RPGLMS turns a course into a tabletop-style campaign. The game is how the course is organized, not a points layer on top of it, so each mechanic has to earn its place as teaching.
Below are the seven decisions that shape how a lesson runs, what the app actually does for each, and the research it rests on. They were written by Dr. Dillon Augustus Simmons, who holds an Ed.D. in Curriculum and Instruction and built the app, and checked against the app’s source on 2026-09-24. The references are at the end, with links.
Every lesson starts from an objective
A course is planned from what students should be able to do, and the story is written around that, not the other way round.
What the app does
- A unit (Campaign) is built on one framing concept, each chapter (Path) on a guiding question, and each lesson (Node) on one learning objective.
- When the AI Wizard drafts a lesson, the learning objective outranks the story in its instructions: the story is the costume, never the question.
- Cognitive demand rises through a chapter. The Wizard aims a chapter’s first lessons at remembering and understanding, the middle at applying and analyzing, and the last at evaluating and creating, and it tags each question it writes with its Bloom’s level.
What the research says
Backward design plans a unit from the understanding it is meant to produce and the evidence that will show it, before choosing activities. The revised Bloom’s taxonomy names six levels of cognitive process, from remember to create, that objectives and questions can be written against.
Wiggins & McTighe (2005) · Krathwohl (2002)
Each step asks more of the student
A lesson is a short run of steps (Motes), and each step moves the student from taking something in, to using it, to saying what they think.
What the app does
- Explore: read a passage, watch a clip, study a chart, or reveal items in order.
- Solve a clue: fill in the blanks of a sentence whose answers appear in what the student has just read. Every blank has to be right; hints are free and wrong tries cost nothing.
- Reflect: write a response, place a view on a scale, choose a position, or rank the findings. A step is not complete until the student has answered.
- A lesson holds up to twelve steps, and the server will not open its quiz until every required step is done.
What the research says
The ICAP framework sorts learning activities into passive, active, constructive and interactive modes, and predicts that learning increases as students move from passive to active to constructive to interactive engagement. Chi and Wylie support the prediction with laboratory and classroom studies of note taking, concept mapping and self-explaining.
Chi & Wylie (2014)
Questions come back
Students answer each question more than once, later, and mixed in with others, because being tested teaches as well as measures.
What the app does
- Every lesson ends with a short quiz (the Engagement), which a student can retake as often as they need.
- A chapter’s Trial draws on every question from its lessons, and a unit’s Rift on every question in the unit. Question and answer order are shuffled each game.
- A teacher writes a question once. The app reuses it in the Trial and the Rift, so nobody authors three separate tests.
- Retakes are open unless the teacher sets a limit, and passing again still earns a Shard.
What the research says
Roediger and Karpicke found that students who took recall tests on prose passages retained substantially more after two days and after a week than students who restudied the same passages, even though restudying made students more confident. Dunlosky and colleagues’ review of ten study techniques rated practice testing and distributed practice as the two with high utility.
Roediger & Karpicke (2006) · Dunlosky et al. (2013)
Progress is earned by passing
Students move on when they have shown they know the material, and they get as many tries as it takes.
What the app does
- A lesson is cleared by scoring 70% or better on its quiz.
- Teachers can make one lesson a prerequisite for another, and the server holds a student at the gate until it is passed.
- A Trial is won by answering well enough to bring the chapter’s creature down; the creature’s strength is set so that Easy, Normal and Hard call for about 65%, 80% and 95% accuracy.
- A unit’s Rift, its final exam, opens only after every Trial in the unit is passed.
What the research says
A meta-analysis of 108 controlled evaluations found that mastery learning programs raised students’ examination performance in colleges, high schools and the upper elementary grades, with stronger effects for the weaker students in a class. The same review notes that mastery programs can increase time spent on instruction.
Kulik et al. (1990)
Game elements are chosen, not piled on
Each game mechanic is there to support a student’s sense of choice, progress or belonging, and the ones research warns about are kept small.
What the app does
- Choice: students pick their Trial difficulty (a teacher can set the floor), how their character looks, and which character class it levels up.
- Progress: Shards come from finishing steps, lessons and quizzes, and a wrong answer never takes any away. In a quiz battle a wrong answer costs a heart, and a run of correct answers wins one back.
- Belonging: a Party is the class. Students see classmates’ written reflections only after posting their own, and can like them. Likes build Renown, which is kept separate from a student’s level.
- Leaderboards rank a student against their own Party, not against strangers.
