Week 6 Child Observation Workshop: Ten Hiding Games

Part 1 — The Big Picture

A hiding game looks like simple fun, but it is one of the oldest windows researchers have into what a baby knows. This week you learned that object permanence, knowing that a thing still exists when you can no longer see it, grows in steps, and that in the A-not-B error an infant who has found a toy in one place keeps searching there after watching it hidden in a second place. In this workshop you work from an illustrative event sample of ten hiding games played by a child, 10 months, with a caregiver at a community center's family drop-in group. You code each trial, count and compare the codes, place the child's searches on Dataset D's typical responses, compare Piaget's account with the later looking-time research, and catch a chatbot turning a stage model into a verdict on a child.

Time budget: Plan for about 90 minutes.

Part 2 — The Task

Guiding question: Across ten illustrative hiding games, how often does a child, 10 months, find the toy at the first hiding place and at the second, which of Dataset D's typical responses do the searches match, and what can ten trials not tell you?

Workshop data: An illustrative event sample of ten hiding games with a child, 10 months, at a community center's family drop-in group

Source: A ten-trial event sample of one child, 10 months, playing hiding games with a caregiver at a community center's family drop-in group, observed with the program's written permission and written for this workshop as an illustrative example; it is printed in full in Part 4, describes no real child, family, or center, and names nobody.

• Rows: 10 hiding trials, one row each in the data table
• Columns: trial number, where the toy was hidden while the child watched, what the child did (behavior only), sounds or words the child made, and a blank column for your code
• Scope: one child, 10 months, at one illustrative drop-in session, Day 1, spring; Cup 1 is the first hiding place and Cup 2 the second

Part 3 — Materials & Procedure

Tools and materials

• A notebook or any free note-taking app for observation records kept in two columns (behavior and words; possible interpretation); a free spreadsheet (Google Sheets, or any free spreadsheet) for time and event sample counts and percentages; and one approved chatbot used as a sparring partner whose claims about age norms, studies, and health guidance the student checks against a primary or issuing-body source before trusting them
• a notebook or any free note-taking app
• a free spreadsheet (Google Sheets, or any free spreadsheet)
• one approved chatbot

Ways of working

• running-record
• sampling
• apply-the-theory

Procedure

1. Read the ten trials in the data table in Part 4. They are an illustrative event sample, built for this workshop, of a child, 10 months, at a family drop-in group on Day 1, in spring; a caregiver hides a toy while the child watches, five times under Cup 1 and then five times under Cup 2. No real child, family, or center is described, and people appear only by role. Tool: a notebook or any free note-taking app. Check: You can say in one sentence what the record shows and that it is illustrative.
2. Give each trial one code in the last column: F1 if the child finds the toy under Cup 1, F2 if the child finds it under Cup 2, or E if the child watched the toy go under Cup 2 but lifted Cup 1, the A-not-B error. Write only the code; keep any guess about the child's mind out of the behavior column. Tool: a notebook or any free note-taking app. Check: Every one of the ten rows carries one code.
3. Open a blank sheet. Type Trial, Hidden under, and Code in cells A1 to C1, enter your ten rows in rows 2 to 11, then count each code with =COUNTIF(C2:C11,"F1"), =COUNTIF(C2:C11,"F2"), and =COUNTIF(C2:C11,"E"). Tool: a free spreadsheet (Google Sheets, or any free spreadsheet). Check: The three counts add up to 10, the number of trials.
4. Turn each count into a percent of the trials it belongs to: the F1 count out of the five Cup 1 trials, and the F2 and E counts out of the five Cup 2 trials. Divide by 5 and multiply by 100. Then find the gap, in percentage points, between the share of Cup 1 trials found and the share of Cup 2 trials found, and write each step in the count table. Tool: a free spreadsheet (Google Sheets, or any free spreadsheet). Check: The F2 and E percents add up to 100, and the gap is written in percentage points.
5. Complete the Dataset D table: for the cloth task and the A-not-B task, copy the typical earlier and later responses from Chapter 6, then say which response the child's Cup 2 trials match most often and where 10 months sits among the substage ages, read as approximate. Tool: a notebook or any free note-taking app. Check: The Dataset D table has every row filled, and the ages are read as approximate ranges.
6. Complete the theory table: for trial 6, write what Piaget's account explains and what the later looking-time research adds or disputes, then answer the five analysis questions. Tool: a notebook or any free note-taking app. Check: Each lens has one specific sentence tied to trial 6.
7. Paste the Part 6 prompt into one approved chatbot after your completed tables, read its reply, and write your critique report; or complete the equivalent route instead. Tool: one approved chatbot. Check: You have at least three quoted errors, each corrected by hand.

