Student Teacher Attitudes to Sex Role Stereotyping: some Australian data

The sex role attitudes of 461 teacher education students were measured on a 32‐item questionnaire. Chi‐square analyses produced significant effects for gender on 22 of the items, showing that the females were more egalitarian than the males. However, most of the students adopted an egalitarian stance on many, though not all, of the items. Responses to some items (women getting drunk and swearing, corporal punishment, boys doing heavy chores, and boys dressing up and playing with dolls) suggest that some traditional stereotypes may be particularly resistant to change. The data also suggest that students may adopt egalitarian attitudes out of self‐interest rather than as a matter of principle, and are more accepting of general principles of gender equity than of specific practices designed to achieve it. Finally, although there is some evidence of ambivalence among the students, particularly the males, it is more accurate to characterise these students as definite in their gender attitudes.     

A Conceptual Approach to Teaching Mathematics to Students With Intellectual Disability

Swedish compulsory school for students with intellectual disability (ID) has been criticized for focusing on care and not presenting the students with enough knowledge-related challenges. The purpose of this study is to investigate how a conceptually-based mathematics curriculum can be interpreted and constructed for students with ID. A total of 18 mathematics lessons in 6 classes for students with ID were filmed, and the teachers were interviewed in connection with the lessons. A qualitative content analysis approach was used to identify aspects of mathematical competency content and to analyze the teaching. Three major groups of teaching strategies are identified: pedagogical mathematics activities, focusing on students’ perceptions of mathematical content, and encouraging dialogue between students.     

Curtailing marking variation and enhancing feedback in large scale undergraduate chemistry courses through reducing academic judgement: a case study

Variation in marks awarded, alongside quality of feedback, is an issue whenever large-scale assessment is undertaken. In particular, variation between sessional teaching staff has been studied for decades resulting in many recorded efforts to overcome this issue. Attempts to curtail variation range from moderation meetings, extended training programmes, electronic tools, automated feedback or even audio/video feedback. Decreased marking variation was observed whenever automated marking was used, potentially due to less academic judgment being used by the markers. This article will focus on a case study of three interventions undertaken at Monash University that were designed to address concerns around the variability of marking and the feedback between sessional teaching staff employed in the chemistry teaching laboratories. The interventions included the use of detailed marking criteria, Excel marking spreadsheets and automated marked Moodle reports. Results indicated that more detailed marking criteria had no effect whilst automated processes caused a consistent decrease. This was attributed to a decrease in the academic judgment markers were expected to use. Only the Excel spreadsheet ensured the provision of consistent feedback to students. Sessional teaching staff commented that their marking loads were reduced and the new methods were easy to use.     

The role of student characteristics in studying micro teaching–learning environments

This study explored the role of student characteristics in studying micro teaching–learning environments. The overarching hypothesis is that teachers teach differently to micro environments in their classrooms. This study is the first of a series exploring the following four questions: (1) What student profiles are identified at the beginning of a school year with respect to cognitive and motivational-affective factors? (2) How do students with different profiles perceive conditions in their learning environment? (3) To what degree do classrooms differ in the composition of student profiles? (4) What are possible consequences for examining micro teaching–learning environments? The study investigated 82 randomly selected high school science classrooms. Student characteristics were assessed at the beginning of the school year. After a video taped teaching unit, students were asked to rate the degree to which they experienced learning conditions as supportive. Latent class analysis (LCA) showed five distinct student profiles that varied along cognitive and motivational-affective dimensions. Multilevel analyses showed effects of student profiles assessed at the beginning of the school year on the students’ perception of learning conditions in a teaching unit 4 months later. To illustrate consequences for examining micro teaching–learning environments, student profiles were linked to video examples. The examples point to the special value of LCA in studying micro teaching–learning environments: they make it possible to focus on the individual student and to investigate the interplay of student characteristics and the learning environment.     

Using camels to teach probability and expected value

There is much debate about the place of probability in an introductory statistics course. While students may or may not use probability distributions in their post‐collegiate lives, they will likely be faced with day‐to‐day decisions that require a probabilistic assessment of risk and reward. This paper describes an innovative way to teach students in an introductory statistics course how to reason about probability and expected value through the board game Camel Up. The in‐class activities described here can be scaled to fit the needs and abilities of the students in a wide range of introductory statistics courses at a variety of levels.     

A study of students’ reasoning about probabilistic causality: Implications for understanding complex systems and for instructional design

Understanding complex systems requires reasoning about causal relationships that behave or appear to behave probabilistically. Features such as distributed agency, large spatial scales, and time delays obscure co-variation relationships and complex interactions can result in non-deterministic relationships between causes and effects that are best understood statistically. Causal Bayesian Research (e.g. Gopnik and Schulz in Causal learning: psychology, philosophy, and computation, Oxford University Press, New York, 2007) suggests that summing across probabilistic instances is inherent to human causal induction, yet other research (e.g. Schulz and Sommerville in Child Development 77(2):427–442, 2006) suggests a human tendency to assume deterministic relationships. Classroom science learning often stresses the replicability of outcomes, putting this learning in tension with understanding probabilistic patterns in complex systems. This investigation examined students’ reasoning patterns on tasks with probabilistic causal features. Microgenetic studies were conducted in multiple sessions over a school year with students in kindergarten, second, fourth and sixth grades (n = 16) to assess their assumptions when dealing with tasks from four domains: social; games; machines; and biology. Later sessions attempted to scaffold students’ understanding using connection making and analogical reasoning. This paper reports on the overall patterns and trends in the data. Most students held a deterministic stance at the outset; however, at least one student at each grade level reasoned probabilistically from the start. All students except one eventually revealed at least one topic for which they held a primarily probabilistic stance. The results have implications for how students reason about complex systems and for how patterns of co-variation and evidence in science are discussed.