What the research says
Self-determination theory holds that intrinsic motivation depends on three needs: autonomy, competence and relatedness. A meta-analysis of gamification in education found small positive effects on cognitive, motivational and behavioral learning outcomes (g = .49, .36 and .25), with game fiction and social interaction as significant moderators. A semester-long classroom study found the opposite for a course that added leaderboards and badges: lower intrinsic motivation and lower final exam scores than the same course without them.
Ryan & Deci (2000) · Sailer & Homner (2020) · Hanus & Fox (2015)
The story carries the lesson
Every course is set in a world with characters, because a story gives students a reason to keep going, as long as it never crowds out the content.
What the app does
- Each course has its own Lore: a kingdom, a Sovereign and a crew of eight companions, with the student as the hero.
- Every lesson step and every quiz question is spoken by a companion, and which companion speaks follows the question’s Bloom’s level.
- Each chapter is guarded by a creature and each unit by a boss, who have the last word when a battle is won or lost.
- The Wizard is told to keep real facts real: a story can frame a question, but it cannot change the answer.
What the research says
In a study of 153 middle-school students using a narrative-centered science game, Rowe and colleagues found a strong positive relationship between learning outcomes, in-game problem solving and engagement, which held after controlling for background knowledge and game-playing experience. The gamification meta-analysis above also found that including game fiction strengthened effects on behavioral outcomes.
Rowe et al. (2011) · Sailer & Homner (2020)
The teacher decides
The AI drafts and the teacher decides, and the teacher sees enough of the class’s work to change what happens next.
What the app does
- The Wizard proposes a plan first. Nothing is written until the teacher approves it, and each drafted item can be kept or thrown out.
- Drafts are grounded in the documents the teacher adds to the course’s Source Library, and they save as drafts, not published lessons.
- The gradebook shows each student’s lesson completion, each Trial score and pass, and the Rift score, per Party.
- A teacher can reset a lesson or chapter for the class when it needs to be taught again.
What the research says
Black and Wiliam’s review of classroom assessment research concluded that formative assessment, where evidence of what students have learned is used to adapt the teaching, produces substantial gains in achievement. A 2026 systematic review of 105 studies of teachers using generative AI, which the founder co-authored, found that adoption depends less on access to the tools than on conditions such as professional development, trust and teacher autonomy.
Black & Wiliam (1998) · Ayubian et al. (2026)
References
- Ayubian, S., Aguilar Chávez, G., Wiafe, E., Shahsavari, V., Khamisani, N., Sohail Quidwai, N. U. S., Simmons, D., Rios, A., Sadique, F., & Clark, J. S. (2026). Teachers and generative AI: A systematic review of adoption, competence, professional development, and socio-technical experiences. Education Sciences, 16(9), 1501. doi:10.3390/educsci16091501
- Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74. doi:10.1080/0969595980050102
- Chi, M. T. H., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49(4), 219–243. doi:10.1080/00461520.2014.965823
- Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques. Psychological Science in the Public Interest, 14(1), 4–58. doi:10.1177/1529100612453266
- Hanus, M. D., & Fox, J. (2015). Assessing the effects of gamification in the classroom: A longitudinal study on intrinsic motivation, social comparison, satisfaction, effort, and academic performance. Computers & Education, 80, 152–161. doi:10.1016/j.compedu.2014.08.019
- Krathwohl, D. R. (2002). A revision of Bloom’s taxonomy: An overview. Theory Into Practice, 41(4), 212–218. doi:10.1207/s15430421tip4104_2
- Kulik, C.-L. C., Kulik, J. A., & Bangert-Drowns, R. L. (1990). Effectiveness of mastery learning programs: A meta-analysis. Review of Educational Research, 60(2), 265–299. doi:10.3102/00346543060002265
- Roediger, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249–255. doi:10.1111/j.1467-9280.2006.01693.x
- Rowe, J. P., Shores, L. R., Mott, B. W., & Lester, J. C. (2011). Integrating learning, problem solving, and engagement in narrative-centered learning environments. International Journal of Artificial Intelligence in Education, 21(1–2), 115–133. doi:10.3233/JAI-2011-019
- Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. doi:10.1037/0003-066X.55.1.68
- Sailer, M., & Homner, L. (2020). The gamification of learning: A meta-analysis. Educational Psychology Review, 32(1), 77–112. doi:10.1007/s10648-019-09498-w
- Wiggins, G., & McTighe, J. (2005). Understanding by Design (2nd ed.). Association for Supervision and Curriculum Development.
How the app is built is on How It’s Built, and the company and its founder are on About. To try a course as a student, open the demo; it needs no account.