Word2Vec4Kids: Interactive Challenges to Introduce Middle School Students to Word Embeddings

Source publication / research team or educational organization described in paper

Not specified in extracted text

Researchers, educators, instructors, or facilitators as described in the source publication

• In-school (K-12)

Classroom, course, or resource-based AI education activity

Not specified in extracted text

The study had a total of seven AI centered applica- tion available to the over 120 participants. The study population consisted of middle-school students aged 11–14 from a Science, Technology, Engineering, and Mathe; such there were three MacOS workstations were available for student use. Of the 41 students who in- teracted with the W2V4K project, 38 consented to their data being used in the study. Participation required sig

NLP / text classification

• Use with minors requires attention to privacy, consent, data minimization, and adult supervision.

6-8

Mixed or not explicitly specified; infer from target learner group and intervention design.

Varies by intervention; not specified unless the paper explicitly describes prerequisites.

• Document the AI education intervention, course, tool, or resource described in the source publication.
• Extract the learner context, AI role, pedagogy, outcomes, and constraints for AAB registry comparison.
• As Artificial Intelligence (AI) continues to integrate into more aspects of society, equipping younger generations with foundational AI knowledge becomes increasingly critical.

• Support AAB comparison across AI literacy, AI education, teacher training, higher education, and workforce contexts.
• Capture evidence maturity, transferability, and limitations rather than treating the publication as product endorsement.

• Not an AAB endorsement of the tool, curriculum, provider, or result.
• Not a direct replication record unless the source paper reports implementation details sufficient for replication.

NLP / text classification

Language context discussed in source publication

• Learning object / concept model

• Primary interaction pattern inferred from publication: Instructional design / AI education.
• AI capability focus: NLP / text classification.

• Use age-appropriate framing and teacher/facilitator oversight for any classroom deployment.

• Review the publication’s reported context, learner group, AI tool or curriculum, implementation process, and outcome evidence.
• Map the case to AAB registry fields for comparison across educational levels and AI capability types.
• Use the source publication and PDF for any manual verification before public registry release.

• Human educators/researchers remain responsible for instructional design, supervision, interpretation, and ethical safeguards.
• AI systems or AI concepts provide the learning object, support tool, evaluator, simulator, or automation context depending on the paper.

• Game-based learning
• Registry extraction emphasizes explicit learning goals, observed outcomes, constraints, and safety limitations.

• Use with minors requires attention to privacy, consent, data minimization, and adult supervision.

• Case classified under: Published design / resource paper.
• Pedagogical pattern: Game-based learning.
• Any additional adaptations should be verified against the full paper before public-facing publication.

• Engagement evidence should be interpreted according to the source paper’s reported method and sample.
• This paper presents Word2Vec4Kids (W2V4K), an interac- tive application designed to familiarize middle school stu- dents with word embeddings, a key aspect of Natural Lan- guage Processing (NLP).

• This paper presents Word2Vec4Kids (W2V4K), an interac- tive application designed to familiarize middle school stu- dents with word embeddings, a key aspect of Natural Lan- guage Processing (NLP).

As Artificial Intelligence (AI) continues to integrate into more aspects of society, equipping younger generations with foundational AI knowledge becomes increasingly critical. This paper presents Word2Vec4Kids (W2V4K), an interac- tive application designed to familiarize middle school stu- dents with word embeddings, a key aspect of Natural Lan- guage Processing (NLP).

• Use age-appropriate framing and teacher/facilitator oversight for any classroom deployment.

• Survey
• Qualitative study

• Can be used as an AAB evidence record for cross-case comparison, standards drafting, and evidence-maturity mapping.
• Supports identification of recurring patterns in AI literacy, AI education implementation, teacher preparation, assessment, and responsible AI learning.

• AI literacy
• Conceptual understanding
• Instructional design / AI education
• NLP / text classification

• Completed

6-8

In-school (K-12)

NLP / text classification

Game-based learning

Low to Medium

Medium

Word2Vec4Kids: Interactive Challenges to Introduce Middle School Students to Word Embeddings

• Nathan Wiatrek
• Yash Verma
• Fred Martin

Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 39 No. 28, EAAI-25

2025

10.1609/aaai.v39i28.35197

https://ojs.aaai.org/index.php/AAAI/article/view/35197

https://ojs.aaai.org/index.php/AAAI/article/view/35197/37352

034_Word2Vec4Kids_ Interactive Challenges to Introduce Middle School Students to Word Embeddings.pdf

8

As Artificial Intelligence (AI) continues to integrate into more aspects of society, equipping younger generations with foundational AI knowledge becomes increasingly critical. This paper presents Word2Vec4Kids (W2V4K), an interac- tive application designed to familiarize middle school stu- dents with word embeddings, a key aspect of Natural Lan- guage Processing (NLP). W2V4K leverages the Word2Vec model, allowing students to explore word associations, sim- ilarity, and vector arithmetic through engaging game modes. The application was tested with 38 middle school students aged 11–14 at a Science Technology Engineering Math (STEM)-focused charter school. Data were collected on stu- dents’ interactions with the application, including screen recordings, audio, and survey responses. Results demon- strated that W2V4K effectively introduces NLP concepts to students. Qualitative observations revealed high levels of en- gagement with students expressing excitement and curios- ity about word relationships. As they progressed through the game modes, students showed increasing confidence in pre- dicting word associations, brainstorming relevant words, and connecting the concepts to real-world applications. Quanti- tative data from post-interaction surveys indicated positive learning outcomes with 44.5% of students achieving per- fect scores on concept-related items. Additionally, students demonstrated an ability to critically think about language rep- resentation. This study suggests that W2V4K provides an ef- fective and engaging method for introducing NLP concepts to middle school students, contributing to the broader goal of enhancing AI literacy among younger generations.

• In-school (K-12)

• Use with minors requires attention to privacy, consent, data minimization, and adult supervision.

Not specified in extracted text unless noted in duration field.

Requires educators/researchers/facilitators with sufficient AI literacy and pedagogy knowledge for the target learners.

Infrastructure depends on AI tool type, learner devices, data access, and institutional policy context.

High

• duration

This entry was automatically extracted from the PDF text and manifest metadata. Fields should be manually verified before public registry publication, especially group size, location, duration, and outcome claims.