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Software testing is the most used technique for quality assurance in industry. However, in computer science education software testing is still treated as a second-class citizen and students are unable to test their software well enough. One reason for this is that teaching the subject of software testing is difficult as it is a complex intellectual activity for which students need to allocate multiple cognitive resources at the same time. A myriad of primary and secondary studies have tried to solve this problem in education, however still with very limited results. Before we can design interventions to improve our pedagogical approaches, we need to gain more in-depth understanding and recognition of sensemaking as it is happening when students design test cases. An initial exploratory study identified four different sensemaking approaches used by students while creating test models. In this paper we present a follow-up study with 50 students from a large university in Spain. The used methodology was based on the previous study with the improvements that originated from its evaluation. We asked the participants to create a test model based on a description of a test problem using a specialized web-based tool for modeling test cases. We measured how well these models fit the test problem, the sensemaking process that students went through when creating the models, and the students' perception of the modeling task. The participants received no compensation for their efforts, and we scheduled the experiment during a regular class. Apart from the created models and their metadata, we also collected recordings of the students' computer screens made during the experiment and used a questionnaire to study their perspectives on the assignment. All the collected textual, graphical, and video data was analyzed using an iterative inductive analysis process to allow new information about the different sensemaking approaches to emerge. We gained better insights into the sensemaking processes of students while modeling test cases for a problem. The results enabled us to refine our previous findings, and we identified new sensemaking approaches. Based on these results, we can further investigate ways to influence the sensemaking process in education, the possible misconceptions that have a negative influence on it, and the desired mental model we want our students to have to design test cases. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) is being located at the focus of educational innovation, as a set of problem-solving skills that must be acquired by the new generations of students to thrive in a digital world full of objects driven by software. However, there is still no consensus on a CT definition or how to measure it. In response, we attempt to address both issues from a psychometric approach. On the one hand, a Computational Thinking Test (CTt) is administered on a sample of 1,251 Spanish students from 5th to 10th grade, so its descriptive statistics and reliability are reported in this paper. On the second hand, the criterion validity of the CTt is studied with respect to other standardized psychological tests: the Primary Mental Abilities (PMA) battery, and the RP30 problem-solving test. Thus, it is intended to provide a new instrument for CT measurement and additionally give evidence of the nature of CT through its associations with key related psychological constructs. Results show statistically significant correlations at least moderately intense between CT and: spatial ability ( r = 0.44), reasoning ability ( r = 0.44), and problem-solving ability ( r = 0.67). These results are consistent with recent theoretical proposals linking CT to some components of the Cattel-Horn-Carroll (CHC) model of intelligence, and corroborate the conceptualization of CT as a problem-solving ability. [ABSTRACT FROM AUTHOR]

Studying fundamental Computer Architecture and Organization topics requires a significant amount of practical work if students are to acquire a good grasp of the theoretical concepts presented in classroom lectures or textbooks. The use of simulators is commonly adapted in order to reach this objective. However, as most of the available educational simulators focus on specific topics, different laboratory assignments usually require the use of different simulators. This paper presents a graphical and interactive reduced instruction set computer (RISC) processor and memory simulator that allows active learning of some theoretical concepts covered in Computer Architecture and Organization courses. The simulator can be configured to present different processor views, from a simple serial one, without caches or pipelines, to a more realistic one with caches and superscalar execution. This approach allows a set of increasingly complex code-based laboratory assignments to be developed using a single simulator, covering topics ranging from assembly language programming to the analysis (If the different kind of cache misses, pipeline hazards or branch prediction hits and misses produced during a program execution. The simulator has been included in a an automatic assessment system that helps the students to complete the assignments and helps teachers to evaluate the correctness of the students solutions in different environments, such as high-enrollment courses or distance education. Since 1996, both the simulator and the automatic assessment system have been successfully used by more than 5000 students in Computer Architecture and Organization courses at the Technical University of Madrid (UPM), Spain. [ABSTRACT FROM AUTHOR]