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FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information School of Computer and Information Sciences Sciences University of South Alabama, Mobile, AL University of South Alabama, Mobile, AL 3668836688
A Melding of A Melding of Educational Strategies to Educational Strategies to Enhance the Introductory Enhance the Introductory
Programming CourseProgramming Course
Leo F. Denton, Dawn Leo F. Denton, Dawn McKinney, and Michael V. McKinney, and Michael V.
DoranDoran
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
CS1 Course:CS1 Course:Introduction to Programming Introduction to Programming and Problem Solving Conceptsand Problem Solving ConceptsCourse formatCourse format 4 credit hours4 credit hours 15 week semester15 week semester One 75-minute and One 75-minute and
three 50-minute three 50-minute sessions (or three 75 sessions (or three 75 minute sessions)minute sessions)
Integrated lecture Integrated lecture and laboratory and laboratory
Topics Topics Problem solving Problem solving
strategiesstrategies Programming conceptsProgramming concepts Internal Internal
representations of representations of datadata
Control structuresControl structures Use of IDEUse of IDE MethodsMethods ArraysArrays OOP basics.OOP basics.
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
PaperPaper View of several techniques View of several techniques
described and studied described and studied separately in prior papers separately in prior papers
Principal elements Principal elements Cognitive course frameworkCognitive course framework Motivational strategiesMotivational strategies Affective objectivesAffective objectives Adjusting course content for novice Adjusting course content for novice
learnerslearners Refining and organizing course contentRefining and organizing course content
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University 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. 218-222.
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University 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 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Principal FindingsPrincipal Findings Course achievement correlates with affective Course achievement correlates with affective
factorsfactors Student interestStudent interest Belonging Belonging EffortEffort
Affective factors often decrease during the Affective factors often decrease during the semestersemester
Sections using systematic affective objectives and Sections using systematic affective objectives and strategies have higher levels of affective factors strategies have higher levels of affective factors and higher course completion ratesand higher course completion rates
Affective factors impact all students including Affective factors impact all students including women and minoritieswomen and minorities
Internalization of professional practices can be Internalization of professional practices can be accomplished in introductory courses and accomplished in introductory courses and correlates with higher course gradescorrelates with higher course grades
Lack of pressureLack of pressure Perceived competencePerceived competence ValueValue
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Principal Principal Assessment InstrumentsAssessment Instruments
QuantitativeQuantitative Intrinsic Motivation Inventory (IMI)Intrinsic Motivation Inventory (IMI) Institutional Integration ScaleInstitutional Integration Scale Anderson-Butcher Belonging ScaleAnderson-Butcher Belonging Scale
QualitativeQualitative Comparative-reflective surveysComparative-reflective surveys Peer EvaluationsPeer Evaluations BAM chart BAM chart
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Bloom-based Bloom-based Cognitive FrameworkCognitive Framework
Levels:Levels: KnowledgeKnowledge ComprehensionComprehension ApplicationApplication AnalysisAnalysis SynthesisSynthesis EvaluationEvaluation
Benefits:Benefits: Standards-Standards-
based approachbased approach Clear Clear
expectationsexpectations TransferabilityTransferability Content-Content-
centeredcentered
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Something’s Amiss …Something’s Amiss …
Overall resultsOverall results Low course completion ratesLow course completion rates Low student satisfactionLow student satisfaction
Three types of studentsThree types of students Non-achievers - Non-achievers - students students
not meeting course objectivesnot meeting course objectives Survivors - Survivors - passed with significant passed with significant
frustrations and low motivationfrustrations and low motivation Excellers Excellers - achieved cognitively, were - achieved cognitively, were
motivated, and internalized course motivated, and internalized course objectivesobjectives
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Obstacles to Achievement, Obstacles to Achievement, Retention, and RecruitmentRetention, and Recruitment
Non-sustained student interestNon-sustained student interest Inadequate faculty and peer supportInadequate faculty and peer support Inadequate prior knowledgeInadequate prior knowledge Attraction of other disciplinesAttraction of other disciplines Intimidating atmosphereIntimidating atmosphere Difficulty of disciplineDifficulty of discipline Poor teachingPoor teaching Large class sizesLarge class sizes Personal problemsPersonal problems
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
MotivationMotivation
Impacts physical process Impacts physical process of learning in the brainof learning in the brain
Promotes individual Promotes individual growthgrowth
Increases group Increases group effectivenesseffectiveness
Leads to higher time-on- Leads to higher time-on- task and overall learningtask and overall learning
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Motivational StrategiesMotivational Strategies Commitments to quality Commitments to quality Discussion approachDiscussion approach
Most desired qualities from the National Most desired qualities from the National Association of Colleges and EmployersAssociation of Colleges and Employers
Armstrong – each person’s potential for geniusArmstrong – each person’s potential for genius Helen Keller – persistence and promiseHelen Keller – persistence and promise Polya, Maslow, KrathwohlPolya, Maslow, Krathwohl
Reflection approach Reflection approach Goal-settingGoal-setting Time managementTime management Self-regulationSelf-regulation
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
BAM ChartBAM Chart
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Krathwohl-basedKrathwohl-basedAffective FrameworkAffective Framework
Benefits Benefits Standards-based Standards-based
approachapproach Transition at-risk Transition at-risk
students to excellersstudents to excellers Achieve valuing Achieve valuing
rather than rather than compliancecompliance
Enhance personal Enhance personal identification with identification with disciplinediscipline
TransferabilityTransferability Learner-centeredLearner-centered
LevelsLevels ReceivingReceiving RespondingResponding ValuingValuing OrganizationOrganization CharacterizatiCharacterizati
onon
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Examples of Affective Examples of Affective ObjectivesObjectives
Receiving: Students come to class ready and willing Receiving: Students come to class ready and willing to programto program
Responding: Students turn in assignments that Responding: Students turn in assignments that follow coding and documentation standards of the follow coding and documentation standards of the class class
Valuing:Valuing: Students recommend the use of Polya’s problem-solving Students recommend the use of Polya’s problem-solving
strategy to fellow classmates who are having difficulty strategy to fellow classmates who are having difficulty solving a problem. solving a problem.
