a b s t r a c t 26 Transfer learning aims to provide a framework to utilize previously-acquired knowledge to solve new 27 but similar problems much more quickly and effectively. In contrast to classical machine learning 28 methods, transfer learning methods exploit the knowledge accumulated from data in auxiliary domains 29 to facilitate predictive modeling consisting of different data patterns in the current domain. To improve 30 the performance of existing transfer learning methods and handle the knowledge transfer process in 31 real-world systems, computational intelligence has recently been applied in transfer learning. This paper 32 systematically examines computational intelligence-based transfer learning techniques and clusters 33 related technique developments into four main categories: (a) neural network-based transfer learning; 34 (b) Bayes-based transfer learning; (c) fuzzy transfer learning, and (d) applications of computational 35 intelligence-based transfer learning. By providing state-of-the-art knowledge, this survey will directly 36 support researchers and practice-based professionals to understand the developments in computational 37 intelligence-based transfer learning research and applications.38

The computing education community has studied extensively the errors of novice programmers. In contrast, little attention has been given to student's mistake in writing SQL statements. This paper represents the first large scale quantitative analysis of the student's syntactic mistakes in writing different types of SQL queries. Over 160 thousand snapshots of SQL queries were collected from over 2000 students across eight years. We describe the most common types of syntactic errors that students make. We also describe our development of an automatic classifier with an overall accuracy of 0.78 for predicting student performance in writing SQL queries.

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This paper presents a quantitative analysis of data collected by an online testing system for SQL "select" queries. The data was collected from almost one thousand students, over eight years. We examine which types of queries our students found harder to write. The seven types of SQL queries studied are: simple queries on one table; grouping, both with and without "having"; natural joins; simple and correlated sub-queries; and self-joins. The order of queries in the preceding sentence reflects the order of student difficulty we see in our data.