Abstract
We present a unified learner modeling approach in a childhood vocabulary tutoring platform that enables learning continuum across multiple learning experiences. By decoupling experiences from learner modeling, multiple learning experiences can be developed independently making learning approaches scalable in an inherently diverse setting: each child, his/her family, environment, geography, cultural differences can all make each learner really unique. By understanding the information-theoretic equivalence of different assessment types, and mapping different play and learning activities to one or more of these types, we can enable a rapid convergence of the learner model to better represent a young learner’s knowledge. More interestingly, when normalized, different assessment types converge at different levels of the normalized score.
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Notes
- 1.
A choice is wrong if it is the correct answer and is not selected, and vice versa.
- 2.
For the simulations, \(\alpha =0.8\) and \(l_0=0.001\).
References
Biemiller, A.: Vocabulary: what words should we teach. Better Evid. Based Educ. Lang. Arts 3, 10–11 (2011)
Biemiller, A.: Which words are worth teaching? Perspect. Lang. Lit. 41(3), 9 (2015)
Biemiller, A.: Words Worth Teaching: Closing the Vocabulary Gap. McGraw-Hill SRA, Columbus (2010)
Brusilovskiy, P.L.: The construction and application of student models in intelligent tutoring systems. J. Comput. Syst. Sci. Int. 32(1), 70–89 (1994)
Desmarais, M.C., Baker, R.S.J.: A review of recent advances in learner and skill modeling in intelligent learning environments. User Model. User-Adap. Inter. 22(1), 9–38 (2012)
Farkas, G., Beron, K.: The detailed age trajectory of oral vocabulary knowledge: differences by class and race. Soc. Sci. Res. 33(3), 464–497 (2004)
Hart, B., Risley, T.R.: The early catastrophe: the 30 million word gap by age 3. Am. Educ. 27(1), 4–9 (2003)
Beck, I.L., McKeown, M.G., Kucan, L.: Bringing Words to Life: Robust Vocabulary Instruction. Guilford Press, New York (2013)
Neuman, S.B., Wright, T.S.: All About Words: Increasing Vocabulary in the Common Core Classroom, Prek-2. Teachers College Press, New York (2013)
Prentzas, J.: Artificial intelligence methods in early childhood education. Artif. Intell. Evol. Comput. Metaheuristics 427, 169–199 (2013)
Shannon, C.E.: A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423 (1948)
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Vempaty, A., Abuelsaad, T., Allain, A., Kokku, R. (2018). Supporting Multiple Learning Experiences on a Childhood Vocabulary Tutoring Platform. In: Nkambou, R., Azevedo, R., Vassileva, J. (eds) Intelligent Tutoring Systems. ITS 2018. Lecture Notes in Computer Science(), vol 10858. Springer, Cham. https://doi.org/10.1007/978-3-319-91464-0_45
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