The teaching of sorting algorithms is an essential topic in undergraduate computing courses. Typically the courses are taught through traditional lectures and exercises involving the implementation of the algorithms. As an alternative, this article presents the design and evaluation of three educational games for teaching Quicksort and Heapsort. The games have been evaluated in a series of case studies, including 23 applications of the games in data structures courses at the Federal University of Santa Catarina with the participation of a total of 371 students. The results provide a first indication that such educational games can contribute positively to the learning outcome on teaching sorting algorithms, supporting the students to achieve learning on higher levels as well as to increase the students' motivation on this topic. The social interaction the games promote allows the students to cooperate or compete while playing, making learning more fun.
This paper presents results of a questionnaire focused on investigating students' confidence and behavioral intention in the area of programming, particularly that of structures, problem solving, and programming commands (Conditional - Loop). Responses from 116 1st year students regarding informatics were used. The results indicate that the engagement with programming logic yields a positive impact on students' confidence and acceptance. In addition, all the measured factors are related relatively strongly. Our findings demonstrate that students' prior direction (at Lyceum) has a significant impact on their Confidence for using Programming Commands (CPC) and Confidence for using Data Structures (CDS); however, prior direction does not have any impact on learners Problem Solving Confidence (PSC) and Behavioral Intention (BI) for programming. In the conclusion, several issues regarding the courses of programming are discussed.
Interaction and feedback are key factors supporting the learning process. Therefore many automatic assessment and feedback systems have been developed for computer science courses during the past decade. In this paper we present a new framework, TRAKLA2, for building interactive algorithm simulation exercises. Exercises constructed in TRAKLA2 are viewed as learning objects in which students manipulate conceptual visualizations of data structures in order to simulate the working of given algorithms. The framework supports randomized input values for the assignments, as well as automatic feedback and grading of students' simulation sequences. Moreover, it supports automatic generation of model solutions as algorithm animations and the logging of statistical data about the interaction process resulting as students solve exercises. The system has been used in two universities in Finland for several courses involving over 1000 students. Student response has been very positive.