Chapter 2 discusses various instructional software programs used in education, classifying them into categories such as drill and practice, tutorials, simulations, instructional games, and problem solving. It highlights the benefits and limitations of each type, providing guidelines for effective use and evaluation. Furthermore, it explores trends in software design, emphasizing multimedia elements and online access.

1. Chapter 2
Computer Applications in Education
INSTRUCTIONAL SOFTWARE
Programs developed specifically to deliver or assist with
student instruction on a topic
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3.*
Instructional Software ClassificationsDrill and Practice skill
practiceTutorial information delivery Simulation
demonstrationexploration
Instructional Games
skill practice
exploration
Problem Solving
skill practice
exploration

2. *
3.*
Problem of Identifying Types of SoftwareToday’s software
packagesHard to classifySeveral different activitiesOverlap of
functions in one packageExample: Reader RabbitDrill
activitiesProblem solvingGames
3.*
Recent Trends in Software Design and DeliveryMultimedia
elementsOnline access and componentsRenewed emphasis on
directed strategies and networked systems
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DRILL AND PRACTICE
TypesFlashcard activityBranching drillExtensive feedback
activities
Criteria for well-designed programs Control over presentation
Appropriate feedback Answer reinforcement
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3. 3.*
DRILL AND PRACTICE
Benefits Immediate feedbackMotivationalSaves teacher time
Limitations and problems
Perceived misuses
Criticism by constructivists
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3.*
DRILL AND PRACTICE
Ways to useTo supplement or replace worksheetsTo assist in
preparing for objective tests
Guidelines for useSet time limitsAssign individuallyUse
learning stations
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3.*
TUTORIALS
Tutorial typesLinear tutorialsBranching tutorials
Criteria for well-designed programs Extensive interactivity
Thorough user control Appropriate pedagogy Adequate answer-
judging and feedback Appropriate graphics Adequate
record keeping

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3.*
TUTORIALS
BenefitsImmediate feedbackMotivationalSaves teacher time
Limitations and problems Criticism by constructivists Hard to
find Reflect only one instructional approach
M. D. Roblyer
Integrating Educational Technology into Teaching, 4/E
Copyright ©2006 by Pearson Education, Inc.
Upper Saddle River, New Jersey 07458
All rights reserved.
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3.*
TUTORIALS
Ways to useSelf-paced reviewsAlternative learning
strategiesWhen teachers are not available
Guidelines for useAssign individuallyUse learning stations or
individual checkout
M. D. Roblyer

5. Integrating Educational Technology into Teaching, 4/E
Copyright ©2006 by Pearson Education, Inc.
Upper Saddle River, New Jersey 07458
All rights reserved.
*
3.*
SIMULATIONS
Types
Physical
Iterative
Procedural
Situational
Criteria for well-designed programs
System fidelity and accuracy
Good documentation to explain system characteristics and uses
M. D. Roblyer
Integrating Educational Technology into Teaching, 4/E
Copyright ©2006 by Pearson Education, Inc.
Upper Saddle River, New Jersey 07458
All rights reserved.
*

6. 3.*
SIMULATIONS
BenefitsCompress timeSlow down processesGet students
involvedMake experimentation safeMake the impossible
possibleSave money and other resourcesAllow repetition with
variationsAllow observations of complex processes
Limitations and problems Accuracy of models Misuse of
simulations
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3.*
SIMULATIONS
Ways to use simulations Lab experiments Replacement or
supplement to role playing Replacement or supplement to field
tripsIntroducing a new topicFostering explorationEncouraging
cooperation and group work
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3.*
INSTRUCTIONAL

7. GAMES
Game types
Rules
Elements of competition and challenge
Amusing or entertaining formats
Criteria for well-designed programs
Appealing formats and activities
Instructional value
Physical dexterity is reasonable
Minimum violence/aggression
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3.*
INSTRUCTIONAL
GAMES
Limitations and problems
Learning versus having fun
Confusion of game rules and real life rules
Inefficient learning
BenefitsHigh interestRetention
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3.*
INSTRUCTIONAL

8. GAMES
GuidelinesUse sparinglyInvolve all studentsEmphasize content
area skills
Ways to use
In place of worksheets and exercises
To foster cooperation and group work
As a reward
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3.*
PROBLEM SOLVING
Criteria for well-designed programs
Challenging and interesting formats
Clear links to developing specific problem-solving skills or
abilities
Problem solving types
Specific to content area
General content-
free skills
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3.*
PROBLEM SOLVING
BenefitsMotivates students to solve problems and spend time

9. on topicKeeps knowledge from becoming inert
Limitations and problems Names versus skills Courseware
claims versus effectiveness Possible negative effects of
directed instruction Transfer
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3.*
PROBLEM SOLVING
Ways to use
Teach component skills in problem- solving strategies
Provide support in solving problems
Encourage group problem solving
CharacteristicsTools to help solve problemsEnvironments that
challenge students to create solutionsProblems to help develop
component problem-solving skillsOpportunities for practice in
solving content-area problems
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3.*
Integrated Learning System (ILS)
Characteristics Instructional objectivesLessons integrated into
standard curriculum Courseware Management system
Criteria for well-designed ILS Good curriculum coverage
Good pedagogical strategies Several different report
formats Easy-to-read and interpret reports

