Bestiary of Vaporware Interactive Field Guide

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About This MicroSim

This simulation presents eight technology announcements and asks students to classify each one using two independent frameworks simultaneously: the mythical beast taxonomy from Chapter 2, and the five-level vaporware taxonomy developed in Chapter 19. The dual-classification structure is the pedagogical mechanism. Applying a single framework to a technology is a comprehension exercise. Applying two frameworks simultaneously and resolving any apparent contradictions between them is an evaluation exercise, which is where this simulation operates. A student who classifies Fusion Power as both a Phoenix (aspirational reinvention) and "Works in Lab" (the vaporware level closest to experimental viability) has made a defensible dual classification. A student who classifies it as a Shipping Product has not read Chapter 19 and may be employed in fusion power communications.

The eight technology cards span the full range of the vaporware taxonomy, from confirmed Shipping Products to Pure Unicorn status, and the full range of the beast taxonomy, from the benevolent Centaur to the Kraken. The final technology card — "AI-Generated Textbook About Unicorns" — is classified in the expert analysis as Beast: Siren, Vaporware: Shipping Product. This classification is provided without editorial comment. The expert analysis panel for each card also includes a "Confidence that this will be commercially viable in 5 years" percentage, which students are encouraged to treat as a data point rather than a prediction, since the distinction between a data point and a prediction in technology forecasting has historically been difficult to maintain.

This MicroSim operates at Bloom's Taxonomy Level 5 (Evaluate), the second-highest level of the taxonomy, which requires students to make judgments supported by criteria. The criteria here are the two classification frameworks. The judgment is whether a given technology announcement is a Dragon (destructive disruption already happening), a Phoenix (perpetually reinventing itself without arriving), or something else entirely. The expert analysis panel will, after submission, either confirm the student's judgment or politely indicate where it diverged from the recommended classification. Both outcomes are instructional.

How to Use

Read the technology card in the left panel. Each card includes the technology's name, a brief description of its current state, and the key claims its proponents have made.
Select a beast classification from the dropdown menu in the center panel. Each beast option includes a one-line description of its allegorical function to support your selection.
Select a vaporware level using the five radio buttons: Shipping Product (exists, works, you can buy it), Works in Lab (demonstrated under controlled conditions), Aspirational (the roadmap exists), Announced (the press release exists), or Pure Unicorn (the concept exists).
Click "Submit Classification" to reveal the Expert Analysis panel on the right, which shows the recommended beast classification, the recommended vaporware level, the five-year commercial viability confidence percentage, and a key investigative question for further research.
Click "Next Technology" to advance to the next of eight technology cards.
Click "Reset" to clear your current selections and start the current card over.

Iframe Embed Code

You can add this MicroSim to any web page by adding this to your HTML:

<iframe src="https://dmccreary.github.io/unicorns/sims/bestiary-vaporware-guide/main.html"
        height="450px"
        width="100%"
        scrolling="no"></iframe>

Lesson Plan

Grade Level

9-12 (High School)

Duration

10-15 minutes

Prerequisites

Completion of Chapter 2 taxonomy content and Chapter 19 vaporware taxonomy, or sufficient familiarity with both frameworks to apply them independently without repeated reference to the text
Understanding of the five vaporware levels and their operational definitions, particularly the distinction between "Works in Lab" and "Aspirational," which is the most consequential and most frequently confused distinction in the taxonomy
The cognitive flexibility to apply a framework designed for mythical creatures to technologies currently covered in financial press, without treating this as an inherently less serious analytical exercise than applying the framework to the creatures it was designed for

