1. Introduction and problem

In the 3-to-6 age band —kindergarten, preschool, CENDI, early childhood school— a package of five artifacts has been installed as if it counted as support for playdough / clay play: a sensor or wearable that “scores molding accuracy” or a “playdough molding accuracy score” / “fine-motor dough score” / “shape compliance score” for the child; a computer-vision / table camera system that labels “mess” or “dough outside the tray” or triggers “mess / off-task dough spilling” alerts; a chatbot/GenAI that generates “playdough figure plans” or “playdough lesson plans” or “STEM dough activities” by prompt (for the child or as a recipe the adult reads); a dashboard of “minutes with playdough” / “molding score” / “fine-motor dough minutes” for administrative surveillance; and an AR layer that “guides” kneading or predicts the “correct shape.” The five allow centers to display that they “already do playdough with AI.” The leap —from molding score, mess alert, generated plan, minutes metric or AR guidance to claiming support— is not authorized by AI-in-ECE mappings nor by the pedagogy of playdough when there is real deformable dough (kneading, pinching, rolling, flattening, cutting with open tools; homemade or commercial dough), real tactile properties (resistance, elasticity, temperature), child agency to explore without an expected product, adult co-presence that names properties and sustains conversation, and tolerance of dough residues on the table as a condition of the medium, not as error.

The thesis of this article is restrictive. A sensor or wearable that “scores molding accuracy” or a “playdough molding accuracy score” / “fine-motor dough score” / “shape compliance score” for the child, a computer-vision / table camera system that labels “mess” or “dough outside the tray” or triggers “mess / off-task dough spilling” alerts, a chatbot/GenAI that generates “playdough figure plans” or “playdough lesson plans” or “STEM dough activities” by prompt, a dashboard of “minutes with playdough” / “molding score” / “fine-motor dough minutes” for administrative surveillance, or an AR layer that “guides” kneading or predicts the “correct shape” do not constitute support for playdough play in the early years. In early childhood playdough develops with real dough, child agency, adult co-presence that names properties and sustains conversation (Yuniyartika & Sudaryanti, 2024; Darizal et al., 2023; Rukmini et al., 2022; Martuty et al., 2025; Sando et al., 2023), and tolerance of mess; not a molding score, a mess classifier, a plan generator that closes uncertainty, or a minutes dashboard. Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Rukmini et al. (2022), Wijaya et al. (2023) and Martuty et al. (2025) provide playdough findings in classroom/kindergarten settings with marked context limits and transfer: they are read through the dough medium, not as a generic motor-skills axis already published; in Wijaya et al. collage is not the axis. That authorizes asking what was measured: molding accuracy, mess label, lesson plan by prompt, fine-motor dough minutes or AR prediction of “correct shape” —not the practice when a child kneads, pinches, rolls, flattens and receives co-presence that names resistance, elasticity or temperature without closing uncertainty.

The problem is worsened by six category confusions. First: playdough / clay play is not sand play —the axis is deformable dough with real tactile properties, not the granular medium already published—. Second: it is not water play —not the liquid already published—. Third: it is not loose parts —Sando et al. (2023) anchor objects-in-play; here the medium is deformable dough, not Nicholson’s collection—. Fourth: it is not motor skills as axis —Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Rukmini et al. (2022), Wijaya et al. (2023) and Martuty et al. (2025) may report lateral motor outcomes; the axis is the dough/clay medium—. Fifth: it is not artistic creativity as axis —here it is not generic plastic expression already published; the axis is playdough as an open-play material—. Sixth: it is not clinical playdough therapy —Ferasinta and Dinata (2021) is a peripheral contrast of play therapy ≠ classroom playdough—. This work does not recycle sand play, water play, outdoor play, free play, loose parts, risky play, block play/spatial, symbolic play, motor skills, STEM/robotics, artistic creativity, SEL, executive functions, environmental education, scientific inquiry as axis, literacy, orality, UDL, documentation, formative assessment, participation, planning, joint attention, adult–child interactions as generic axis, teacher education, music or numeracy. Galbraith (2022) is a peripheral contrast of pedagogies of play, not a teacher-education axis already published. The question is what counts as support for playdough when a center “does AI and playdough play.”