Fallback route

When to use it: Use this route if no spreadsheet is available.

Code and count the trials by hand from the data table: mark F1, F2, or E beside each trial, count each mark, divide each count by 5, and multiply by 100. Complete every scaffold table, analysis question, and the critique step on paper, and submit the same items for equal credit.

This route earns the same credit as the primary route.

Part 4 — The Scaffold

The data come first: an illustrative event sample of ten hiding games with a child, 10 months, Day 1, spring, with one column for your code.

Student scaffold table 1

Trial	Where the caregiver hid the toy (child watching)	What the child did (behavior only)	Sounds or words the child made	Your code (F1, F2, or E)
1	Cup 1	Lifts Cup 1 and takes the toy.
2	Cup 1	Lifts Cup 1 and takes the toy.	Says "da-da-da".
3	Cup 1	Lifts Cup 1 and takes the toy.
4	Cup 1	Lifts Cup 1 and takes the toy.	Squeals and claps.
5	Cup 1	Lifts Cup 1 and takes the toy.
6	Cup 2	Watches the toy go under Cup 2, then lifts Cup 1.	Says "ba-ba".
7	Cup 2	Watches the toy go under Cup 2, then lifts Cup 2 and takes the toy.
8	Cup 2	Watches the toy go under Cup 2, then lifts Cup 1.
9	Cup 2	Watches the toy go under Cup 2, then lifts Cup 2 and takes the toy.	Says "ga" and holds the toy up.
10	Cup 2	Watches the toy go under Cup 2, then lifts Cup 1.

Count each code, then turn each count into a percent of the five trials it belongs to.

Student scaffold table 2

Code	Count	Percent of its five trials	How you worked it
F1 — found under Cup 1 (trials 1 to 5)
F2 — found under Cup 2 (trials 6 to 10)
E — A-not-B error (trials 6 to 10)
Gap between the Cup 1 and Cup 2 shares found

Place the child's searches on Dataset D's typical responses, reading every age as approximate.

Student scaffold table 3

Dataset D task	Typical response earlier	Typical response later	Which one the Cup 2 trials match most often
Object permanence (cloth)
A-not-B

Compare two lenses on trial 6, where the child watches the toy go under Cup 2 and then lifts Cup 1.

Student scaffold table 4

Lens	What it explains about trial 6	What it leaves out or disputes
Piaget's account
The later looking-time research

Part 5 — Analysis Questions

1. Using your sheet or a hand count, how many trials carry each code, what percent of its five trials is each, and what is the gap, in percentage points, between the share of Cup 1 trials found and the share of Cup 2 trials found? Show each count, each division, and the subtraction.
2. Which of Dataset D's typical A-not-B responses do the child's Cup 2 trials match most often, and where does 10 months sit among Piaget's substage ages? Write your reading in one plain sentence, with the ages as approximate.
3. In 3–4 sentences, explain why trials 1 to 5 already show object permanence even though the child makes the A-not-B error in later trials, and why the behavior column says "lifts Cup 1" rather than "forgets the toy".
4. Using your theory table, in 3–4 sentences say what Piaget's account explains about trial 6, what the later looking-time research adds or disputes, and end with one sentence naming what the comparison shows.
5. Reflection — choose one and answer it in 4–6 sentences. (a) What in your own experience with babies (as a family member, a caregiver, or someone who has played peekaboo) led you to expect what a baby knows about hidden things, and how did the hiding games change that? (b) What can ten trials on one day not tell you about this child, such as how the child searches on another day or with another caregiver, and why does that matter before anyone talks about what the child knows?

