Experiencing failure in the classroom and across the university

ABSTRACT

In this article, 10 award-winning post-secondary instructors use narrative inquiry to explore failure individually by reflecting on their own definition and framework of failure, by giving examples of their experience with failure, and by elaborating how they deal with and learn from failure. The outcome of this collective exploration is an article that reflects the reality of life in academia where members of the academic community face failures, their own and those of others, on a daily basis.     

“Accepting Emotional Complexity”: A Socio-Constructivist Perspective on the Role of Emotions in the Mathematics Classroom

A socio-constructivist account of learning and emotions stresses the situatedness of every learning activity and points to the close interactions between cognitive, conative and affective factors in students’ learning and problem solving. Emotions are perceived as being constituted by the dynamic interplay of cognitive, physiological, and motivational processes in a specific context. Understanding the role of emotions in the mathematics classroom then implies understanding the nature of these situated processes and the way they relate to students’ problem-solving behaviour. We will present data from a multiple-case study of 16 students out of 4 different junior high classes that aimed to investigate students’ emotional processes when solving a mathematical problem in their classrooms. After identifying the different emotions and analyzing their relations to motivational and cognitive processes, the relation with students’ mathematics-related beliefs will be examined. We will specifically use Frank’s case to illustrate how the use of a thoughtful combination of a variety of different research instruments enabled us to gather insightful data on the role of emotions in mathematical problem solving.     

A cross-disciplinary approach to teaching data literacy and proportionality

The Thinking with Data project (TWD) expands on current notions of data literacy by (1) focusing on proportional reasoning as key to data literacy and (2) leveraging the non-mathematics disciplines to engage students in deep thinking about the context of data and the application of proportionality. A set of four 2-week, sequential modules for cross-disciplinary implementation in seventh-grade classrooms was designed and evaluated. Using a quasi-experimental approach, we found that student data literacy was increased through the focused integration of social studies, mathematics, science, and English language arts. In this article, we describe our theoretical approach to designing and implementing the modules, report on student learning gains in mathematics, and describe teacher reactions to the materials. In sum, our study provides evidence that the TWD approach has the potential to build data literacy while also allowing students to learn core discipline-based content standards.     

Child Care Quality and Cognitive Development: Trajectories Leading to Better Preacademic Skills

The associations between trajectories of child care quality from ages 2 to 4 years and children's cognitive performance at 4 years (n = 250) were tested. Distinct quality trajectories were identified: low and high ascending Teaching and Interactions trajectory; low and high Provision for Learning trajectory. Membership in the high ascending Teaching and Interactions trajectory was associated with better numeracy (effect size [ES] = .39, confidence interval [CI] = .21–.66), receptive vocabulary (ES = .41, CI = .14–.68), and school readiness (ES = .32, CI = .06–.58). The results suggest that a pattern of increasing quality of teacher–child interactions during the preschool years, particularly with regard to supporting the development of language, has a moderate impact on children's cognitive development.     

Achievement among first-year university students: an integrated and contextualised approach

This paper presents a prospective study aimed at identifying the predictors of academic achievement among first-year university students. It tries to develop an inclusive view of academic achievement by taking into account the possible differential impact of several predictors in two different faculties of the university. Some 317 university students from the two faculties (science and physical education), who were in their first year at university, participated in the study. During the academic year, these students completed a questionnaire. The outcome variable was their average academic mark at the end of the year. Multiple regression analyses were performed to identify the most powerful predictors of achievement. The results showed that past school failure, parental education and self-efficacy beliefs predicted achievement in both programs. Age, secondary-school specialisation, reasons for choosing the program, deep processing, time spent studying and intention to persist have also been highlighted as significant predictors of success, but only in one of the two faculties. Self-efficacy was the most powerful predictor of achievement in physical education courses, whereas intention to persist was the most powerful predictor in science. These results show the importance of adopting an integrated and contextualised approach to exploring the predictors of academic achievement at university.     

Focusing on the Complexity of Emotion Issues in Academic Learning: A Dynamical Component Systems Approach

Understanding the interrelations among students’ cognitive, emotional, motivational, and volitional processes is an emergening focus in educational psychology. A dynamical, component systems theory of emotions is presented as a promising framework to further unravel these complex interrelations. This framework considers emotions to be a process that is composed of cognitive, neurophysiological, motor expression, and motivational processes—as well as feelings—that mutually regulate each other over time and within a particular context. This comprehensive view of emotions provides a more complete understanding of the social and dynamical nature of emotions and the integration of emotions within learning processes. Using a dynamical, component systems view of emotional processes, interrelated with learning processes, involves a shift in research methodologies and instruments to adequately investigate the role(s) of emotions within learning contexts. But more importantly, it may provide a powerful framework that can clearly show teachers and parents the role(s) that emotions play in students’ acquisition of knowledge and skills.

Admission to selective schools,alphabetically

One's position in an alphabetically sorted list may be important in determining access to over-subscribed public services. Motivated by anecdotal evidence, we investigate the importance of the position in the alphabet of Czech students for their admission chances into over-subscribed schools. Empirical evidence based on the population of students graduating from secondary schools and applying to universities is consistent with the use of alphabet in admission procedures at both secondary and tertiary level, implying potential inefficiency in the matching of students with universities.     

In the Shadow of Schumpeter: W. Rupert Maclaurin and the Study of Technological Innovation

J. Schumpeter is a key figure, even a seminal one, on technological innovation. Most economists who study technological innovation refer to Schumpeter and his pioneering role in introducing innovation into economic studies. However, despite having brought forth the concept of innovation in economic theory, Schumpeter provided few if any analyses of the process of innovation itself. This paper suggests that the origin of systematic studies on technological innovation owes its existence to the economist W. Rupert Maclaurin from MIT. In the 1940s and 1950s, Maclaurin developed Schumpeter’s ideas, analyzing technological innovation as a process composed of several stages or steps, and proposed a theory of technological innovation, later called the linear model of innovation. The paper also argues that Maclaurin constructed one of the first taxonomies for measuring technological innovation.     

Influences of population size and density on birthplace effects

Contextual influences on talent development (e.g., birthplace effects) have become a topic of interest for sport scientists. Birthplace effects occur when being born in a certain city size leads to participation or performance advantages, typically for those born in smaller or mid-sized cities. The purpose of this study was to investigate birthplace effects in Portuguese volleyball players by analysing city size, as well as population density – an important but infrequently used variable. Participants included 4062 volleyball players (M_age = 33), 53.2% of whom were men. Using Portuguese national census data from 1981, we compared participants (within each sex) across five population categories. In addition, we used ANOVAs to study expertise and population density. Results indicated that men and women athletes born in districts of 200,000–399,999 were 2.4 times more likely to attain elite volleyball status, while all other districts decreased the odds of expert development. For men, being born in high-density areas resulted in less chance of achieving expertise, whereas there were no differences for women. The results suggest that athletes’ infrastructure and social structure play an important role in talent development, and that these structures are influenced by total population and population density, respectively.