There is, moreover, an economy of coordination: the five artifacts fit on a slide; the prolonged episode with real dough, child agency, tolerated mess and co-presence that names tactile properties does not. NAEYC (2022) and OECD (2021, 2023) require meaningful interactions and subordinated digitalization. Inference: support is not fulfilled by scoring molding or generating figure plans by prompt. The contributions are three: separate craft from artifacts; examine marked cases (Yuniyartika & Sudaryanti, 2024; Darizal et al., 2023; Rukmini et al., 2022; Wijaya et al., 2023; Martuty et al., 2025; Sando et al., 2023; Ferasinta & Dinata and Galbraith peripheral); and offer four tests of support for playdough / clay play.

2. State of the art: from situated playdough practice to the artifact on display

It is useful to separate four strata that the “AI for playdough in ECE” market often blends. The first is the construct of playdough / clay play ages 3–6 as open exploration of a deformable material with real tactile properties —kneading, pinching, rolling, flattening, cutting with open tools; homemade or commercial dough; resistance, elasticity, temperature— and mess of dough residues on the table as a condition of the medium (Yuniyartika & Sudaryanti, 2024; Darizal et al., 2023; Rukmini et al., 2022; Wijaya et al., 2023; Martuty et al., 2025; Sando et al., 2023). The second is the pedagogical craft that cultivates it —real dough at table or tray; agency without expected product; co-presence that names properties; tolerance of mess; not substituting exploration with molding accuracy or a mess classifier— (Yuniyartika & Sudaryanti, 2024; Darizal et al., 2023; Rukmini et al., 2022; Martuty et al., 2025; Galbraith, 2022, peripheral contrast; NAEYC, 2022; OECD, 2021, 2023). The third is evidence on AI affordances in ECE and child-centered GenAI —without equating them to situated playdough with real dough— (Chen, 2024; Su & Yang, 2022; Su & Zhong, 2022; Ljungcrantz, 2026; Nikolopoulou, 2025). The fourth is the rights, systems and developmentally appropriate practice framework that treats the 3–6-year-old as a subject who explores the deformable, not as a vector of signals for a playdough molding accuracy pipeline nor as a passive recipient of GenAI plans or AR “correct shape” predictions that close uncertainty (UNESCO, 2021; Miao & Holmes, 2023; U.S. Department of Education, 2023).

In construct and craft, Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Rukmini et al. (2022), Wijaya et al. (2023) and Martuty et al. (2025) articulate playdough media play / games in early childhood: empirical findings with marked transfer toward the dough medium (not motor skills as axis; collage not as axis in Wijaya). Sando et al. (2023) —N = 928— associate manipulable objects with deep-level learning: objects-in-play, not loose parts or sand/water. Ferasinta and Dinata (2021) are a clinical peripheral contrast; Galbraith (2022), an adult peripheral contrast. Inference: a molding accuracy score does not name deformable properties; a child who kneads and an adult who converses do.

In the artifact stratum, Chen (2024), Su and Yang (2022), Su and Zhong (2022) and Ljungcrantz (2026) map affordances, curricula and the state of the art of AI in ECE without equating them to situated playdough. Nikolopoulou (2025) balances promises and challenges of child-centered GenAI under teacher mediation: caution framework. In the systems stratum, UNESCO (2021) requires human oversight. Miao and Holmes (2023) set pedagogical validation and age thresholds for generative AI —direct framework for generators of “playdough figure plans” or STEM dough activities by prompt—. U.S. Department of Education (2023) requires AI to support, not replace, professional judgment. OECD (2021, 2023) anchor meaningful interactions and subordinated digitalization; NAEYC (2022) anchors developmentally appropriate practice.

