Search

This study describes the development and validation process of a computational thinking (CT) test for adults. The team designed a set of items and explored a subset of those through two qualitative pilots. Then, in order to provide validity evidence based on the test content, a team of 11 subject-matter experts coded the initial pool of items using two different systems of categories based on CT components and contents. Next, the items were piloted on a sample of 289 participants, 137 experts in CT, and 152 novices. After a series of confirmatory factor analyses, a unidimensional model that represents algorithmic thinking was adopted. Further analyzing the psychometric quality of the 27 items, 20 of them with excellent reliability indices were selected for the test. Thus, this study provides a tool to evaluate adults' CT: the Algorithmic Thinking Test for Adults (ATTA), which was developed according to psychometric standards. This article also reflects on the nature of CT as a construct.

Background: Research shows that active pedagogies could play an important role in achieving more equitable outcomes for diverse groups of students in Science, Technology, Engineering, and Mathematics (STEM). Although flipped classes are a popular active methodology, there is a lack of high-quality studies assessing their impact in ecologically valid settings and exploring how outcomes are related to gender and to prior education. Purpose: This paper presents two modified replications of an experimental study investigating the impact of the flipped class approach on students' achievement in a large, first-year class in an engineering bachelor's degree. Methodology: We added a new strand, progressively flipped over 3 years, to eight parallel strands of a high-stakes mandatory linear algebra course for engineers. The study followed a replicated-between-subjects design, with students in the flipped strand learning the same material as those in the other strands and taking the same final exam. Results: Our results demonstrate that the flipped format did not have any significant impact on students' achievement compared to traditional lecturing. However, both replications in the flipped condition show a reduced attainment gap for women and students with less prior knowledge in mathematics. Conclusion: While the flipped class seems to have weaker effects on learning than other active methodologies, the evidence in this study indicates that it may have an impact on reducing the attainment gap between different groups of students. It may therefore be particularly interesting to consider in efforts to achieve more equitable outcomes for women and where students have heterogeneous educational backgrounds.

Engineering accreditation bodies express a strong consensus that in addition to technical and scientific skills, engineering education also needs to promote the development of professional skills. In general, team-based projects are considered to be valuable approaches to develop such skills and have been extensively added to engineering curricula. Yet, it remains unclear which skills and to what extent students learn from these interventions. The challenge of assessing the development of those skills is an important factor in this gap. In this paper, we used a standardised self-reporting questionnaire to evaluate the development of students' self-efficacy beliefs through in-course and capstone projects. Results suggest that students only marginally develop these skills when they are not explicitly addressed as part of the project, showing ways to more effectively support student learning of professional skills. The questionnaire also proved to be an effective and scalable way to assess large classes.

Through their role in labs, exercise/recitation sessions and tutorials, graduate or doctoral teaching assistants play a significant role in the education of engineering students. Yet doctoral assistants frequently get little pedagogical training, what training is offered may be generic rather than specifically adapted to the subject epistemologies of science and engineering, and the training itself may not actually influence their teaching practice in any meaningful way. In this article, we describe an evidence-informed model of a pedagogical training workshop for doctoral assistants in engineering and science which is short, focused on the specific teaching methods associated with the disciplines in question (rather than general pedagogy), and based upon recent best evidence about teacher education. Feedback data from 191 participants over 3 years found that the vast majority of participants (98%) indicated that they would use the pedagogical skills in their own teaching practice.

Although it is frequently claimed that learning analytics can improve self-evaluation and self-regulated learning by students, most learning analytics tools appear to have been developed as a response to existing data rather than with a clear pedagogical model. As a result there is little evidence of impact on learning. Even fewer learning analytics tools seem to be informed by an understanding of the social context and social practices within which they would be used. As a result, there is very little evidence that learning analytics tools are actually impacting on practice. This paper draws on research in self-regulated learning and in the social practices of learning and assessment to clarify a series of design issues which should be considered by those seeking to develop learning analytics tools which are intended to improve student self-evaluation and self-regulation. It presents a case study of how these design issues influenced the development of a particular tool: the Learning Companion.