Thinking Activities

Posted on November 20, 2023 by Robert "Bob" Bilyk

Robert N. Bilyk
President, LodeStar Learning Corporation

Introduction

We want students to think. That’s the common refrain among educators. Ideally, we move students beyond the classroom and textbook and put them in situations where they apply their learning.

As instructors and trainers, we are also desperately strapped for time. We seek resources from publishers and Open Education Repositories but seldom find the challenging activity that helps students put it all together for our specific course and intended outcomes.

If we consider home-growing a ‘thinking’ activity, we are presented with a continuum of possibilities. In this discussion, we look at different types of activities along the continuum. In my next post, I’ll suggest a new type of activity that can be developed in a short time frame with skill that is within reach of instructors and trainers. I call it the State Response Engine. But for now, let’s look at the “Thinking Activities” continuum.

Thinking Activities Continuum

By continuum, I mean a sequence, series or system in which adjacent elements are not perceptibly different from each other, although the extremes are quite distinct.

In this case the continuum represents categories of learning experiences that promote thinking. The ends of the continuum (in this case, Readings and Discussion, and Context-Challenge-Activity-Feedback) seem extremely different but the activities in the middle vary imperceptibly at least in terms of the skill needed to design and develop them.

Reading and Discussions

On the easier end, we educators can assign readings. By easy, I mean technically easy. We know our content, or we can work with a subject matter expert. With a little ingenuity we can develop prompts to promote discussions, team-based problem-solving, role-playing and so forth. The technology can be as simple as a discussion board or a content page in a learning management system. The technology is easily mastered by instructors and trainers.

Quizzes and Puzzles

In addition to assigned readings and discussions, we can challenge trainees and students with multiple choice questions, true or false, fill-in-the blanks, matching, crosswords, word games and drag and drop exercises. This implies a new skill level that requires knowledge to construct these interactions and form good questions.

As Ben Clay wrote, “Technically correct and content-appropriate multiple choice and true-false test items require an extensive amount of time to write and revise.”¹ This category can also include flashcards, quick knowledge checks, click-and-reveal, and other memory-recall exercises. There is a significant skill involved in developing memory games and good assessment items, to be sure. But on the technical side, instructors can quickly master their learning management system’s quizzing tool or choose a good authoring tool with templates.

However, our goal isn’t to prepare students to answer multiple choice questions. We want students and employees to assess their current situation, recall relevant concepts, principles, rules, and procedures and apply them to the situation. To be fair, in the view of the authors of Make it Stick ², it’s important for students ‘to get it out in order to get it in’ – to make it stick. Any recall activity is helpful in that regard. But, in my view, we need additional strategies to simulate real-world situations to help students draw from their knowledge and apply it appropriately. And that’s why we progress to a higher level.

Simple Simulations

Further down the continuum we have simple simulations such as Clark Aldrich’s ShortSim³ that I’ve written about in the past. The technical difference and the skill involved is almost imperceptible from developing online MCQ assessments.

If an instructor can use an authoring tool and devise multiple choice questions, fill-in-the-blanks and so forth, then they will be able to do the things needed for a ShortSim. And that is, write narrative, add graphics, present decision options, advance the narrative. Related to the latter, the instructor can choose a linear path or branch. Branching allows students to experience something different as a consequence of their decisions. Authoring systems like LodeStar, Captivate, StoryLine and BranchTrack make it relatively easy to set up branches. But it is a new skill level and it takes a little time to master.

This category can also include simple virtual tours, which require branching and media like 360-degree panoramas and Photospheres.

Interactive Case Studies

Interactive case studies help students put their knowledge into practice. They help students develop the ability to analyze, judge, and make decisions. Interactive case studies often include information that a student must consult to make the right decision. In nursing, the information might come from a simulated electronic health record. In economics, it might include a Dow Jones Index for a given time period.

Akin to interactive case studies, decision-making scenarios display content and test the knowledge of learners by challenging them to make decisions and observe the consequences. Each screen presents new situations and new choices.

In a lesson on patient management, the student is stepped through the patient history, an initial evaluation, physical examination, patient report and diagnosis. The student is evaluated on time and budget management and on patient care management.

The interactive case studies and decision-making scenarios that belong to this category are highly developed. They might include multiple resources, graphs, charts, fact sheets, data sets, videos, biographies, etc. They may include people to interview and glean information from. They may include programmatic branches that send students down instructional paths based on the choices they made.

Technically, interactive case studies and decision-making scenarios are just a step up from a ShortSim. They involve more time and effort in deciding the level of detail and developing all of the resources to immerse the student in the case or decision-making situation. In the Patient Management example, the additional technical challenge is in presenting an animated graphic that shows the student’s performance in time and patient management. The Patient Management lesson now requires us to store student performance data in variables and then control a graphic based on the variables.

This category can also include interactive fiction/non-fiction, problem-based scenarios, historical case analyses, crisis management simulations, and role-playing scenarios.

Context Challenge Activity Feedback

Context, Challenge, Activity, and Feedback (CCAF) is a design model used to create interactive learning activities. Designers like Allen Interactions, Rivertown Communications, TrueUp, and KDG Interactive build media-rich CCAF-type activities that include not only graphics, animation, video, and other media but performance indicators, branched instruction, resources, coaching, and simulations – all beautifully illustrated and intended to immerse the student in a real-life context.

CCAF activities are generally free-form activities. They don’t appear to be produced from templates but represent an original treatment of an environment that sets the challenge for the learner. Underlying these treatments may be re-purposed models (interaction types) but the presentation doesn’t appear to be repurposed and template based.

This category can also include simulated experiments, virtual laboratories, software simulations, equipment operation simulations, process simulations.

Virtual Reality/Augmented Reality

Virtual reality and Augmented reality applications can span the entire continuum of thinking activities, but they require specialized knowledge. VR and AR can range from simple multiple-choice types of activities to simulations that are simple or quite sophisticated. Applying VR and AR to thinking activities requires knowledge of platforms such as Unity and 3D creation tools like Blender.

Conclusion

The Thinking Activities continuum represents the technical skill needed by a trainer or instructor to develop activities at different levels. At one end of the continuum, the instructor needs to be familiar with the learning management system to post discussions and collaborative problem-solving narratives. To create quiz items and different types of exercises like drag and drops and matching, the instructor must be familiar with either the native tools of the learning management system or an authoring tool like Storyline, Captivate or LodeStar. Then we get into the category of Simple Sims and the idea of branched instruction. That carries upward to interactive case studies and decision-making scenarios that present resources and media and show the consequences of decisions. Depending on the design, case studies and decision-making scenarios may introduce more sophisticated branching. At the highest level in terms of time/expense and skill are activities that follow the CCAF model. They often recreate real-world situations that blend media with branching logic and data.

The challenge for instructors and trainers is often time. Activities at the higher end of the continuum require more time to develop. Instructors and trainers are smart people. With today’s authoring tools, they can acquire the skills as they work their way from quizzes to short sims to interactive case studies. I’ve observed many instructors and trainers move along the continuum. But at some point, we all need a return on our investment of time or money. That ROI might be supported by the numbers of students that we teach or the significance of the skill in the curriculum. For example, the instructor might invest time in a project that helps students through a significant and known stumbling block. In math that might mean difficulty with word problems and translating real-world situations into mathematical equations. In chemistry, understanding chemical bonding. In computer science, understanding data structures and algorithms. In machining, the use of the sine bar and basic trig. In interpersonal relations, recognizing unconscious biases. Every subject has its stumbling points. Time invested in helping students through those stumbling blocks is time well invested.

From here

That brings us back to the midpoint of the continuum, which includes ShortSims. In my view we need to uncover and invent more types of activities that are easily within the technical reach of the intrepid instructor and producible in a short period of time.

I have developed several models that fit the bill. The next post will re-introduce the State Response Engine (SRE). The SRE randomly picks situations and then challenges students to choose the right responses or actions based on the randomly chosen situation. Here is a link to that post:

State Response Engine

References

¹Clay, Ben “Is This a Trick Question”, 2001, Kansas Curriculum Center

² Brown, R. M. (2014). Make it Stick. Brown, Roediger, McDaniel.

³ShortSim is a term coined by Clark Aldrich in his book ShortSims
Aldrich, Clark (2020) ShortSims, CRC Press

The Teaching Machine – Past, Present and Future

Posted on October 25, 2023 by Robert "Bob" Bilyk

Robert N. Bilyk
President, LodeStar Learning Corporation

I’ve been reading Teaching Machines, The History of Personalized Learning by Audrey Watters¹, who may be best known for her “Hack Education” blog. Teaching Machines is a great read. It was published in 2021. Since then, Audrey Watters posted her last on ‘Hack Education’ and, according to her post, no longer writes about Tech Education.

The Past

A good part of Teaching Machines is dedicated to B.F. Skinner’s Teaching Machine. By today’s standards, it’s a crude mechanical device. The early versions were wood boxes that displayed questions through a small window and required students to write answers on a paper strip. Once students submitted their answers, they pulled a lever to display the answer and advance the paper strip. The questions and answers were printed on a paper disk partitioned into pie wedges.

For fun, I simulated an early prototype of B.F. Skinner’s Teaching Machine. I used our LodeStar Authoring tool to simulate how the early machine worked.

See the simulation at https://lodestarlearning.github.io/Teaching-Machine/index.htm

Films from that era (the 50s) conjure up rows of students working on the machines – a setting not unlike a factory floor with row upon row of workers at their sewing machines.

And yet, as Watters writes, the impetus – the motivation – behind the design of these teaching machines was largely, in the opinion of their inventors, altruistic and intended for the benefit of the student.

Watters recalls how Skinner visited his daughter’s 4^th grade math class. The teacher wrote math problems on the board. Some students finished quickly and squirmed in their seats as they waited for the class to progress. Other students struggled to complete the problem and perhaps never successfully finished.

Fast forward thirty years. I was a high school language arts teacher in the 80s. One of my classes consisted of students who could not read or write very well. I’ve spoken about this a dozen times. The underlying reasons for their inability to read or write very well had to do with who they were: some students were newly immigrated from non-English speaking countries; other students had learning disabilities; and others hated school. I was handed one curriculum that treated the class as one homogenous body. I really needed materials and strategies that addressed the needs of at least three populations. I needed some form of teaching machine.

Skinner, in response to his daughter’s class, decried that “something must be done”. I approached our Instructional Materials Center Coordinator and asked if, in any way, the Apple IIe machine in the library could help me ‘individualize’ the instruction. For Skinner, the realization led to his idea of a teaching machine. For me, I began a career-long journey into the world of technology-assisted personalized learning.

Minnesota Educational Computing Consortium’s (MECC) Oregon Trail on an Apple II.

From time to time, I’ve challenged myself to take a hard look at the principles that drove my pursuit to help students with technology. As a starting point, I was interested in the following ideas:

For the student:

Go at your own pace, where the learning objective is constant, but time is variable.
Get quick feedback.
Have fun.
Pursue lesson branches based on your interest, choices and performance.
Be challenged.

For the instructor:

Free up time for individualized help.
Get information on what questions students are consistently getting wrong.
Inform future lesson plans.

I used computer programs on the Apple IIe, but I wanted to write my own. Several years later, I was headed home on a dark country road, listening to Minnesota Public Radio. I was listening to a story about interactive video discs – and I became smitten. At this point in my career, I worked at a college. I asked my dean (who had a background in instructional systems), what I needed to learn to program interactive discs. He answered, “Learn C”. And so I began my study of both learning theory and computer programming and camped out at their crossroads.

At the University of Minnesota, I studied curriculum and instruction. At Saint Paul College, where I worked, I took classes from programmers who made their living at Unisys, Honeywell and other industries. As I soon discovered, my dean’s advice was both bad and good. It was bad because, by the 90s, one did not need to learn a low-level programming language, like C, to control a video disc player. The TenCore Language Authoring System could do that with a much higher level language (thus easier). It was good because I became proficient at programming and could extend authoring systems with lower-level code. In short, I was never limited by the authoring tool, only by my imagination. Later I worked on teams to design a content management system, several instructional products and two authoring systems.

The Tencore Language Authoring System (LAS)
was a TUTOR (PLATO) derivative developed by Paul Tenczar

The Interactive Videodisc was a laser– readable random-access disc that contained both audio and analog video. The videodisc’s full motion video was displayed on a computer with the help of a video overlay card that superimposed the analog video on a digital monitor.

Authoring systems like TenCore, Authorware and Toolbook enabled designers to program the computer to send commands to the player via serial communications.

In the early 90s, the University of Minnesota introduced me to Course of Action, which was later renamed Authorware. Authorware was a game-changer. With this system, I could finally efficiently realize all the ideas I had started out with and that now took the form of:

Individualized instruction
Immediate feedback, or strategically delayed feedback, based on the design.
Fun interaction with analog video, high-fidelity sound, dithered graphics (256 color displays), three-dimensional animation (yes, in the early 90s), simulations, games….
Branched, non-linear instruction.
Data collection and reporting. (The installed computer program could gather data and, using an early standard from the aviation industry (AICC), report it to the instructor.)

It was a great start and a step toward the present.

Authorware, designed by Dr. Michael Allen and his amazing team, changed everything. The work shifted from arcane computer commands to the design of learning experiences. Authors dragged icons onto a flowline that commanded the computer to present graphics and text, animate, play audio and video, branch instruction and execute simple scripts.

The Present

The promise of personalized instruction is partially realized today. Our current teaching machines are programmed by smart authoring systems that can present and control media, animate, branch instruction, simulate real-world conditions in various degrees of fidelity, and report student performance through standards like SCORM, xAPI and CMI5. We also have virtual reality, which can immerse learners in some ‘real-world’ or imaginary context, and augmented reality, which can add a digital layer over one’s interaction with the physical world.

