This paper describes a study of students' meaningful learning of the engineering design process during their participation in robotics activities. The population consisted of middle-school students (ages 13-15 years) who participated in the FIRST® LEGO® League competition. The methodology used was qualitative, including observations and interviews. The analysis was based on the Revised Bloom Taxonomy. Almost all the groups demonstrated meaningful learning, although some reached higher levels than others. Most of the groups demonstrated the understanding/applying level during each of the design process phases (searching and decision making, construction and testing, diagnosing and debugging), some demonstrated the analyzing/evaluating level, but only a few demonstrated the higher level of creating. Factors that seemed to play a role in the students' learning include: (a) the teaching or mentoring style; (b) the absence of a robotics textbook; (c) the extra-curricular competition-oriented nature of the activities; and (d) the unstable nature of the design of the robot.
In the last years, a growing trend in different educational contexts focused on Computational Thinking (CT) skills acquisition for both in-service teachers and students. But very low attention has been paid to pre-service teachers' education in regards to CT skills. To solve this issue, an empirical experimentation has been carried out with141 Italian pre-service teachers, that attended at a programming course, with the following aims: 1) provide them the main coding concepts by using Scratch 2.0; 2) offer practical advice on how to design educational applications (apps) to be applied into school context; 3) assess their apps by applying an already existing methodology, useful to give them feedback on their programming expertise and CT skills. Empirical findings showed that most of the participants achieved a medium-high level of CT skills, combining both design and programming skills in their school internship. Moreover, they reported a sense of greater self-esteem in teaching practice and a great emotional response from kids.
In computer science education at school, computational thinking has been an emerging topic over the last decade. Even though, computational thinking is interpreted and integrated in classrooms in different ways, an identification process about what computational thinking is about has been in progress among computer science school-teachers and computer science education researchers since Wing's initial paper on the characteristics of computational thinking. On the other hand, the constructionist learning theory by Papert, based on constructivism and Piaget, has a long tradition in computer science education for describing the students' learning process by hands-on activities. Our contribution, in this paper, is to present a new mapping tool which can be used to review classroom activities in terms of both computational thinking and constructionist learning. For the tool, we have reused existing definitions of computer science concepts and computational thinking concepts and combined these with our new constructionism matrix. The matrix's most notable feature is its scale of learners' autonomy. This scale represents the degree of choices learners have at each stage of development of their artefact. To develop the scale definitions, we trialed the mapping tool, coding twenty-one popular international computing activities for pupils aged 5 to 11 (K-5). From our trial, we have shown that we can use the mapping tool, with a moderate to high degree of reliability across coders, to analyse classroom activities with regard to computational thinking and constructionism, however, further validation is needed to establish its usefulness. Despite a small number of activities (n = 21) being analysed with our mapping tool, our preliminary results showed several interesting findings. Firstly, that learner autonomy was low for defining the problem and developing their own design. Secondly that the activity type (such as lesson plan rather than online activity) or artefact created (such as physical artefact rather than onscreen activity or unplugged activity), rather than the computational thinking or computer science concept being taught was related to learner autonomy. This provides some tentative evidence, which may seem obvious, that the learning context rather than the learning content is related to degree of constructionism of an activity and that computational thinking per se may not be related to constructionism. However, further work is needed on a larger number of activities to verify and validate this suggestion.
As computing has become an integral part of our world, demand for teaching computational thinking in K-12 has increased. One of its basic competences is programming, often taught by learning activities without a predefined solution using block-based visual programming languages. Automatic assessment tools can support teachers with their assessment and grading as well as guide students throughout their learning process. Although being already widely used in higher education, it remains unclear if such approaches exist for K-12 computing education. Thus, in order to obtain an overview, we performed a systematic mapping study. We identified 14 approaches, focusing on the analysis of the code created by the students inferring computational thinking competencies related to algorithms and programming. However, an evident lack of consensus on the assessment criteria and instructional feedback indicates the need for further research to support a wide application of computing education in K-12 schools.
