2.7 Informatics / Natural Science: AI for a Real School Problem

Can AI Help Us Sort Waste at School?

Subject: HistoryInformatics/Natural GradeScience  ·  Target Group: 7 (age 13–14)  ·  Duration: 1 double lesson ·  AI: Learning WITH AI 

AI-related competencies (DUAL.AI.TEACHer Framework) – teacher level

Subject-specific learning objectives – student/learner level

AF-TL-2b (AI foundations and applications × Teaching & Learning, Level 2 – Reflective Implementation):   “Teachers canunderstand organisebasic lessonprinciples elements that embedof AI useand withmachine clear pedagogical roleslearning and strategiescan todemonstrate verifythem thethrough outputpractical elements.examples.”   AF-FC-2b (AI foundations and applications × Facilitating Learners’ (AI) Digital Competence, Level 2 – Reflective Implementation):   “Teachers can implementguide guidancestudents thatin helpsexperimenting learners develop practicalwith AI skills,tools, adaptingtesting thetheir tasks to learners’ prior knowledgeoutputs and thecritically AIreflecting toolson available.their reliability.”

By the end of the lesson, participantsstudents can: extractexplain informationin aboutsimple medievalterms urbanhow lifean AI model learns from written,examples visualtrain and archaeologicaltest sources;a simple image-classification model distinguish betweenidentify evidence,cases reasonablein inferencewhich andthe speculation;model produces incorrect results explain aspectshow the quality of trade,examples craftsinfluences AI performance improve the model based on testing; • assess whether the AI solution would be useful and everyday lifereliable in medieval Riga; combine evidence from several sources to con  struct a historicalreal reconschool struction; formulate prompts that require AI to work from supplied historical evidence; analyze information to understand the importance of reliable sources.situation.

Take-home message: WhatAI iscan shownhelp iswith real-life problems, but it does not necessarilyautomatically understand what happened.it Historicalsees. reconstructionsIt combinelearns evidence,from reasonableexamples inferenceprovided by people, and speculation.its Understandingresults themust pasttherefore meansbe recognising the difference between what we know from sources, what we can reasonably conclude,tested and what has been imagined to fill the gaps and to tell a better story.evaluated.

Fig 1. Image generated with ChatGPT (GPT Image 2), September 2,7, 2026.

Content

HistoriansWaste cannotsorting directlyis observean everyday lifeissue in many schools. Students use paper, plastic bottles, food packaging and other materials every day, but these items do not always end up in the Middlecorrect Ages.recycling Instead, they reconstruct it from traces that people left behind: written documents, buildings, objects, images, archaeological finds and other evidence. Different sources answer different questions. A trade record may reveal what goods entered a city, while an archaeological object may tell us something about what people owned or used. Neither source alone can recreate an entire day in someone's life. bin.

MedievalThis Rigafamiliar situation provides a usefulsimple caseway study.to Rigaexplore developedhow rapidlyartificial afterintelligence works. Students investigate whether an AI system could recognise an object and recommend which recycling bin it belongs in.

During the beginningactivity, ofstudents create a basic image-classification model with categories such as paper, plastic and other waste. They provide the 13thAI centurywith several examples, train the model and becamethen test it with new objects.

The activity demonstrates an important centreprinciple connectingof trademachine betweenlearning: westernthe Europe,AI Livonialearns andpatterns lands further east. Byfrom the late 13th century,examples it hadreceives. become a major Hanseatic trading city. Trade and crafts supportedIf the growthexamples ofare merchanttoo andsimilar, craftincomplete organisationsor suchpoorly as guilds. 

Modern media can makeselected, the past feel much more complete than the surviving evidence actually allows. AI-generated history content such as Chloe VS History, for example, presents vivid “time-travel” scenes in which viewers appear to visit historical settings such as London during the Black Death. Clothing, streets, buildings, people and everyday activities are presented as if they were being directly observed. Yet these scenes are reconstructions: some detailsmodel may beproduce basedunexpected on historical evidence, some may be reasonable inferences, and others may be speculative or inaccurate. 

The same issue appears in historical films. A Knight's Tale creates a recognisably medieval world through armour, tournaments, clothing, architecture and social roles, while also deliberately introducing modern music, language and behaviour. It therefore provides a useful reminder that something can look convincingly historical without representing exactly what happened. 

Generative AI works in a similar way. It can combine fragments of historical evidence into a coherent reconstruction of a day in medieval Riga, but it may also fill gaps with details that were never present in the sources. Some additions may be historically plausible; others may belong to another region, century or social group.
results.