We also benefit from gamification, adaptive learning, learning experience platforms, learning management systems, microlearning, digital story-telling, three-dimensional graphics, and 360 imagery and video. In short, Teaching Machines have come a long way from questions displayed in a tiny window.

And yet there is still something significantly missing that would have benefited both Skinner’s daughter and my high school students…or any learner.

The Future

When it comes to the future, I’m on thin ice. I offer this up more as an invitation to hear from others who have greater insights than I. There is so much happening in academia, industry and in academic-commercial partnerships that I’m just not aware of. But I’ll briefly touch on what has been nagging me for years – and return to this theme in a later post with, perhaps, your contributions.

The problem, in my view, is in the finiteness of our present- day teaching machines. As an example, years ago, my colleagues put out a math series on interactive video disc, then later on CDROM, and then later on the web. The lessons were well presented and followed by numerous exercises in various topics like college-level algebra.

I observed students working through the math programs in Saint Paul College’s Instructional Technology Center. If students didn’t ‘get it’ from the presentation or the exercise feedback, they had little recourse. Fortunately, in some settings, a qualified instructor would then take over and help the student with a different tactic. I observed settings, however, where similar programs were being used but with underqualified tutors. If the students didn’t comprehend the lesson, that was the end of the line. The lab monitor was unable to help them.

A lot of topics rely on a student’s prior knowledge, which may or may not be present. In short, prerequisite skills.

Several years ago, a fleet of‘adaptive learning’ platforms appeared on the market that proposed to remedy this short-coming. (examples of adaptive learning systems include CogBooks, Acrobatiq, Knewton). A lot of investment and effort went into assessing student’s performance and confidence with the subject matter and providing alternative instruction. Some of the platforms catalogued open educational resources and used, what they called, semantic engines to match students with open resources to help them.

Adaptive learning systems are software platforms that optimize the content to adjust for the learner’s goals and current state of knowledge. They are designed to address challenges such as slow pace, difficulty, lack of practice, and insufficient mastery of content. In traditional e-learning courses, students linearly follow the path an instructor creates. They watch videos, read articles, take quizzes, and practice interactive modules often in a predetermined order. An adaptive learning system contains the same types of material but the order, pacing, and content may change for each learner. The system decides which content to show the learner based on the learner’s goal, performance and confidence level. If the system determines the current path is too easy for the learner, it can branch to more challenging material. If it finds out the current path is too difficult, it may intervene and review prerequisite content, reduce the challenge, or slow down the pace.

Most of these systems are proprietary and operate through subscription or a pay wall. Presumably, students who use them benefit from them but the modern teaching machine (i.e., authoring systems, Learning management systems, learner experience platforms) needs to tap into the same technology and benefit from open systems.

Work is being done to open-source systems that use such approaches as Bayesian Knowledge Tracing. Bayesian Knowledge Tracing is used in a number of Cognitive Tutoring systems. This approach develops a model of a student’s knowledge in a given domain and constantly updates that model based on the student’s performance. Probability of skill mastery can be computed from the student’s current knowledge and the proposed learning material. Efforts are underway to use these systems to link learning management systems with open content repositories.

A possibility in the future is that the entire web becomes the new teaching machine. In the past, several concepts and specifications rose and fell in popularity. We may see their renaissance. One concept was Tim Berners-Lee’s Semantic web.

The goal of the semantic web as it relates to education is to make content on the web machine readable – and therefore categorizable and discoverable. To support the description of educational resources several specifications exist including the Resource Description Framework, and the Web Ontology Language.

A recently published article titled ‘Investigating the potential of the semantic web for education: Exploring Wikidata as a learning platform’² explores the application of the semantic web in academic pursuits.

In short, if one could accurately describe educational content (which may reside in an open educational repository), then authoring tools, Learning Management Systems, adaptive systems, etc. could discover and propose the content to a student who is struggling to achieve an objective.

The key is in an accurate and meaningful description so that its appropriateness can be evaluated for a given student and a given objective.

In the past, we haven’t done well with descriptions, ontologies, taxonomies, metadata and the like. (By we, I mean the teaching profession.) Even the concept of the re-usable learning object (RLO) fell to criticism. A learning object was described by IEEE Learning Object Metadata specification. The LOM standard defined the attributes required to describe learning content. Unfortunately, learning objects were created without adequate descriptions (after all, what was the point?) and their reusability was called into question. In general, it’s possible that content authors don’t have the knowledge or the means to properly describe their content in a way that is meaningful to authoring, tutoring or adaptive systems.

The game-changer will probably be machine learning. Blogs have been filled with examples of how artificial intelligence has supported content generation. Another important use of AI will be to scan and describe open learning content.

For fun, I asked ChatGPT to parse some educational content on an electrical circuit and then provide me with a description that followed both the Resource Description Framework and then IEEE Learning Object Metadata. I then asked ChatGPT to come up with its own machine-readable schema that included keywords and reading level. The simple schema (markup in XML) is shown in the appendix.

The future Teaching Machine may be the semantic World Wide Web

Conclusion:

In my view, to personalize learning, the future Teaching Machine needs to tap into the World Wide Web as a resource to shore up prerequisite knowledge needed to achieve an educational objective. The systems can’t be proprietary. They must be open and available to a variety of platforms through an application programming interface (API). The platforms include authoring systems like LodeStar eLearning authoring system, Captivate, and Storyline as well as learning experience platforms, adaptive learning systems, cognitive tutors and learning management systems.

As importantly, the resources should remain in their repositories, but still report performance to a learning management system or learning experience platform. That is now possible through standards like CMI5, but — as I’ve lamented in the past — few learning management systems support CMI5.

The teaching machine began with limited content printed on paper disks. It progressed to include all of the affordances of the modern computer. Its future promise might lie in open standards that connect learner needs to appropriate content scattered across the globe.

References

¹Watters, A. (2021). Teaching machines the history of personalized learning. The MIT Press.

²Evenstein Sigalov, S., Nachmias, R. Investigating the potential of the semantic web for education: Exploring Wikidata as a learning platform. Educ Inf Technol 28, 12565–12614 (2023). https://doi.org/10.1007/s10639-023-11664-1

Appendix

ChatGPT generated XML schema for a learning resource on electrical fundamentals.

<educational_resource>

 <title>Understanding Electrical Fundamentals: Voltage, Current, and Resistance</title>

 <keywords>

 <keyword>Voltage</keyword>

 <keyword>Current</keyword>

 <keyword>Resistance</keyword>

 <keyword>Electricity</keyword>

 <keyword>Electrical Power</keyword>

 <keyword>Ohm’s Law</keyword>

 <keyword>Circulatory System</keyword>

 <keyword>Electrical Concepts</keyword>

 </keywords>

 <reading_level>High School / Early College</reading_level>

 <content>

 Just as your heart produces the pressure to make blood circulate, a battery or generator produces the pressure or force to push electrons around a circuit. …..(the remaining content omitted for the sake of brevity)

 </content>

</educational_resource>

Beyond Presentations and Puzzles … to Problems

Posted on October 10, 2023 by Robert "Bob" Bilyk

Introduction

The thrill of learner experience design is in finding the tools, techniques and strategies to engage learners with designs that go well beyond presentations and puzzles. Often learners must solve problems to achieve a performance or academic goal and it’s in the nature of the problem that we find the best-suited strategies.

I use the term ‘problem’ very broadly to encompass many different things. The late David H. Jonassen presented a typology of problems in his work, ‘Toward a design theory of problem solving’¹. He wrote that ‘learning to solve problems is too seldom required in formal educational settings.’ Even outside of formal education, we’re often asked to create presentations with assessments that cover some area of compliance whether it be data security, diversity in the workplace, or health and safety. But often we’re challenged with a training problem that can’t be addressed without engaging learners with the problem.

David H. Jonassen published many books on constructivism, problem-solving and learning with technology.

The Challenge

Our challenge is to develop the right thing that gets the best results with the least expenditure of time and money. We need strategies that are well-suited to the problem. Seasoned designers have a wide repertoire of strategies, templates, and models that can be used given a level of learning, type of learning, and type of problem. However, this industry sees new entrants every year² and the casual developer (an instructor, for example) may not have uncovered all of their options or know when to apply them.

What are the activity types that provide a situation, a problem to solve, and an activity that elicits student performance and constructive feedback? What are the activities that help designers and instructors engage students at a level that involves challenge, activity and feedback. More generally, what activities promote higher order thinking that allow us to integrate component skills into a coordinated response that enables us to complete tasks, analyze data, solve problems, and create things?

We have limited time and money. The quick solution to any higher order learning objective is to simply talk about it, present on it, show a video, hear from an expert, ask some questions, and then, forgive me, throw the learners in the deep end. Moreover, if we take the time to create an activity that makes the learner do things we may ask ourselves: was the result commensurate with the time and effort? In other words, given a learning objective and educational goal, the online instructor or trainer might wonder about the return of investment for a given strategy. For example, an instructor may ask ‘Is it worth my time to create an activity rather than a multiple choice test?’ And what would that activity be?

Our industry doesn’t make it easy. It turns out that the industry has many names for things. There is no standard taxonomy with precise attributes. And yet we can start with a few widely recognizable terms: Interactive case study. Decision-making scenario. ShortSims³. Simulation. Branching interaction. Interactive Non-Fiction.

Matching Strategies to the Problem

Our first clue that we need more than a presentation is that we’re asking learners to do more than just recall. We recognize a need to engage learners’ ability to analyze, apply, synthesize, evaluate, make decisions, create things – all of which requires thinking beyond simple recall. Of course, the learner may need to recall the right fact, principle, concept, or rule that is useful in a given situation. But it is the application of that information that is the key. We recognize that we need a story, a context, possibly varying levels of difficulty, and possibly a challenge in the form of incomplete information, confusion and stress.

So what’s the solution? The solution is suggested by the problem.

We can be guided by the nature of the problem that we want learners to solve or engage in. M. David Merrill tells us that ‘effective instruction is problem-centered’. Robert Gagné asserted that the point of education was to help learners become better problem solvers. Michael Allen emphasizes the importance of context (‘a problem-solving environment’) and challenge. Richard Mayer wrote that ‘a major challenge of education is improving students’ minds–a goal that is reflected in people being able to solve novel problems they encounter’.

In ‘Toward a Design Theory of Problem Solving’, David H. Jonassen creates a typology of problems – a useful tool that might help in the selection of instructional activities to promote problem solving.

Categorizing Problems

David Jonassen gave us a way to categorize problems based on problem variation. Does the problem have multiple solutions or only one? How many steps are included in the solution? Does the problem solution draw from multiple principles, concepts, or even disciplines? Does it require research beyond the content offered in a program of study? Is the problem domain specific – can it only be solved by learners who are schooled in a specific area of study — or is it general? Do learners need varying stages of support or scaffolding as they engage in the problem?

If we’re tackling one aspect of the problem, we can think of a key principle from ‘How Learning Works’ ³. Loosely, learners need practice on component skills and then practice with integrating them. Is our learning objective focused on one component skill or does it involve integration of multiple skills? If the component skill is simple enough, we might prescribe an activity like a word problem or matching type of exercise. If we engage students in a synthesis of skills, we’re going to need something more – something that has story (context) and multiple challenges. Jonassen recommends embedding instruction in some authentic context. Context is also a key element to the CCAF model.

Now we’re in the territory of ShortSims (generically, simple sims), decision making scenarios, interactive non-fiction, interactive case studies and other forms of interactions that place learners in realistic settings, challenge them, and make them do things.

A Document Management System was simulated with the LodeStar eLearning authoring tool that challenged new employees to find key documents based on varying search criteria

One way of rationalizing the design and development time relates to the complexity of thinking and acting …and the complexity of the problem.

In a ShortSim the learner is presented with choices. The choices can cause the narrative to branch or simply advance the narrative in a linear progression. Making better choices might cause the learner to recall past learning, read and analyze information while looking for clues. The learner might wonder ‘Is this an instance of, for example, the unconscious bias that I’ve been told about? If I make the wrong choice, am I compromising data security, risking my safety, … making my supervisor unhappy?’

A ShortSim can engage the learner in some pretty advanced stuff with the clever use of graphics, text and choices.

Clark Aldrich wrote a How-To book, ShortSims,
that walks designers through the process of planning and producing
a simple decision-making simulation. Full reference below

Further down the continuum of simulations, our learning objective might require the learner to make decisions in an environment that includes many variables. The underlying model might not be a finite set of choices but a complex interplay of multiple variables. The activity might require a coordinated, intelligent response to an infectious disease outbreak, for example. The underlying model might be the SEIR model, which represents a population that is susceptible to a specific disease, exposed, infected and partly recovered. The learning program might vary the number of treatment days, incubation period, contacts per day, and fatality rate. The learner might need to observe the data and then prescribe a response. The computer environment can present one scenario from a nearly infinite number of possible scenarios.

The choice of one strategy over the other can relate to the complexity of the problem we are wanting learners to solve. Jonassen helps us here. The level of realism and variability of the problem will require increasingly more sophisticated (and time-consuming) designs.

Logical problems that require students to recall information might suggest a word game, a crossword puzzle, or a multiple-choice quiz.

Algorithmic problems require learners to progress through a series of procedural steps and this might suggest a ShortSim or decision-making scenario.

Story problems with embedded procedures might suggest word problems or interactive fiction or non-fiction that houses word problems in a longer narrative.

