Computational thinking (CT) can be considered a 21st century core skill and, accordingly, it should be taught to students at an early age. Nevertheless, the implementation of CT in school curricula is still in an experimental stage, given that different performance metrics remain unclear, including the appropriate age for learning each skill, the significant and achievable computational concepts for each school year, teaching strategies, learning effectiveness, and strategies for assessing development. Based upon constructivist problem-solving learning strategies and supported by a three-dimensional framework, a game-based environment with both individual and collaborative playing modes has been developed as a learning and an assessment tool via learning analytics. Moreover, an exploratory case study has been carried out involving 176 primary school students. Results suggest that this environment is suitable as a learning and assessment tool for CT skills in primary school, providing enduring learning, particularly when it engages the collaborative playing mode. It seems to be better adapted to early primary school stage students, who showed greater improvements and who were able to assimilate more computational concepts than expected. Likewise, special needs or low percentile students benefit even more greatly from the learning tool and especially from the collaborative playing mode. The combination of different assessment methodologies—including CT pre- and posttests, data-driven analytics, direct observation, and questionnaires—provides assessment for each of the framework computational dimensions.

Learning to program at an early age has been shown to be a vehicle for the development of Computational Thinking. Game-based environments are often used to develop these skills, but they lack sufficient voluntariness to assess aspects related to intrinsic motivation, such as interests, skills, persistence in solving a problem and behavior in response to rewards. These aspects directly affect achievement and academic performance, so it is necessary to analyze possible age and gender differences in order to adjust Computational Thinking curricula. With this aim, we deployed a voluntary video game which addresses basic computational concepts, based on intrinsic motivation, and aimed at early ages. Data were collected and analyzed using game learning analytics for 15 months, during which 4124 users played more than 28187 games. The analysis shows significant age and gender differences in relation to interests, skills, achievement, and progression through attempts. It was observed that the concepts addressed were achievable between the ages of 3 and 6 years and full mastery was possible by the age of 4 years, regardless of gender, as children persist with the challenge, intrinsically motivated, until it is overcome. In terms of persistence, significantly different behaviors were observed in the face of the challenge, which can help us to adjust the different learning methodologies to each age group and gender, adapting the way we provide reinforcement and rewards, especially for boys in the more complex challenges and for girls from the age of 5 years onwards.

Bebras tasks are considered to develop Computational Thinking (CT) and are currently used for this purpose in many studies. However, the relationship between Bebras tasks and CT is recent and, given the scarcity of validated instruments for assessing CT that are not associated with a specific learning environment, the expected development of CT through Bebras tasks has not been sufficiently evaluated, especially in Primary School. For this reason, we designed the ABC-Thinking program for the development of CT in which a set of Bebras tasks were selected and categorised according to the CT skills they were related to, specific lesson plans were designed to integrate these tasks in a 12-week curriculum, and teachers were trained to apply the program. Using the competent Computational Thinking test (cCTt) in a pre-post-test experimental design, we looked to determine whether Primary School students developed specific CT skills after the program, and, therefore, whether Bebras could be considered suitable for the development of this competence. The results show a significant development in specific CT skills, interesting findings in the gender differences in this development, and between high and low performers. Finally, qualitative data indicate the suitability of the ABC-Thinking program with respect to teachers’ practice.

Few teachers include information and communication technology in the classroom, despite their potential for increasing attention and motivation for students. Educational authoring tools are intended to turn teachers into designers and deliverers of technology-enhanced educational content, and increasing the adoption of these tools is a key element for speeding up this transformation. This paper emphasizes the importance of learnability for preventing rejection or abandonment by of such an authoring tool, and how acceptance is deeply affected by the interaction paradigm and the creation metaphor used in the tool. We present an analysis comparing two design paradigms: the widespread menu-based and choice-guided interaction paradigm versus a consistent metaphor with direct manipulation. The latter was implemented in DEDOS-Editor, a novel authoring tool that allows the creation of diverse educational activities that can be performed on different devices, such as PCs, digital blackboards, tablets, and multitouch surfaces. An experimental study shows the tremendous impact that interface choices have on the tool's learning curve. The results provide the first mapping of the choice of a direct-manipulation interface and its effect on the learning curve's entry point, as well as a consistent interaction metaphor with smoother and fast-growing learning curves. This allows users to complete more tasks and gain more knowledge through experience, in contrast to menu-based interfaces. The initial use of the tool is thus made easier for users with no experience or information about the tool, and the advantages of experience and expertize in facing new challenges are facilitating. This work also highlights the appropriateness of learning curves as a tool for measuring learnability