intelligence Systems investigates the incorporation of data mining
into business technologies used in the decision making process.
Emphasizing cutting-edge research and relevant concepts in data
discovery and analysis, this book is a comprehensive reference
source for policymakers, academicians, researchers, students,
technology developers, and professionals interested in the
application of data mining techniques and practices in business
information systems.
E-learning plays a significant role in education, and its
importance increases day by day. Learning environments can take a
myriad of distinct forms. Learning management systems (LMS) have
emerged as an important platform to support effective learning
environments. Learning management systems are used throughout
higher education institutions (HEI) and the need to know and
understand its adoption and usage arises. However, there is a lack
of information about how LMS are being used, which are the most
adopted, whether there is a country adoption standard and which
countries use more LMS. Higher Education Institutions and Learning
Management Systems: Adoption and Standardization provides insights
concerning the use of learning management systems in higher
education institutions and aims to increase understanding of LMS
adoption and usage, providing relevant academic work, empirical
research findings and an overview of LMS usage in higher education
institutions all over the world.
|
|