A Melding of Educational Strategies to Enhance the Introductory Programming Course

1. A Melding of Educational Strategies to Enhance the Introductory Programming Course Leo F. Denton, Dawn McKinney, and Michael V. Doran

2. 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 Topics Problem solving strategies Programming concepts Internal representations of data Control structures Use of IDE Methods Arrays OOP basics. CS1 Course:Introduction to Programming and Problem Solving Concepts School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

3. Paper • View of several techniques described and studied separately in prior papers • Principal elements • Cognitive course framework • Motivational strategies • Affective objectives • Adjusting course content for novice learners • Refining and organizing course content School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

4. 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. 218-222. School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

5. 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. School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

6. Principal Findings • Lack of pressure • Perceived competence • Value • Course achievement correlates with affective factors • Student interest • Belonging • Effort • 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 School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

7. Principal Assessment Instruments • Quantitative • Intrinsic Motivation Inventory (IMI) • Institutional Integration Scale • Anderson-Butcher Belonging Scale • Qualitative • Comparative-reflective surveys • Peer Evaluations • BAM chart School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

8. Bloom-based Cognitive Framework Levels: • Knowledge • Comprehension • Application • Analysis • Synthesis • Evaluation Benefits: • Standards-based approach • Clear expectations • Transferability • Content-centered School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

9. Something’s Amiss … • Overall results • Low course completion rates • Low student satisfaction • Three types of students • Non-achievers - students not meeting course objectives • Survivors - passed with significant frustrations and low motivation • Excellers - achieved cognitively, were motivated, and internalized course objectives School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

10. Obstacles to Achievement, Retention, and Recruitment • 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 School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

11. Motivation • Impacts physical process of learning in the brain • Promotes individual growth • Increases group effectiveness • Leads to higher time-on- task and overall learning School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

12. Motivational Strategies • Commitments to quality • Discussion approach • 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 • Goal-setting • Time management • Self-regulation School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

13. BAM Chart School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

14. Benefits Standards-based approach Transition at-risk students to excellers Achieve valuing rather than compliance Enhance personal identification with discipline Transferability Learner-centered Levels Receiving Responding Valuing Organization Characterization Krathwohl-basedAffective Framework School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

15. 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: 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 Examples of Affective Objectives School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

16. The Intellectual Challenge Remains • Mostly first time programmers and a few experienced hackers • Instructors have expert tacit knowledge that is not easily decomposed into distinct • Computational concepts • Programming language syntax • Problem solving methodologies School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

17. Moving Novices Toward Expert Understanding • Soloway’s methodology • 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 • 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 School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

18. Organizing and Refining Content • Instructional templates • Whitehead’s rhythm of education • Keller’s ARCS model • Gagné’s nine events of instruction • Support for various learning styles • Relevant content • Interesting • Related to professional development • Feedback from students School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

19. Whitehead’s Rhythms of Education Cyclical Periods of Learning • Romance period • Fascination with the broad significance of the idea • Motivation to actively pursue the more rigorous learning • Precision period • Mastery of data collection techniques, notations, procedures • Development of relevant problem-solving strategies • Near transfer • Generalization • Realized patterns, meaning, and general applications • Understanding of the worth of the learning • Far transfer School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

20. Keller’s ARCS Model • Confidence • Organization of content • Clear requirements • Positive attributions • Choice • Satisfaction • Natural and unexpected rewards • Attention • Incongruity • Inquiry/participation • Concreteness • Humor • Relevance • Experience / modeling • Present / future worth • Power / affiliation / achievement perspectives • Needs matching School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

21. Gain attention Inform learner of objectives Stimulate recall of prior learning Present content Provide guidance to learners Get the learners to practice / perform Provide feedback Assess learners Enhance retention of what was learned and transfer Gagné’s Nine Events of Instruction School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

22. Balance TeachingTo Match Multiple Learning Styles School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

23. Concept Map Example School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

24. Recap and Concluding Remarks • Principal elements of whole • 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 School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688

25. Leo F. Denton ldenton@usouthal.edu Dawn McKinney dmckinney@usouthal.edu Michael V. Doran mdoran@usouthal.edu http://www.cis.usouthal.edu/~mckinney/FIE2005CS1.ppt School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688