Educational data mining for improving learning outcomes in teaching accounting within higher education

• Published in: The international journal of information and learning technology Vol. 32; no. 5; pp. 272 - 285
• Main Authors: Chamizo-Gonzalez, Julian, Cano-Montero, Elisa Isabel, Urquia-Grande, Elena, Muñoz-Colomina, Clara Isabel
• Format: Journal Article
• Language: English
• Published: Emerald Group Publishing Limited 02.11.2015; Emerald Publishing Limited
• Subjects: Accounting; Assignments; Campus systems; College Faculty; Computer Simulation; Correlation; Data mining; Education; Educational Improvement; Foreign Countries; Learning; Learning Activities; Learning Analytics; Learning Management Systems; Links; Methodology; Multimedia Materials; Outcomes of Education; Student Participation; Students; Teachers; Teaching; Teaching Methods; Technology & learning; Undergraduate Students; Spain (Madrid); Educational data mining; Virtual learning environment; Learning outcomes; Accounting
• ISSN: 2056-4880; 2056-4899
• DOI: 10.1108/IJILT-08-2015-0020

Purpose – The purpose of this paper are twofold. First, to disclose whether accounting students who participate more in online activities proposed by the teacher achieve better learning outcomes. Second, to identify which virtual learning activities achieve improved outcomes. Design/methodology/approach – Data mining is a computer-based tool devoted to analyzing massive data sources, generating information and discovering deeper knowledge and links among variables. Findings – There were differences between universities and subjects in the association of level of activity and learning outcomes. These findings will help teachers adjust their teaching guide, schedule and explanations. Research limitations/implications – Further developments should include the level of online compromise of the lecturers, and the correspondence of the online activity with the designed activities in the teaching guide. In order to identify the value-added activities performed by the students to achieve better deep learning outcomes. Practical implications – Higher Education should provide students with cognitive and transversal skills for successful incorporation into the labor market. In this sense, teaching methodology combined with online tools facilitates the process of teaching and learning with the implementation of different multimedia resources. Originality/value – Recently, the impact of virtual platform usage on students’ learning outcomes has started to be analyzed using “data mining” techniques. Educational data mining is a new focus to disclose existing links among students, lecturers and its activity.