The teaching and learning of programming has proven to be a challenge for students of computer courses, since it presents challenges and requires complex skills for the good development of students. The traditional teaching model is not able to motivate students and arouse their interest in the topic. The tool proposed herein, the REA-LP, aims to facilitate the study and retention of content related to the discipline of programming logic at the technical level by presenting its content through various types of media, in addition to allowing students to actively participate in the construction of their knowledge, favoring engagement and motivation. From the results of an empirical study with 39 students, it can be concluded that the tool was very well accepted, being effective in facilitating and assisting participants in their learning, motivation, and interest in classes, mainly due to the way in which the content is presented by REA-LP.
Learning programming logic remains an obstacle for students from different academic fields. Considered one of the essential disciplines in the field of Science and Technology, it is vital to investigate the new tools or techniques used in the teaching and learning of Programming Language. This work presents a systematic literature review (SLR) on approaches using Mobile Learning methodology and the process of learning programming in introductory courses, including mobile applications and their evaluation and validation. We consulted three digital libraries, considering articles published from 2011 to 2022 related to Mobile Learning and Programming Learning. As a result, we found twelve mobile tools for learning or teaching programming logic. Most are free and used in universities. In addition, these tools positively affect the learning process, engagement, motivation, and retention, providing a better understanding, and improving content transmission.
Teaching algorithmic thinking enables students to use their knowledge in various contexts to reuse existing solutions to algorithmic problems. The aim of this study is to examine how students recognize which algorithmic concepts can be used in a new situation. We developed a card sorting task and investigated the ways in which secondary school students arranged algorithmic problems (Bebras tasks) into groups using algorithm as a criterion. Furthermore, we examined the students’ explanations for their groupings. The results of this qualitative study indicate that students may recognize underlying algorithmic concepts directly or by identifying similarities with a previously solved problem; however, the direct recognition was more successful. Our findings also include the factors that play a role in students’ recognition of algorithmic concepts, such as the degree of similarity to problems discussed during lessons. Our study highlights the significance of teaching students how to recognize the structure of algorithmic problems.
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.
The Lithuanian Informatics Olympiads (LitIO) is a problem solving programming contest for students in secondary education. The work of the student to be evaluated is an algorithm designed by the student and implemented as a working program. The current evaluation process involves both automated (for correctness and performance of programs with the given input data) and manual (for programming style, written motivation of an algorithm) grading. However, it is based on tradition and has not been scientifically discussed and motivated. To create an improved and motivated evaluation model, we put together a questionnaire and asked a group of foreign and Lithuanian experts having experience in various informatics contests to respond. We identified two basic directions in the suggested evaluation models and made a choice based on the goals of LitIO. While designing the model in the paper, we reflected on the suggestions and opinions of the experts as much as possible, even if they were not included into the proposed model. The paper presents the final outcome of this work, the proposed evaluation model for the Lithuanian Informatics Olympiads.
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.