Rule-Using Problems and Decision-Making problems that involve defined procedures and methods can be handled with ShortSims, other forms of interactive branching and decision-making scenarios, and role-playing.

Trouble-shooting problems can begin with interactive trouble-shooting guides or low fidelity simulations but when the problem state has variation and complexity then a virtual lab or full-blown simulation might be needed that can a) generate variable states, b) represent those states to the learner in the form of dials, instruments, changes in the environment, changes in characters, etc., c) elicit learner response and d) and provide feedback in the form of dialog, pop-ups, and/or changes in the environment.

Case-analysis problems can be presented through problem-based learning scenarios, historical case analyses, interactive case studies in which the learner is presented with case descriptions and data and asked to accomplish a goal.

Additional forms of problems in Jonassen’s typology include design problems and dilemmas. The types of problems can certainly be expanded to include additional categories of problems: for example, strategic performance problems that involve business simulations and strategy games. And the list goes on …. all beyond presentations and puzzles.

Conclusion

After the designer has looked at the learner, the learner’s environment, the performance goal, the gap analysis, etc., the performance might be whittled down to a problem type that the learner may need to solve. The problem can range from providing performance feedback to evaluating equations, from delegating authority to applying statistics to improve production. The type of program often suggests the treatment. The fun of being a learning experience designer is in exploring strategies and applying them where appropriate in a cost-effective, time-saving manner.

In past articles, I have covered some of these strategies. You’re welcome to visit them.

ShortSims

Interactive Storytelling

Interactive Case Studies

Decision-Making Scenarios

Simulations

References

¹Jonassen, D.H. Toward a design theory of problem solving. ETR&D 48, 63–85 (2000). https://doi.org/10.1007/BF02300500

²In a 2021 survey held by Devlin Peck (n=615) (Instructional Designer Full Report 2021 | Devlin Peck), 44% of the respondents had 0 – 3 years’ experience.

³Aldrich, Clark (2020) ShortSims, CRC Press

⁴ Ambrose, S., Bridges, M., & Lovett, M. (2010). How learning works: 7 research-based principles for smart teaching. John Wiley and Sons.)

Designing with Animation

Posted on April 29, 2023 by Robert "Bob" Bilyk

Animation can enrich the learning experience and, when used appropriately, improve learning outcomes. New standards and new technology under the hood of the modern browser give learning experience designers a whole new set of tools and techniques to apply to their designs. I’ll parse out the different types of animations and their uses, discuss the underlying technologies and present examples.

To start, let’s reprise Richard Mayer, the author of Multimedia Learning.

Mayer defines a concise narrated animation. He explains that concise refers to a focus on the essential steps in the process. If the objective is related to understanding how a four-cycle engine works, then a concise animation would include only the details that related to the objective. For example, I might include a simple animation of a piston traveling up and down a cylinder, compressing gas, power stroking from the combustion, exhausting the spent fuel and then refilling with fresh gas.

Wikimedia Commons ((CC BY-SA 3.0)

Concise in this example means that we focus on the crankshaft, the traveling piston, the ignition, the intake and the exhaust. The learner is not distracted by anything not related to the objective

The image above is an animated GIF. Most authoring tools can easily import an animated GIF. This technology, however, has its uses and its limitations. It is difficult to use the animated GIF in a concise narrated animation because it is difficult synchronizing the 4 cycles with the narration. If you understand four-cycle engines, the GIF makes sense. If not, then narration will help learners understand each cycle of the process. Fortunately, there are easy ways to sync animation with narration. This brings us to the timeline animation.

Timeline Animation

The basic idea behind a timeline is that you control animation effects according to time. In tools like Storyline, each row of the timeline represents a different screen element. You can then apply entrance and exit animations to the screen element at specific times.

The timeline in our authoring tool, LodeStar, works differently. LodeStar displays one timeline per graphical element. Each row represents a different property such as left, top, opacity, rotation and scale. With these five properties you can control the position of an element on the x and y axis at a specific time and you can control fade-in and fade-out, rotation and size. These are the properties that designers typically want to animate.

In the screenshot below, you can see that I have two gears. A left gear and a right gear. When I select a gear or choose it from the lower right pull-down menu, I get its corresponding timeline.

As you can see on the timeline, each row represents a different property.

LodeStar Animation Editor with SVG graphic

To understand the positioning properties, we need to understand the difference between the SVG image and its sub-elements. We also need to understand other types of images like PNGs, GIFs, and JPEGs. These are called bitmapped or raster graphics because that is precisely what the graphic is: a map of binary digit (bit) values for every colored pixel. The rules for positioning bitmapped graphics and SVG elements differ.

To understand this, let’s first tackle the SVG graphic.

SVG

SVG stands for Scalable Vector Graphics. It is a vector image format that can be scaled up or down without losing any image quality. This is different from the bitmap or raster graphics which are made up of pixels and can become pixelated or blurry when they are resized.

SVG graphics are great for logos, icons, and other types of graphics that need to be scalable and look crisp at any size. They can also be easily edited with text editors or graphic design software, and they support interactivity and animation through script.

We can think of an SVG graphic in two ways: as a whole image or as a collection of elements. Examine the SVG image of an old Buick below. The automobile can be animated from left to right, for example, like any bitmapped graphic.

We can do that with a timeline:

The timeline shows a duration of 5 seconds. At 0 seconds the car’s left property is 1. That means 1% of the width of the window. At 5 seconds, the left value is 100%. This means that the left edge of the graphic will be at the right edge of the window – in other words the car rolls off the screen.

This animation would be less than satisfactory because the tires don’t rotate. So, if we only animated the entire graphic we’d get an inferior result.

That now brings us to SVG elements. Loosely described, these are the sub elements of the SVG graphic. They consist of polygons, lines, rectangles, ellipses, paths, layers, groups, and more. In the screenshot below of LodeStar’s SVG editor, we see that the rear tire is selected. It has a cryptic id, which we can change to an easier name. Whatever the name, this element is both programmatically addressable (meaning we can change it with a simple script) and it is separately animate-able. For example, we can rotate the tire. Now we can move the whole graphic from left to right and rotate two of its sub-elements to improve the animation. (You will see this in an animation sampler introduced in the conclusion.)

Bitmapped Graphics

Bitmapped graphics, also known as raster graphics, are digital images made up of tiny colored squares called pixels. Each pixel represents a small portion of the image and can be assigned a specific color value. Generally, only programs like Photoshop allow us to manipulate bitmapped graphics at the pixel level. Examples of bitmapped graphics are PNGS, JPEGs, and GIFs.

With bitmapped graphics we can animate the entire graphic’s position, opacity, rotation and scale. But we can’t take one of its subparts (a small sub-section of pixels) and independently animate that section. At least, not without sophisticated code. Nevertheless, bitmapped graphics have their advantages. Any photorealistic image is best captured in a bitmapped graphic.

The animate-able properties

In LodeStar, the meaning of left and top differ between SVG graphics and bitmapped graphics. To best explain this, we need to place images in three categories: the entire SVG graphic, an SVG element (sub-element) and bitmapped graphics that are not inside an SVG graphic.

For SVG elements, left means a translation or change along the x axis. 1 means that the graphic has shifted 1 pixel to the right. 100 means that the graphic has shifted 100 pixels to the right.

For images (including JPEGS, PNGS, GIFS and the SVG graphic as a whole), left means the percentage of the window. 0 means that graphic is painted at the very left of the window. 50 means that the graphic is painted half-way across the window on the x axis. The reason for the difference is that LodeStar projects maintain their responsiveness to different devices with different screen widths whenever possible.

Technically, when we reposition an image, we are removing it from its normal place in the HTML document. When we assign a timeline to an image, we are removing it from the HTML flow and assigning it an absolute position.

If you didn’t want to remove the image from the flow (its position in the document), then you can lock the image position in the image dialog.

An absolute position means a position relative to its parent. If its parent is 1000 pixels wide, a left position of 10 places the image 100 pixels to the left of its parent’s left edge. If the image is positioned beyond its parent’s boundaries, it is hidden.

SVG elements are displayed inside a viewbox. We transform the position, scale and rotation of these elements without removing them from the flow. They are painted or shown inside the viewbox. If we shift the position beyond the boundaries of the viewbox, the element is clipped or hidden.

For SVG elements it is important, when adding a left, top or rotate keyframe to also add a keyframe at the same time offset for the other two properties. SVG transformations (change of position and rotation) are defined by all three properties.

Controlling animations with script

LodeStar animations can be controlled by the timeline, as we’ve seen in the example above. They can also be controlled by script or by a combination of timeline and script.

Let’s return to the gears example. In this example there are two SVG elements inside an SVG graphic. In the example, the SVG graphic is not animated at all. However, its elements (the gears) are positioned and rotated. One gear is rotated from 0 to 360, the other gear is rotated from 35 to -325. This causes the gears to rotate in opposite directions at a slight offset from one another so that they mesh.

A separate timeline for each graphic or SVG element

In the example we also positioned a rectangle with rounded corners at the bottom of the viewbox. We are treating this graphic as a button. We added a branch option to the rectangle, which converts it into a button that responds to clicks.

The branch option that we applied to the rectangle is called a ‘Select Branch Option’. When clicked, the button executes the following script:

appendValue(“rate”, 1);
var rate= getValue(“rate”)
updateAnimation(“1681686408319”, “play”, “”, “”,10, rate);

In this script, we are adding 1 (appending) to a stored value named “rate”. We then get that value from storage and assign it to a variable named ‘rate’. ‘var’ means variable.

In the third line we use the variable in a function called updateAnimation(). This function allows us to

Identify a page by a page unique identifier called a UID.
Set the state of the animation: play, pause, or reverse
Optionally we can set the current time in the animation. By default it starts at 0 seconds. That is why we use “” in the function and don’t bother setting the current time.
Optionally, we can also state the duration of the animation. By default, the duration is set by the timeline. We therefore use “” in the function. We could shorten or lengthen the duration.
We set the number of iterations or the number of times the animation repeats.
Lastly we set the rate. A rate of 1 is standard. A rate of 2 is twice as fast. Every time we click on the button, the animation speeds up. The gears turn faster.

Controlling animation with LodeStar Script

Animation synced with narration

In the next example, graphics are synced to different points in the narration with the use of the timeline.

Modern browsers now offer us fast and efficient animations and audio support with the ability to synchronize the two. This is a significant development in the web platform.

In the example below, the author added a narration and a SVG graphic to the same LodeStar page. In the SVG graphic, the piston, connecting rod, crankshaft, valve, etc. are all SVG elements. As you can see in the screenshot, the crankshaft is selected and shows an ID of ‘crank2’. This helps to identify the element in the animation editor.

After the audio narration was imported and the SVG graphic created, the author launched the animation editor. The play button now plays the audio narration and the animation. The author can pause the narration and add keyframes to control the position of the piston, the position and rotation of the connecting rod and so forth.

The pivot point or anchor point of the connecting rod is changed with the following buttons TL, TR, C, BL, BR. These buttons place the pivot point top-left, top-right, center, bottom-left, and bottom-right respectively. Essentially, we are pinning down the center or a corner so that the rotation happens around this point. Under the hood, we are really changing the transformation origin. The transformation origin is the point around which a transformation such as a rotation is applied.

Listening to narration in Animation Editor and adding keyframes to control position, opacity, scale and rotation

Finally, once a timeline is created for an element it can be given a unique identifier and applied to any element with script. For example, if I rotated a rectangle with a timeline on one page, I could apply that animation to a triangle on another page — with the use of script. The script function is webAnimate. (See appendix A)

Conclusion

In the sampler linked below, we can see multiple uses of animation. On page one, we see a simple decorative animation of an attitude indicator or artificial horizon used in airplanes. You can easily imagine how this can be applied to a simulation.

One page two, we illustrate how an SVG graphic is moved from left to right while its elements (the tires) are rotated.

On page three is the gear example. Click on the faster button repeatedly to see a demonstration of how we controlled speed programmatically by changing rate..

On page four we have a simple graphic with foreground and background synced to an audio file.

One page five, we can immerse the viewer in a scene with the use of parallax. Parallax is a visual effect where the background of a web page appears to stay still or move in the opposite direction of the foreground.

Finally, on page six we show a narration synced to an animation. Pausing or replaying the narration causes the animation to pause or reset. The narration and animation are synchronized.

(Best viewed in Chrome, Edge, and Safari)

Animation Sampler

https://lodestarlearning.github.io/Animations/index.htm

Author’s Note:

Animations were done in LodeStar 10 (Beta Build 5). Secondly the script for the 4-cycle engine explanation was generated by ChatGPT, and the narration was text-to-speech using Amazon Polly.

Appendix A

webanimate(elementid, timelineid, duration (optional), direction (optional), currentTime (optional), position (optional), callBack (optional))

animates the element’s css properties based on a timeline creating with the animation editor, where id is element ID (no hashtag), timelineid is the id of an existing timeline created in the editor, duration is the length of the animation in seconds, currentTime is where to start the animation in seconds, position is the css position property which is usually set to ‘absolute’ to support top and left movement, and callBack is the name of a page whose branch options will be called when animation finishes.

The Role of Artificial Intelligence in Learning Experience Design

Posted on February 2, 2023 by Robert "Bob" Bilyk

Introduction

I recently asked ChatGPT to list the five most influential instructional designers.

ChatGPT, of course, is an artificial intelligence chatbot that has grabbed the attention of the world. Locally, it was put to the test by University of Minnesota Law School. It answered questions from law school exams in several legal subject areas and when judged blindly, it earned a C+. On every front, businesses and institutions are assessing opportunity – and risk. (New York City has blocked ChatGPT on school devices and networks*.) Every news outlet is talking about it. Artificial intelligence has stepped off the silver screen and into our lives in a new way.

