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By CSUF MSIDT Scholar Bill Bennett

Bill Bennett

Bill Bennett

  • Instructional Technologist
    Associate Professor
  • Mt. San Jacinto College
  • Menifee, CA 92584

  • Education:
  • B.S. Vocational Ed., CSUSB
  • M.A. Career & Technology Education (CTE) - Coordination & Supervision, CSUSB
  • M.S. Instructional Design & Technology (IDT), CSUF

  • Professional Certifications:

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7 Incredible Al Tools You’ve DEFINITELY Never Seen Before! (Underground AI #2)

Actually, ChatGPT is INCREDIBLY Useful (15 Surprising Examples)

AI Godfather's STUNNING Predictions for AGI, LLaMA 3, Woke AI, Humanoid Robots, Open-Source

BREAKING: OpenAI Reveals the TRUTH About Elon Musk's Lawsuit

Build Anything with AI Agents, Here's How

Build Your First App in Minutes with ChatGPT!

Build Your Mobile App Using ChatGPT || FREE Method

ChatGPT and Mindmapping | How to make a mindmap in ChatGPT

Deep Learning Basics: Introduction and Overview

Deep Learning State of the Art (2020)

Gemini Advanced vs ChatGPT Plus Comparison

Gemini Ultra 1.0 - First Impression (vs ChatGPT 4)

Generative A.I - We Aren’t Ready.

Genesis, this movie entirely made by AI, 4K

GPT-3 vs Human Brain

How to Build Mobile Apps with ChatGPT for FREE in Minutes

How To Make an App With ChatGPT (Without Knowing Code)

How to Use ChatGPT with Your Own Data

I Made 3 Games Using ChatGPT ? in Just 5 Minutes !

I Made an App with GPT-4 in 72 Hours

Introducing Visual Copilot 1.0: AI powered design-to-code using YOUR components

LPUs, NVIDIA Competition, Insane Inference Speeds, Going Viral (Interview with Lead Groq Engineers)

Meet The Kid Who Made $1M with ChatGPT

Mind-maps and Flowcharts in ChatGPT! (Insane Results)

NEW AI Jailbreak Method SHATTERS GPT4, Claude, Gemini, LLaMA

NVIDIA's STUNNING Breakthroughs: Blackwell AI Chip, Robots, AGI, World Model and more!

Open Interpreter's 01 Lite - WORLD'S FIRST Fully Open-Source Personal AI AGENT Device

Open-Source AI Agent Can Build FULL STACK Apps (FREE “Devin” Alternative)

OpenAI GPT Store Ideas + How to Connect an API to Your GPTs

OpenAI's "AGI Pieces" SHOCK the Entire Industry! AGI in 7 Months! | GPT, AI Agents, Sora & Search

OpenAI's NEW "AGI Robot" STUNS The ENITRE INDUSTRY (Figure 01 Breakthrough)

Run your own AI (but private)

Stop paying for ChatGPT with these two tools | LMStudio x AnythingLLM

The NEW Smartest AI (Claude 3 Just Shocked the Industry)

The ULTIMATE Guide to ChatGPT in 2024 | Beginner to Advanced

Top 10 ways to use ChatGPT Code Interpreter

Watch WebGPT?? Beat DEVIN at AI Software Engineering [No-Code Pong]

What Is Q*? The Leaked AGI BREAKTHROUGH That Almost Killed OpenAI

Why & When You Should Use Claude 3 Over ChatGPT

Yann Lecun: Meta AI, Open Source, Limits of LLMs, AGI & the Future of AI | Lex Fridman Podcast #416

Baby Hawks

Coitus Interuptus

Meow Meow Meow Meow


Bee In Flower

The Mr. Phil Show

Eddie Sghetti





Bennett Ranch's Hot & Sassy


Bennett's Majestic Testa rosa

Bennett's Tijuana Taxi

Bennett's Pretty in Paisley

Dottie Goes to the Dentist

Bennett's Reina Rojo

J. R. the Emu

Bennett's Joe Cool

Birth of the Black Pearl

Comcast Interview

MSJC BTC Preview

My World

My World II

Floral & Fruitful

Skies Over Woodcrest

Beard Shaving Dad

RHB Tribute

Perfect Pizza Commercial

Riverside Sings Competition

Video Place

John Sweller Cognitive Load

The Machine is Us/ing Us

A Day Made of Glass 2

Anything, Anything (I'll Give You)

