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Vol.4 , No. 2, Publication Date: Jun. 13, 2017, Page: 16-23
 for programming, which can provide students with personalized hints of students’ solving process in programming exercises. Our goal in this paper is to review and classify analysis techniques that are requested to generate data-driven hints in ITSs for programming. The classification of Data-Driven Hint Generation is the main contribution of this paper. The paper also proposes several future research directions.&picture=http://www.aascit.org/aascit/decorators/img/journal/912.jpg)
| [1] | Hieu Bui, Faculty of Information Technology, Ho Chi Minh City University of Transport, Ho Chi Minh City, Vietnam. |
The ability to write code accurately and fluently is a core competency for every engineering student. Introductory programming is an essential part of the curriculum in any engineering discipline in universities. However, for many beginning students, it is very difficult to learn. In particular, these students often get stuck and frustrated when attempting to solve programming exercises. One way to assist beginning programmers to overcome difficulties in learning to program is to use intelligent tutoring systems (ITSs) for programming, which can provide students with personalized hints of students’ solving process in programming exercises. Our goal in this paper is to review and classify analysis techniques that are requested to generate data-driven hints in ITSs for programming. The classification of Data-Driven Hint Generation is the main contribution of this paper. The paper also proposes several future research directions.
Keywords
Intelligent Tutoring System, Intelligent Programming Tutor, Programming Tutor, Programming Tutoring System, Data-Driven Hint Generation, Programming Exercises
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