ChatGPT Lists 5 Influential Instructional Designers

I’ve asked ChatGPT several questions over the past two months. But last evening, I turned its attention on instructional design and learning experience design.

So, I ask it: who are the five most influential instructional designers.

Here was ChatGPT’s reply:

Influential Instructional Designers:

Richard Mayer – Known for his work on multimedia learning and cognitive theory of multimedia learning, Mayer has made significant contributions to the field of instructional design.

Clark Aldrich – A pioneer in the field of simulation-based learning, Aldrich has designed numerous training programs and simulations that are used widely in corporate and military settings.

Michael Allen – The founder of Allen Interactions, Allen has designed over 1,000 e-learning courses and is known for his work in instructional design and performance support.

Julie Dirksen – Dirksen is a leader in the field of user experience (UX) design for learning, and has written several influential books on instructional design and UX.

Will Thalheimer – A researcher and consultant, Thalheimer is known for his work on evidence-based instructional design and his writing on instructional design best practices.

The five designers listed are certainly influential. In our Learner Experience Design graduate courses at Metropolitan State University, we’ve included the writings and/or texts of Clark Aldrich, Michael Allen and Julie Dirksen. In working with faculty, I’ve used research from both Richard Mayer and Will Thalheimer.

And so, I liked its answer and my curiosity was piqued. To explore further the role of AI in Learning Experience Design, I wondered if ChatGPT could provide content for a quick lesson on that very topic — Learning Experience Design. (It also gave me the opportunity to take the latest nightly build of LodeStar 10 on a little road test.)

The query produced interesting results.

Disclaimers

Before I show that content, a few admissions and disclaimers. First, I’m not advocating for the use of AI in the instructional design process. In the near future, I will certainly evaluate its utility. Secondly, in my example I offered ChatGPT no directives. I didn’t specify grade level, target audience, prerequisite knowledge, cultural or situational context. I simply asked it to spit out information.

A further admission is that I’m very uneasy about the topic of artificial intelligence. AI obviously presents both opportunity and challenge. I have a dystopian dread over AI and yet I recognize the many opportunities that it presents. I’ve long held out hope for truly adaptive learning systems that could individualize the scope and sequence of instruction for the benefit of learners. Many systems have appeared on the market with ‘semantic’ engines that don’t quite measure up to a system that can learn from a students’ successes, missteps, preferences and confidence level, and make appropriate decisions. Adaptive Learning is one area that benefits tremendously from AI.

The other thing I recognize is that the information that ChatGPT prints out is, at best, raw material for an instructional designer. The design must include learning experiences that help students engage with the material, think critically, make decisions, make meaning, and make memory.

David Wiley blogs about this more eloquently in AI, Instructional Design, and OER – improving learning (opencontent.org). Here is an excerpt from his blog:

“What distinguishes an educational resource from an informational resource is that the latter shows some intentional application of knowledge about how people learn. I have previously argued that the minimum amount of effort you could invest to convert an informational resource into an educational resource was to add practice with feedback. That simple sounding task quickly explodes in complexity as you consider the research on what form that practice should take, how long it should last, when it should be scheduled, what kind of feedback should be provided, whether the feedback should come immediately or after some delay, etc.”

David Wiley

That leads to my biggest disclaimer. Just for fun, I wanted to see what ChatGPT would produce and how I could use it in a project with minimum effort.

David Wiley writes:

“LLMs will dramatically increase the speed of creating the informational resources that comprise the content infrastructure. Of course the drafts of these informational resources will need to be reviewed and improvements will need to be made – just as is the case with all first drafts – to insure accuracy and timeliness. But it appears that LLMs can get us 80% or so of the way to reasonable first drafts orders of magnitude faster, eliminating the majority of the expense involved in this part of the process.”

I took the ChatGPT output and sprinkled in some activities. The disclaimer is that these are not activities that any of the above authors would endorse. The design is just a simple present-and-check. But I would hazard to say its not unlike the content that gets pumped out by course mills. It’s not unlike the content that one consumes to meet a compliance check or earn continuing professional education credit. It’s not unlike most of the stuff out there that our 5 influential instructional designers decry.

In doing this short exercise, I was reminded of David Thornburg’s often quoted “Any teacher that can be replaced by a computer, deserves to be.” Perhaps, any instructional designer who can be replaced by an artificial intelligence chatbot deserves to be. Or perhaps the real line of enquiry should be: can a chatbot be trained to make decisions that imitate an instructional designer? Can a chatbot be trained to pass the LXD equivalent of a Turing test? (See appendix A for what happened when I gave ChatGPT more information about the audience.)

But disclaimers aside, it is intriguing to me to view what ChatGPT produced.

Rules of Engagement

Here were my rules when applying the content:

Spend very little time (under two hours)
Retain all of ChatGPT’s text – even if there were errors (example, Bloom’s Taxonomy was produced in 1956, not the sixties.)
Format the content in different ways, including placing it in a time line
Add videos or audio from external sources to supplement ChatGPT and provide some human connection.
Return ChatGPT’s content to the engine and ask ChatGPT to create a final quiz from that content

You can see this for yourself by clicking on the following link and/or joining me on a screen-by-screen tour (not all screens shown).

Link to content: Learner Experience Design ChatGPT (lodestarlearning.github.io)

Screen by Screen Commentary

First, in my title screen, I give full credit to ChatGPT.

I asked ChatGPT to explain instructional design versus learning experience design. I simply presented the information as a choice between two explanations: one that matched Learning Experience Design and the other that matched Instructional Design. ChatGPT provided the content; I added this little warm-up learner engagement.

I added ChatGPT’s definition of What is Learning Experience Design.

I then added a video from YouTube so that we have an LXD person describe the characteristics of LXD. This reinforces the information and humanizes it.

I asked ChatGPT to list the important events in the history of Instructional Design. It put out a list of events. Interestingly, the earliest event was the publishing of Didactica Magna in 1600s. I took that information and presented it in an interactive timeline.

ChatGPT output the importance of Learner’s Needs and Goals. I added a video where the host really challenges his guests on how LXD designers actually translate goals and user research into meaningful experiences.

ChatGPT output an explanation of instructional methodology. I did a strike-through on key words and asked LodeStar to convert them into fill-in-blanks. I then provided a randomized word list. So rather than just reading, the learner has to think about the context and type in the appropriate word.

To supplement ChatGPT’s explanation of Technology and Tools, I added a podcast of instructors talking about the use of technology and tools in response to COVID.

In the Assessment and Feedback session I added a word problem related to calculating the volume of a cylinder (as an example). The dimensions of the cylinder (radius and height) are randomly generated from a defined range. Students can work on these problems all day and always get a new set when they refresh the lesson.

For User Experience and Interaction Design, ChatGPT spat out content and I added a slideshow viewer of three interesting designs.

Finally, I gave back ChatGPT ‘s content and asked it to produce an assessment. I then took the question stem and answer options and fed them into a Multiple Choice/Multiple Select Question Widget.

Most of the activities were assigned a point value. I then added a report page to send this off to either a Learning Management System or a Learner Record Store (CMI5/xAPI).

LodeStar Report Page supports SCORM and CMI5/xApi reporting

Finally,

I submitted the content to Open AI’s text classifier so that it could determine whether or not the content was possibly AI-generated.

Here is the result:

*OpenAI announced the AI Text Classifier to help determine whether or not content was AI-generated

Conclusion

OpenAI already offers specific application programming interfaces (API) to its language processing engine. For example it offers auto completion in its Text Completion API. OpenAI is now inviting developers to its waiting list to use ChatGPT in new and existing applications. One can easily imagine the day when toolmakers will invoke the API commands in order to, in David Wiley’s words, “dramatically increase the speed of creating the informational resources that comprise the content infrastructure”.

We’ve just completed LodeStar 10 and continue to test it. We have no current plans to interface with AI but have been added to the waiting list by OpenAI to explore ChatGPT API capabilities. Who knows where that will lead? In the meantime, our focus is to help designers start with simple projects and then offer them more capability as their designs grow from simple present-and-checks to short simulations, story-telling, decision-making scenarios and CCAF (Context Challenge Activity Feedback) projects that the five influential instructional designers would endorse. As far as AI is concerned, we have a lot to learn about the role of AI in learning experience design. I would love to read your comments.

Doubtless, the course mills will go into overdrive on this technology. Caveat emptor.

Appendix A

In a second attempt I gave ChatGPT a little more information about the target audience.

Here is my prompt:

Write about Learning Experience Design for an audience of high school students who know very little about instructional design or cognitive science. Write at an eighth grade level.

Here is ChatGPT’s response:

Learning Experience Design is all about creating educational experiences that are engaging, effective, and enjoyable. It’s a field that combines ideas from instructional design and cognitive science to help people learn new things.

Think about it like this: have you ever taken a boring class where you couldn’t stay focused or retain information? That’s where Learning Experience Design comes in! The goal is to create lessons that grab your attention and make you remember what you’ve learned.

The designers use research from cognitive science to understand how people learn best. For example, they know that people remember information better when they’re actively engaged in the learning process, instead of just passively listening. They also understand that people remember information better when it’s presented in a way that makes sense to them and connects to their own experiences.

So, Learning Experience Design combines these ideas to create learning experiences that are tailored to the way people learn. This might include interactive activities, simulations, games, videos, and more. The goal is to make learning a fun and memorable experience that sticks with you, so you can use what you’ve learned in the future.

Overall, Learning Experience Design is a field that’s all about making learning better. If you’re interested in making education more exciting and effective, this might be a great field for you to explore!

When I asked ChatGPT to comment on the reading level of this example, it answered:

This content is appropriate for high school students or early college students.

When I applied the Flesch-Kincaid Reading Grade Level test, it scored 10.4. Just saying.

Top Influences on the Development of LodeStar 10

Posted on January 6, 2023 by Robert "Bob" Bilyk

Introduction

Modern web pages offer designers a rich palette of media types and standards to create engaging learning experiences. The web page has become an amazing success story. It started as a battle ground of competing standards and self-interests and has arguably matured to become a meeting ground.

If you aren’t on the bleeding edge, you’ll benefit from the convergence of standards. In CanIUse.com, browser support for many enabling technologies such as SVG and WebGL (explained later) shows up as green tiles across the table of browsers. Green means these technologies are commonly supported, which is good news because learning experience designers can put these technologies to work.

caniuse.com by Alexis Deveria, available under a Creative Commons Attribution 4.0 License

Many of today’s eLearning projects are essentially webpage applications with additional standards that support communication to learning management systems or learner record stores. Many of the technologies that make the web interactive, responsive, accessible, and expressive are the same technologies used in eLearning applications. Most of the major eLearning authoring systems are web page design systems for web pages that are hosted in learning management or content management systems. There are many exceptions, of course, which include augmented reality systems, gaming engines and environments, and other virtual spaces that are not built on HTML5. But let’s stay focused, for a moment, on the web.

For maturing standards, the web has become a place of agreement. In the not-too-distant past, basic HTML markup and styling had to address the many differences between browsers and how they interpreted the World Wide Web Consortium (W3C) standards. Even a technology that most of us take for granted, the audio file, was once unsupported by a single file format that every browser could play. Designers had to choose both an audio format and a fallback format. Thankfully that has changed. All browsers can now legally play the .mp3 file or the HTML5 Ogg Vorbis audio format.

Soon the .m4a audio file (AAC) will be supported by all browsers and offer even higher quality audio at less the data cost.

But audio is only the beginning. All modern browsers (IE 11 excluded) support GIF, animated GIF, JPEG, PNG images, animated PNG, and motion video in the MPEG-4/H.264 video format.

All browsers support the language features of the last major revision to JavaScript. JavaScript is the code that makes the web interactive. It is the code that makes eLearning projects interactive. Standardization allows all of us to benefit from the interactions that eLearning authoring tools produce with less worry about browser and device differences. (I emphasize less worry because there is always something to worry about.)

Interactive 3D has become a new frontier for eLearning. All major browsers support WebGL, which is a method of generating 3D graphics using JavaScript and hardware acceleration. In the early 90’s, when I first created 3D worlds, I needed an entire lab of computers dedicated to rendering three-dimensional meshes into an animation of three-dimensional images that we would transfer onto a laser disc. Today, WebGL enables us to render a mesh into a rotatable, scalable image in real-time, all in a browser. If you’re not familiar with WebGL, please read on.

In short, Learning Experience designers, instructors and trainers can now use audio, video, imagery, text, three-dimensional graphics, scalable vector graphics, math mark-up, interactivity, and logic to realize their grandest designs and create engaging experiences for their learners.

On the eve of LodeStar 10’s release, I am taking stock of these standards and other influences that had a strong bearing on where our product is headed. Like all toolmakers, I am keeping an eye on effective strategies as well as emerging and maturing technologies and am imagining the opportunities for designers as we work to make these technologies practical and accessible.

Here is a list of standards and strategies that are central to LodeStar’s current development.

Scalable Vector Graphics

A lot of our development has focused on Scalable Vector Graphics. SVG offers the designer many benefits. Simple graphics such as the famous SVG tiger pictured here keep their sharpness regardless of the display size and the resolution. They are scalable. They also offer more opportunity for accessibility. Scaling can help learners with low vision. The SVG title is readable by most screen readers. Also importantly, the SVG graphic is made up of individual elements whose properties can be changed by program code or user interaction.