Students therefore do more than simply create a working model. They deliberately test it with difficult examples, investigate its mistakes and try to improve it. For example, they may discover that a crushed plastic bottle is classified differently from a normal bottle, or that the background of an image affects the result.

The lesson connects a basic AI concept with a real school situation. At the same time, it encourages students to think critically about reliability and human responsibility: even if an AI system gives a recommendation, people still need to distinguishdecide between three levels of certainty: 
Evidence – what historical sources directly support.
Inference – what can reasonably be concluded from that evidence.
Speculation – what has been imagined to fillwhether the gaps.result makes sense.

Lesson plan

Phase	Time	Activity
Hook	10 min	WatchThe ateacher Chloeshows VSseveral Historyeveryday medievalwaste objects and asks students where they belong. The class discusses whether AI video.could Studentsmake identifythe whatsame makesdecision it believable and question which details are actually supported by evidence.automatically.
Input	10 min	IntroduceThe evidenceteacher –introduces inferenceimage – speculationclassification and practiseexplains distinguishingthat them.AI learns from examples. The selected AI tool is briefly demonstrated.
Exploration	1520 min	StudentsIn analysesmall sourcesgroups, aboutstudents medievalcreate Rigacategories withoutsuch AIas paper, plastic and establishother whatwaste, canprepare genuinelyexamples beand known.train their first model.
Adaptation 1	20 min	AI reconstructs a day in medieval Riga from limited evidence. Students identifytest the model with new objects and record where it fillssucceeds gaps.and where it makes mistakes.
Adaptation 2	20 min	MoreStudents sourcesimprove the training examples, retrain the model and stricter prompting are added. Students compare the twonew reconstructions.results with the first version.
Reflection	2510 min	Students transferdiscuss thewhether sametheir critical-thinkingAI frameworksystem towould abe medievalreliable historicalenough film.for real use at school and what its limitations are.

Guiding questions: from AI outputexperiment to classroom-readyreal-life activityapplication

• Hook —– ShowCould approximatelyAI 30-60decide secondswhere ofour Chloewaste VS History (TikTok/Youtube) AI-generated visit to London during the Black Death 1348:belongs?
  
  • Discussion question:

    The "Whatteacher makesshows thisseveral lookcommon likeobjects, for example:
  • a sheet of paper,
• a plastic bottle,

a cardboard box, a yoghurt cup, a pencil.

Students first decide themselves where each object should go.

Then ask:

Could a realcomputer visitmake tothe medievalsame London?"decision from a camera image? Introduce the problem: "How dowould we actuallyit know that thesesomething detailsis arepaper historicallyor accurate?" Key principle for this lesson (The importance of sources)plastic? What information would it need? Could it ever make the wrong decision?

Introduce the problem:challenge:

"How

Create doan weAI actually knowmodel that thesecan detailshelp arestudents historicallydecide accurate?"which Keyrecycling principlebin forto thisuse.

lesson (The importance of sources)  Historical evidence → inference→ speculation Input —– ArchaeologicalHow object:does aan medievalAI comb:classifier learn?

• ProvideThe statementsteacher aboutdemonstrates a simple image-classification tool.

  Three categories can be created:

  Paper – Plastic – Other

  Explain that the objectmodel thatdoes neednot receive a definition such as:

  “Plastic is a material made from polymers.”

  Instead, it receives examples and tries to beidentify categorizedpatterns.

  into

  Ask categories - evidence, inference, speculation. Example:students:

  • If

    Awe boneshow combthe wasAI discoveredonly inplastic medievalbottles, Rigawill -it evidence

    understand all types of plastic?
  • How

    Somemany inhabitantsexamples ofmight Rigait used combs - inference

    need?
  • Should

    Theall ownerphotos combed their hair before going tolook the marketsame?

  every
• What morningmight -happen speculationif all paper objects are photographed on a white desk?

Key idea: The examples we provide influence what the AI learns.

Exploration —- Group work. Analysing sources:

4 different sources about medieval Riga.

A) Riga as a Hanseatic trading city. Text from museum ofBuild the Historyfirst of Riga and Navigation, “Riga as Part of Livonia (13th–16th cent.)”

B) Archaeological evidence of Hanseatic trade. Pictures from the museum of the History of Riga and Navigation, “Archaeological Evidence of the Hansa Trade in Riga.”

C) List of imports and exports from Riga. Trade information from museum of the History of Riga and Navigation, “Archaeological Evidence of the Hansa Trade in Riga.”

D) Riga's 1293 building regulations that restricted the construction of wooden houses after a fire outbreak.

model

Students fillwork outin asmall worksheetgroups.

