Augmenting Gifted Education Through Artificial Intelligence: A Four-Dimensional Framework for AI Tutoring Integration

Abstract

This theoretical work presents a conceptual framework for integrating artificial intelligence (AI) tutoring within gifted education programming. Drawing upon established gifted education frameworks, student-centered learning practices, and recent advances in AI technology, the proposed framework leverages AI capabilities across four key dimensions: affect, content, process, and product. The framework addresses persistent challenges in gifted education, including the need for personalized instruction, advanced content delivery, and meaningful mentor relationships. By augmenting traditional gifted programming with AI tutoring, this approach enables more scalable differentiation while supporting student autonomy and engagement. The integration of AI across these dimensions represents a significant advancement in how educators can approach gifted instruction, moving beyond traditional constraints to create dynamic learning environments. Through systematic integration of AI tools across these dimensions, educators can provide more personalized, challenging, and engaging learning experiences that better align with gifted students’ accelerated developmental needs in modern educational environments.

Keywords

gifted education artificial intelligence tutoring student-centered learning educational technology theoretical

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References

Aziz

A. R. A.

Ab Razak

N. H.

Sawai

R. P.

Kasmani

M. F.

Amat

M. I.

Shafie

A. A. H.

(2021). Exploration of challenges among gifted and talented children. Malaysian Journal of Social Sciences and Humanities, 6(4), 242–251. https://doi.org/10.47405/mjssh.v6i4.760

Beckmann

Minnaert

(2018). Non-cognitive characteristics of gifted students with learning disabilities: An in-depth systematic review. Frontiers in Psychology, 9, 504. https://doi.org/10.3389/fpsyg.2018.00504

Berman

K. M.

Schultz

R. A.

Weber

C. L.

(2012). A lack of awareness and emphasis in preservice teacher training: Preconceived beliefs about the gifted and talented. Gifted Child Today, 35(1), 18–26. doi:https://doi.org/10.1177/1076217511428307

Center for Creative Learning (2010). The Levels of Service (LoS) approach to programming for talent development: An overview. https://www.creativelearning.com/∼clearning/images/freePDFs/LoS-Overview.pdf

Clement

Roy

Oudeyer

P.-Y.

Lopes

(2015). Multi-armed bandits for intelligent tutoring systems. Journal of Educational Data Mining, 7(2), 20–48. https://doi.org/10.5281/zenodo.3554667

Cornejo-Araya

C. A.

Gómez-Araya

C. A.

Muñoz-Huerta

Y. P.

Reyes-Vergara

C. P.

(2021). What do we know about giftedness and underachievement? A bibliometric analysis. International Journal of Research in Education and Science, 7(2), 400–411. https://doi.org/10.46328/ijres.1481

Cross

J. R.

Cross

T. L.

(2015). Clinical and mental health issues in counseling the gifted individual. Journal of Counseling & Development, 93(2), 163–172. https://doi.org/10.1002/j.1556-6676.2015.00192.x

Ecker

(2023). Universal design for learning as a framework for designing and implementing learner-centered education. IntechOpen, 10.5772/acrt.16.

Ecker

(2024). Making AI tutors your classroom teaching assistants. Literacy Today, 42(2), 56–57.

10.

Esparza

Smith

M. K.

(2023). Professional social connections are associated with student science identity in a research-based field biology course. Ecosphere, 14(9), e4662. https://doi.org/10.1002/ecs2.4662

11.

Farkas

Duffett

(2008). High-achieving students in the era of NCLB: Results from a national teacher survey (Part 2) [Report]. Thomas B. Fordham Institute. https://files.eric.ed.gov/fulltext/ED501703.pdf

12.

Feijo

Ouellette

(2023). What will the future of education look like in a world with generative AI? MIT Open Learning. https://medium.com/open-learning/what-will-the-future-of-education-look-like-in-a-world-with-generative-ai-6cef54177579

13.

Guilbault

K. M.

Eckert

Szymanski

(2024). Caregiver perceptions of the social and emotional characteristics of gifted children from early childhood through the primary school years. Roeper Review, 46(4), 265–281. https://doi.org/10.1080/02783193.2024.2392096

14.

Guilbault

K. M.

Kane

(2016). Asynchronous development. NAGC Parenting for High Potential TIP Sheet.

15.

Guilbault

K. M.

McCormick

K. M.

(2023). The underachievement of gifted learners in school. In Collins

K. H.

Roberson

J. J.

Piske

(Eds.), Underachievement in gifted education: Perspectives, practices, and possibilities (pp. 25–41). Routledge.