3. Review method

A critical narrative review was conducted, not a primary meta-analysis. The purpose was not to estimate a homogeneous effect size of the five artifacts, but to articulate a pedagogical-category argument with verified sources. Inclusion criteria: (a) 2021–2026, with marked transfer when the sample is not equivalent to ages 3–6; (b) playdough, clay play, deformable dough, tactile dough properties, or AI in ECE with artifact/craft relevance; (c) kindergarten, preschool, CENDI or ages 3–6; (d) peer-reviewed journal, DOI or NAEYC/UNESCO/OECD report; (e) verifiable DOI or editorial page. Axes already used in this series were excluded as central objects —sand play, water play, generic outdoor play, free play, loose parts, risky play, block play/spatial, symbolic play, STEM/robotics, artistic creativity as axis, motor skills as axis, SEL, executive functions, environmental education, scientific inquiry as axis, literacy, orality, UDL, documentation, formative assessment, participation, planning, joint attention, adult–child interactions as generic axis, teacher education, music and numeracy—. Ferasinta and Dinata (2021) only as clinical peripheral contrast; Galbraith (2022) only as pedagogies-of-play peripheral contrast. Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Rukmini et al. (2022), Wijaya et al. (2023) and Martuty et al. (2025) are read through the playdough medium, not as a motor-skills axis already published. Wijaya et al. (2023): collage is not the axis. Sando et al. (2023) are read for objects-in-play (dough/manipulables), not as loose parts, sand play or water play.

The search was executed on 3 September 2026 (slot 21:02 America/Mexico_City) on DOI pages, Crossref, Springer, Elsevier, Taylor & Francis, MDPI, JAIR, OECD iLibrary, UNESDOC, NAEYC, Retos, Common Ground and editorial sites. Each source was verified. Empirical finding, framework and pedagogical inference were distinguished. No N, d, r, AUC or DOI were invented: when an artifact lacks a verified study with playdough molding accuracy / fine-motor dough / shape compliance scoring, mess/off-task dough spilling alerts, molding-score dashboard or AR “correct shape” prediction metrics in ages 3–6, it is discussed as a category ceiling supported by AI-in-ECE mappings (Chen, 2024; Su & Yang, 2022; Ljungcrantz, 2026) and by the pedagogies-of-play contrast (Galbraith, 2022). The nineteen verified corpus sources were used.

4. Case 1. Sensor/playdough molding accuracy score / fine-motor dough score / shape compliance score, CV/table camera with mess or off-task dough spilling alerts, GenAI of “figure plans” / playdough lesson plans / STEM dough activities, minutes/molding-score dashboard or AR that guides kneading or predicts correct shape do not constitute support for playdough play

Chen (2024), Su and Yang (2022) and Ljungcrantz (2026) saturate the portrait of the artifact ceiling when AI in ECE is presented as if it were support for playdough. Chen (2024) maps global AI affordances in early childhood education: scoping finding on emerging uses —tutoring, analytics, content generation—, not a finding that a molding-accuracy wearable cultivates open deformable exploration with resistance, elasticity or temperature. Su and Yang (2022) review the AI-in-ECE field: synthesis finding on trends, not on tolerated mess or co-presence that names dough properties. Ljungcrantz (2026) reviews AI–ECE interaction 2020–2024: state-of-the-art finding, not situated playdough. Pedagogical inference, marked as such: the gesture “the child had high molding accuracy = there was support for playdough” is a molding-precision analytics ceiling. Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Rukmini et al. (2022) and Sando et al. (2023) ask for real dough, conversation about properties and objects-in-play; a score useful for administration can coexist with absence of agency, tolerated mess and co-presence that names without closing.

