|
HOME
Sign up
for Collaboration Newsbytes
Read
past issues of Newsbytes
Get involved!
Contact Us
ABOUT US
Mission
Staff
Board of Directors
Current Members
Become a Member
Map
and Directions
PROGRAMS &
SERVICES
Conferences
Traveling Workshops
Institute
for Academic Innovation
Program Consulting & Evaluation Services
MEMBER RESOURCES
Newsletter
Members' Hotline
Teachers' Resources
Travel Grants
PRODUCTS
Newsletter
Videos
Casebook
LINKS
|
|

|
Collaboration Resources for
College and University
Teachers
Deep Learning
College faculty and administrators
are often keenly aware that what we want students to learn (how to
think critically about important ideas, how to form meaningful connections
between and among disparate pieces of information, how to communicate orally
and in writing, etc.) often doesn’t match what they actually do
learn (separate bits of data, often memorized for a test and forgotten soon
thereafter).
The literature on “deep
learning” helps shed light on this dilemma. The mismatch occurs, in
part, as a result of a student’s approach to learning. As Ramsden (1992) puts it: “What students learn
is…closely associated with how they go about learning it.”
Two Contrasting Approaches to Learning:
Shallow vs. Deep
- Shallow learning: The learner is largely
passive, receiving information uncritically and in isolated bits of
data, seeking to memorize facts and ideas in order to reproduce them for
a test. Course content is often seen as a hurdle to overcome, merely
something to learn in order to attain the desired grade. This approach
to learning can be described as “quantity without quality.”
- Deep learning: The learner is active,
examining ideas critically, seeking to make sense of new information and
working to link ideas with each other, with larger concepts, and with
life outside the classroom. Rather than focusing on memorization in
order to attain a grade, the deep learner seeks to understand and takes
a holistic approach to the various new facts and ideas he or she
encounters. This approach to learning can be described as
“quantity and quality.”
How Can We Foster Deep Learning?►
|
|