Death By Bikini

"I Want To Kill You"

Route 66 by the Juice Weasles

Lovely Rita [Cover]

Making of Lovely Rita

Eleanor Rigby

Decimal To Binary Conversion


Numbering Systems

Dreamweaver Smart Objects

Creating a C# Sharp Console Project On Visual Studio for Mac Community

CSIS 111B Assignment 2 Hello Input Input

CSIS 111B Creating a C# Console Project in Visual Studio

CSIS 111B Binary Encoding

CSIS 111B Assignment 5 Hello (Input) (Input)

CSIS 111B Lesson 5 Data Types

CSIS 111B Midterm Assignment

CSIS 111B Lesson 7 Sorting Algorithms

CSIS 111B Creating a C# Console Project in Visual Studio

CSIS 111B Lesson 8 Repetition Structures

CSIS 111B Assignment 9 Decision Structures

CSIS 111B Binary Encoding

CSIS 111B Lesson 9 Decision Structures

CSIS 111B Lesson 10 Modular Programming

CSIS 111B Lesson 11 File I O

CSIS 111B Lesson 12 Exception Handling

CSIS 113B Lecture 3 - Decision Structures (Part 1)

CSIS 113B Demo

CSIS 113B Welcome

CSIS 113B Lecture 1 - Introduction to Java Programming

CSIS 113B Guided Practice 1

CSIS 113B Lecture 2 - Java Data Types (Updated)

CSIS 113B Guided Practice 2A

CSIS 113B Guided Practice 2B

CSIS 113B Lecture 3

CSIS 113B Lecture 3A - Decisions (part 1)

CSIS 113B Guided Practice 3A

CSIS 113B Lecture 3B - Decisions (part 2)

CSIS 113B Guided Practice 3B

CSIS 113B Lecture 4A - Repetition Structures (part 1)

CSIS 113B Lecture 4 - Decision Structures (part 2)

CSIS 113B Guided Practice 4

CSIS 113B Guided Practice 5

CSIS 113B Lecture 5 - Iteration (part 1)

CSIS 113B Lecture 6 - Iteration (part 2)

CSIS 113B Guided Practice 6A

CSIS 113B Guided Practice 6B

CSIS 113B Lecture 7

CSIS 113B Guided Practice 7A

CSIS 113B Guided Practice 7B

CSIS 113B Guided Practice 7C

CSIS 113B Lecture 8

CSIS 113B Guided Practice 8A

CSIS 113B Guided Practice 8B

CSIS 113B Lecture 9

CSIS 113B Guided Practice 9A

CSIS 113B Guided Practice 9B

CSIS 113B Guided Practice 9C

CSIS 113B Lecture 10

CSIS 113B Guided Practice 10A

CSIS 113B Guided Practice 10B

CSIS 113B Guided Practice 10C

CSIS 113B Lecture 11

CSIS 113B Guided Practice 11A

CSIS 113B Guided Practice 11B

CSIS 113B Guided Practice 11C

CSIS 115A How To Complete Prep Assignment

Fundamental Concepts of the World Wide Web

The Hypertext Transfer Protocol (HTTP)

HTML Introduction

Introduction to HTML

CSIS 115A Review Assignment 1 (RA1)

CSIS 115A Review Assignment 2 (RA2)

CSIS 115A Review Assignment 3 (RA3)

CSIS 115A Review Assignment 4 (RA4)

CSIS 117D Chapter 1 End of Chapter Exercise

CSIS 117D Lesson 1 Publishing

CSIS 117D Lesson 2 End of Chapter Exercise

CSIS117D Lesson 4 End of Chapter Excercise

CSIS 117D Chapter 5 End of Chapter Exercise

CSIS 117D Chapter 6 End of Chapter Exercise

CSIS 117D Chapter 7 End of Chapter Exercise

CSIS 117D Chapter 8 End of Chapter Exercise

CSIS 119A Lesson 8

Collision Versus Broadcast Domains

CSIS 202 Address Resolution Protocol (ARP)

