State Response Engine

Robert N. Bilyk
President, LodeStar Learning Corporation

Kjrsten Holt
Faculty, Minneapolis Community and Technical College

Introduction

I’ve written about a ‘Thinking Activities’ continuum that categorizes the skills needed by an instructor or trainer to develop various levels of thinking activities.

At one end of the continuum, trainers and instructors can promote thinking with reading assignments and discussions; at the other end, they can use realistic simulations that immerse students in a real-world environment.

Creating a realistic simulation can be daunting.  It requires time, effort, and a specialized skill.

Therefore, in my opinion, we need to uncover and discover more thinking activities that fall in the middle range – activities that trainers and instructors can create given their time constraints and skill level.   This article proposes one such activity.

An introduction to the State Response Engine

A “State Response Engine” (SRE) randomly selects a “state” or situation and presents responses to learners in the form of actions. This approach is designed to promote higher-order thinking by presenting learners with different scenarios and challenges based on the randomly chosen state. The SRE allows for a variety of responses, some of which can be correct in one situation but incorrect in another. It introduces an element of unpredictability and adaptability to the learning process, encouraging learners to think critically and make decisions based on the presented context.

In a composting problem example, the SRE randomly selects states like “You are presented with bags and bags of brown leaves” or “You are presented with bags and bags of vegetable produce” and then provides corresponding response options. This dynamic and adaptable approach to learning is what defines the State Response Engine, making it an appropriate name for this type of activity. It offers a state-based framework for presenting challenges and responses to learners, promoting engagement and problem-solving skills.

Let’s see one in development from start to finish:

The need

Kjrsten Holt is a faculty member at Minneapolis Community and Technical College.  She teaches web and graphic design.  Originally, she created a ShortSim¹ script for her class on web design fundamentals, part of a two-year program in graphic and web design.  This article takes her original design and translates it into a State Response Engine activity.

A little more background in Kjrsten’s own words:

Students in the course are a mix of print design and web design majors, ranging from high-school age to adults with previous degrees. One of the course’s learning objectives is to be able to successfully optimize images for various publishing formats. Upon completing this learning experience, students should be able to choose the correct image size and export format for print images, and web images.

The ShortSim strategy was an excellent choice for Kjrsten’s learning outcome because students would be presented with a situation and required to make the right choices related to technique, image size, filetype, compression type, and so forth.

I proposed that we try the SRE strategy to accomplish the same objective and Kjrsten agreed.  The SRE isn’t a better strategy than ShortSim.  It simply offers the following:

• Easily generated – A little more difficult than setting up a multiple choice but not much more difficult
• Quickly generated.
• Largely text-based thus saving time although images can be used.
• Randomly chooses a situation.  The students’ selections are judged right or wrong based on the randomly chosen situation, thus creating another element of challenge.
• Uses delayed response, which means that students’ responses are evaluated after they’ve completed the entire scenario.  They get feedback and are then encouraged to improve their score.  Students are encouraged to read and remember the feedback to improve their score on the second round. 

Why is this important?

We need strategies that make students think but don’t require a disproportionate amount of time to generate.    Students get tired of discussions that seem perfunctory.  They also tire of strategies that have worn out their welcome from repeated use.  We need new strategies!

How do we use the SRE strategy?

We’ll use the LodeStar eLearning authoring tool to illustrate the SRE.  LodeStar makes configuring an SRE easy, but with a little ingenuity the same can be accomplished in StoryLine or Captivate.

The first step in LodeStar is to choose the Challenger Page Type in the ActivityMaker Template.  The Challenger Page type is based on the SRE strategy.

The Situations (States)

The next step is to construct the randomly selected states.

In our example, the State Response Engine randomly chooses a state from two possible situations: 

State 1:  Your task is to take a portrait of a musical band for a print poster.  Decide what device to take and, if needed, set it to an appropriate resolution.

State 2:  Your task is to take a photograph for a social media post for a band.  Decide what device to take and, if needed, set it to an appropriate resolution.

This is what it looks like from the author’s point of view:

The ‘Situation’ category will either display “Your task is to take a photograph for a print poster.” or “Your task is to take a photograph for a social media post.” 