16.

Handa

M. C.

(2009). Learner-centred differentiation model: A new framework. Australasian Journal of Gifted Education, 18(2), 55–66. https://doi.org/10.3316/ielapa.985225022615818

17.

Holmes

Bialik

Fadel

(2019). Artificial intelligence in education: Promises and implications for teaching and learning. [Book excerpt]. Center for Curriculum Redesign. https://curriculumredesign.org/wp-content/uploads/AIED-Book-Excerpt-CCR.pdf

18.

Joynes

Rossignoli

Amonoo-Kuofi

E. F.

(2019). 21st century skills: Evidence of issues in definition, demand and delivery for development contexts [K4D Helpdesk report]. Institute of Development Studies. https://assets.publishing.service.gov.uk/media/5d71187ce5274a097c07b985/21st_century.pdf

19.

Kelly

(2025). First therapy chatbot trial yields mental health benefits. Dartmouth News. https://home.dartmouth.edu/news/2025/03/first-therapy-chatbot-trial-yields-mental-health-benefits

20.

Kettler

Taliaferro

(2022). Personalized learning in gifted education: Differentiated instruction that maximizes students’ potential. Prufrock Press.

21.

Krsmanović

Deek

F. P.

(2023, September). AI applications in education for working with gifted children: Future uses and psychosocial effects [Conference presentation]. Mensa Sixth International Scientific and Professional Conference, Working with the Gifted: Methods and Programs. https://www.researchgate.net/publication/374381304_AI_Applications_in_Education_for_Working_with_Gifted_Children_Future_Uses_and_Psychosocial_Effects

22.

Luckin

Holmes

Griffiths

Forcier

L. B.

(2016). Intelligence unleashed: An argument for AI in education. Pearson.

23.

Marantika

J. E. R.

(2021). Metacognitive ability and autonomous learning strategy in improving learning outcomes. Journal of Education and Learning (EduLearn), 15(1), 88–96. doi:https://doi.org/10.11591/edulearn.v15i1.17392

24.

Matthews

Lin

Zeidner

Roberts

R. D.

(2018). Emotional intelligence and giftedness. In Pfeiffer

S. I.

Shaunessy-Dedrick

Foley-Nicpon

(Eds.), APA Handbook of giftedness and talent (pp. 585–600). American Psychological Association.

25.

Mollick

(2024). Co-intelligence: Living and working with AI. Portfolio.

26.

Motschnig

Silber

Švábenský

(2021). How does a student-centered course on communication and professional skills impact students in the long run? arXiv. https://doi.org/10.48550/arXiv.2101.00883

27.

Oğurlu

Sevgi-Yalın

Yavuz-Birben

(2018). The relationship between social–emotional learning ability and perceived social support in gifted students. Gifted Education International, 34(1), 76–95. https://doi.org/10.1177/0261429416657221

28.

Pane

J. F.

Steiner

E. D.

Baird

M. D.

Hamilton

L. S.

(2015). Continued progress: Promising evidence on personalized learning. RAND Corporation.

29.

Papadopoulos

(2020). Psychological framework for gifted children’s cognitive and socio-emotional development: A review of the research literature and implications. Journal for the Education of Gifted Young Scientists, 8(1), 305–323. https://doi.org/10.17478/jegys.666308

30.

Papadopoulos

(2021). Parenting the exceptional: Social-emotional needs of gifted and talented children: What do we know? Children, 8(11), 953. https://doi.org/10.3390/children8110953

31.

Patrick

Kennedy

Powell

(2013). Mean what you say: Defining and integrating personalized, blended and competency education. International Association for K-12 Online Learning. https://files.eric.ed.gov/fulltext/ED561301.pdf

32.

Pittman

(2024). Learner-centered ecosystems as a path forward for public education: A convergence of perspectives and research . Aurora Institute, https://aurora-institute.org/cw_post/learner-centered-ecosystems-as-a-path-forward-for-public-education-a-convergence-of-perspectives-and-research/

33.

Reis

S. M.

McCoach

D. B.

(2000). The underachievement of gifted students: What do we know and where do we go? Gifted Child Quarterly, 44(3), 152–170. https://doi.org/10.1177/001698620004400302

34.

Ridgley

L. M.

DaVia Rubenstein

Callan

G. L.

(2020). Gifted underachievement within a self-regulated learning framework: Proposing a task-dependent model to guide early identification and intervention. Psychology in the Schools, 57(9), 1365–1384. https://doi.org/10.1002/pits.22408

35.