Nikolopoulou (2025) and Miao and Holmes (2023) name the risk of the generator of “playdough figure plans” or “playdough lesson plans” / “STEM dough activities” from a prompt that closes uncertainty. Nikolopoulou (2025) balances promises and challenges of child-centered GenAI under teacher mediation: caution framework. Miao and Holmes (2023) require pedagogical validation and age thresholds for generative AI. Status: normative and review framework, not a trial of lesson plans by prompt versus a playdough episode with real dough and co-presence that sustains conversation (Yuniyartika & Sudaryanti, 2024; Darizal et al., 2023; Martuty et al., 2025). Inference: producing a “playdough figures” or “STEM dough” plan by prompt may be subordinated teacher preparation; support for playdough begins when there is real dough (homemade or commercial), child agency to knead, pinch, roll or flatten without an expected product, mess as a condition of the medium, and an adult who names properties without turning the episode into a recipe. Su and Zhong (2022) propose AI curriculum design in ECE as a future direction —AI literacy curriculum, not situated playdough—. Limit inference: an AI curriculum does not sign deformable exploration.

The computer-vision / table camera that labels “mess” or “dough outside the tray” or triggers “mess / off-task dough spilling” alerts, the “minutes with playdough” / “molding score” / “fine-motor dough minutes” dashboard and the AR layer that “guides” kneading or predicts the “correct shape” lack, in the verified corpus, trials with reported N, d, r or AUC for molding accuracy / shape compliance scoring, mess/dough spilling classification, molding-score dashboard or AR correct-shape prediction in preschool ages 3–6; figures are not invented. Chen (2024), Su and Yang (2022) and Ljungcrantz (2026) map analytics and generation as an AI-in-ECE trend, without equivalence to mediated playdough. The playdough studies in the corpus measure situated practice with limits, not a mess classifier; Sando et al. (2023; N = 928) measure human observations; Galbraith (2022) is a peripheral contrast only when the adult sustains the craft. Restrictive inference: Galbraith ≠ molding-accuracy sensor; GenAI plans ≠ Yuniyartika/Darizal/Rukmini/Martuty who open without closing; AR of correct shape ≠ open deformable exploration. UNESCO (2021) and U.S. Department of Education (2023) require human oversight. The five artifacts share one substitution grammar: the score speaks for exploration; the alert substitutes mess tolerance; GenAI closes; the dashboard substitutes observation; AR directs what craft leaves open. A sensor can score molding; craft articulates human playdough, not AUC. Inference: “high molding accuracy” or “lesson plan according to the model” does not sign support.

5. Case 2. What the kindergarten does when there is support for playdough play: deformable properties, Yuniyartika and Sudaryanti, Darizal et al., Rukmini et al., Wijaya et al., Martuty et al., Sando et al. —with Ferasinta and Dinata and Galbraith as peripheral contrast

Yuniyartika and Sudaryanti (2024) saturate the empirical craft floor: playdough media play and early childhood development, with lateral fine-motor and cognitive outcomes. Status: empirical finding. Marked transfer: motor/cognitive outcomes are read toward the deformable dough medium; this article is not converted into the motor-skills article already published. Pedagogical inference: a center may call it support for playdough when it protects real dough, agency and conversation about tactile properties —not when it scores molding accuracy—. Playdough is not a molding accuracy score: it is kneading, pinching, rolling, flattening, cutting with open tools, comparing homemade or commercial dough, and sustaining mess of residues on the table as a condition of the medium, while the adult names resistance, elasticity or temperature.

Darizal et al. (2023), Rukmini et al. (2022), Wijaya et al. (2023) and Martuty et al. (2025) anchor playdough play/games in kindergarten and ECE with marked context limits and transfer: they are read through the dough medium (collage is not the axis in Wijaya), not as a fine-motor dough score or shape-compliance tracking. Sando et al. (2023) —N = 928— anchor manipulable objects in deep-level learning: dough as object-in-play, not loose parts or sand/water. NAEYC (2022) and OECD (2021, 2023) anchor meaningful interactions and subordinated digitalization.