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Integrated Learning System (ILS)
BenefitsHelp provide supplemental educational services
required by NCLB ActBenefits of drill, tutorials, simulations,
instructional games, and problem solving—depending on
selectionEasier to access via network or onlinePersonalized
instructionSummary progress data
Limitations and problems Costs Research on impact Concerns
about the role of ILSs
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Integrated Learning Systems (ILS) GuidelinesCost of hardware
and software resourcesEstimate educational benefitsObtain ILS
updates from vendorsEvaluate ILS for match with
expectationsCalculate personnel and fiscal impact
Clear problem Closed or open system Match scope and
sequence Match to target population Adequacy of
reporting and management system
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11. 3.*
Integrated Learning Systems (ILS)
Ways to useRemediation Mainstream delivery systemResource-
rich environments
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Courseware Evaluation
Recommended Sequence
Begin with an identified need
Locate titles
Complete hands-on reviews
Collect student reviews
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Courseware Evaluation
Essential QuestionsDoes it teach?Is the content accurate,
current, and appropriate?Is it “user friendly”?Does it work
correctly?
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12. 3.*
Courseware Evaluation
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3.*
Courseware Evaluation
*
ITS 832
Chapter 5
From Building a Model to Adaptive Robust
Decision Making Using Systems Modeling
InformationTechnology in a Global Economy
Introduction
• Modeling & Simulation

13. • Fields that develops and applies computational methods to
address complex system
• Addresses problems related to complex issues
• Focus on decision making abilities
• Opportunities to leverage interdisciplinary approach, and learn
across fields to understand complex systems.
• Legacy System Dynamics (SD) modeling and others
methods are presented
• Recent innovations
• What the future holds
• Examples
Systems Modeling
• Dynamic complexity
• Behavior evolves over time
• Modeling Methods
• System Dynamics (CD)
• Discrete Event Simulation (DES)
• Multi-actor Systems Modeling (MAS)
• Agent-based Modeling (ABM)
• Complex Adaptive Systems Modeling (CAS)
• Enhanced computing supports model based decision making
• Modeling and simulation has become interdisciplinary

14. • Operation research, policy analysis, data analytics, machine
learning,
computer science
Legacy System Dynamics Modeling
• 1950’s – Jay W. Forrester
• Primary characteristics
• Method to model complex systems or issues
• Feedback effects – dependent on their own past
• Accumulation effects – building up intangibles/ mental or
other
states for a complete model.
• Behavior of a system is explained
• Casual theory – model generates dynamic behavior
• Works well when:
• Complex system responds to feedback and accumulation
Recent Innovations
• Detailed list of individual innovations
• Deep uncertainty
• Analysts do not know or cannot agree on
• Model

15. • Probability distributions of key features
• Value of alternative outcomes
• Two primary evolutions:
• Smarter methods (Data Science)
• Usability/accessibility advances
What the Future Holds
• Better models, as a result of technology innovation
• More data (“Big Data”)
• Social media
• Advanced capabilities for:
• Hybrid Modeling: mixing and matching models.
• Simultaneous Modeling
• Modeling multiple models or uncertainty
• Adopting all recent innovations and opportunities would bring
the
future state in Modeling and Simulation, as presented in Fig. 5.1
Modeling and Simulation

16. Examples
• Assessing the Risk, and Monitoring, of New Infectious
Diseases
• Simple systems model with deep uncertainty
• Integrated Risk-Capability Analysis Under Deep
Uncertainty
• System-of-systems approach
• Policing Under Deep Uncertainty
• Smart model-based decision support system
Summary
• Modeling has long been used with complex systems
and issues / simulation.
• Recent evolutions have advanced modeling
• Increase computing power
• Social media and Big data
• Sophisticated analytics
• Multi-method and hybrid approaches are now feasible
• Continued move into interdisciplinary study
• Advanced modeling for complex systems
• Operation research, policy analysis, data analytics, machine
learning, computer science

17. Sheet1Students
NameWritingSpellingReadingPronunciationGrammarHugo
Bolanos32.5433.6Sandra Morales2.82.933.23.8Roberto
Montealegre432.63.42.8Mario Villafuerte32.83.433.5Rhina
Rojas443.643.3Camilo Torrez3.43.643.13.4Claudia
Bonilla3.5333.32.9Jorge Luis Cruz3.63.22.943Roberto
Guevara43.42.83.53.4Students Perfomance31.328.429.330.529.7
Students Perfomance Writing Spelling Reading
Pronunciation Grammar 31.3 28.4 29.3 30.5 29.7 Hugo
Bolanos Writing Spelling Reading Pronunciation
Grammar 3 2.5 4 3 3.6 Sandra Morales
Writing Spelling Reading Pronunciation Grammar
2.8 2.9 3 3.2 3.8 Roberto Montealegre Writing
Spelling Reading Pronunciation Grammar 4 3
2.6 3.4 2.8 Mario Villafuerte Writing Spelling
Reading Pronunciation Grammar 3 2.8 3.4 3
3.5 Rhina Rojas Writing Spelling Reading
Pronunciation Grammar 4 4 3.6 4 3.3 Camilo
Torrez Writing Spelling Reading Pronunciation
Grammar 3.4 3.6 4 3.1 3.4 Claudia Bonilla
Writing Spelling Reading Pronunciation Grammar
3.5 3 3 3.3 2.9 Jorge Luis Cruz Writing
Spelling Reading Pronunciation Grammar 3.6 3.2
2.9 4 3 Roberto Guevara Writing Spelling
Reading Pronunciation Grammar 4 3.4 2.8 3.5
3.4
1
2
3
4

18. 5
6
7
8
9
A
B
C
Students Name
Writing
Spelling
Hugo Bolanos
3
2.5
Sandra Morales
2.8
2.9
Roberto Montealegre
4
3
Mario Villafuerte
3
2.8
Rhina Rojas
4
4
Camilo Torrez
3.4
3.6
Claudia Bonilla
3.5
3
Jorge Luis Cruz
3.6
3.2