By Nabila Bousbia, Idriss Belamri (auth.), Alejandro Peña-Ayala (eds.)
This publication is dedicated to the Educational information Mining enviornment. It highlights works that convey correct proposals, advancements, and achievements that form tendencies and encourage destiny examine. After a rigorous revision strategy 16 manuscripts have been approved and arranged into 4 components as follows:
· Profile: the 1st half embraces 3 chapters orientated to: 1) describe the character of academic info mining (EDM); 2) describe easy methods to pre-process uncooked info to facilitate information mining (DM); three) clarify how EDM helps govt regulations to augment education.
· Student modeling: the second one half comprises 5 chapters focused on: four) discover the standards having an influence at the student's educational good fortune; five) observe student's character and behaviors in a tutorial online game; 6) expect scholars functionality to regulate content material and techniques; 7) establish scholars who will so much reap the benefits of instruct aid; eight) hypothesize the scholar solution correctness in response to eye metrics and mouse click.
· Assessment: The 3rd half has 4 chapters relating to: nine) study the coherence of pupil examine proposals; 10) instantly generate assessments in keeping with competences; eleven) realize scholars actions and visualize those actions for being awarded to lecturers; 12) locate the main based attempt goods in scholars reaction data.
· Trends: The fourth half encompasses 4 chapters approximately tips on how to: thirteen) mine textual content for assessing scholars productions and aiding academics; 14) test pupil reviews through statistical and textual content mining strategies; 15) caricature a social community research (SNA) to find scholar habit profiles and depict versions approximately their collaboration; sixteen) overview the constitution of interactions among the scholars in social networks.
This quantity might be a resource of curiosity to researchers, practitioners, professors, and postgraduate scholars aimed toward updating their wisdom and locate pursuits for destiny paintings within the box of academic facts mining.
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Additional info for Educational Data Mining: Applications and Trends
D. ) Handbook of Educational Data Mining, Chapman and Hall/CRC Data Mining and Knowledge Discovery Series, pp. 417–426. CRC Press, Boca Raton (2011) 53. : Spectral clustering in educational data mining. , Stamper, J. ) Proceedings of 4th International Conference on Educational Data Mining, pp. 129–138. International Educational Data Mining Society, Eindhoven (2011) 54. : Collaborative filtering applied to educational data mining. J. Mach. Learn. Res. (2010) 55. : Classification via clustering for predicting final marks based on student participation in forums.
Mining Sakai to measure student performance: opportunities and challenges in academic. In: Proceedings of Enterprise Computing Community Conference (2011) 47. : Using data mining on student behavior and cognitive style data for improving e-learning systems: a case study. Int. J. Comput. Intell. Syst. 5(3), 597–610 (2012) 48. : Using educational data mining methods to study the impact of virtual classroom in e-learning. I. ) Proceedings of 3rd International Conference on Educational Data Mining, pp.
In: Proceedings of IJCA International Conference and Workshop on Emerging Trends in Technology, pp. 11–16 (2012) 1 Which Contribution Does EDM Provide to Computer-Based Learning 27 28. : Analyzing participation of students in online courses using social network analysis technique. , Stamper, J. ) Proceedings of 4th International Conference on Educational Data Mining, pp. 21–30. International Educational Data Mining Society, Eindhoven (2011) 29. : Process mining from educational data. d. ) Proceedings of Handbook of Educational Data Mining, Chapman and Hall/CRC Data Mining and Knowledge Discovery Series, pp.