BREAKOUT SESSION #3: ADAPTIVE
LEARNING: EARLY IMPLEMENTATION
MODELS AND SUCCESSES
Rebecca Orr, Ph.D.
Professor of Biology, Collin College
Background Information
• Professor of Biology at Collin College in Plano,
Texas
• Two year public college, three campuses serving
approximately 27,000 credit students
• Total enrollment in Biology 1406 is ≈2000/year
• Most of my students’ goals:
• Nursing/Dental Hygiene/Surgery
Technology/etc.
• Transfer to a university
No two students are identical — they learn and forget at
different rates, come from different educational
backgrounds, and have different intellectual capabilities,
attention spans, and modes of learning. As a result,
designing a real-time recommendation engine that is
sensitive to the characteristics of each student is an
immensely complex task.
http://www.knewton.com/assets-v2/downloads/knewton-adaptive-learning-intro.pdf
My Implementation of Adaptive Follow-Up:
Summer 2013
• No Adaptive Follow-Up was offered during first two
exam periods.
• Exam 1 & 2 scores were averaged and utilized to compare
student ability of Spring and Summer student cohorts.
• Adaptive Follow-Up was offered for second two exam
periods and was made “optional.”
• Two sets of items were selected for Follow-Up.
• Follow-Up was due two days after parent assignment.
• Test-out option was allowed and set at 95%.
• Value was set as “extra credit” and added to homework
component of the lecture grade.
Adaptive Follow-up in Mastering
• “Parent” Assignment created
• Item selection, difficulty, and estimated time for completion is
instructor directed
• Adaptive Follow-Up is enabled for selected “parent”
assignments
• Time spent in follow-up and number of problem sets issued is
instructor directed
• Knewton engine creates Adaptive Follow-Up sets for the
student using IRT based engine
• Items selected are individual to the student, based on:
• Demonstrated proficiencies and lack of proficiencies in current and
previous assignments
• Content prerequisites necessary for future, scheduled assignments
Does Adding Adaptive Follow-Up
Increase Student Success on Exams?
Student Participation in Adaptive Follow-Up:
Summer 2013
• Almost 92% of students either tested out of or
actively worked on the first Adaptive Follow-Up
assignment.
• Average participation rates observed over the course
of Adaptive Follow-Up offerings were:
• 16.7% tested out of Adaptive Follow-Up by scoring 95% or
better on the parent assignment.
• 58.1% chose to actively work on the Adaptive Follow-Up sets
after completing the parent assignment.
• 25.2% did not participate in Adaptive Follow-up.
Addition of Adaptive Follow-up Increased Exam
Averages: Summer 2013 (error bars- standard error)
85
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
0
Spring 2013:
No Adaptive
Follow-up for
Exam 3 & 4,
n=121
Summer 2013:
With Adaptive
Follow-up for
Exam 3 & 4,
n=37
Exam 1&2
Exam 3
Exam 4
Student Feedback on Adaptive Follow-Up
• “I really like how it [Adaptive Follow-Up] takes me
back to the basics so I know where I need to study to
build my strengths.”
• “I originally thought that the Adaptive Follow-Up
assignments were going to be a waste of time, but it
actually is more of a benefit.”
• “It was helpful, plus I felt confident when taking the
test.”
Interesting Effect of Adaptive Follow-Up
• Students reported putting more effort into the
Mastering parent homework:
“…Adaptive Follow-Up questions served as
motivation to learn the material better…I really
think it's just the idea of "testing out" of something
that makes me feel smarter and encourages me
to get a better grade on the [Mastering parent]
homework.
Conclusions
• Adaptive Follow-Up provides individualized
recommendations to increase student proficiency in
content.
• Adaptive Follow-Up is based on demonstrated
understanding of topics as well as the content graphed as
prerequisite for success of future assignments.
• Adaptive Follow-Up may increase student success.
• Effect of Adaptive Follow-up on student success is being
examined this semester implementing required
completion of Adaptive Follow-ups and using a larger
sample size.
Questions?
• Please feel free to email me at dr_orr@att.net