The Use of an Intelligent Tutoring Program to Promote Independent Problem-Solving Skills of Students With Learning Disabilities or Difficulties

Abstract

Educational laws and current standards emphasize fostering conceptual understanding in problem-solving, as well as cultivating higher-order thinking and reasoning skills, with the ultimate goal of developing independent mathematical thinkers. The purpose of this study, conducted at a Midwest U.S. elementary school, was to explore the impact of the Please Go Bring Me-COnceptual Model-based Problem-Solving intelligent tutor on word problem-solving skills and multiplicative concept development of students with learning disabilities or difficulties in mathematics. The multiple-probe across-participants design was used to explore the functional relationship between the intervention program and students’ problem-solving skills and the development of conceptual knowledge. Concept development was measured by the levels of independence in solving problems provided by the intelligent tutor. Results showed that the tutoring system was effective in promoting students’ critical thinking and word problem-solving performance. It seems that features, such as the guided discovery strategy embedded in the tutoring system may have contributed to students’ development as an independent problem solver.

Keywords

word problem-solving intelligent tutor independent problem solver conceptual knowledge

Get full access to this article

View all access options for this article.

References

Boaler

(2016). Mathematical mindsets: Unleashing students’ potential through creative math, inspiring messages and innovative teaching. Jossey-Bass/Wiley.

Common Core State Standards Initiative. (2012). Common core state standards for mathematics practice. http://www.corestandards.org

Cook

S. C.

Collins

L. W.

Morin

L. L.

Riccomini

P. J.

(2020). Schema-based instruction for mathematical word problem solving: An evidence-based review for students with learning disabilities. Learning Disability Quarterly, 43(2), 75–87. https://doi.org/10.1177/0731948718823080

Cooper

J. O.

Heron

T. E.

Heward

W. L.

(2020). Applied behavior analysis. Pearson Education.

Council for Exceptional Children. (2021). Why now is the perfect time to solve the special education teacher shortage. Council for Exceptional Children. https://exceptionalchildren.org/blog/why-now-perfect-time-solve-special-education-teacher-shortage

Dell

A. G.

Newton

D. A.

Petroff

J. G.

(2016). Assistive technology in the classroom: Enhancing the school experiences of students with disabilities (3rd ed). Pearson. http://ci.nii.ac.jp/ncid/BB1181732X

Every Student Succeeds Act, 20 U.S.C. § 6301. (2015). https://www.congress.gov/bill/114th-congress/senate-bill/1177

Gast

D. L.

Spriggs

A. D.

(2010). Visual analysis of graphic data. In Gast

D. L.

(Ed.), Single subject research methodology in behavioral sciences (pp. 199-233). Routledge/Taylor & Francis Group.

Horner

R. D.

Baer

D. M.

(1978). Multi-probe technique: A variation of the multiple baseline. Journal of Applied Behavior Analysis, 11(1), 189–196. https://doi.org/10.1901/jaba.1978.11-189

10.

Hughes

E. M.

Witzel

B. S.

Myers

Lin

T. H.

(2023). Unpacking and understanding specific learning disabilities in mathematics. TEACHING Exceptional Children, 56(1), 26–32. https://doi.org/10.1177/00400599231175509

11.

Kennedy

C. H.

(2005). Single-case designs for educational research. Pearson/A & B.

12.

Kim

S. J.

Xin

Y. P.

(2022). A synthesis of computer-assisted mathematical word problem-solving instruction for students with learning disabilities or difficulties. Learning Disabilities: A Contemporary Journal, 20(1), 27–45. https://www.ldw-ldcj.org/images/Kim__Xin_2022.pdf

13.

Kim

S. J.

Xin

Y. P. A.

(2025). Meta-analysis of technology-based word-problem interventions for students with disabilities. Education Sciences, 14, 1372. https://doi.org/10.3390/educsci14121372

14.

Mayer

(2004). Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction. The American Psychologist, 59(1), 14–19. https://doi.org/10.1037/0003-066X.59.1.14

15.

Myers

J. A.

Witzel

B. S.

Powell

S. R.

Pigott

T. D.

Xin

Y. P.

Hughes

E. M.

(2022). A meta-analysis of mathematics word-problem solving interventions for elementary students who evidence mathematics difficulties. Review of Educational Research, 92(5), 695–742. https://doi.org/10.3102/0034654321107004

16.

National Association of State Boards of Education (NASBE). (2023). Addressing teacher shortages: State policy strategies for retaining educators. https://www.nasbe.org

17.

National Center for Education Statistics. (2022). NAEP report card: The 2022 NAEP mathematics assessment highlighted results at grades 4 and 8 for the nation, states, and districts. U.S. Department of Education.