CSIS 202 Chapter 1: The Data Communications Industry

CSIS 202 Chapter 2: Data Communications Concepts

CSIS 202 Chapter 3: Basic Data Communication Technology

CSIS 202 Chapter 4: Local Area Networks

CSIS 202 Chapter 5: Voice Communication Concepts and Technology

CSIS 202 Chapter 6: Wide Area Networking Concepts Architectures & Services

CSIS 202 Chapter 7: Local Area Network Communications Protocols

CSIS 202 Chapter 8: Advanced TCP/IP Network Design

CSIS 202 Chapter 9: Local Area Network Operating Systems and Remote Access

IP Address/Subnet Mask Relationship

CSIS 202 Chapter 11 - Network Management (part 1)

CSIS 202 Chapter 11 - Network Management (part 10)

CSIS 202 Chapter 11 - Network Management (part 11)

CSIS 202 Chapter 11 - Network Management (part 12)

CSIS 202 Chapter 11 - Network Management (part 5)

CSIS 202 Chapter 11 - Network Management (part 6)

CSIS 202 Chapter 11 - Network Management (part 7)

CSIS 202 Chapter 11 - Network Management (part 8)

CSIS 202 Chapter 11 - Network Management (part 9)

CSIS202 Chapter 11 - Network Management (part 2)

CSIS202 Chapter 11 - Network Management (part 3)

CSIS202 Chapter 11 - Network Management (part 4)

Network Management Part 1

Local Area Networks

CSIS 525 Review Assignment 10

CSIS 525 Review Assignment 11

CSIS 525 Review Assignment 12

CSIS 525 Review Assignment 13

Technology to Support Learning

Buffalo Annie

Miller/Davidson Theory

Batman and Robin 8mm

Floating Leaf



Class Assignments

IDT 550: Practicum
IDT 597: Project

Learning Objects Archive

 Instructional Approaches

Table of Contents

Direct Approach

When standardized tests are used to assess student attainment of basic skills, "direct of explicit instruction models most often produce the highest student scores" (Huitt, Monetti, & Hummel, 2009, in Reigeluth & Carr-Chellman).

General Model of Direct Instruction

In order for direct instruction to be successful, only students who demonstrated mastery of prerequisite knowledge should be allowed to receive instruction which builds upon the prerequisite knowledge.

"Essential content should be taught to students via an active presentation of information" (Huitt, Monetti, & Hummel, 2009 in Reigeluth & Carr-Chellman, p. 79).

Bloom (1981) stated that teachers should provide a clear organization of the presentation with step-by-step progression from subtopic to subtopic based on prerequisite knowledge and skills.

Pretesting or prompting of relevant knowledge (Block, 1971).

More student-teacher interaction (Walberg, 1991).

The use of many examples, visual prompts, and demonstrations to mediate between concrete and abstract concepts (Gage & Berliner, 1998).

A constant assessment of student understanding before, during, and after the lesson (Brophy & Good, 1986).

The Transactional Model of Direct Instruction (Huitt, Monetti, & Hummel, 2009 in Reigeluth & Carr-Chellman)