In the screenshot below, the tiger graphic is opened in an SVG editor in LodeStar. The author has right-clicked on an eyeball and can now choose branch options based on selection, deselection, drag, hover over and hover out. All of LodeStar’s branching options and script can be executed based on any of the above events. For example, based on the click of an eye, things can happen: the eye color changes, an audio description plays, an overlay appears with a complete description of a tiger’s vision and so on.

With LodeStar, designers edit SVG graphics and add interactivity

Importing PowerPoint as SVG

We’ve never been huge fans of starting an eLearning Project as a PowerPoint. That hasn’t changed, but LodeStar10 does support importing a single PowerPoint slide or an entire PowerPoint presentation as a series of SVG pages.

PowerPoint supports exporting a slide or series of slides as SVG.

LodeStar 10 adds support for importing a single SVG image or an entire folder of SVG images. LodeStar interrogates each slide and looks for things like Base64-encoded images. PowerPoint converts imported images to a long string of characters called Base64. This is a great format for transporting images inside a single file but browsers tend to load and render Base64-encoded images very very slowly. LodeStar detects the Base64 encoding and then translates the characters back into an image file that is loaded into the project.

The result is that vector graphics are editable as SVG elements, and embedded images load and display quickly. The designer can display the slide as is, edit elements and add branch options to elements.

Designer edits a PowerPoint slide in SVG editor

MathML

For a short while, all browsers supported the MathML markup language, enabling markup without the need for add-ons.

But there have been setbacks. We’re looking forward to when MathML is once again available in all browsers. Given the likelihood of that, LodeStar continues to support MathML.

MathML (Mathematical Markup Language) is supported by W3C as the preferred way of displaying mathematics on a web page or eLearning application. MathML describes structure and content of mathematical notation and provides for a higher level of accessibility than simply displaying an image. Designers can quickly edit and manipulate the size of a MathML expression. This is an improvement over taking a picture of an equation, for example, and pasting the image into a presentation. In the past LodeStar automatically converted expressions into images or it used the MathJax library to convert expressions written in Latex to MathML. But now we’re banking on full support for MathML in the near future.

SimpleSim

For years, LodeStar offered the Interviewer Page Type to support what we called decision-making scenarios and simple simulations. We continue to offer that page type but have expanded the number of layout options for interactive decision-making.

For starters, we added a new page type called the SimpleSim. This page type supports graphics, interactive widgets, text and whatever else is needed to set the scene. At center stage is the situational prompt and three decision options (as pictured below). All of LodeStar’s branching options can be invoked based on the learner’s choice. For example, the ‘Jump to Page’ branch option can bring up a scene that matches the choice and advances the narrative. Branching options also allow us to add feedback, keep track of points, collect user responses and so forth.

To style the scene shown below, the author used a palette for the color scheme, added a header graphic through Tools>Themes, selected a layout style that set the window width and navigation at the top, and added a background graphic. The use of palettes, themes, layouts and page types enables the author to control every aspect of this simple simulation, including the interactivity.

Look and feel is controlled by Layout, Theme, and Palette

CCAF

It’s no secret that we are huge fans of Dr. Michael Allen’s Context-Challenge-Activity-Feedback model. In a project that was intended to improve employees’ social sales index (SSI) in LinkedIn, we set the context as a simulated LinkedIn. For the challenge, the learner must improve the main character’s SSI score by providing the right advice and interacting with a simulated profile, notifications, messaging, etc. – just like LinkedIn!

CCAF projects are not page turners or Present-and-Checks. They can be quite advanced. To support a more sophisticated interaction than the display of content and multiple-choice questions, LodeStar offers LodeStarScript, which can be written in the Execute Command branch option.

LodeStarScript enables designers to change the properties of graphics on the fly, including SVG graphics. Properties can include color, position, image source, rotation, opacity, etc. LodeStarScript offers the designer the power of conditional logic, loops, local and global scoped variables, and a long long list of functions.

In the simulation below, the learner can select a camera aperture and control exposure. The effects of exposure are simulated with the simple change of the color and opacity properties of an SVG element.

xAPI/CMI5

Megan Torrance, a veteran of learning design, authored a research paper sponsored by the Learning Guild. I won’t steal her thunder and encourage you to read the paper for yourself, but I’ll cite two statistics from her research that tell the story of xAPI.

https://www.learningguild.com/insights/289/2022-the-state-of-xapi-adoption/?utm_campaign=researchAPI&utm_medium=link&utm_source=lspub%20

In a survey of 368 respondents, the majority of whom belong to organizations that create or purchase learning solutions, 44.9% of the respondents indicated that ‘We are interested in xAPI but have not used it at all.”

Version 1.0 of xAPI was released way back in 2013, and yet 10 years later adoption is not widespread.

So what is xAPI, how does it relate to CMI5, and why are we so interested in it? In short, xAPI and CMI5 are game changers. They are not the same thing but they are close cousins. An eLearning activity that uses CMI5 can generate an xAPI statement, which gets recorded in a Learner Record Store. CMI5 can also tell the LMS whether the learner passed or failed.

So, let me be a little more specific.

With these technologies, I can store my eLearning projects in my own repository — GitHub for example. I can then import a very lean and simple file to the Learning Management System, which tells the LMS from where to launch the activity. The LMS then passes to the activity learner information and a token for secure communication.

CMI5 uses xAPI technology but it also understands the vocabulary that LMSs require. Pass/Fail. Incomplete/Complete. xAPI reports to a learner record store any statement that the designer has added to the eLearning activity. ‘Learner has reached Level Two. Learner completed a video. Learner attempted Level Three four times.’ CMI5 can generate any kind of xAPI statement in the form of learner actions. In addition, CMI5 can tell the LMS whether the learner passed and/or completed the module.

But among the reasons why people don’t yet use it are: lack of knowledge, lack of Learner Record Store, and LMS does not support it.

I am extremely fortunate in that our Learning Management System is Prolaera. It is designed for the CPA industry. Prolaera can import a CMI5 activity. As a result, I can do the following:

Send a statement about the learner reaching Level 5 to the learner record store.

Read a list of learner experiences from the Learning Management System’s Learner Record Store. (the learner’s name has been erased from the screenshot).

From the screenshot above, you can see that we can report on any learner experience. For example, the learner first experienced the results page with a score of 200 points. We can also see that the learner passed, satisfied the requirements, completed the module and terminated the activity. These are all terms that the Learning Management System understands.

It may take time but CMI5/xAPI will eventually be widely adopted. These standards are incredibly important to the advancement of eLearning. It begins with awareness. The more designers learn about it, the more they can encourage their learning management system vendors to support it. In the meantime, we are ready for it!

3D

Glen Fox’s Littlest Tokyo is a great example of what is possible with Three Dimensional objects viewed jn a browser. The object is beautifully detailed with a running streetcar animation as an integral part of the 3D object.

Designers will be able to use free tools like Blender, TinkerCAD, Sketchup or even their smartphones to produce 3D meshes.

Smartphones like iPhone 12 come equipped with LIDAR. LIDAR emits a laser pulse that reflects off of solid surfaces and returns to a sensor on the smartphone. The round-trip duration is noted. From that, the software can accurately position the solid surface in three-dimensional space. LIDAR has been available in specialty instruments for a long time but for designers to be able to use this technology practically, the software needed to improve.

In whatever way the 3D model gets created (3D graphics software, downloaded from a warehouse, generated by LIDAR) it can then be loaded into a viewer and manipulated (scaled, rotated, navigated) by the learner. Imagine vital organs or historical places or complicated machines as manipulable objects.

Currently, we’re working on a loader and viewer for 3D Models. The first LodeStar 10 release won’t include a 3D model viewer, but we’ll introduce it later in a minor release.

In the meantime, we do support photospheres. Photospheres use the same underlying technology: WebGL. WebGL enables hardware-accelerated physics and image processing and rendering onto the HTML5 canvas. The hardware is a dedicated processor called the Graphical Processing Unit or GPU.

The photosphere that appears in the screenshot shows a distorted view of an art gallery. The first art gallery image (shown below) was produced in Blender. The second art gallery image was taken with an iPhone at the Minnesota Marine Art Museum in Winona.

The image appears distorted – in fact, spherical.

Once in LodeStar, the designer can add images, markers, and hotspots to the photosphere. All of these things get correctly positioned on the sphere.

In the LodeStar editor below, I am adding Lawren Harris’ paintings to the gallery as well as hotspots. A hotspot click takes the learner to another room in the gallery. A click on the painting brings up an image overlay. A click on the video graphic starts a video.

LodeStar editor adds interactivity to Photosphere

The end result:

Interactive Art Gallery on the Group of Seven

Conclusion

2023 marks the twentieth anniversary of LodeStar Learning. We filed with the Minnesota Secretary of State on March 11, 2003. I’m pleased that LodeStar has adapted to all of the technology changes over the years. LodeStar began as code embedded in Lotus’ LearningSpace. It then enabled instructors to create rich learning activities in ActionScript and Flash. In 2013, LodeStar Learning pivoted to a whole new generation of software that used HTML5. LodeStar10 continues that progression and harnesses the power of HTML5, SVG, 3D and so much more to help designers create great learning experiences.

Meeting the CCAF Challenge

Posted on March 18, 2022 by Robert "Bob" Bilyk

By Robert “Bob” Bilyk

Introduction

I recently watched Ethan Edwards present ‘Cracking the e-Learning Authoring Challenge’. This post is my attempt at cracking the e-Learning authoring challenge.

But first a little background.

As many of you have the privilege of knowing, Ethan Edwards is the Chief Instructional Strategist for Allen Interactions. Cracking the challenge is all about building interactivity in an authoring tool – specifically, CCAF interactivity. CCAF is an acronym for Context-Challenge-Action-Feedback. The four components of CCAF are part of Michael Allen’s CCAF Design Model for effective learning experiences. Michael Allen is the founder of Allen Interactions, the author of numerous books on eLearning, and the chief architect of Authorware and ZebraZapps. Both authoring systems were designed for people with little technical expertise to be able to build – you guessed it — CCAF learning experiences.

In Ethan’s presentation, he demonstrates building a CCAF activity with Articulate Storyline. In a nutshell, the CCAF learning experience is the experience of “doing”. Rather than reading or viewing content, the learner experiences first-hand the application of principles, concepts, strategies, and problem-solving in completing a task and succeeding at a challenge.

In Ethan’s demo, his task is to detect a refrigerant leak. The learner is shown refrigeration equipment and given a leak detector. The learner doesn’t at first read a pdf or watch a video but performs an action. In CCAF activities, text and videos might come in the form of feedback to a learner’s action.

Some of the CCAF learning experiences that I designed include running a multiple hearth wastewater incinerator, troubleshooting a cable network, supporting the adoption of a special needs child, designing an online class, assessing risk of recidivism, and, most recently, searching for documents in a document management system. In all cases, most of the learning came from being immersed in a ‘real world’ setting’, presented with a challenge, and getting feedback because of learner actions.

Ethan’s presentation piqued my curiosity and a bit of self-reflection. He lists things that are essential in an authoring tool to enable the design of a CCAF learning experience. As a toolmaker, I explored each of the items on his list and I applied them to a small project built with our own LodeStar eLearning authoring tool.

As we explore each item on Ethan’s list, I’ll illustrate with LodeStar. If you follow along, you’ll see the development of a simple CCAF application. You’ll learn about the components of CCAF. And you’ll also learn a little about LodeStar and its capabilities.

But first an important caveat. CCAF comes in all forms, shapes and sizes. Ethan’s example and my example happen to be very simple simulations. The principles of CCAF are not limited to simulations. They can be applied to anything that requires action on the part of the learner — which includes making a decision, crafting a plan, analyzing and solving a problem — a host of things.

This is but one example of CCAF to illustrate its principles and test whether or not our authoring tool is up to the challenge.

Introduction to the Demo Application

The objective of the application is for learners to test an electrical outlet and determine which wires are hot or ‘energized’. In completing this task, the learner must turn on an electrical multimeter and connect its probes to the various wires in an electrical outlet. A multimeter is a measuring instrument that typically measures voltage, resistance, and current. Once someone has learned the difference between these things, the practical skill is in choosing the right setting for the task and safely using the meter to complete the task.

So that’s the challenge: find the hot wire with a multimeter. The context is a simple residential electrical outlet.

Typical eLearning applications would use text, graphics and video to illustrate the use of the multimeter and explain underlying concepts. CCAF applications challenge learners to complete the task in a manner that is an educational approximation of the ‘real thing’. Text, graphics and video can offer explanations but not in lieu of the real-world task and often as a form of feedback.

A LodeStar Application: Testing an Electrical Circuit

Basic Capabilities

But let’s start with an overview of the basic requirements. To paraphrase Ethan, an authoring tool must have these capabilities:

Complete visual freedom
Variables
Alternative branching
Conditional logic
Action/response structures

I’ll elaborate on each of these requirements in my demonstration.

Complete Visual Freedom

LodeStar combines HTML flow layout and SVG layout. Images imported into the HTML editor are placed in the HTML flow and are laid out according to the rules of HTML. Images can also be taken out of the flow and applied with a CSS rule so that text flows around the image.

In addition, LodeStar authors can use the Scalable Vector Graphics (SVG) canvas to layout out graphics freely in any position on the x and y axis.

In other words, the graphical elements on the SVG canvas are laid out freely. The SVG canvas itself is just another HTML element. Depicted below is a flow of HTML elements like text, images, divs, tables, etc. The SVG canvas is in the ‘flow’ right along with them. Inside the canvas, graphical elements can be positioned anywhere, but the canvas itself follows the HTML document flow. shrinking and expanding as needed.

The visual freedom is that LodeStar combines the benefits of a responsive HTML flow with the precise positioning of an SVG canvas.