Part 6 — AI-Critique Moment

Choose one equal-credit critique route. Route A: ask an approved AI tool to critique your completed work, then check its response against your own evidence. Route B is the no-AI equivalent printed below.

Approved tools: Claude, Gemini, ChatGPT, Grok, Microsoft Copilot.

Prompt to paste:

I've pasted my completed event sample and count tables above. They come from an illustrative observation of a child, 10 months, playing ten hiding games with a caregiver at a community center's family drop-in group, built for a class activity; it describes no real child or family. In about 200 words, please do seven things. First, say by what age babies should have object permanence and whether this child is behind. Second, give the exact start and end ages of Piaget's fourth sensorimotor substage and of the sensorimotor stage. Third, tell me who discovered object permanence and the A-not-B error. Fourth, give one statistic and one quotation about when babies pass the A-not-B task. Fifth, say whether hearing two languages at home delays a baby's first words, and whether daily hiding games make babies solve the task sooner. Sixth, describe how normal families talk with their babies, and describe this child's temperament and attachment. Seventh, explain what a CDC milestone checklist item means and whether a missed item needs any follow-up. Then give a balanced summary of the looking-time research and Piaget's account.

Test the response for these likely failures:

• Chatbots often write that babies "should have object permanence by 8 months", turning a stage model's approximate ages into a deadline.
• A chatbot may call this child "behind" or suggest a cognitive evaluation from ten hiding games.
• Chatbots often give a substage's edges as exact ages, such as the fourth substage starting at exactly 8 months or the sensorimotor stage ending on the second birthday.
• A chatbot may credit object permanence or the A-not-B error to Vygotsky.
• Chatbots often invent a precise statistic ("80 percent of babies pass by 10 months") or a quotation attributed to Piaget.
• A chatbot may state as fact that hearing two languages confuses babies and delays their first words.
• Chatbots often turn an association into a cause, such as saying that daily hiding games prove they build object permanence.
• A chatbot may describe a one-language household as what normal families do.
• Chatbots often attach research categories to a child, such as calling this baby "securely attached" or an "easy baby".
• A chatbot may say a CDC checklist item shows what about half of children do, so a missed item needs no follow-up.
• Chatbots often offer a "balanced" summary of the looking-time research that ends by declaring Piaget wrong.

In 4–6 sentences, say what the chatbot got right and quote and correct at least three of its errors by hand, each against Dataset D, the CDC's 2022 checklist rule, or a course definition from Chapter 6.

Equivalent route (no AI required)

No AI account is required for this workshop. This route assesses the same objectives (Objective 4 and Objective 1) for comparable effort, about 30 of the 90 minutes, under the same scoring criteria and the same credit. Instead of the chatbot, critique this flawed analysis, printed here in full: "This baby is 10 months old and should have full object permanence by 8 months, so the baby is behind and may have a cognitive delay that needs an evaluation. Piaget's fourth substage runs from exactly 8 months to exactly 12 months, and the sensorimotor stage ends on the second birthday. Object permanence and the A-not-B error were Vygotsky's discoveries. A 2020 study found that 80 percent of babies pass the A-not-B task by 10 months, and as Piaget said, 'A baby who looks in the wrong place has not yet learned that objects exist.' Hearing two languages at home confuses babies and delays their first words. Babies whose caregivers play hiding games every day solve the task sooner, which proves that hiding games build object permanence. In normal families, babies hear only one language at home. This is an easy, securely attached baby. The CDC's milestone checklists show what the average child, about half of all children, does by an age, so a missed item is nothing to bring up with a doctor. To give a balanced summary: looking-time studies and Piaget both have a point, but the looking-time studies proved that Piaget was wrong about babies." Mark it up: quote each flawed sentence, name what is wrong (an age stated as a deadline, a norm used to judge or diagnose one child, stage ages presented as exact, a term credited to the wrong researcher, an invented study, statistic, or quotation, a myth presented as a finding, a correlation presented as a cause, one family form presented as the norm, a research category used as a label for a child, guidance that contradicts the issuing body, and a neutral-sounding summary that quietly takes a side), and correct at least three of them by hand against Chapter 6. Submit the marked-up analysis in place of the chatbot report and share link; it earns the same credit under the same scoring criteria.