The ‘Situation’ category can be assigned two or any number of randomly selected states.  This is what it looks like to the student:

In the screenshot, the student has chosen the situation category and is presented with the task as well as some choices to make that are related to type of device and resolution needed for the task.

Based on the situation, the student chooses the appropriate photographic device, sets the correct resolution, and then conducts the photoshoot and editing accordingly.

For example, for a print poster, the correct actions are:

• Choose an 18-megapixel digital SLR.
• Set device to shoot at 5184 x 3456 pixel resolution at 300 dpi.
• Shoot a lot of images (always true).
• Bring extra batteries or a charge cord (always true).
• Consider the purpose and goals of the photoshoot. (always true)
• Convert Image to TIFF.
• Change color space to CMYK (optional).

The author sets the SRE options from one of the following:

• Always correct
• Never correct
• Correct if dependency exists
• Not Applicable

This is how it looks:

The selection option is the title:  Choose an 18-megapixel digital SLR.

The option will be displayed under the “Situation” Category.  Categories can be steps in a procedure or phases or categories or whatever.

We’ve already crafted our random states and so we select ‘No’ or leave the option blank.

Choosing an 18-megapixel camera depends on the task.  The prerequisite task must be to create a print poster.  This option is only correct if we’re shooting for a print poster. Therefore, the dependency is set to “Take a portrait of a band for a print poster…”

We then assign points.  If the student correctly selects this option, they gain 10 points.

We select the condition for which this choice is indeed the correct response. It is correct if the dependency exists.  The dependency is “Take a portrait of a band for a print poster…”

We indicate any resources that should be made available to support the student in making the right selection.  The resource is another page in the project that displays when we click a resource button.  In the screenshot above, “Resolutions” appears as a resource.

Finally, we provide feedback.  Feedback A is feedback that is displayed if the item is incorrectly selected.  Feedback B is feedback that is displayed if the item is incorrectly omitted.  (The tooltip shown on mouse-hover reminds us of this.)  In our example, if the student doesn’t select an 18-megapixel camera, we provide feedback that the student needs a high-resolution camera.

In our example we kept it simple.  We have 18 selections, which include the two random states.

Optionally, we can add more random states to the other categories.  For example, the SRE can randomly choose good or bad weather conditions.   The choice to use artificial lighting is correct only if a) we are doing a photoshoot for a print poster and b) we’re forced indoors because of the weather.  Here is how we configure the option:

In the above example using artificial lighting is dependent on the task of taking a portrait for a print poster and shooting inside because of the weather.  If those two dependencies are not present, the selection is judged incorrect.

The artificial lighting option was just an example that we did not include.  We kept our prototype simple.   The emphasis was really on resolutions and file types according to the stated learning outcome.

In our example, once the student completed all three categories ‘Situation’, ‘Photoshoot’ and ‘Editing’, they are shown the ‘Submit’ button.  When the student submits, the SRE offers feedback.  Here is a snippet.

You incorrectly omitted ‘Reduce image size so that it fits on your monitor’. Reducing file size is useful when handling images for the web.

You incorrectly omitted ‘Compress file with software and select JPG format’. JPG is a good choice when you need a smaller file size.

Also, in our example, we display the score and give the option for the student to try again.

Conclusion

The skill level needed to configure the State Response Engine is just slightly higher than constructing multiple choice or fill-in-the-blank questions in an authoring system.   The added value comes from mixing it up – putting students into different situations so that they exercise their thinking with different propositions or rules. 

If A, then…  

The SRE practices students on what Smith and Ragan² call procedural rules and relational rules or principles.   

These relationships are often described in the form of an if-then or cause-effect relationship.

If we want students to think, we need to place them in situations where they can practice thinking.  The SRE makes it possible for trainers and instructors to construct these situations with a reasonable level of skill, time, and effort.

To view the prototype, visit Photoshoot

References

1. ShortSim is a term coined by Clark Aldrich in his book ShortSims
   Aldrich, Clark (2020) ShortSims, CRC Press
2. Smith, P. L., & Ragan, T. J. (n.d.). Instructional design. 1999.

Thinking Activities

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

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

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

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