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.
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.
The role of mobile technology has significantly increased and been emphasized in English education. However, research investigating EFL teachers' attitudes and behaviors related to mobile technology has been limited in descriptive aspects of the technology, leading to misunderstandings about EFL teachers' needs. Furthermore, many prior studies have examined various aspects of electronic learning (e-learning) and technological developments of mobile learning (m-learning) in English education from the learners' perspective. Therefore, this study proposed a research model that empirically examines behaviors of EFL teacher's' m-learning acceptance by using Fred Davis's Technology Acceptance Model (TAM) as the research framework. As external variables, this research model includes instant connectivity, compatibility, interaction, content enrichment, and computer self-efficacy, influencing the perceived usefulness of TAM. Structural Equation Modeling (SEM) with the data of 189 EFL teachers was used to analyze causal relationships between external variables and TAM variables. The results provide evidence that supports the tested hypotheses. The implications of the findings suggest a new direction for future studies on m-learning.
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.