Formative E-Assessment of Schema Acquisition in the Human Lexicon as a Tool in Adaptive Online Instruction

Guadalupe Elizabeth Morales Martínez, Yanko Norberto Mezquita Hoyos, Claudia Jaquelina Gonzalez, Ernesto Octavio López Ramírez, Jocelyn Pamela García Durán

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter presents comprehensive method of implementing e-assessment in adaptive e-instruction systems. Specifically, a neural net classifier capable of discerning whether a student has integrated new schema-related concepts from course content into her/his lexicon is used by an expert system with a data based containing natural mental representations from course content obtained from students and teachers for adapting e-instruction. Mental representation modeling is used to improve student modeling. Implications for adaptive hypermedia systems and hypertext-based instructions are discussed. Furthermore, it is argued that the current research constitutes a new cognitive science empirical direction to evaluate knowledge acquisition based on meaning information
Original languageEnglish
Title of host publicationFrom Natural to Artificial Intelligence
Subtitle of host publicationAlgorithms and Applications
EditorsRicardo López Ruíz
Place of PublicationLondon, United Kingdom
PublisherIntechOpen
Chapter4
Pages69-88
Number of pages19
Edition1
ISBN (Electronic)978-1-78984-703-1
ISBN (Print)978-1-78984-702-4
DOIs
Publication statusPublished - 12 Dec 2018

Publication series

NameFrom Natural to Artificial Intelligence - Algorithms and Applications

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  • Cite this

    Morales Martínez, G. E., Mezquita Hoyos, Y. N., Gonzalez, C. J., López Ramírez, E. O., & García Durán, J. P. (2018). Formative E-Assessment of Schema Acquisition in the Human Lexicon as a Tool in Adaptive Online Instruction. In R. López Ruíz (Ed.), From Natural to Artificial Intelligence: Algorithms and Applications (1 ed., pp. 69-88). (From Natural to Artificial Intelligence - Algorithms and Applications). IntechOpen. https://doi.org/10.5772/intechopen.81623