The clinical peripheral contrast is Ferasinta and Dinata (2021): play therapy using playdough toward fine motor skills in preschoolers. Status: CLINICAL play-therapy finding, not pedagogical classroom playdough. Marked transfer: read only to fix therapy ≠ kindergarten playdough. Inference: play therapy with playdough does not authorize the five artifacts as classroom playdough. The adult peripheral contrast is Galbraith (2022): pedagogies of play in initial teacher education. Status: framework/finding toward the adult. Inference: subordinated digital —an adult who deepens human pedagogies to sustain conversation at the dough table— can be coherent; it does not authorize the five artifacts as craft. Galbraith is not converted into a teacher-education article already published. Mediation —NAEYC (2022), OECD (2021); Yuniyartika & Sudaryanti (2024); Darizal et al. (2023); Rukmini et al. (2022); Martuty et al. (2025)— is co-presence that offers real dough, tolerates mess, names properties, observes agency without expected product and expands without a digital script that closes. Inference: pedagogical observation reads the episode with the deformable; the dashboard counts minutes. A dashboard does not build lived elasticity; a child and an adult who converse about dough resistance or temperature do.

6. Case 3. Playdough ≠ sand play, water play, loose parts, motor skills as axis, artistic creativity as axis or clinical therapy

The first frontier is sand play already published: playdough shares with sand play the logic of a material medium with real physical properties and tolerated mess, but here the axis is deformable dough (resistance, elasticity, temperature; kneading, pinching, rolling, flattening), not the sandbox granular. Inference: “we have a sandbox = there is playdough” does not sign; nor is a molding-accuracy sensor sand play or playdough. The second is water play already published: the axis is not the liquid of the water table. Inference: “we have a water table = there is playdough” does not sign. The third is loose parts: Sando et al. (2023) anchor manipulable objects; here the medium is continuous deformable dough, not Nicholson’s open collection of loose pieces. The fourth is curricular motor skills as axis: Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Rukmini et al. (2022), Wijaya et al. (2023) and Martuty et al. (2025) may report motor outcomes; they do not authorize reducing playdough to a motor curriculum or to “fine-motor dough score” tracking. The fifth is artistic creativity as axis: playdough may sustain expression, but here the axis is the open-play material with tactile properties, not generic plastic expression already published nor a GenAI of “figure plans” that closes aesthetic uncertainty. The sixth is clinical therapy: Ferasinta and Dinata (2021) fix play therapy ≠ classroom playdough. UNESCO (2021), Miao and Holmes (2023) and U.S. Department of Education (2023) require human oversight. Inference: coherent AI use at ages 3–6 remains on the adult side (Galbraith, 2022), contrasted with Yuniyartika and Sudaryanti (2024), Darizal et al. (2023) and Martuty et al. (2025). It does not enter as scorer, mess classifier, GenAI of plans, dashboard or AR predicting correct shape.

7. Inferential framework: four tests to claim support for playdough play, not an artifact

The framework that follows is pedagogical inference of this article, anchored in the cases and verified instruments. It is not a new international standard. It distinguishes four tests. If a kindergarten, preschool, CENDI or early childhood school fails them, it cannot declare that the five artifacts constitute support for playdough / clay play.

7.1. Test of situated practice with real dough —kneading, pinching, rolling, flattening; resistance, elasticity, temperature—, child agency and mess as a condition of the medium, not of the molding accuracy / shape compliance sensor or the AR layer that guides or predicts correct shape. Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Rukmini et al. (2022), Wijaya et al. (2023), Martuty et al. (2025) and Sando et al. (2023) define the craft as observable deformable exploration. Chen (2024), Su and Yang (2022) and Ljungcrantz (2026) map analytics and generation as AI affordances, not as playdough. Inference: evidence of support for playdough is verified in whether the child explored real dough with agency and without an expected product. If the center’s “evidence” is a playdough molding accuracy score or an AR correct-shape prediction, the center has done analytics or digital direction that closes, not support for playdough.

7.2. Test of adult co-presence that names properties and sustains conversation, not of GenAI “figure plans” / playdough lesson plans / STEM dough activities. Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Martuty et al. (2025), Galbraith (2022) and NAEYC (2022) situate conversation, playdough games and pedagogies of play / developmentally appropriate practice. Miao and Holmes (2023) require pedagogical validation of generative AI. Inference: producing plans or STEM dough activities by prompt that close uncertainty does not show that there was co-presence that names resistance, elasticity or temperature. A script may exist; it does not sign the playdough episode.