This paper presents an approach to the initial programming learning using the four components instructional model and the Alice software. The quasi-experimental design was developed with two groups of students that attended two schools with very different socioeconomic status and school retention levels. The differences obtained in the mean of the programming knowledge test when co-variated with the Logical Development Scale score were positive in the two groups, with no statistical significance in the difference between both (p = 0.05). The differences obtained in the Logical Development Scale score (Échelle Collective de Devéloppement Lógique [ECDL]), before and after the experimental treatment, revealed positive differences in the experimental group with no statistical significance (p > 0.05), and in the control group with statistical significance (p < 0.05). These results suggest that the Alice software when combined with the 4C-ID instructional model has positive effects in programming learning and in logical reasoning.
Computerized Adaptive Testing (CAT) is now widely used. However, inserting new items into the question bank of a CAT requires a great effort that makes impractical the wide application of CAT in classroom teaching. One solution would be to use the tacit knowledge of the teachers or experts for a pre-classification and calibrate during the execution of tests with these items. Thus, this research consists of a comparative case study between a Stratified Adaptive Test (SAT), based on the tacit knowledge of a teacher, and a CAT based on Item Response Theory (IRT). The tests were applied in seven Computer Networks courses. The results indicate that levels of anxiety expressed in the use of the SAT were better than those using the CAT, in addition to being simpler to implement. In this way, it is recommended the implementation of a SAT, where the strata are initially based on the tacit knowledge of the teacher and later, as a result of an IRT calibration.
In this paper we report a study in which we have developed a teaching cycle based closely on Bloom's Learning for Mastery (LFM). The teaching cycle ameliorates some of the practical problems with LFM by making use of the STACK online assessment system to provide automated assessment and feedback to students. We report a clinical trial of this teaching cycle with groups of university level engineering students. Our results are modest, but positive: performance on the exercises predicted mastery according to the formative tests to a small extent. Students also report being supportive of the use of the new teaching cycle.
This longitudinal study investigates the impact of an extra-curricular programming workshop in student interest development in computer science. The workshop was targeted at 12-18-year old youngsters. A survey was sent to all previous participants with a known home address; 31.5% responded the survey (n = 197). This data was then combined with pre-workshop survey data, and analyzed with mixed methods. Positive development of interest was discovered for 57% of the respondents, of which nearly all attributed their interest increase to the workshop at least partly (92%). Qualitative inspection revealed that the workshop provided three anchors that facilitated students' reengagement with programming and development of interest: disciplinary content, a concrete artifact built by students themselves, and tools. Neutral development and interest regress were also discovered, though the impact of the workshop on these interest trajectories remains unclear.
During the last decade, coding has come to the foreground of educational trends as a strong mean for developing students' Computational Thinking (or CT). However, there is still limited research that looks at coding and Computational Thinking activities through the lens of constructionism. In this paper, we discuss how the knowledge we already have from other thinking paradigms and pedagogical theories, such as constructionism and mathematical thinking, can inform new integrated designs for the cultivation of Computational Thinking. In this context, we explore students' engagement with MaLT (Machine Lab Turtle-sphere), an online environment of our design that integrates Logo textual programming with the affordances of dynamic manipulation, 3D graphics and camera navigation. We also present a study on how the integration of the above affordances can promote constructionist learning and lead to the development of CT skills along with the generation of meanings about programming concepts.
The aim of this study was to reveal pre-service teachers' experiences in learning robotics design and programming. Data were collected from 15 pre-service teachers through semi-structured interviews and analyzed using the content analysis method. Three themes were identified in this study: Course process, professional development and teaching children. The pre-service teachers indicated that they found opportunities to learn by doing and experience, enjoyed doing robotics activities and felt in flow in this process. They also expressed that the robotics programming course positively influenced their attitudes towards programming and improved their programming skills. They emphasized the importance of keeping their intrinsic motivation high by maintaining their individual efforts to solve problems. Moreover, they made various suggestions for teaching robotics to children. Implications are discussed in terms of practices for educational robotics in teacher training, and further research directions.