Rogers

E. M.

Singhal

Quinlan

M. M.

(2014). Diffusion of innovations. In Stacks

D. W.

Salwen

M. B.

(Eds.), An integrated approach to communication theory and research (2nd ed, pp. 432–448). Routledge.

36.

Schroeder

(2024). How will AI disrupt higher education in 2024? Inside Higher Ed, https://www.insidehighered.com/opinion/blogs/online-trending-now/2024/01/05/how-will-ai-disrupt-higher-education-2024

37.

Siegle

(2018). Understanding underachievement. In Pfeiffer

S. I.

(Ed.), Handbook of giftedness in children: Psychoeducational theory, research, and best practices ((2nd ed, pp. 285–297). Springer.

38.

Siegle

(2023). A role for ChatGPT and AI in gifted education. Gifted Child Today, 46(3), 134–141. https://doi.org/10.1177/10762175231168443

39.

Smith

S. R.

(2017). Responding to the unique social and emotional learning needs of gifted Australian students. In Frydenberg

Martin

A. J.

Collie

R. J.

(Eds.), Social and emotional learning in Australia and the Asia-Pacific: Perspectives, programs and approaches (pp. 147–166).

40.

Smith

S. R.

(2020). Introducing the social-emotional domain—a discussion paper for school leaders and teachers. NSW Department of Education. https://education.nsw.gov.au/content/dam/main-education/teaching-and-learning/high-potential-and-gifted-education/HPGE-Social-emotional-discussion-paper.pdf

41.

Tamim

F. J.

(2025). How gifted students harness AI: Opportunities, challenges, and future prospects. International Journal of Research in Education and Science, 11(1), 129–139. https://doi.org/10.46328/ijres.3590

42.

Tomlinson

C. A.

(2017). Differentiated instruction. In Cross

T. L.

Cross

J. R.

(Eds.), Fundamentals of gifted education: Considering multiple perspectives (2nd ed, pp. 311–324). Routledge.

43.

Tomlinson

C. A.

Imbeau

M. B.

(2011). Key elements of differentiated instruction. Association for Supervision and Curriculum Development (ASCD).

44.

Treffinger

D. J.

Selby

E. C.

(2009). Levels of Service (LoS): A contemporary approach to programming for talent development. Center for Creative Learning. http://www.creativelearning.com/∼clearning/images/freePDFs/ContempApproach.pdf

45.

U.S. Department of Education, Office of Educational Technology (2024). Empowering education leaders: A toolkit for safe, ethical, and equitable AI integration. https://tech.ed.gov/education-leaders-ai-toolkit/

46.

VanLehn

(2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369

47.

VanTassel-Baska

Hubbard

G. F.

Robbins

J. I.

(2020). Differentiation of instruction for gifted learners: Collated evaluative studies of teacher classroom practices. Roeper Review, 42(3), 153–164. https://doi.org/10.1080/02783193.2020.1765919

48.

VanTassel-Baska

Stambaugh

(2005). Challenges and possibilities for serving gifted learners in the regular classroom. Theory into Practice, 44(3), 211–217. https://eric.ed.gov/?id=EJ692318. doi:https://doi.org/10.1207/s15430421tip4403_5

49.

Vasani

(2024, May 24). ChatGPT, explained. The Verge. https://www.theverge.com/24161231/chatgpt-generative-ai-explained

50.

Vialle

Heaven

P. C.

Ciarrochi

(2007). On being gifted, but sad and misunderstood: Social, emotional, and academic outcomes of gifted students in the Wollongong Youth Study. Educational Research and Evaluation, 13(6), 569–586. https://doi.org/10.1080/13803610701786046

51.

Wang

(2023). The impact of student-centered learning on academic motivation and achievement: A comparative research between traditional instruction and student-centered approach. Journal of Education, Humanities and Social Sciences, 22, 346–353. https://doi.org/10.54097/ehss.v22i.12463

52.

Zakreski

M. J.

(2018). When emotional intensity and cognitive rigidity collide: What can counselors and teachers do? Gifted Child Today, 41(4), 208–216. http://doi.org/10.1177/1076217518786984

53.

Zawacki-Richter

Marín

V. I.

Bond

Gouverneur

(2019). Systematic review of research on artificial intelligence applications in higher education—where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0

54.

Zeidner

(2017). Tentative guidelines for the development of an ability-based emotional intelligence intervention program for gifted students. High Ability Studies, 28(1), 29–41. https://doi.org/10.1080/13598139.2017.1292895

55.

Zewe

(2023). Explained: Generative AI. MIT News, https://news.mit.edu/2023/explained-generative-ai-1109