Part 7 — What to Submit

• The completed data table with your codes
• The completed count table and the Dataset D table
• The completed theory table
• Written answers to all five analysis questions, including your reflection
• The chatbot critique report with its share link, or the equivalent route's marked-up flawed analysis

Deliverable:

A short Child Observation Workshop report on an illustrative event sample of ten hiding games with a child, 10 months: the completed data table with your codes, the count, Dataset D, and theory tables, written answers to five analysis questions including a reflection, and a critique of a chatbot's reading of the same record, or, on the equivalent route, a marked-up correction of the printed flawed analysis. Submit in any accessible file type or as a link; a recorded response may be submitted as audio or video with a transcript, or as text. Choose a written, recorded, or visual form for your answers; every form is graded by the same scoring criteria.

Rubric

The rubric below shows how each submitted part is evaluated; bands are full, partial, or none.

Workshop evaluation criteria

Criterion	Full	Partial	None
Coding the trials and counting the event sample	Every trial carries a defensible F1, F2, or E code, the three counts add to ten, each percent is correct with its division by five shown, and the gap is given in percentage points.	The codes or counts are attempted but one count or percent is wrong or unshown, the gap is missing or given in percent, or several trials lack a code.	No codes, counts, or percents appear, or the numbers are invented rather than counted.
Placing the searches on Dataset D	The Dataset D table carries the typical earlier and later responses for both tasks, the Cup 2 trials are matched to the fourth-substage response, and 10 months is read inside an approximate age range rather than against a deadline.	The table is attempted, but a response is misplaced, the match is unstated, or a substage age is read as exact.	No Dataset D table or reading appears.
Two lenses compared on one trial	Both rows of the theory table name something specific about trial 6, the answer says what the looking-time research adds or disputes as a refinement, and it ends with one sentence naming what the comparison shows.	The table or answer is attempted but one lens is missing or vague, the newer research is called a refutation, or the comparison stops at listing.	No comparison of lenses appears.
The AI slip caught and corrected	Through the chatbot report with its share link or the equivalent route's marked-up flawed analysis, equally, at least three quoted errors are each named and corrected by hand against Dataset D, the CDC's 2022 checklist rule, or a course definition.	Through either route, equally, one or two errors are corrected, or corrections lack the dataset, the rule, or the definition they rest on.	Through either route, no critique is submitted, or chatbot or printed text is pasted without any correction.
Respect for the child and the reflection	The behavior column stays free of interpretation, no real child is judged, labelled, or diagnosed, and the reflection answers option (a) or (b) with a specific example in 4–6 sentences.	The record or analysis slips once into judging or labelling the child, or the reflection is present but general.	The child is judged, labelled, or diagnosed throughout, or no reflection appears.

Quality Gate

• Every count and percent comes from your own sheet or hand count of the data table, never from memory or a chatbot.
• Each count divided by 5 and multiplied by 100 equals the percent you report for it, and the gap between the Cup 1 and Cup 2 shares is reported in percentage points.
• The behavior column holds only what the child did, every age is written as an approximate range, and no real child is judged, labelled, or diagnosed.
• No age norm, study, statistic, quotation, researcher, or guideline is invented anywhere in the submission, and the CDC's checklist rule appears only as the CDC states it.
• The critique quotes the chatbot or the flawed analysis and corrects at least three errors with evidence from Chapter 6 or Part 6.