Surface and deep learning according to the Bigs model among a sample of students from the Faculty of Education at Tishreen University - منصور علي; دياب رامي (Latakia University Journal - Arts and Humanities Sciences Series, 2020)
The research aims mainly to identify the differences between the two methods of superficial and deep learning among a sample of students of the Faculty of Education at Tishreen University according to the variables: gender, academic year. The researcher used in the study the questionnaire of the modified-two-factor study processes (RSPQ-2F): prepared by Biggs & et al (2001) and the Arabization of Jumana Khouzam in (2014) The study sample consisted of (320) male and female students from the Faculty of Education, Tishreen University, in the first and fourth years. Among the most important findings of the research: - There was no statistically significant difference between male and female in the surface learning method. - There was no statistically significant difference between male and female in the deep learning method. - There is no statistically significant difference in the method of superficial learning according to the variable of the school year. - There is a difference between the sample members in the deep learning method according to the variable of the school year in favor of fourth year students. The research ended with a set of recommendations and proposals: - Conducting more studies dealing with the methods of superficial and deep learning and their relationship to variables such as academic achievement, patterns of thinking, personality patterns, etc., which helps in revealing the factors affecting these methods and their impact on students. - Enlightening students with the methods they use in the learning process, training them on how to deal with information effectively and encouraging them to follow a deep learning method. - Preparing seminars for teachers on students’ learning methods and how to reconcile them with teaching methods to help improve the teaching and learning process.