Transactional model of direct instruction.
  • The Presentation Phase
    • There are five important instructional methods that should be used during the presentation phase of direct instruction:
      1. Review of previous material or prerequisite skills
      2. A statement of the specific knowledge or skills to be learned
      3. A statement or experience that provides students with a reason or explanation of why these particular objective are important
      4. A clear, active explanation of the knowledge or skills to be learned
      5. Multiple opportunities for students to demonstrate their initial understandings in response to teacher probes
    • Learning is made more meaningful if the presentation is proceeded by an advance organizer (Ausbel, 1960). Three methods should occur before the explanation new concepts begins:
      • Review. It is important to have students activate prior knowledge so that they can more easily establish links to new information (called elaboration by information processing theorists such as Craik & Lockhart, 1972).
      • What. Describe what is to be learned in the lesson. Teachers should state objectives and how the student is to be held accountable for the learning activity (Gronlund, 2003; Mager, 1997). Perkins (1992) maintains that clarity of content is one of the most important conditions for quality instruction. This clarity should include what is to be learned and the standards for mastery.
      • Why. Describe why a particular objective is important for students to master. Ultimately it is important that students have a personal reason to be engaged in the learning process.
      • Explanation. Provide an active, careful explanation to students of the content or skill to be learned. The teacher should move from subtopic to subtopic in an efficient manner, introducing new material in small portions and connecting each new subtopic to the previous one (Bloom, 1981; Walberg, 1999). One of the most important considerations is to sequence the presentation such that organization is clear and obvious to students. Researchers have identified a number of organizations that might be used:
        • Component relationships-the lesson could be organized from parts to whole (inductive) or from whole to parts (deductive). Research suggests a rule-example-rule approach as an effective means to teach concepts to students (Van Patten, Chao, & Reigeluth, 1986).
        • Relevance relationships-Organizing content based on logical or empirical relationships among factors or categories within the lesson that are not hierarchically organized.
        • Sequential relationships-Organizing a lesson in terms of a step-by-step sequence.
        • Transitional relationships-Organizing a lesson in terms of the movement or transformation from one phase to another in the content being taught.
      • Additionally, teachers should use many examples, visual aids, and demonstrations in their presentation to enhance the effectiveness and efficiency in instruction.
      •  Probe and Respond. Probe students regarding their initial understandings. These are formative assessment activities and should be quick, short explanations of students knowledge or skills that inform the teacher if students are acquiring the concepts being presented. Teachers need to make instructionally effective use of wait-time, defined as the interval between a teacher probe and student response (wait-time I) or the interval between the student response and the teacher response (wait-time II). Rowe (1974a, 1974b) found that increasing either led to increased achievement, with increases in both having a compound effect. Fagan, Hassler, and Szabo (1981) found that using both higher-order questions and increased wait-time had greater impact than using either separately.
  • The Practice Phase
    • Perkins (1992) suggested that providing learners with numerous opportunities to practice the skills being learned is a critical activity for student learning.
      • Guided Practice. Students practice the newly learned knowledge or skills under the teacher's direct supervision (Walberg, 1999). At this point in the lesson, the teacher must actively monitor student activity while providing immediate feedback. At the end of this method, teachers should have rather precise information regarding each student's knowledge or skill with respect to the lesson objective(s).
      • Independent Practice. Student practice the new concepts independently. This may be done in the classroom or at home. While there has been some research that homework is relatively less important for elementary students, the vast majority of research supports the positive effects of homework for for middle and high school students. Most importantly homework must be be completed and graded if it is to be effective. It seems obvious that if the instructional day can be increased, thereby giving students more engaged time, then student achievement will increase.
      • Periodic Review. This method can be incorporated into teacher probes, guided practice, and independent practice. Teachers would be well served, when designing instruction, to make sure students have opportunities to revisit material learned a week, a month, or even a year previously. While cognitive research has shown that once material is in long-term memory it is there permanently (Atkinson & Shiffrin, 1968), students need practice retrieving that information and using it appropriately. This is an excellent place in the lesson to use cooperative learning techniques.
  • The Assessment and Evaluation Phase
    • Assessment and evaluation involves collecting data and making decisions about end-of-lesson or end-of-unit assessments.
      • Formative Assessment. Teachers make formative evaluation decisions about students on a daily basis to determine if they are making progress. Data from the previous methods of probing and responding, guided and independent practice, and periodic review activities might be used. The primary function of this evaluation process is to make plans for additional teaching on the topic, if necessary. Walberg (1999) asserts that additional teaching should occur when students perform at less than a 90% level during guided and independent practice exercises.
      • Summative Assessment. Teachers gather summative assessment data to see if students have mastered the required concepts and skills. This usually is in the form of unit tests or projects covering material from a week or two of instruction. Other types of summative evaluation may include semester or annual exams. It is important that summative evaluations match the content, form, and standards of external audits of classroom learning. Teachers should know the expectations of standardized tests, the requirements of any related courses students might take in the future, and requirements for future employment.
  • Monitoring and Feedback
    • There are two important instructional methods that should occur throughout the lesson on an "as needed" basis: providing cues and prompts, and providing corrective feedback and reinforcement.
      • Cues and Prompts. Providing cues and prompts, is often used when teachers review previous material, ask questions or probes, or have students engage in guided practice. The use of cues to hint at important information or indicate lesson transitions and the use of prompts when having students demonstrate the initial understanding of during guided practice are important instructional activities. When a student is in what Vygotsky (1978) called the zone of Proximal Development, the student will sometimes need a cue or prompt in order to be able to recall the required information or demonstrate the desired skill. However, when no amount of prompting evokes the desired response, further instruction is indicated. This assistance of further instruction should take place through a process of scaffolding whereby the teacher models the learning task or activity and then carefully and systematically relinquishes more and more responsibility to the student to perform it (Moll, 1992).
      • Corrective Feedback. Providing corrective feedback and reinforcement is done whenever the teacher has made an assessment of student learning at any point in the lesson. Perkins (1992) suggested that corrective feedback is one of the most important instructional activities provided during instruction. Walberg (1986), in his meta-analysis of research on teaching, found that providing corrective feedback and reinforcement showed the strongest relationship to student achievement of any single teacher action studied. Feedback should be provided for both correct and incorrect responses. An important principle is that students should not only hear or see the correct answers; they should also know why a particular answer is correct or incorrect. Dihoff, Brosvic, Epstein, and Cook (2004) showed that immediate feedback is superior to delayed feedback and the teacher should strive to provide feedback as quickly as possible.
    • The relationship of reinforcement during instruction to academic achievement has been one of the most consistent findings in process-product research (Brophy & Good, 1986; Roseshine, 1995; Walberg & Paik, 2000). The most common form of such reinforcement is teacher attention: a nod, a smile, or a quick comment. Cheery notes on the assignment or stickers can be used effectively. Making a practice of sending a positive note home to parents or caregivers for at least one student in subject area or class period is an excellent way to provide reinforcement for quality work.