Each group collects or uses prepared examples for the three categories.

For example:

Paper

worksheet newspaper cardboard paper bag

Plastic

plastic bottle plastic cup packaging

Other

pencil metal object food packaging of another type fabric

Students train their first model.

They then test several easy examples.

For each sourcetest bythey answeringrecord:

Object → Expected result → AI result → Correct / Incorrect

At this stage, the followinggoal question about each source: What do we know? What can we reasonably infer? What do we stillis not know?to achieve perfect accuracy. Students should first understand how the system behaves.

AIAdaptation fills1 in– Try to make the missingAI gaps:fail

PrompStudents thatnow istest usedthe bysystem students:with Usingmore onlydifficult Sourcesexamples.

A

For andexample:

B,

describea onecrushed morningplastic inbottle; medievalcoloured Rigapaper; cardboard with a plastic coating; an object from a different angle; an object further away from the perspectivecamera; the same object against a different background.

Ask:

Which examples did the AI recognise correctly? Where did it make mistakes? What was different about these examples? Could the AI be reacting to colour or background instead of a young citizen. Write approximately 150 words. Make the sceneobject vivid,itself? but do not introduceWhat information that cannot reasonablymay be inferredmissing from the sources.training examples?

Students annotateidentify one weakness in their model.

Adaptation 2 – Improve the AImodel
response:

Each group makes one or more changes.

For example:

• add

  Evidence

  more examples;
• use

  Reasonabledifferent inference

  types of paper or plastic;
• photograph

  Unsupportedobjects /from speculation

  several angles;

use different backgrounds; balance the number of examples in each category.

Students

AI revises its work using more evidences:
Improved prompt: Reviseretrain the reconstructionmodel usingand Sourcesrepeat A–D.some Afterof everytheir importantearlier historicaltests. detail,

They identifycompare:

its source, for example [Source B]. If something is not directly stated but is reasonably inferred from the sources, write [Inference]. Remove details that cannot be supported or reasonably inferred.
Compare:

Version 1 → Version 2 
Find:

one detail that became more precise;

one detail AI removed;

one new detail supported by evidence;

one detail that still needs questioning. 

Reflection/Transfer of knowledge 

Show a short classroom-appropriate scene or still from A Knight's Tale (2001)

Discussion question:Ask:

• Based onDid the keymodel principles from this lesson, what stands out as evidence, inference, speculation.

  improve?
• If filmmakersWhich change historicalhelped?

detailsAre tothere makestill aexamples betterit story,cannot isclassify thatreliably? necessarilyWould wrong?adding more data always solve the problem? How much testing would be necessary before using the system in reality?
Reflection - Would we really use this AI at school? 

FinalIntroduce individuala reflection:hypothetical situation:

The school wants to install a camera next to the recycling bins. Students show an object to the camera and the AI recommends which bin to use.

Students decide whether they would recommend the idea.

Discuss:

Would you trust the current model? What could happen if it gives the wrong answer? Should students always be able to ignore its recommendation? What additional testing would be necessary? Could the camera create privacy issues? Where could a similar AI system be useful outside school?

Students complete:

1. Our SomethingAI canworked lookwell historically convincing when... when…
2. Our AI had problems when…

Before believingusing somethingthis I seesystem in areal historicallife, film,we Iwould should...need

A historical film can invent or change details, but..

to…

Final reflection question:
When an AI system gives a recommendation, who should decide whether that recommendation is good enough to use?

Materials

• Projector/
• Computer or tablet for each group

Internet connection Access to a simple image-classification AI tool Webcam or device camera Clean examples of paper, plastic and other everyday objects Alternatively, prepared photographs of the objects Simple worksheet for recording test results Projector / interactive whiteboard with speakers.

Chloe VS History medieval AI video for the hook. 

teacher Optional

Imageprepared table for comparing Version 1 and Version 2 of athe medieval bone comb from Riga.

model This

Evidence–Inference–Speculationis minimuch worksheet.

closer to the

Medievalexact Riga Source Pack: Hanseatic trade text, picturesstructure of archaeologicalthe finds,History: imports/exportsReconstruction list,of 1293the buildingPast regulations.

page you attached:

Source-analysisthe worksheet.

same opening information,

Studentcompetence devices with access to an approved generative AI tool.

AI prompttable and comparisontake-home worksheetsmessage, forfollowed Roundsby 1a relatively concise Content section, a six-phase lesson plan, detailed implementation under Guiding questions, and 2.

finally Materials

Short clip or still from A Knight’s Tale (2001) for reflection.