Transcript A Melding of Educational Strategies to Enhance the Introductory Programming Course

A Melding of
Educational Strategies to
Enhance the Introductory
Programming Course
Leo F. Denton, Dawn McKinney,
and Michael V. Doran
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
CS1 Course:
Introduction to Programming
and Problem Solving Concepts
Course format
 4 credit hours
 15 week semester
 One 75-minute and
three 50-minute
sessions (or three 75
minute sessions)
 Integrated lecture and
laboratory
FIE 2005
Indianapolis, Indiana
Topics
 Problem solving
strategies
 Programming concepts
 Internal representations
of data
 Control structures
 Use of IDE
 Methods
 Arrays
 OOP basics.
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Paper
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View of several techniques
described and studied
separately in prior papers
Principal elements
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Cognitive course framework
Motivational strategies
Affective objectives
Adjusting course content for novice learners
Refining and organizing course content
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Denton, L. F. and McKinney, D. “Affective Factors and Student
Achievement: A Quantitative and Qualitative Study,” 34th
ASEE/IEEE Frontiers in Education Conference, Savannah, GA,
October 20 – 23, 2004.
Denton, L. F., D. McKinney, and M. V. Doran. “Promoting Student
Achievement With Integrated Affective Objectives,” American
Society for Engineering Education Annual Conference &
Exposition, Nashville, Tennessee, USA, 2003.
Denton, L. F., M. V. Doran, and D. McKinney. “Integrated Use of
Bloom and Maslow for Instructional Success in Technical and
Scientific Fields,” in the Proceedings of the 2002 American Society
for Engineering Education Annual Conference & Exposition,
Montreal, Canada, 2002.
Doran, M. V. and D. D. Langan. “A Cognitive-Based Approach to
Introductory Computer Science Courses: Lessons Learned.” in the
Proceedings of the 26th SISCSE Technical Symposium On
Computer Science Education, March 1995, Nashville, TN, pp. 218222.
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
McKinney, D. and Denton, L. F. “Affective Assessment of Team Skills
in Agile CS1 Labs: The Good, the Bad, and the Ugly,”
Proceedings of the 36th SISCSE Technical Symposium On
Computer Science Education, St. Louis, MO, February 2005.
McKinney, D. and Denton, L. F., “Houston, we have a problem:
there’s a leak in the CS1 affective oxygen tank,” Proceedings of
the 35th SISCSE Technical Symposium On Computer Science
Education, March, Norfolk, VA, 2004.
McKinney, D., Froeseth, J., Robertson, J., Denton, L. F., and
Ensminger, D. “Agile CS1 Labs: eXtreme Programming Practices
in an Introductory Programming Course,” Proceedings of
XP/Agile Universe 2004.
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Principal Findings
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Course achievement correlates with affective factors
 Student interest
 Lack of pressure
 Belonging
 Perceived competence
 Effort
 Value
Affective factors often decrease during the semester
Sections using systematic affective objectives and
strategies have higher levels of affective factors and
higher course completion rates
Affective factors impact all students including women
and minorities
Internalization of professional practices can be
accomplished in introductory courses and correlates with
higher course grades
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Principal
Assessment Instruments
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Quantitative
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Intrinsic Motivation Inventory (IMI)
Institutional Integration Scale
Anderson-Butcher Belonging Scale
Qualitative
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Comparative-reflective surveys
Peer Evaluations
BAM chart
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Bloom-based
Cognitive Framework
Levels:
 Knowledge
 Comprehension
 Application
 Analysis
 Synthesis
 Evaluation
FIE 2005
Indianapolis, Indiana
Benefits:
 Standards-based
approach
 Clear
expectations
 Transferability
 Content-centered
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Something’s Amiss …
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Overall results
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Low course completion rates
Low student satisfaction
Three types of students
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Non-achievers - students
not meeting course objectives
Survivors - passed with significant frustrations
and low motivation
Excellers - achieved cognitively, were
motivated, and internalized course objectives
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Obstacles to Achievement,
Retention, and Recruitment
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Non-sustained student interest
Inadequate faculty and peer support
Inadequate prior knowledge
Attraction of other disciplines
Intimidating atmosphere
Difficulty of discipline
Poor teaching
Large class sizes
Personal problems
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Motivation
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Impacts physical process
of learning in the brain
Promotes individual
growth
Increases group
effectiveness
Leads to higher time-ontask and overall learning
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Motivational Strategies
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Commitments to quality
Discussion approach
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Most desired qualities from the National Association of
Colleges and Employers
Armstrong – each person’s potential for genius
Helen Keller – persistence and promise
Polya, Maslow, Krathwohl
Reflection approach
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Goal-setting
Time management
Self-regulation
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
BAM Chart
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Krathwohl-based
Affective Framework
Levels
 Receiving
 Responding
 Valuing
 Organization
 Characterization
FIE 2005
Indianapolis, Indiana
Benefits
 Standards-based
approach
 Transition at-risk
students to excellers
 Achieve valuing rather
than compliance
 Enhance personal
identification with
discipline
 Transferability
 Learner-centered
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Examples of Affective Objectives
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Receiving: Students come to class ready and willing to
program
Responding: Students turn in assignments that follow
coding and documentation standards of the class
Valuing:
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Students recommend the use of Polya’s problem-solving strategy
to fellow classmates who are having difficulty solving a problem.