The Scripted Model of Direct instruction

Methods used are the same as the General Model, but differ in terms of the specificity of teacher statements and student responses. Scripted lessons present smaller amounts of new information and skill training in each lesson, often accounting for only 10 to 15% of the total lesson (S. Engelmann, 1999). The remainder of the lesson firms and reviews content presented in earlier lessons. As in the general model, a scripted lesson approach assumes that nothing is completely taught in a single lesson. Instead, new content is presented in parts of two or three consecutive lessons to provide students with enough exposure so they are able to use it in applications. Each lesson presents content that is new today; content that is being firmed, having been presented in the last two or three lessons; and content that was presented even earlier in the sequence and is assumed to be thoroughly mastered. This content often takes the form of problems or applications that require earlier-taught content (S. Engelmann, 1999). Thus, scripted lesson approaches could potentially utilize more allocated class time than other approaches to address learning objectives.

While a scripted lesson approach was originally developed as a method to help predominately impoverished children who were not academically successful in traditional public school programs, it has been shown to be effective and efficient with both low and high performing students (Adams & Engelmann, 1996). In Project Follow Through, this scripted-lesson approach was compared to eight other models of instruction (including traditional and constructivist approaches and a home-based model) on outcome measures of three dimensions: academic basic skills, cognition, and affect (Stallings & Kaskowitz, 1974). The scripted-lesson approach produced the highest average performance of any program in all three dimensions (Watkins, 1988). In an analysis of Project Follow Through, Watkins (1988) found that there was an increased emphasis on mastery of content and skill prerequisites for additional lessons for all students. The analysis also indicated that a high degree of student success helped raise students' self-efficacy and, indirectly, improved the students' satisfaction with their schooling.

Gersten, Taylor, and Graves (1999) assert that an emphasis on detail sets a scripted lesson approach apart from the general model.

The scripted lesson approach shares many similarities with the general model of direct instruction. Scripted lessons begin with outcome behaviors being identified and then aligned with national or state curricular standards. The responsibility for this identification and alignment rests with the party (the individual teacher, a group of teachers, or a commercially available program) who generated the scripted lesson(s). These identified and aligned outcomes are then thoroughly "task analyzed." This involves breaking the complex skill or concept specified in the outcome into its component parts so that every student in a particular track has background skills and knowledge to learn the new skills and content. The scripted lesson approach differs from the general model in that: (1) the scripted lesson approach often involves a more detailed analysis, producing smaller steps in the task analysis than might be used in the general model; and (2) in scripted lessons, the exact wording the teacher and student use is written down.

Format: answer→ question→ response (Huitt, Monetti, & Hummel in Reigeluth, 2009)

Discussion Approach


Experiential Approach


Problem-Based Approach

Problem-Based Learning (PBL) is a teaching method originally developed by Howard Barrows to teach problem-solving techniques to students of clinical medicine.

Problem-based instruction (PBI) is rooted in experience-based education.

Research and theory on learning suggest that by having students learn through the experience of solving problems, they can learn both content and thinking strategies.

