Abstract
This paper deals with the field of mathematics education where the aim is to generate exercises with randomized data. The process of exercise generation involves, first, identification of common errors that may be performed when solving the exercise, then, modeling of these errors by appropriate functions and recognition and distinction of errors through algorithms. Thus, although randomized, the exercise parameters must be chosen in such a way that it would be possible to understand the error the student committed and with it to guarantee a proper feedback on his answer. We call this process smart assessment. In this paper we present two algorithms for exercise generation admitting smart assessment.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Belmonte, M.V., Guzman, E., Mandow, L., Millan, E., Perez de la Cruz, J.L.: Automatic Generation of Problems in Web-based Tutors. In: Virtual Environments for Teaching and Learning, pp. 237–281. World Scientific Publishing (2002)
Tomás, A.P., Leal, J.P.: A CPL-based tool for Computer aided generation and solving of Maths exercises. In: Dahl, V. (ed.) PADL 2003. LNCS, vol. 2562, pp. 223–240. Springer, Heidelberg (2002)
Sangwin, C.J., Grove, M.J.: STACK: Addressing the needs of the neglected learners. In: 1st WebALT Conference and Exhibition, pp. 81–95. Technical University of Eindhoven, WebALT Inc., University, Netherlands (2006)
Guerman, A., Santos, C., Costa, R., Raposo, A., Mendonça, A., Lopes, C.: Plataforma SEMENTE: Tecnologias de Informação para o Ensino na UBI. Engenharias 07 Inovação & Desenvolvimento Conference. Covilhã (2007)
Tomás, A.P., Leal, J.P., Domingues, M.A.: A Web Application for Mathematics Education. In: Leung, H., Li, F., Lau, R., Li, Q. (eds.) ICWL 2007. LNCS, vol. 4823, pp. 380–391. Springer, Heidelberg (2008)
Pereira, R.M.S., Brito, I., Machado, G.J., Malheiro, T., Vaz, E., Flores, M., Figueiredo, J., Pereira, P., Jesus, A.: New e-learning objects for the Mathematics courses from Engineering degrees: Design and Implementation of Question Banks in Maple T. International Journal of Education and Information Tecnologies 4, 7–14 (2010)
Millan, E., Descalço, L., Castillo, G., Oliveira, P., Diogo, S.: Using Bayesian Networks to improve knowledge assessment. Journal Computers and Education 60, 436–447 (2013)
Queirós, R., Leal, J.L.: A survey on e-Learning content standardization. CCIS 278, 433–438 (2013)
Almeida, J.J., Araújo, I., Brito, I., Carvalho, N., Machado, G.J., Pereira, R.M.S., Smirnov, G.: Math exercise generation and smart assessment. TICAMES (2013)
Almeida, J.J., Araújo, I., Brito, I., Carvalho, N., Machado, G.J., Pereira, R.M.S., Smirnov, G.: PASSAROLA: High-Order Exercise Generation System. CISTI 2013, Lisboa (2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Araújo, I., Brito, I., Machado, G.J., Pereira, R.M.S., João Almeida, J., Smirnov, G. (2015). New Algorithms for Smart Assessment of Math Exercises. In: Rocha, A., Correia, A., Costanzo, S., Reis, L. (eds) New Contributions in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 353. Springer, Cham. https://doi.org/10.1007/978-3-319-16486-1_121
Download citation
DOI: https://doi.org/10.1007/978-3-319-16486-1_121
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16485-4
Online ISBN: 978-3-319-16486-1
eBook Packages: Computer ScienceComputer Science (R0)