7.3. Test of human mediation —including the Ferasinta and Dinata and Galbraith peripheral contrasts—, not of the minutes/molding-score dashboard or the CV/camera of mess or off-task dough spilling alerts. OECD (2021, 2023) require meaningful interactions and subordinated digitalization. Galbraith (2022) anchors pedagogies of play toward the adult. Ferasinta and Dinata (2021) fix the therapy ≠ classroom frontier. Sando et al. (2023) anchor objects-in-play and deep-level learning observed by humans. Inference: “high minutes with playdough” or a “mess alert” may raise an administrative threshold without raising co-presence quality or child exploration. Pedagogical observation reads the episode with the deformable; the dashboard counts surveillance. Adult human knowledge/pedagogy is legitimate periphery; the wearable/CV that substitutes exploration or mess tolerance is not.

7.4. Test of category distinction and professional judgment, not of the product catalog. Playdough ≠ sand play, water play, loose parts, motor skills as axis, artistic creativity as axis or clinical therapy. Sando et al. (2023) prevent reducing dough objects to loose parts as axis. Ferasinta and Dinata (2021) prevent confusing pedagogical playdough with play therapy. Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Rukmini et al. (2022), Wijaya et al. (2023) and Martuty et al. (2025) prevent confusing lateral motor outcomes with curricular motor skills as axis or with a fine-motor dough score. UNESCO (2021), Miao and Holmes (2023), U.S. Department of Education (2023), NAEYC (2022) and OECD (2021, 2023) require human oversight, pedagogical validation and not replacing professional judgment. Inference: a center cannot treat the infant as a molding-accuracy vector nor as exclusive recipient of GenAI plans. Support for playdough play is not fulfilled by better scoring “precision” or surveilling “mess.” It is fulfilled by practicing real dough, child agency to explore without an expected product, adult co-presence that names properties and sustains conversation, and tolerance of mess.

The framework admits digital subordinated to adult pedagogies/preparation and validated human mediation (Galbraith, 2022; Chen, 2024; Su & Yang, 2022; Ljungcrantz, 2026). It rejects declaring support by the five artifacts (Miao & Holmes, 2023; Nikolopoulou, 2025; UNESCO, 2021). The four tests are read together.

8. Discussion

Three tensions organize the discussion. The first is between displaying the five artifacts and exercising support for playdough. Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Rukmini et al. (2022), Wijaya et al. (2023), Martuty et al. (2025), Sando et al. (N = 928), Ferasinta and Dinata and Galbraith (peripheral) sustain the craft or its frontier; Chen (2024), Su and Yang (2022) and Ljungcrantz (2026) map AI without equivalence to situated playdough. It is not a finding that the artifacts produce the craft.

The second is between automated assessment of molding accuracy / shape compliance or mess and pedagogy of the deformable. Chen (2024), Su and Yang (2022) and Ljungcrantz (2026) objectify analytics; they do not report verified scoring or mess-alert trials in preschool ages 3–6 —metrics are not invented—. Inference: declaring support by a molding score or a dough-outside-tray alert is inverted pedagogy.

The third is between GenAI plans / AR of correct shape and integral craft. Miao and Holmes (2023) and Nikolopoulou (2025) set limits; Yuniyartika and Sudaryanti (2024), Darizal et al. (2023) and Martuty et al. (2025) set playdough games and media play. Inference: selling prompt plans or AR as “playdough with AI” confuses product with deformable exploration. The empirical playdough cases confirm situated practice with limits without authorizing a score; UNESCO (2021), Miao and Holmes (2023) and U.S. Department of Education (2023) subordinate AI to professional judgment.

