@inproceedings{esteves_adaptive_2020,
	title = {An {Adaptive} {System} {Architecture} {Model} for the {Study} of {Logic} and {Programming} with {Learning} {Paths}},
	isbn = {978-989-758-423-7},
	url = {https://doi.org/10.5220/0009412406790690},
	doi = {10.5220/0009412406790690},
	abstract = {The number of dropouts and evasion rates in computing courses are among the highest in Brazilian universities. To reduce this rate, eLearning technologies are being used to compose solutions. Because of such reality, this work aims at showing an adaptive system architecture with learning paths that best fit the student’s profiles and interests. In order to take student’s profiles and interests into account, two theories will be used: constructivist and constructionist. The fundamentals of these theories were analysed to formulate a teaching structural model for the system. The literature was researched to find adaptive systems with theories similar to constructivism and constructionism. Then it was designed a collaborative agent system based on intelligent software agent techniques to help the student on its paths and content choices. In this system, the student’s difficulties, characteristics, and knowledge obtained from other users can be reused. An environment with a content hierar chy which allows more attractive learning path construction options may ease the learning, make the study more interesting and help reduce evasion rates in computing courses.},
	language = {Português},
	booktitle = {Proceedings of the 22nd {International} {Conference} on {Enterprise} {Information} {Systems}},
	publisher = {SCITEPRESS - Science and Technology Publications},
	author = {Esteves, Adson and FILHO, ALUIZIO and Raabe, André Luís Alice and DAZZI, RUDIMAR},
	year = {2020},
}

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