Trait emotional intelligence: Evidence from italian adolescents and adults

Emotional intelligence (EI) represents an attribute of contemporary attractiveness for the scientific psychology community. Of particular interest for the present thesis are the conundrum related to the representation of this construct conceptualized as a trait (i.e., trait EI), which are in turn reflected in the current lack of agreement upon its constituent elements, posing significant challenges to research and clinical progress. Trait EI is defined as an umbrella personality-alike construct reflecting emotion-related dispositions and self-perceptions. The Trait Emotional Intelligence Questionnaire (TEIQue) was chosen as main measure, given its strong theoretical and psychometrical basis, including superior predictive validity when compared to other trait EI measures. Studies 1 and 2 aimed at validating the Italian 153-items forms of the TEIQue devoted to adolescents and adults. Analyses were done to investigate the structure of the questionnaire, its internal consistencies and gender differences at the facets, factor, and global level of both versions. Despite some low reliabilities, results from Studies 1 and 2 confirm the four-factor structure of the TEIQue. Study 3 investigated the utility of trait EI in a sample of adolescents over internalizing conditions (i.e., symptoms of anxiety and depression) and academic performance (grades at math and Italian language/literacy). Beyond trait EI, concurrent effects of demographic variables, higher order personality dimensions and non-verbal cognitive ability were controlled for. Study 4a and Study 4b addressed analogue research questions, through a meta-analysis and new data in on adults. In the latter case, effects of demographics, emotion regulation strategies, and the Big Five were controlled. Overall, these studies showed the incremental utility of the TEIQue in different domains beyond relevant predictors. Analyses performed at the level of the four-TEIQue factors consistently indicated that its predictive effects were mainly due to the factor Well-Being. Findings are discussed with reference to potential implication for theory and practice.

How teachers think about the role of digital technologies in student assessment in mathematics

This study concerns teachers’ use of digital technologies in student assessment, and how the learning that is developed through the use of technology in mathematics can be evaluated. Nowadays math teachers use digital technologies in their teaching, but not in student assessment. The activities carried out with technology are seen as ‘extra-curricular’ (by both teachers and students), thus students do not learn what they can do in mathematics with digital technologies. I was interested in knowing the reasons teachers do not use digital technology to assess students’ competencies, and what they would need to be able to design innovative and appropriate tasks to assess students’ learning through digital technology. This dissertation is built on two main components: teachers and task design. I analyze teachers’ practices involving digital technologies with Ruthven’s Structuring Features of Classroom Practice, and what relation these practices have to the types of assessment they use. I study the kinds of assessment tasks teachers design with a DGE (Dynamic Geometry Environment), using Laborde’s categorization of DGE tasks. I consider the competencies teachers aim to assess with these tasks, and how their goals relate to the learning outcomes of the curriculum. This study also develops new directions in finding how to design suitable tasks for student mathematical assessment in a DGE, and it is driven by the desire to know what kinds of questions teachers might be more interested in using. I investigate the kinds of technology-based assessment tasks teachers value, and the type of feedback they give to students. Finally, I point out that the curriculum should include a range of mathematical and technological competencies that involve the use of digital technologies in mathematics, and I evaluate the possibility to take advantage of technology feedback to allow students to continue learning while they are taking a test.