The four tests in section 7 read these tensions. The empirical contrast —Yuniyartika/Sudaryanti; Darizal; Rukmini; Wijaya (collage not axis); Martuty; N = 928; Ferasinta and Galbraith peripheral— defines the floor the artifacts do not reach alone. Inference: support erodes when they are treated as if they were the practice. Subordinated digital is legitimate toward the adult (Galbraith, 2022); inverting the sequence is not (NAEYC, 2022; OECD, 2021, 2023; Yuniyartika & Sudaryanti, 2024).

9. Limits

This review is narrative. It does not apply its own PRISMA nor estimate primary combined effects. Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Rukmini et al. (2022), Wijaya et al. (2023) and Martuty et al. (2025) provide playdough findings with marked context/transfer limits; absent N, d, r or AUC are not invented. Wijaya et al. (2023) include collage: it is not the axis. Sando et al. (2023; N = 928), Ferasinta and Dinata (2021; peripheral therapy) and Galbraith (2022; peripheral pedagogies) delimit frontiers. Chen (2024), Su and Yang (2022), Su and Zhong (2022), Ljungcrantz (2026) and Nikolopoulou (2025) map AI in ECE, not molding accuracy or mess alerts. No verified trials of the five artifacts in CENDI ages 3–6 were located; they are discussed as a category ceiling. NAEYC, UNESCO and OECD are framework sources. Section 7 inferences are category hypotheses, not implementation evidence.

10. Conclusions

A sensor or wearable that “scores molding accuracy” or a “playdough molding accuracy score” / “fine-motor dough score” / “shape compliance score” for the child, a computer-vision / table camera system that labels “mess” or “dough outside the tray” or triggers “mess / off-task dough spilling” alerts, a chatbot/GenAI that generates “playdough figure plans” or “playdough lesson plans” or “STEM dough activities” by prompt, a dashboard of “minutes with playdough” / “molding score” / “fine-motor dough minutes” for administrative surveillance, or an AR layer that “guides” kneading or predicts the “correct shape” do not constitute support for playdough / clay play in an early childhood education center. Chen (2024), Su and Yang (2022) and Ljungcrantz (2026) confirm AI affordances without equivalence to situated playdough. Nikolopoulou (2025) and Miao and Holmes (2023) set GenAI limits. Ferasinta and Dinata (2021) require reading play therapy as peripheral contrast —therapy ≠ classroom playdough—. Galbraith (2022) requires reading pedagogies of play as peripheral contrast —adult ≠ sensor, mess CV, GenAI, dashboard or AR—. Yuniyartika and Sudaryanti (2024), Darizal et al. (2023), Rukmini et al. (2022), Wijaya et al. (2023) and Martuty et al. (2025) set playdough games / media play. When there is support, there is situated practice: playdough media play (Yuniyartika & Sudaryanti, 2024); playdough in Yogyakarta kindergarten (Darizal et al., 2023); playdough game (Rukmini et al., 2022); playdough with collage not as axis (Wijaya et al., 2023); playdough games Group B (Martuty et al., 2025); objects-in-play N = 928 (Sando et al., 2023); DAP and interactions (NAEYC, 2022; OECD, 2021, 2023). Playdough is distinguished from sand play, water play, loose parts, motor skills as axis, artistic creativity as axis and clinical therapy. The guidance documents require human oversight (UNESCO, 2021; Miao & Holmes, 2023; U.S. Department of Education, 2023; Su & Zhong, 2022).

Where sources do not measure a kindergarten, this article does not affirm it. Where they measure AI mappings, GenAI, play therapy or pedagogies of play toward the adult, it does not translate them into support via score or mess alert. Accompanying three-to-six-year-olds in playdough play is to exercise real dough (kneading, pinching, rolling, flattening, without expected product), child agency, adult co-presence that names properties, and tolerance of mess as a condition of the medium. The rest is a playdough molding accuracy / fine-motor dough / shape compliance sensor, a mess classifier, a plan generator that closes uncertainty, a minutes dashboard and an AR layer that guides or predicts correct shape. It is not support for playdough play in early childhood education, and it must not be presented as what it is not.

Editorial Laboratory of NEXTECH.IA / Ingeniero Mitre.

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