PBI is facilitated problem solving where student learning is organized around a complex problem that does not have a single solution. PBI typically starts with the presentation of the problem rather than a lecture or reading assignment intended to impart discipline-specific knowledge to the student. Students engage with the problem, generate ideas and possible solutions, determine what they currently know and do not know, establish learning goals, conduct research to acquire knowledge and skills needed to develop a viable solution to the problem, reflect on the problem utilizing the new information, and reflect on their problem-solving process (Savery & Duffy, 1995). As the learners work through the hypothetical-deductive reasoning process, the tutor provides support for their learning and their development of metacognitive skills.

PBI is sometimes confused with a case-based approach. While there are several similarities between a problem-based approach and case-based approach, there are significant differences, as clearly explicated by Williams (1992). The fundamental difference lies in the purpose of the instruction. If the tenet it to provide vivid and complex exemplars that assist the learner in forming conceptual relationships that may be abstract, then the well-written cases are an excellent vehicle. A well-structured case study will include critical information needed to arrive at a predetermined conclusion. With most case studies there is one right answer and the learning task for the student is to pick up on all the clues that are important (and avoid the red herrings). A problem-based approach is different in that the nature of the problem selected is clearly less defined-part of the task for the learner is to refine the general problem into component parts-and the solution or range of solutions is not predetermined. By utilizing current resources, solutions to a problem can change over time.

Learning is Knowledge Dependent

Research by Glaser (as cited by Resnick, 1989) suggests that both reasoning and learning are knowledge driven and, more specifically, that "Those who are knowledge-rich reason more profoundly. They elaborate as they study and thereby learn more effectively. Knowledge thus begets knowledge" (p. 2). Knowledge and experience are supported by research on problem solving as critical elements in effective problem analysis and the development of a viable solution (Jonassen, 2004).

Learning Is Highly Tuned to the Situation

Cognitive flexibility theory (Spiro et al., 1991) suggests that using complex, messy, real-world problems helps students transfer the knowledge and skills they learn to future complex, real-world problems and learn to apply the knowledge and skills to novel or ill-structured problems (Jonassen, 1997). In a similar vein, Bransford, Brown, and Cocking (2000) identify PBI as a strategy to encourage transfer of learning between school and everyday life (p. 77). Situated cognition theory (Brown, Collins, & Duguid, 1989) identifies the importance to learning of ill-defined, authentic problems. Thus these three areas of learning theory collectively underscore the use of a problem-based approach.

PBI has been adopted by different disciplines and, in the process, has been changed in both small and substantial ways to accommodate local conditions. This has led to some misapplications and misconceptions of PBI, and consequently certain practices that are still called PBI or PBL do not achieve the anticipated learning outcomes.

Universal Principles or Methods for PBI

There is remarkable consistency and convergence among researchers and practitioners concerning guiding principles for the design of effective PBI. The four main clusters of principles are:

  1. Select problems that are authentic and fit within the curriculum for the discipline and encourage cross-discipline thinking.
  2. The role of the tutor is to support the development of the learner's metacognitive processing skills and the learner's expertise as a problem-solver.
  3. Use authentic assessment practices to validate the learning goals.
  4. Use consistent and thorough debriefing activities to consolidate key concepts learned from the experience.


One common criticism of PBL is that students cannot really know what might be important for them to learn, especially in areas which they have no prior experience. Therefore teachers, as faciliators, must be careful to assess and account for the prior knowledge that students bring to the classroom.

Another criticism is that a teacher adopting a PBL approach may not be able to cover as much material as a conventional lecture-based course. PBL can be very challenging to implement, as it requires a lot of planning and hard work for the teacher. It can be difficult at first for the teacher to “relinquish control” and become a facilitator, encouraging the students to ask the right questions rather than handing them solutions.


Barrow, H. S. (1986). A taxonomy of problem-based learning methods. Medical Education, 20, 481-486.

Savery, John R., Duffy, Thomas M. (1995). Problem based learning: An instructional model and its constructivist framework. Educational Technology 35(5), 31-38.

Discusses the link between the theoretical principles of constructivism, the practice of instructional design, and the practice of teaching. Defines constructivism, lists three primary principles of learning and understanding, identifies eight instructional principles needed for the design of constructivist learning environments, and presents a detailed instructional model of problem-based learning. (JMV)

Simulation Approach

One or more dynamic models of physical or conceptual systems . . . that engage the learner in interactions with the models that result in state changes. . . . According to nonlinear logic . . . with supplementation by one or more designed augmenting instructional functions. . .  employed in the pursuit of one or more instructional goals (Gibbons, McConkie, Seo, Wiley, 2009 in Reigeluth 2009)