Students value the efficiency that can be gained from effective
algorithms, data structures such as arrays, and problem-solving
techniques.
Students prefer to use arrays to solve problems rather than
using non-aggregate data items when appropriate.
Organization: Students develop habits of reflective
problem solving as it relates to developing software
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
The Intellectual Challenge Remains
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Mostly first time programmers and a few
experienced hackers
Instructors have expert tacit knowledge
that is not easily decomposed into distinct
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Computational
concepts
Programming language
syntax
Problem solving
methodologies
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Moving Novices
Toward Expert Understanding
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Soloway’s methodology
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Explore and evaluate multiple data representation
Explore and evaluate multiple problem decompositions
Select and compose a particular solution
Implement solution
Reflect on the solution and the process
Minimizing cognitive overload
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Zone of proximate development – Vygotsky
Spiral coverage – Bruner
Subsumption learning – Ausebel
Treat computational concepts, syntax, and problem-solving
dimensions separately even when there is overlap
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Organizing and Refining Content
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Instructional templates
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Support for various learning styles
Relevant content
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Whitehead’s rhythm of education
Keller’s ARCS model
Gagné’s nine events of instruction
Interesting
Related to professional development
Feedback from students
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Whitehead’s
Rhythms of Education
Cyclical Periods of Learning
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Romance period
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Precision period
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Fascination with the broad significance of the idea
Motivation to actively pursue the more rigorous learning
Mastery of data collection techniques, notations, procedures
Development of relevant problem-solving strategies
Near transfer
Generalization
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Realized patterns, meaning, and general applications
Understanding of the worth of the learning
Far transfer
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Keller’s ARCS Model
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Attention
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Incongruity
Inquiry/participation
Concreteness
Humor
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Relevance
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Experience / modeling
Present / future worth
Power / affiliation /
achievement
perspectives
Needs matching
FIE 2005
Indianapolis, Indiana
Confidence
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Organization of
content
Clear
requirements
Positive
attributions
Choice
Satisfaction
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Natural and
unexpected
rewards
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Gagné’s Nine Events of Instruction
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Gain attention
Inform learner of
objectives
Stimulate recall of
prior learning
Present content
Provide guidance to
learners
FIE 2005
Indianapolis, Indiana
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Get the learners to
practice / perform
Provide feedback
Assess learners
Enhance retention of
what was learned and
transfer
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Balance Teaching
To Match Multiple Learning Styles
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Concept Map Example
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Recap and Concluding Remarks
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Principal elements of whole
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Cognitive course framework
Motivational strategies
Affective objectives
Adjusting course content for novice learners
Refining and organizing course content
Incremental implementation
Positive faculty cross-training and development
Course completion rates
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688
Leo F. Denton
[email protected]
Dawn McKinney
[email protected]
Michael V. Doran
[email protected]
http://www.cis.usouthal.edu/~mckinney/FIE2005CS1.ppt
FIE 2005
Indianapolis, Indiana
School of Computer and Information Sciences
University of South Alabama, Mobile, AL 36688