HTML elements are laid out on the page in a flow. If the page width narrows, the element isn’t by default clipped. It’s just bumped to the next line. The SVG canvas flows right along with the other elements. Its contents, however, are positioned with local XY coordinates.

I started with a multimeter image that I took from Pexels.com, a repository of free stock photos. I used Photoshop to cut out the dial and imported it in the SVG canvas as a separate image. I did this because I wanted the learner to be able to rotate the switch to place the multimeter in the right mode. I also imported the image of an electrical box so that I could draw wires overtop.

Variables

As I wrote in the Humble Variable (The Humble Variable | LodeStar Web Journal (wordpress.com)), variables are critical to some eLearning designs. In this example, I need to store the position of the multimeter switch. That’s what variables do. They are storage places in the computer memory. As the learner clicks on the switch, the dial rotates. As an author, I must store the value of that rotation. If the value of the rotation is 40 degrees, the code judges the switch to be in the right position.

To enter the code that uses the variable, I right-click on the switch and select, ‘Select Branch Options’. Branch Options are basically things that happen as a result of displaying a page or clicking on a button or choosing a multiple-choice option or doing one of many things.

Branch Options can be as simple as turning a page or as complex as executing a whole list of instructions. The following is a basic example of the latter:

The Multimeter code

var rotation = getValue(“dialRotation”);

rotation+= 10;

setValue(“dialRotation”, rotation);

changeRotation(“dial”,rotation ,13,27);

if(rotation % 360 == 40){

changeOpacity(“display”, 1);

appendValue(“actions”, “Turned on multimeter. ”);

}

else{

changeOpacity(“display”, 0);

}

This code looks complicated to a non-programmer. But it is not. It just takes practice to write. It’s on the same difficulty level as an Excel formula.

Here is the same code but with an explanation (in italics) underneath:

var rotation = getValue(“dialRotation”);

get the value of dialRotation from long-term memory and assign it to a local or temporary variable named ‘rotation’

rotation+= 10;

add 10 degrees to value of rotation. In other words, rotation = the old value of rotation plus 10.

setValue(“dialRotation”, rotation);

store the new value in long-term memory in a location called ‘dialRotation’

changeRotation(“dial”,rotation ,13,27);

change the property of a graphic with the ID of ‘dial’. All LodeStar graphics can be assigned an ‘ID’.

More specifically, change the rotation property by 10 degrees (the value of rotation). Pivot the rotation at the precise point that equals 13% of the width of the SVG canvas and 27% of the height of the canvas. That point is the center of the dial in its current position on the canvas. If the dial were in the dead center of the canvas we would use 50, 50.

if(rotation % 360 == 40){

This line can be simplified to if(rotation == 40) I used the modulo operator (that is, ‘%’) in case the learner kept rotating the dial around and around. If rotation = 400, then 400 % 360 would equal 40. 360 divides into 400 once with a remainder of 40. So, if rotation is equal to 40, then do the following:

changeOpacity(“display”, 1);

change the opacity of a graphic with the id of ‘display’ This is the text box used to show the voltage.

appendValue(“actions”, “Turned on multimeter. ”);

store the learner’s actions in long-term memory in a place called ‘actions’

}

else{

changeOpacity(“display”, 0);

if the rotation of the dial does not equal 40, then shut off the display by changing its opacity to 0.

}

The Probe Code

I won’t explain the probe code in as much detail. Basically, when you drag the red or black probe, then the following code is executed. It essentially checks whether or not the probes are in the right spot. If they are, the multimeter display shows 110 volts.

var condition1 = isOverlap(“RedProbeTip”, “BlackWireBTarget”);

var condition2 = isOverlap(“BlackProbeTip”, “box”);

if(condition1 == true && condition2 == true){

changeText(“display”, “110.0”);

appendValue(“actions”, “Moved red probe to correct position. Black probe in correct position. ”);

}

else if(condition1 == true){

changeText(“display”, “0”);

appendValue(“actions”, “Moved red probe to correct position. ”);

}

else{

changeText(“display”, “0”);

appendValue(“actions”, “Moved red probe to incorrect position. ”);

}

These are the drag branch options that are tied to an object with a specific ID.

Red probe in place; black probe is not. Therefore the meter shows ‘0’.

Red probe in place. Black probe in place. Meter shows 110 volts.

Alternative branching

Once the learner has tested the wires with the probes, with one probe connected to the wire and the other grounded, then the learner must select A, B, C, or D. Here’s where alternative branching comes in. Learners who select the right answer might go on to a more difficult scenario. The above scenario is as easy as it gets. Perhaps they must do a continuity test to detect where there is a break in the circuit. Learners who select the wrong answer can be branched to a simple circuit or given an explanation that one black wire is coming directly from the power source, and the second black wire is passing on that power to the next outlet or switch.

CCAF applications accommodate the differences in learners. The application can alter the sequence of experiences based on learner performance. This is a profoundly different thing than typical eLearning applications where every learner reads the same text, watches the same videos, and completes the same quiz.

Conditional Logic

Ethan also lists conditional logic as a basic requirement of CCAF applications. Conditional logic comes in the form of if-else statements as evidenced by the code. Conditional logic also comes in the form of alternative branching. Select the wrong answer and then get help. In LodeStar, conditional logic is supported by not only its language and branch options but also by logic gates.

In the display below, we see what happens when the learner reaches a gate. (Incidentally, learners don’t actually see a gate. When they page forward, the application checks the gate’s logic and then branches them according to some condition. In this example, the author might configure the Gate with a pass threshold. Let’s say 80%. If the learner meets or exceeds a score of 80%, they are branched to the ‘Results’ page’. If not, they may be routed to Circuit Basics. Follow the dotted lines.

Branches at the ‘page’ level are visualized in the Branch View.

Action/response structures

In our example, the learner moves the probes around. If the multimeter is turned on, the learner sees a voltage display. The action is moving the probe. The response is a voltage display.

First, this a ‘real world’ action and ‘real world’ response. I write ‘real-world’ in contrast to what happens in a typical multiple-choice question. In a multiple-choice question, the learner clicks on a radio button and possibly sees a checkmark. That’s only ‘real-world’ to an educational institution. The world doesn’t present itself as set of multiple-choice questions.

Second, when the learner sees a voltage display, that is feedback in the CCAF sense of the word. The learner does something and then gets feedback. Now, in our example, we did choose to combine ‘real-world’ feedback with a multiple-choice question. Ultimately, the learner is asked to choose the letter next to the ‘hot’ wire. In our example, we logged the learner’s actions and can unravel how they arrived at their final decision. Did they connect the red probe to the right wire and did they ground the black probe? If they selected the right answer but didn’t perform the correct actions that would lead to the right answer, we know they haven’t learned anything at all.

Conclusion

Authoring tools that enable one to create CCAF must have these capabilities: complete visual freedom, variable support, alternative branching, conditional logic, and action/response structures.

The hot wire example is an example of a very simple simulation. But, as I wrote, the concept of CCAF isn’t restricted to this type of simulation. CCAF can be found in decision making scenarios, for example. The learner might be placed in a situation and challenged to make the right decision or say the right thing. That too is CCAF. CCAF lies at the heart of effective learning experiences.

eLearning Strategies to Support Memory Recall

Posted on February 9, 2022 by Robert "Bob" Bilyk

Introduction

At the university where I worked for eight years, occasionally I observed non-traditional students in class well into the evening, struggling to stay alert, struggling to soak it in, trying to make something better for themselves. Several years earlier, I watched a new employee at a software company resign in utter defeat. Nothing he had studied before in terms of software language, database, and mathematics prepared him for a new domain of knowledge. It was all foreign, and it was disheartening, and it was delivered in a manner that was all too much.

Late evening classes or eight-hour training days push more and more information at the learners, until they literally break down, quit, or somehow miraculously hang on to fight another day.

The tremendous tax on learners is not unusual in either the corporate or the academic environment. Both schools and companies place a heavy demand on the learner’s ability to remember things.

The constraints of human memory! Our lack of understanding of memory would be almost humorous if it weren’t for the wasted effort of students and employees alike. In this vacuum of understanding, myths and falsehoods and deceptive practices have filled in. Fortunately we have people like Will Thalheimer (The Debunker Club : Debunking Resources – The Debunker Club) and the authors of The Urban Myths of Learning and Education to help set us straight.

The Forgetting Curve

What we do know, and what research supports, is that we are wired to forget. Many of us cite Herman Ebbinghaus’ ‘Forgetting Curve’. The forgetting curve is real and, in some cases, very steep depending on a number of factors, but as Dr. Thalheimer points out, you just can’t put a number on it. You can’t say with any certainty, for example, that learners will forget 70% of what they have learned within a day.

Let’s consider the forgetting curve just for a moment, and then we’ll turn to eLearning.

The forgetting curve was the outcome of research done in the late 1800s by Herman Ebbinghaus. He scientifically observed his own recall of nonsense syllables. He made up lists of three-letter nonsense words and committed them to memory. Once he successfully memorized 100% of a list, he attempted to recall the list. The forgetting curve shows that he forgot 42% of the words within 20 minutes. After a day he retained only 33% of this list of nonsense.

We know that people forget, perhaps at disheartening rates, but the rate of forgetfulness is based on dozens of factors. Are these new employees who are being introduced to something new to them, or are they seasoned employees? Do they have any prior knowledge that will help them organize new information? Are they paying attention or are they distracted? Are they motivated to learn – intrinsically or with an external reward? Is there a threat if they don’t learn? Is there too much of a threat that inhibits their learning? Are they just trying to earn CPE credit? Are they taught how to recall the information in the right place at the right time for the right reason? Is the material difficult? Are they asked to recall the information? How many times?

Try placing those variables in a formula. It’s impossible.

We know that the forgetting curve is real. It has been replicated recently (Replication and Analysis of Ebbinghaus’ Forgetting Curve (nih.gov)) and it will accurately mirror our students’ or employees’ rate of forgetfulness if we do not:

Help learners recall prior knowledge
Help learners organize new knowledge
Provide storage and retrieval cues that will help them use the information in the right context
Practice retrieval of the new knowledge
Space the retrieval over time.
Integrate the new knowledge with other knowledge
Apply the new knowledge before forgetting

This is where eLearning plays a role. Oftentimes, trainers are busy workers or busy teachers who can’t address deficits in prior knowledge, for example, or even assess prior knowledge, or fit spaced practice or simulated application into their training.

That is where I think eLearning can shine.

I know, I know. I’m an eLearning developer and an eLearning authoring toolmaker. But there are reasons why I chose this field. This is one of them.

The design of eLearning experiences can help improve the training experience, even if the latter is traditional face-to-face teaching. As I’ve observed, many people dread eLearning because of the page-turner drudgery they’ve been subjected to. Medical workers, lawyers, and accountants, and anyone with continuing education demands, have had too many bad self-study experiences. In my current company, group-live (face-to-face) instruction is preferred over eLearning. That doesn’t, however, eliminate the option of eLearning. As a pre-training preparation or a post-training reinforcement and application, eLearning can still play a role.

Against this backdrop, here are some strategies or designs that can help:

Plan the training or academic curriculum to include pre-training activities and post-training reinforcements. Make room for recalling prior knowledge in the training or lesson plans of future courses.

Flip the training. That means, use eLearning (or self-studies) to present the content and use face-to-face training time to observe student performance and provide feedback. Data from 317 studies shows that flipped classroom interventions produced positive gains across all three learning domains (To Flip or Not to Flip? A Meta-Analysis of the Efficacy of Flipped Learning in Higher Education – Carrie A. Bredow, Patricia V. Roehling, Alexandra J. Knorp, Andrea M. Sweet, 2021 (sagepub.com))

Pre-training

Let the post-training assessments for the last course or training session be the pre-training assignments for the new thing — not as assessments, but as highly scaffolded activities with prompts and hints and feedback and textbook references and video helps and whatever. The point is to help recall and to prepare learners for what lies ahead.

Design activities that help learners recall vocabulary, basic concepts, laws, principles and procedures. Activities can help prompt that recall and reduce the cognitive load of the new stuff. If an accounting teacher makes references to cash or accrual accounting, do you want students struggling to recall the terms or do you want them paying attention to the new information? It’s hard for them to do both.

Use flashcards, crosswords, matching, categorization, and other activities. They’re not as sophisticated as things I’ve discussed in past posts, but they can play a useful role in helping recall.

Embed a video or a short Powtoon presentation.

Use quizzes with circular queues (missed questions get repeated) or variable interval queues (missed questions get repeated at spaced intervals).

Make it fun. Gamify it.

Post-training

All of the pre-training suggestions apply to post-training as well. But you can do even more.

Interactive Storyboards

This strategy walks the learner through the presented content in a storyboard fashion. In the interactive storyboard, however, the learner must fill in the missing pieces. Recently our HR department presented on employee feedback and the different roles that in-charges, supervisors and talent advisors play in giving feedback to accountants and auditors. She talked about a process that included feedback in review notes, one-on-one meetings with supervisors, and regular meetings with talent advisors. The post-training activity can follow along in the life of an accountant but leave blanks for the learner to fill or questions for the learner to answer. It causes the learner to retrieve important elements of the presentation and become an active participant in reconstructing the information. When the learner gets it wrong, that’s an opportunity for feedback!