18.

Otis

A. J.

Lennon

R. T.

(1995). Otis-Lennon school ability test (7th ed.). Pearson Education.

19.

Pearson Inc. (2004). Stanford achievement test series, tenth edition technical data report.

20.

Rose

D. H.

Meyer

(2002). Teaching every student in the digital age: Universal design for learning. Association for Supervision and Curriculum Development.

21.

Scruggs

T. E.

Mastropieri

M. A.

(1998). Summarizing single-subject research: Issues and applications. Behavior Modification, 22(3), 221–242. https://doi.org/10.1177/01454455980223001

22.

Scruggs

T. E.

Mastropieri

M. A.

Casto

(1987). The quantitative synthesis of single-subject research methodology and validation. Remedial and Special Education, 8(2), 24–33. https://doi.org/10.1177/074193258700800206

23.

Seo

Y. J.

Bryant

(2012). Multimedia CAI program for students with mathematics difficulties. Remedial and Special Education, 33(4), 217–225. https://doi.org/10.1177/0741932510383322

24.

Shin

Bryant

D. P.

(2017). Improving the fraction word problem solving of students with mathematics learning disabilities: Interactive computer application. Remedial and Special Education, 38(2), 76–86. https://doi.org/10.1177/0741932516669052

25.

Steffe

L. P.

(1990). Adaptive mathematics teaching. In Cooney

T. J.

Hirsch

C. R.

(Eds.), Teaching and learning mathematics in the 1990s (pp. 41–45). National Council of Teachers of Mathematics.

26.

Steffe

L. P.

D’Ambrosio

B. S.

(1995). Toward a working model of constructivist teaching: A reaction to Simon. Journal for Research in Mathematics Education, 26(2), 146–159. https://doi.org/10.2307/749206

27.

Sweller

(1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1016/0364-0213(88)90023-7

28.

Sweller

(2011). Cognitive load theory. In Mestre

J. P.

Ross

B. H.

(Eds.), The psychology of learning and motivation: Cognition in education (pp. 37–76). Elsevier Academic Press. https://doi.org/10.1016/B978-0-12-387691-1.00002-8

29.

Tzur

Johnson

H. L.

McClintock

Kenney

R. H.

Xin

Y. P.

Woordward

Hord

Jin

(2013). Distinguishing schemes and tasks in children’s development of multiplicative reasoning. PNA, 7(3), 85–101. https://doi.org/10.30827/pna.v7i3.6128

30.

Tzur

Xin

Y. P.

(2022). Multiplicative reasoning with whole numbers. In Xin

Y. P.

Tzur

Thouless

(Eds.), Enabling mathematics learning of struggling students: International perspectives (pp. 291–314). Springer.

31.

United States National Mathematics Advisory Panel & United States Department of Education. (2008). Foundations for success: the final report of the National Mathematics Advisory Panel. U.S. Department of Education.

32.

Vygotsky

L. S.

(1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press.

33.

Xin

Y. P.

(2012). Conceptual model-based problem solving: Teach students with learning difficulties to solve math problems. sense. https://link.springer.com/book/10.1007/978-94-6209-104-7

34.

Xin

Y. P.

Kim

S. J.

Lei

Liu

B. Y.

Wei

Kastberg

S. E.

Chen

Y. V.

(2023). The effect of model-based problem solving on the performance of students who are struggling in mathematics. The Journal of Special Education, 57(3), 181–192. https://doi.org/10.1177/00224669231157032

35.

Xin

Y. P.

Park

Tzur

(2020). The impact of a conceptual model-based mathematics computer tutor on multiplicative reasoning and problem-solving of students with learning disabilities. The Journal of Mathematical Behavior, 58, 100762. https://doi.org/10.1016/j.jmathb.2020.100762

36.

Xin

Y. P.

Tzur

(2008-2015). Nurturing multiplicative reasoning in students with learning disabilities in a computerized conceptual-modeling environment. National Science Foundation Funded Project.

37.

Xin

Y. P.

Tzur

Hord

Liu

Park

J. Y.

(2017). An intelligent tutor-assisted math problem-solving intervention program for students with learning difficulties. Learning Disability Quarterly, 40(1), 16. https://doi.org/10.1177/07319487166487400

38.

Yang

Xin

Y. P.

(2021). Teaching problem posing to students with learning disabilities. Learning Disability Quarterly, 45(4), 280–293. https://doi.org/10.1177/0731948721993117

39.

Zentall

S. S.

(2014). Students with mild exceptionalities: Characteristics and applications. Sage.