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Intelligence Unleashed: An Argument for AI in Education

Authors:
  • Educate Ventures Research
Intelligence Unleashed:
An Argument for AI in Education
What is AIEd?
Computer systems that
are articially intelligent
interact with the world
using capabilities (such
as speech recognition)
and intelligent behaviours
(such as using available
information to take the
most sensible actions
toward a stated goal)
that we would think of
as essentially human.
At the heart of articial
intelligence in education
is the scientic goal to
make knowledge, which
is often left implicit,
computationally precise
and explicit.
In other words, in addition
to being the engine behind
much ‘smart’ ed tech, AIEd
is designed to open up
the ‘black box of learning,’
giving us more ne-grained
understandings of how
learning actually happens.
Now we can...
Provide one-on-one
tutoring to every
student, in every subject
Provide intelligent
support to learners
working in a group
Create authentic virtual
learning environments
Soon we will...
Develop lifelong
learning companions
powered by AI that can
accompany and support
individual learners
throughout their studies
– in and beyond school
Develop new forms
of assessment that
measure learning while
it is taking place, shaping
the learning experience
in real time
These will help
us with...
Achievement Gaps
Teacher Retention
and Shortage
Ultimately, AIEd tools
will help teachers create
learning environments
that are more ecient,
exible and inclusive than
those currently available.
These tools will help
learners prepare for an
economy that is swiftly
being reshaped by
digital technologies.
www.pearson.com
Join the conversation
@Pearson
#Openideas
#AIEd
Chapter
Full-text available
Advancements in modern technologies have resulted in the integration of artificial intelligence (AI) in the field of education. It is imperative that educators are knowledgeable and skilled with various AI-based tools. However, little is known about the extent of the knowledge and skills of preservice teachers in utilizing AI-based tools in education or about the extent of their ethical considerations when using AI-based tools. Preservice teachers are the vanguard of 21st century teaching and it is important that they have the capacity to incorporate technology into pedagogy. This study employed a descriptive-quantitative correlational approach to determine the extent of knowledge and skills of 212 preservice teachers in using AI-based tools, as well as the extent of the respondents’ ethical considerations in utilizing AI-based tools in education, with the use of the Intelligent-TPACK survey form adapted from Celik (2023). The data gathered were analyzed through descriptive analysis, namely mean, standard deviation and percentage, as well as inferential statistics of Pearson bivariate correlation to determine if there was a significant interrelationship among technological knowledge (TK), technological pedagogical knowledge (TPK), technological content knowledge (TCK) and technological pedagogical and content knowledge (TPACK). The results revealed that preservice teachers possess high levels of TK, TPK, TCK, and TPACK. Furthermore, the participants are capable of skillfully utilizing technology into teaching, which indicates that preservice teachers are up to date with the trends in artificial intelligence. In addition, the participants were revealed to have high levels of ethical consideration in utilizing AI-based tools, where they can discern which tools will be best in improving the students’ works and give fair feedback in assessing the works of the students. Finally, significant interrelationships among TK, TPK, TCK, and TPACK were also found, in which competency in one component also equates to competency in other components.
Book
Full-text available
Over the last ten years learning analytics (LA) has grown from a hypothetical future into a concrete field of inquiry and a global community of researchers and practitioners. Although the LA space may appear sprawling and complex, there are some clear through-lines that the new student or interested practitioner can use as entry points. Four of these are presented in this chapter, 1. LA as a concern or problem to be solved, 2. LA as an opportunity, 3. LA as field of inquiry and 4. the researchers and practitioners that make up the LA community. These four ways of understanding LA and its associated constructs, technologies, domains and history can hopefully provide a launch pad not only for the other chapters in this handbook but the world of LA in general. A world that, although large, is open to all who hold an interest in data and learning and the complexities that follow from the combination of the two.
Conference Paper
Digitalization and the use of computers in the process of education has been in place for years. Recently we have also seen a growing interest of Artificial Intelligence in the education and learning on various fields, like, digital lessons, AI tutoring, AI in testing systems, AI in research, education related task automations and more. Through this research we present the importance of AI in education and learning processes along with challenges that we are facing nowadays during the integration of it in our education systems. In addition to that we also present the importance of AI in research through a proposed model to increase the quality of research and improve the time spend and quality of content used for different research topics. The final outcome of this paper helps us understand the different places where AI can help in the education process, alternatives that we can use for integration of AI in current systems and challenges that we are facing today in terms of resources and infrastructure.
Article
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