An interactive Storyboard, created with the LodeStar eLearning authoring tool

An added benefit to the activity is that we can see how learners experienced the post-training activity through the xAPI statements that the (CMI5-conformant) activity generated. In the following screenshot from the Learner Record Store, we can see that this employee missed the point that there is a connection between one-on-one meetings and talent development meetings. We also see that this employee did hit the results page with a decent score the first time around. The employee satisfied the requirements of the assignable unit (AU) and completed the course. That tells us a lot. If we were to analyze all of the items that employees missed, we could either improve the presentation or improve the questions.

xAPI statements, generated by an activity authored in LodeStar

Embedded Discussions

Higher education instructors often invite students to discuss topics online after a presentation. There is a reason for this. At the most elemental level, it forces recall of the presentation. At a higher level, it generates new knowledge as students hear differing perspectives.

In my time in higher ed, I’ve seen this done well and I’ve seen it done poorly. My poster child for doing it right was a marketing instructor who simulated product advertising pitches in a discussion forum. My hunch is that online discussion in corporate training environments is rarer. To my point, our corporate Learning Management System (LMS) doesn’t even offer a discussion board.

The following screenshot depicts an activity prototype with an embedded discussion board. For this prototype, we used Tribe from Tribe | A Customizable Community Platform. Tribe allows you to create and embed your discussion board. (I’m not necessarily endorsing Tribe.) The strategy is to refresh employees on the fundamental principles of giving and receiving feedback and then ask them to discuss what works for them.

The key idea is to immerse learners in the content with enough information to prompt their recall of the training. Then we invite them to share their insights or strategies with others. They don’t need to leave the activity and log in to another service. They can share their thoughts right there and then.

This is an important idea in a general strategy that we’ve been working out called 3Di. That means delivery of interactive content, discussion, and then decision. Students apply what they have both learned and discussed to make a decision.

A discussion forum embedded in an eLearning activity

Staged Journals

We first developed this strategy for a literature teacher. She taught students how to be analytical of fairy tales. She instructed them on the Propp analysis based on the work of Vladimir Propp. In the staged journal technique, students would be presented with one step or stage of the analysis. They would complete the step and go on to the next. In the end, they had a journal that was compiled of all the steps.

The screenshot below depicts an employee who types in his greatest difficulty when asked to give a subordinate corrective feedback. The learner brainstorms difficulties, and then brainstorms remedies.

Here is an excerpt from a journal that compiles it all together in a feedback summary.

Conclusion

Face-to-face instruction may have its supporters, but even this delivery type should include pre-training and post-training eLearning activities. We know from research and from our own surveys that students and employees forget too much of what we teach. The amount and rate of forgetfulness may not precisely follow Ebbinghaus’ curve but unless we address forgetfulness, students won’t achieve the desired outcomes of the training.

More in-depth activities might include decision-making scenarios and simulations. I’ve written about those in past articles but, in this post, I have featured activities that can be quickly and easily generated. All three activities represent strategies that can help in the reflection and recall of training.

CMI5: A Call to Action

Posted on October 29, 2021 by Robert "Bob" Bilyk

Introduction

Since 2000 a lot has changed. Think airport security, smart phones, digital television, and social media. In 2000, the Advanced Distributed Learning (ADL) Initiative gathered a set of eLearning specifications and organized them under the name of SCORM. In 2021, in a time of tremendous technological change, SCORM still remains the standard for how we describe, package, and report on eLearning.

However, finally, we are on the eve of adopting something new and something better: CMI5.

We no longer have landlines, but we still have SCORM

CMI5 Examples

To many, CMI5 is another meaningless acronym. To understand the power and benefit of CMI5, consider these very simple examples:

A Learning and Development specialist creates a learning activity that offers managers several samples of readings and videos from leadership experts. The activity allows the managers the freedom to pick and choose what they read or view; however, the specialist wants to know what they choose to read or watch as well as how they fare on a culminating assessment.

CMI5 enables the activity to capture both the learner experience (for example, the learner read an excerpt from Brené Brown’s Daring to Lead ) and the test score. CMI5 can generate a statement on virtually any kind of learner experience as well as the traditional data elements such as score, time on task, quiz questions and student answers. In this sense, CMI5 supports both openness and structure.

Let’s consider another example:

An instructor authors a learning activity that virtually guides students to places in Canada to observe the effects of climate change. She wants students to answer questions, post reflections and observe the effects of climate change on glaciers, Arctic ice, sea levels and permafrost. She sets a passing threshold for each activity. Once students have completed all of the units, then the learning management system registers that the course was mastered.

Let’s go further:

The instructor wants the learning activity to reside in a learning object repository or website outside of the learning management system – but still report to the learning management system. In fact, she wishes that no content reside on the learning management system. Regardless of where the content resides, she wants to know what sites students visited, how they scored on short quizzes, and how students reacted to the severe impact of climate change on Canada.

For students with disabilities, the instructor makes an accommodation and requests that the LMS administrator adjust the mastery score without editing the activity.

As the course becomes more and more popular, she anticipates placing the website and its activity onto CloudFlare or some content distribution network so that students all around the world can gain faster access to the learning activities.

The instructor works as adjunct for multiple universities and wants each of their learning management systems to get the content from a single location. In some cases, she wants the content locked for anyone who circumvents the Learning Management System and in other cases she openly lists the unlocked content with OER libraries like Merlot and OER Commons.

Before CMI5 much of this was difficult to achieve, if not impossible. So, let’s review what CMI5 offers us.

CMI5 captures scores in the traditional sense. But it also records data on learning experiences such as students virtually observing the change in the permafrost. CMI5 allows instructors and trainers to set the move-on criteria for each unit in a course (i.e. passing score before student moving on to the next unit).

CMI5 activities can reside anywhere – on one’s own website, for example, and still report to the learning management system. CMI5 enables an LMS administrator to change the mastery score from the LMS for the benefit of students who need accommodations and essentially trump what is set in the unit.

LodeStar’s CMI5 Implementation allows
authors to indicate where the content resides

CMI5 is a game changer. And yet for many – learning and development leaders, instructional designers, technologists and students – it doesn’t seem that way in 2021. CMI5 seems like a non-event. It feels like something we all talked about – a welcome change of weather on the horizon –and then nothing. Not a drop of rain.

We have been talking about and anticipating CMI5 for a long time – and yet, major learning management systems both in the corporate and academic worlds still don’t support it. CMI5 was envisioned in 2010, released to developers in 2015, and then released to the public in its first edition in 2016. We are now in the waning days of 2021—with limited adoption.

But that is likely to change.

For one, Rustici Software and ADL delivered on their promise of Catapult. Catapult is likely to accelerate adoption of CMI5. It provides many benefits to developers, including the ability to test if a CMI5 package conforms to the standard.

In my view, the learning technology architects have done their part. They brought us a meaningful set of specifications. They brought us the tools to test learning packages and to test the learning management system’s implementation of CMI5. Now’s it’s up to learning and development specialists and the instructional design community to cheer CMI5 on. It is my belief that once the community understands CMI5, spreads the word, and imposes its collective will on the LMS providers, CMI5 will become an important part of our tool bag. I urge you to share this article and others like it.

In the meantime, let’s take a deeper dive into CMI5’s potential.

Benefit One: Freedom to capture and report on any learner experience.

With CMI you can report on scores, completion status, and just about anything else. You can report on standard assessment results, and the not-so-standard learning experiences.

To understand this, we need to re-look at SCORM.

One should consider CMI5 as a replacement for SCORM – an improved specification. Conforming to SCORM was useful because a learning object or learning activity could be imported into just about any modern learning management system. As an instructor, if you created a game, quiz, presentation, simulation, whatever and exported it as a SCORM package, your activity could be imported into Moodle, BrightSpace, Canvas, Cornerstone, Blackboard, and any learning management system that supported SCORM. So, the benefit of SCORM was that it was a set of standards that most LMS systems understood. The standards that fell under the SCORM umbrella included metadata, a reporting data model, and standard methods for initializing an activity, reporting scores, reporting on interactions, and reporting passing or failing and completion status.

The data model included dozens of elements. One example of a data element is cmi.core.score.min. Related to score, SCORM conformant activities reported on the minimum score, the maximum score, the raw score (absolute number) and the scaled score ( a percentage between 0 and 1).

SCORM supported a lot of different data elements. A SCORM conformant activity could report on a variety of things. The limitation of SCORM, however, was that, despite the large number of elements, it was still a finite list. Take a Geolocation Storytelling activity as an example or an eBook reading. If I wanted to capture and report that the student virtually or physically visited location A, then B, and then C, I would have to work around the limitations of SCORM. I could not generate a statement such as, for example, ‘Student visited the Amphitheater in Arles’. If I wanted to capture a student’s progress through an eBook, SCORM would be problematic.

At this point, you might be protesting, but xAPI does that! xAPI? Another acronym! Yes. xAPI, or The Experience API is a new specification that makes it possible to report on a limitless range of things that a learner has experienced: such as, completed a chapter of an eBook; watched a video; toured a museum, and on and on. So, if we have this thing called xAPI, why CMI5?

The benefit of xAPI is that it supports the reporting of anything. The downside to xAPI is that, by itself, it doesn’t have a vocabulary that the LMS understands such as launched, initialized, scored, passed, completed. That is what CMI5 offers. CMI5 is, in fact, an xAPI profile that includes a vocabulary that the LMS understands. In addition, CMI5 can report on any type of learner experience. Here is the definition of CMI5 from the Advanced Distributed Learning Initiative:

cmi5 is a profile for using the xAPI specification with traditional learning management (LMS) systems
(Advanced Distributed Learning).

With CMI5, you can have your cake and eat it too. You can report on learner activity in a way that LMS understands and you can report on just about anything else that the Learning Management System stores in a Learner Record Store. The Learner Record Store or LRS is a database populated by statements about what the learner experienced.

xAPI Statements can capture an
any learner experience, including reading the instructions

Benefit Two: Freedom to put the learning activity anywhere

With CMI5, you can place a learning activity in a repository, in GitHub, on a web server, in a Site44 drop box site, in SharePoint, in a distributed network, wherever….without restricting its ability to connect with a learning management system. CMI5 content does not need to be imported. A CMI5 package can contain as little as one XML file, which among other things, tells the LMS where to find the content.

To appreciate this, we need to look back at SCORM once more (as if it were ancient history).

I’ll start with a pseudo technical explanation and then follow with why it matters.
The way SCORM works is that the learning activity sits in a window. The learning activity uses a simple looping algorithm to find the Learning Management System’s SCORM Adapter. It checks its parent window for a special object. If the window’s parent doesn’t contain the object, the activity looks to the parent’s parent, and so on. In other words, somewhere in that chain of parents, there must be that special object. Typically, the SCORM activity can only communicate to the learning management system if it is a child window of that system or if some server-side technology is used.

CMI5 works quite differently. CMI5 gives us freedom to leave our parents’ home. Whereas SCORM uses a Javascript Application Programmer Interface to communicate, CMI5 uses xAPI to reach across the internet and call a web service’s methods. Loosely, it’s like the difference between a landline and a cellular phone service. To use the landline you must be in the house; to use a cell phone, you must be in the network.

Benefit Three: A simplified sequencing model.

SCORM supported simple sequencing, which many say is not so simple. CMI5’s ‘move on’ property, in contrast, is very easy. A CMI course can contain one or more Assignable Units (AUs). The instructor spells out what the learner must achieve in an assignable unit before being able to move on. The move on property has one of the following values:

• Passed
• Completed
• Completed Or Passed
• Completed And Passed
• Not Applicable

Once the student has ‘moved on’ through all of the assignable units, the LMS notes that the course has been satisfied by that student.

Benefit Four: An assignable unit passing score can be overridden

In SCORM, the mastery score is hard-coded in the activity. In a SCORM activity, the instructor can base completion status on a passing score. But what if that hard-coded score were inappropriate for a group of students, for whatever reason? The specification enables an LMS to pass the mastery score to the Assignable Unit upon launch. So the LMS launches the AU, and sends it student name and mastery score (among other things). By specification, the AU cannot ignore the mastery score but must use it to trump what is hard-coded in the unit or refuse to run.

Benefit Five: Theoretically, CMI5 isn’t hamstrung by pop-up blockers.

When an LMS launches a SCORM activity, it either embeds the activity in an Iframe or launches a window. Both scenarios are problematic. The content may not be well suited for an iFrame and a pop-up blocker can obstruct the launched window.

Theoretically, CMI5 AU can replace the LMS with its own content. It’s not in an embedded iFrame and it’s not a pop-up window. When the LMS launches the AU, along with student name and mastery score, the LMS sends the AU a return URL. When ended, the AU returns the student to that return URL, which is the address of the LMS.

I write “theoretical” because the LMS should not but may ignore this requirement.

Benefit Six: CMI5 activities securely communicate to the Learner Record Store

As I wrote, the activity can send information about learner experiences clear across the internet to the learner record store. But how does the AU have the authorization to do this from, let’s say, a web site? And how does it happen securely?

This is the marvel of 2021 technology versus 2000 technology. Before 2000, we had difficult-to-use protocols for passing information securely across the internet. Oftentimes, special rules needed to be added to internet routers. Then along came a simpler protocol that the first version of CMI5 used (SOAP). Then came an even better way (OAUTH and REST). After launch, the LMS hands the AU a security token (kind of like a key that dissolves in time). The AU uses that key to gain access and to post information to the Learner Record Store.

Conclusion

CMI5 returns power to the instructor and to the L&D specialist. CMI5 allows one to choose where the content resides and to choose what the content reports. CMI5 captures learner experiences more completely and yet it communicates with Learning Management Systems with a vocabulary that LMSs understand. CMI5 supports accommodations for a special group of students without needing to change the code of the Assignable Unit. Finally, CMI5 uses current technology to send data over the internet.

