Jan 27, 2023
LIS 260 - Learning in the Information Age 3 Credits, 3 Contact Hours
3 lecture periods 0 lab periods
Study of how digital technologies are changing how people learn. Includes an examination of how technology-based learning supports new approaches to assessment, how theories of learning are being developed to support research in these emerging areas, and how research on human learning is informing the design of computers that learn.
Course Learning Outcomes
- Compare and contrast the advances of Machine Learning to human learning.
- Explore the impact Machine Learning is having on our society.
- Discuss how social media, Machine algorithms, and various other technological tools are impacting the way we learn.
- Generate a more modern and fluid definition of technological learning to align with our current teaching and learning experiences, both within personal, academic, and workplace environments.
- Define traditional learning theories (Behavioral, Cognitive, and Constructivist) of the 20th and 21st Centuries within traditional school settings.
- Compare and contrast these traditional learning theories to distant learning theories (online learning).
- Explore how the integration of technology can impact your own learning.
- Examine the impact modern technology has had on generations born before 1980.
- Learning Theory
- 20th and 21st century learning theories.
- Teaching–Learning Process.
- Use of technologies to enhance pedagogical practices.
- Social, economic, and technical barriers.
- How Technology has Impacted How We Learn and Teach
- Experiential Learning.
- Using technology to motivate and engage learners.
- How technology is changing our brain structures.
- Online teaching and learning.
- Artificial Intelligence (Machine Learning)
- Introduction to Machine Learning.
- Automation and minimal human interaction (pros/cons).
- Comparing Machine Learning to Human Learning.
- Will machines take over?
- Ethical and Moral considerations.
- Where Are We and How Do We Move Forward?
- Facebook and Popular Platforms Debacle.
- Ethical Issues.
- More of AI and Machine Learning.
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