Students value the efficiency that can be gained from Students value the efficiency that can be gained from effective algorithms, data structures such as arrays, and effective algorithms, data structures such as arrays, and problem-solving techniques.problem-solving techniques.
Students prefer to use arrays to solve problems rather than Students prefer to use arrays to solve problems rather than using non-aggregate data items when appropriate. using non-aggregate data items when appropriate.
Organization: Students develop habits of reflective Organization: Students develop habits of reflective problem solving as it relates to developing softwareproblem solving as it relates to developing software
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
The Intellectual Challenge The Intellectual Challenge RemainsRemains
Mostly first time programmers and a Mostly first time programmers and a few experienced hackersfew experienced hackers
Instructors have expert tacit Instructors have expert tacit knowledge that is not easily knowledge that is not easily decomposed into distinct decomposed into distinct Computational Computational
concepts concepts Programming language Programming language
syntaxsyntax Problem solving Problem solving
methodologiesmethodologies
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Moving Novices Moving Novices Toward Expert Understanding Toward Expert Understanding
Soloway’s methodologySoloway’s methodology Explore and evaluate multiple data representation Explore and evaluate multiple data representation Explore and evaluate multiple problem decompositionsExplore and evaluate multiple problem decompositions Select and compose a particular solutionSelect and compose a particular solution Implement solutionImplement solution Reflect on the solution and the processReflect on the solution and the process
Minimizing cognitive overloadMinimizing cognitive overload Zone of proximate development – VygotskyZone of proximate development – Vygotsky Spiral coverage – BrunerSpiral coverage – Bruner Subsumption learning – AusebelSubsumption learning – Ausebel Treat computational concepts, syntax, and problem-Treat computational concepts, syntax, and problem-
solving dimensions separately even when there is solving dimensions separately even when there is overlapoverlap
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Organizing and Refining Organizing and Refining Content Content
Instructional templatesInstructional templates Whitehead’s rhythm of educationWhitehead’s rhythm of education Keller’s ARCS modelKeller’s ARCS model Gagné’s nine events of instructionGagné’s nine events of instruction
Support for various learning stylesSupport for various learning styles Relevant contentRelevant content
InterestingInteresting Related to professional developmentRelated to professional development
Feedback from studentsFeedback from students
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Whitehead’s Whitehead’s Rhythms of EducationRhythms of Education
Cyclical Periods of LearningCyclical Periods of Learning Romance period Romance period
Fascination with the broad significance of the ideaFascination with the broad significance of the idea Motivation to actively pursue the more rigorous learningMotivation to actively pursue the more rigorous learning
Precision periodPrecision period Mastery of Mastery of data collection techniques, notations, data collection techniques, notations,
proceduresprocedures Development of relevant problem-solving strategiesDevelopment of relevant problem-solving strategies Near transferNear transfer
GeneralizationGeneralization Realized patterns, meaning, and general applicationsRealized patterns, meaning, and general applications Understanding of the worth of the learningUnderstanding of the worth of the learning Far transferFar transfer
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Keller’s ARCS ModelKeller’s ARCS Model AAttentionttention
IncongruityIncongruity Inquiry/participationInquiry/participation ConcretenessConcreteness HumorHumor
RRelevanceelevance Experience / modelingExperience / modeling Present / future worthPresent / future worth Power / affiliation / Power / affiliation /
achievement achievement perspectivesperspectives
Needs matchingNeeds matching
CConfidenceonfidence Organization of Organization of
contentcontent Clear Clear
requirementsrequirements Positive Positive
attributionsattributions ChoiceChoice
SSatisfactionatisfaction Natural and Natural and
unexpected unexpected rewardsrewards
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Gagné’s Nine Events of Gagné’s Nine Events of InstructionInstruction
Gain attentionGain attention Inform learner of Inform learner of
objectivesobjectives Stimulate recall of Stimulate recall of
prior learningprior learning Present contentPresent content Provide guidance Provide guidance
to learnersto learners
Get the learners to Get the learners to practice / performpractice / perform
Provide feedbackProvide feedback Assess learnersAssess learners Enhance retention Enhance retention
of what was of what was learned and learned and transfertransfer
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Balance TeachingBalance TeachingTo Match Multiple Learning To Match Multiple Learning
StylesStyles
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Concept Map ExampleConcept Map Example
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Recap and Concluding Recap and Concluding RemarksRemarks
Principal elements of wholePrincipal elements of whole Cognitive course frameworkCognitive course framework Motivational strategiesMotivational strategies Affective objectivesAffective objectives Adjusting course content for novice learnersAdjusting course content for novice learners Refining and organizing course contentRefining and organizing course content
Incremental implementationIncremental implementation Positive faculty cross-training and Positive faculty cross-training and
developmentdevelopment Course completion ratesCourse completion rates
FIE 2005FIE 2005Indianapolis, IndianaIndianapolis, Indiana
School of Computer and Information Sciences School of Computer and Information Sciences University of South Alabama, Mobile, AL 36688University of South Alabama, Mobile, AL 36688
Leo F. DentonLeo F. [email protected]@usouthal.edu
Dawn McKinneyDawn [email protected]@usouthal.edu
Michael V. DoranMichael V. [email protected]@usouthal.edu
http://www.cis.usouthal.edu/~mckinney/FIE2005CS1.ppthttp://www.cis.usouthal.edu/~mckinney/FIE2005CS1.ppt