The implications of this emerging specification are tremendous. It is better suited to mobile learning and it is better suited to the learner experience platforms that are emerging (e.g. LinkedIn Learning’s Learning Hub). Soon instructors may be able to organize content from a variety of providers (like LinkedIn Learning, Khan Academy, or OER Commons) but retain the learning management system as an organizer of content, data collector, and credentialing agent. Now instructors, average instructors, may be able participate in that content market from their own GitHub repositories and web sites.

But many LMSs have yet to adopt CMI5. The architects have done their part. Now it’s on us to understand this technology and advocate for it. Start by sharing this article. Thank you.

Appendix A — How it Works (A simplified flow)

For those interested in a deeper dive, let’s walk through the CMI5 process flow step-by-step. (See diagram)

To begin, the author (instructor, L&D specialist) exports content as a CMI5 package. The package can be a simple file that instructs the LMS where to find the content or it can include the content itself.

(1) When a student needs the content, the Learning Management System (LMS) launches the content and sends the Assignable Unit (a course can contain one or more Assignable Units) (2) information that includes student name, a fetch URL and the activity ID.

(3) The Assignable Unit (AU) uses the fetch URL to retrieve a security token. The security token enables the AU to communicate securely to the Learner Record Store (LRS).

(4) As the student interacts with the content, the AU can optionally send Experience API (xAPI) statements to the LRS . (5) At some point, the AU reports that the student passed and/or completed the unit.

(6) The LMS uses the ‘move-on’ information to determine whether or not the student can move on to the next assignable unit. The move-on options are passed, completed, passed and completed, passed or completed, or not applicable.

Finally, when all of the assignable units within a course are completed, the course is marked as satisfied for the specific learner.

A simplified process flow that starts with the
launch of the CMI5 Assignable Unit by the LMS

Short Sims

Posted on September 17, 2021 by Robert "Bob" Bilyk

Introduction

Some of us aren’t content with simply presenting information in a linear fashion in an online course. We have dozens of words to express what we wish to achieve: interactive, game-like, thought-provoking, challenging, problem-based…. We are also hard-pressed to find the time or the budget or the design that will fulfill our highest aspirations for eLearning.

It’s easy to get discouraged – but occasionally we’re offered a strategy that works within our budget and time constraints. One such strategy is the basis of Clark Aldrich’s recent book, “Short Sims” (Aldrich, C. (2020). Short sims: A game changer. Boca Raton: CRC Press.)

In his book, Clark Aldrich discusses the methodology of the short simulation. He begins by lauding the virtues of interactivity. Interactivity allows learners to experiment, customize their experience, role-play, make decisions and apply skills. He writes that game-like interactivity is expensive to build. We all recognize that. Short Sims, on the other hand, can be built in the “same time frame as linear content”. Short Sims engage students in making decisions, doing things, meeting challenges, solving problems, learning from mistakes and so forth. Essentially Short Sims offer us a strategy – a methodology – to do things differently and more effectively.

The hook comes from this excerpt:

“From a pedagogical perspective, the more interactivity the better. Connecting user action with feedback has long been proven to be critical for most neuron connections”.
Aldrich, 2020

Aldrich credits the Journal of Comparative and Physiological Psychology for that insight. But again, in Aldrich’s words, “game-like interactivity is expensive to build. It is time-consuming.” Aldrich offers a new Short Sim methodology as an antidote to linear-style presentation — the death-by-PowerPoint approach.

Short Sims

Show, not tell

Engage learners quickly and are re-playable

Are quick to build and easy to update

Short Sims square with the Context-Challenge-Activity-Feedback model that we’ve heard so much about from Dr. Michael Allen, Ethan Edwards and the designers at Allen Interactions. They are a solution to M. David Merrill’s lament that so much learning material is shovelware. ShortSims are not shovelware. They are a cost-effective means of engaging students.

Quite frankly, the LodeStar eLearning authoring tool was made for the Short Sim. Instructors have used LodeStar for years to produce Short Sims but never used that term. We called them Simple Sims, which sometimes included decision-making scenarios, interactive case studies, problem-based learning and levelled challenges. We solved the same problem. We made it easy for instructors to create Short Sims quickly.

Our design methodology has a lot in common with Aldrich’s methodology as described in his book. The following ten points outline our approach to creating a simple decision-making scenario, which, in our view, is one form of Simple Sim. To avoid mischaracterizing Aldrich’s methodology, I’ll use our own terms in this outline.

Select Challenge
Pick Context
Determine the Happy Path
Determine Distractors
Pick a setting – background graphic
Choose a character set
Produce the Happy Path
Add the Distractors
Add Branches
Add Randomness

Select Challenge

Selecting the right problem and the right scope is, in itself, a challenge for the instructor or trainer. Straightforward processes that present clear consequences for each decision are easy to simulate. Processes like strategic planning that are influenced by dozens of variables are much more difficult. The Short Sim methodology itself would be good candidate for a Short Sim. Another example would be the backwards design method of instructional design. In my early days at Metro State, a decade ago, we discussed the backwards design approach with instructors. We then used a Short Sim to rehearse instructors on the key questions to ask during each phase of the backwards design process. We based a lot of our thinking on Dee Fink’s “Creating Significant Learning Experiences” and Grant Wiggins’ “Understanding By Design”. Our objective was to help instructors design with the end in mind. In Backwards Design, outcomes and assessments come before the development of activities. The Short Sim did the trick. Planning instruction is complicated business. A simple and short simulation is not, in itself, transformative. But we just wanted assurance that instructors understood the basic principles of backward design by the decisions they made.

Pick Context

In the Backwards Design example, a dean asks an instructor to design an online class to help K12 teachers use educational technology in their classrooms. So, in this context, the learner is playing the role of online course designer. The learner is challenged to make the right decisions at the right time. If the learner holds off on designing activities until completing an analysis, defining outcomes and creating assessments, then the learner succeeds in the challenge.

Determine the Happy Path

The happy path is all the right decisions in the right order. Situational Analysis -> Learner Outcomes -> Assessments -> Activities -> Transfer. It is all of the right answers with no distractors. It’s like creating a multiple choice test with only one option: the correct answer.

Determine Distractors

Now come the distractors. What are the common pitfalls to Backward Design? What might tempt the learner to go astray. If we were designing a Short Sim on the Short Sim methodology, the pits and snares might be what Aldrich calls the Time Sucks: choosing the wrong authoring tool, too many decision-makers on the project, custom art, and so on. The learner might be tempted with “the medium is the message. Invest in the medium. Commission a graphic artist to create a compelling interface.” The point of Short Sims is to not invest heavily in artwork or graphic design. The focus is more on describing the context, presenting choices to the learner, and showing the consequence of learner choices.

Pick a Setting

A background photo helps to set the context. Images that display settings without people can be found on sites like Pexels, Wikimedia Commons, in the public domain section of stock image services and, of course, on stock image sites. Because one image often suffices in a short sim, authors can snap their own photos and not waste too much time.

Alternatively, vector artwork can serve as an effective background. Vector art can be found and downloaded from such sites as https://publicdomainvectors.org/. (LodeStar Learning doesn’t endorse any of these sites – but we have used them all.)

In either case, if the scene is relevant to the learning context and not just a vain attempt to gamify, it might actually contribute to content retention and recall.

Choose a character set

A popular approach to Short Sims is the use of cutout characters with different poses and expressions. Cutout characters can be photo-realistic images with transparent backgrounds or illustrations. To see examples, please google ‘elearning interactive case studies’, select ‘images’ and you’ll see thousands of examples. Despite their popularity, finding cutout characters cheaply can be frustrating. Several authoring tools offer a built-in catalog of characters. These tools tend to be expensive. Many stock photo sites offer character packs but usually one must subscribe to these sites for a monthly charge. Some sites offer pay-as-you-go services, meaning that you pay for the character pack once, without signing on to a monthly subscription. The character pack can be as cheap as $4. One such site is eLearning Templates for Course Developers – eLearningchips. A complete character pack purchased from eLearningChips with more than 137 poses costs as little as $54. No subscription. No additional fee. (Again, we’re not endorsing eLearningChips, but we have used their service.)

Produce the Happy Path

With the LodeStar authoring tool, we had several options for producing the Happy Path. We used the ActivityMaker template and, after the title page, added a sequence of Interview Pages. The ActivityMaker template offers a range of page types. The Interview Page is one of them. In an Interview Page, we dropped in a character and filled in the best choice. We didn’t concern ourselves with the distractors (the wrong options) quite yet. Again, we were focused on the Happy Path.

Here is the author view:

Here is what the student sees:

Add the distractors

Once we sorted out the happy path – a sequence of perfect, well-informed choices, we thought about the pits and snares—the problems and challenges.

In our course design example, a common problem is that we think too early about the content–that is, what topics should the course cover. We anticipated those problems when designing our Short Sim. If a learner unwittingly falls into our trap, we have the opportunity of providing feedback. It’s a teachable moment.

An alternative to the Interview Page type is the Text Page. In a text page, we can add images and widgets. These give us a bit more flexibility than the Interview Page Type. On a Text page, we can add an image (left or right aligned), then a Text Layout Widget. Here you can see the page with image and the Text Layout widget. The image was composed in our SVG editor.

Here is what the student sees.

Add Branches

In one sense, a branch is a place where we get sent based on our decisions. If this were a customer service sim and we made poor choices, the customer would appear more and more irritated and ultimately we lose his or her business. Programmatically, the place where we get sent is a page that shows an irate customer and choices that represent a difficult situation. The branches could lead us down a path of destruction but we may also have the opportunity of winning back the customer’s trust with a string of good decisions.

Branching adds variety to the sim. It gives us a customized experience or allows us safely to ‘test’ bad choices.

Branching can also be viewed as the consequence of a decision or choice. In LodeStar, branch options include going to the next page, last page or jumping to a page. They also include bringing up a web resource, adding an instructive overlay, setting a variable value, etc. It could also mean the execution of a script or series of commands to make a lot of things happen simultaneously, such as setting a variable (that tracks our failings), sending us down a path, changing the image of a happy customer to an unhappy one, showing feedback, marking the choice with red, and more.

It’s probably most effective to show the learners the natural consequence of their decisions–an unhappy customer for example. As designers, we might also need to be explicit and display feedback, or introduce a coach who provides feedback. As Clark Aldrich writes, the sign of a good Short Sim is one that is played over and over again. Branching helps us make the sim a different experience each time.

Add Randomness (optional)

Randomness might be difficult to achieve and should, therefore, be considered optional.

Randomness is more than randomizing distractors. (Randomizing distractors happens automatically on an Interview Page. It’s done through a simple checkbox in a Text Layout widget.) More sophisticated randomness might include a randomly generated sum of money, or a randomly selected path or scene, or randomly generated assets that are assigned to the learner. It might be a randomly generated length of fuse that represents the customer’s patience. In our course design example, it might be randomly generated student characteristics that include age, gender, and subject interest. That level of randomness is best achieved with the help of LodeStar’s scripting language and is best left to its own article.

Conclusion

Short Sims represent a level of interactivity that goes beyond the linear presentation of information. They have the potential of promoting learner retention and application. With the right tool (and there are plenty), everyone can build short simulations. One tool, LodeStar, was designed from the very start with the short simulation and the intrepid instructor in mind. Short Sims may vary in sophistication and design but, in any form, they cause learners to think and to see the consequence of their actions. The short sim is a strategy that is doable and repeatable within our budgets and time constraints. Make it happen in your world!

	Rita de Heer on Thinking Activities
	Robert "Bob" Bilyk on Thinking Activities
	Rita de Heer on Thinking Activities
	Thinking Activities… on State Response Engine
	John O'Reilly on Thinking Activities

Robert N. BilykPresident, LodeStar Learning Corporation

Introduction

Thinking Activities Continuum

Reading and Discussions

Quizzes and Puzzles

Simple Simulations

Interactive Case Studies

Context Challenge Activity Feedback

Virtual Reality/Augmented Reality

Conclusion

From here

The Past

The Present

The Future

Conclusion:

References

Appendix

<educational_resource>

<title>Understanding Electrical Fundamentals: Voltage, Current, and Resistance</title>

<keywords>

<keyword>Voltage</keyword>

<keyword>Current</keyword>

<keyword>Resistance</keyword>

<keyword>Electricity</keyword>

<keyword>Electrical Power</keyword>

<keyword>Ohm’s Law</keyword>

<keyword>Circulatory System</keyword>

<keyword>Electrical Concepts</keyword>

</keywords>

<reading_level>High School / Early College</reading_level>

<content>

Just as your heart produces the pressure to make blood circulate, a battery or generator produces the pressure or force to push electrons around a circuit. …..(the remaining content omitted for the sake of brevity)

</content>

</educational_resource>

Introduction

The Challenge

Matching Strategies to the Problem

Categorizing Problems

References

Timeline Animation

SVG

Bitmapped Graphics

The animate-able properties

Animation synced with narration

Conclusion

Animation Sampler

Author’s Note:

Appendix A

Introduction

ChatGPT Lists 5 Influential Instructional Designers

Disclaimers

Rules of Engagement

Screen by Screen Commentary

Appendix A

Introduction

Scalable Vector Graphics

Importing PowerPoint as SVG

MathML

SimpleSim

CCAF

xAPI/CMI5

3D

Conclusion

Introduction

Introduction to the Demo Application

Basic Capabilities

Complete Visual Freedom

Variables

Alternative branching

Conditional Logic

Action/response structures

Conclusion

Introduction

The Forgetting Curve

Pre-training

Post-training

Interactive Storyboards

Embedded Discussions

Staged Journals

Conclusion

Robert N. Bilyk
President, LodeStar Learning Corporation