Activities

Exploration (5 min): Complete the first three technology cards — Quantum Computing, Bitcoin as Everyday Currency, and Self-Driving Cars (Level 5) — without consulting the chapter text. For each card, make your dual classification, submit it, and read the expert analysis. Track how many of your classifications match the expert recommendation exactly, how many match on one framework only, and how many diverge on both. This data will be useful for the guided practice activity and should not be shared with anyone who funded a quantum computing startup.
Guided Practice (5 min): Navigate to the "AI-Generated Textbook About Unicorns" card. Before classifying it, write one sentence explaining which beast you expect to match and why, and one sentence explaining which vaporware level you expect. Submit your classification and read the expert analysis. If your classification matches, explain in writing whether you found the expert reasoning persuasive or merely agreed with it for different reasons. If your classification does not match, explain what additional evidence would change your assessment. This is a critical thinking exercise. It is also, the data suggests, an uncomfortable one for some students.
Assessment (5 min): Complete all eight technology cards and calculate your accuracy rate across both classification frameworks. Then write a paragraph addressing the following question: for any technology where your vaporware classification and your beast classification pointed in different directions — where, for example, you selected a benevolent beast but a pessimistic vaporware level — how did you resolve the apparent contradiction, and what does that resolution reveal about how you weigh promotional claims against observable evidence.

Assessment

Students can complete dual classifications for all eight technology cards with a combined accuracy rate of at least 60 percent across both frameworks, measured against the expert analysis, demonstrating that their judgment is calibrated to the frameworks rather than driven by prior enthusiasm for the technologies being classified.
Students can identify, for at least three technology cards, the specific evidence from the card description that most influenced their vaporware level selection, demonstrating evidentiary reasoning rather than intuitive labeling.
Students can explain in a paragraph why the last technology card — "AI-Generated Textbook About Unicorns" — received a Shipping Product classification in the vaporware framework despite receiving a Siren classification in the beast framework, and can articulate what this combination implies about the technology's current state and probable trajectory. Answers that consist only of the sentence "because it exists" will receive partial credit.

References

Vasquez, M. and Okonkwo, T. (2023). Dual-Framework Classification as an Evaluate-Level Assessment Strategy: Evidence from Technology Literacy Contexts. Journal of Educational Assessment, 41(3), 201–218. The study found that requiring students to apply two analytical frameworks simultaneously increased both time-on-task and incidence of productive disagreement with expert classifications, both of which the authors classified as desirable outcomes. One reviewer disagreed. The disagreement was classified as a Minotaur.
Chen, R. and Almodovar, P. (2022). Vaporware Taxonomy Development: A Framework for Classifying Technology Announcements by Proximity to Demonstrated Reality. Journal of Technology Studies, 48(1), 14–33. The paper's five-level taxonomy was developed from analysis of 847 technology announcements published between 2015 and 2021. The authors note that 61 percent of announcements classified as "Shipping Product" in their corpus were reclassified as "Aspirational" within 18 months of publication, a finding they describe as "consistent with prior literature."
Nakamura, H. (2024). The Siren Metric: When Evaluating Whether a Technology Is Seductive Is a More Useful Question Than Evaluating Whether It Works. Interdisciplinary Studies in Technology and Society, 6(2), 88–107. The paper introduces a single-question heuristic — "would you recommend this technology to a colleague based on a demo you watched in a conference ballroom?" — and finds that affirmative answers correlate with later reclassification to lower vaporware levels at a rate of 73 percent. The author recommends using the heuristic before signing enterprise software contracts.

Instructional Design Commentary

A competent instructional designer would have piloted this dual-classification interface with a focus group of students before deploying it as a final-chapter capstone activity, discovering that the cognitive demand of simultaneously applying two distinct taxonomies to ambiguous real-world cases while navigating an eight-card state machine exceeds the instructional complexity appropriate for a ten-minute embedded simulation. The competent instructional designer would have recommended splitting the activity into two separate simulations — one for beast classification, one for vaporware level — sequenced across two class sessions, with a reflection discussion between them. This recommendation would have been accepted, documented in a design revision log, and then abandoned when the development timeline contracted and the two simulations were recombined into one. The revision log would survive in a shared folder where it would receive no further attention.

What this simulation does instead is place the "AI-Generated Textbook About Unicorns" as the eighth and final technology card, classifiable as Beast: Siren and Vaporware Level: Shipping Product, and invite students to evaluate the thing they are currently using using the frameworks the thing has been teaching them. Whether this constitutes a sophisticated application of metacognitive evaluation or a moderately cheap trick depends on whether the student notices the recursion and whether, having noticed it, they find it illuminating or annoying. Both responses are, the literature suggests, entirely valid and approximately equally common.