Paul Sander

Measuring academic behavioural confidence: the ABC scale revisited

The Academic Behavioural Confidence (ABC) scale has been shown to be valid and can be useful to teachers in understanding their students, enabling the design of more effective teaching sessions with large cohorts. However, some of the between‐group differences have been smaller than expected, leading to the hypothesis that the ABC scale many not be unidimensional and that inherent subscales may be behaving in different ways, reducing the size of anticipated ABC effects. This study aimed to analyse the factor structure of the ABC scale. Pre‐existing data sets were combined into a large composite data set (n = 865) of undergraduate student respondents to the ABC scale. Exploratory factor analyses using SPSS, and confirmatory factor analysis in AMOS, were carried out. A reduced, 17‐item ABC scale can be considered as having four factors, grades, verbalising, studying and attendance. From the data sets, the discriminative power of the factor structure has been confirmed, with the results providing further criterion validity of the ABC scale.

Working with student expectations of tutor support in distance education: testing an expectations‐led quality assurance model

Action research studies in the United Kingdom with Open University students have shown that students come to distance education courses with variable expectations of the levels of service and support they will receive from their tutors. It has been further suggested that a specific expectations‐led quality assurance process that enables the sharing of these expectations before a course starts could be of mutual benefit to the student and the tutor, as well as generally improving the overall quality of tutor support provided by the distance learning organisation. This process, it is argued, would be appreciated by the students, have beneficial effects on student satisfaction with tutor support, reducing student drop‐out and increasing course completion rates. Could such a process that asks tutors to collect student expectations before a course begins be instituted effectively into a distance learning organisation and how would students and tutors respond to it? This paper reports on a large‐scale project carried out by Oscail (the Irish National Distance Education Centre) aimed at developing and testing how students and tutors valued being involved in just such an Open and Distance Learning expectations‐led quality assurance process. In the study reported here, all 96 tutors on an Oscail B.A. distance learning programme were asked two weeks before their course began to circulate the student expectations questionnaire to the 950 students on their tutorial lists. Tutors were asked to collect the questionnaires, reflect on the expectations of the students and consider how their tutorial practice and student support might change as a result of the exercise. Tutor and student views on the effectiveness of the exercise were also gathered through questionnaires and focus group meetings. The findings suggested that the majority of students and tutors involved in the study did see the value of the process and that it did help tutors (especially newly appointed ones) consider and respond to the type of support students hoped to receive. The practice of issuing student expectation questionnaires has now been embedded in Oscail introductory courses.

Medical students are from Mars - business and psychology students are from Venus - University teachers are from Pluto?

This study explores further the reasons given by the first year medical students in comparison with first year business and first year psychology students for their selection of lectures, student role play, and student presentations as their least preferred teaching method. The reasons were originally given in a questionnaire exploring student expectations of university teaching completed by 195 medical, 128 business and 72 psychology students in their first week at university (Sander et al, 2000). The analysis reported here suggests that whilst students irrespective of course gave similar reasons for not liking lectures, there were subtle differences between medical students and business and psychology students in the reasons they gave for not liking student role play and student presentations. These differences suggest that many first year medical students can be suspicious of the value of student centred learning methods. Teachers hoping to use these methods should acknowledge student suspicion and work to help students see the value of these techniques to encourage their full participation.

Gender, Psychology Students and Higher Education:

Our interest in gender differences in orientation to academic study was prompted by an accumulation of anecdotal data that male and female students seem to behave differently in relation to their academic studies. In this paper, we will introduce some provoking pilot survey data from our Level 1 students (N = 126), set against a background literature which together suggest that Level 1 male undergraduate students in a psychology degree tend to have a different orientation to their studies from that of their female colleagues, a difference that is also perceived by their peers. From this, the implications for teaching psychology will be considered.

The role of personal self-regulation and regulatory teaching to predict motivational-affective variables, achievement, and satisfaction: a structural model.

The present investigation examines how personal self-regulation (presage variable) and regulatory teaching (process variable of teaching) relate to learning approaches, strategies for coping with stress, and self-regulated learning (process variables of learning) and, finally, how they relate to performance and satisfaction with the learning process (product variables). The objective was to clarify the associative and predictive relations between these variables, as contextualized in two different models that use the presage-process-product paradigm (the Biggs and DEDEPRO models). A total of 1101 university students participated in the study. The design was cross-sectional and retrospective with attributional (or selection) variables, using correlations and structural analysis. The results provide consistent and significant empirical evidence for the relationships hypothesized, incorporating variables that are part of and influence the teaching–learning process in Higher Education. Findings confirm the importance of interactive relationships within the teaching–learning process, where personal self-regulation is assumed to take place in connection with regulatory teaching. Variables that are involved in the relationships validated here reinforce the idea that both personal factors and teaching and learning factors should be taken into consideration when dealing with a formal teaching–learning context at university.

Personal Self-regulation, Self-regulated Learning and Coping Strategies, in University Context with Stress

Personal self-regulation is an important variable in education and research, but self-regulated learning is the construct seen most often in the educational context. Existing studies do not seek to establish relationships between personal self-regulation and other educational variables. We define conceptual characteristics and relationships of personal self-regulation (personal presage variable), self-regulated learning (meta-cognitive, process variable) and coping strategies (meta-motivational, meta-affective process variable), establishing the importance of these variables in future meta-cognition research. These relationships have been established conceptually and empirically within the 3P and DEDEPRO Models, and are confirmed in recent research: namely, the importance of personal self-regulation in determining the degree of cognitive self-regulation during the process of university learning with stress; the relationship between personal self-regulation and the type and quantity of coping strategies, and the relationship between self-regulated learning and coping. We conclude by discussing our experience with an online self-help system designed for university students.

Using Structural Equation Modelling to Understand Predictors of Undergraduate Students’ Academic Performance

This chapter argues that there are many, just many many variables which contribute to academic performance as measured in degree outcome, and, as such, simple bivariate analysis is inappropriate. We use structural equation modelling, and explore the contribution of academic behavioural confidence, to make the point that it does contribute to academic performance, but to a lesser extent than self-efficacy theory argues. We suggest that this is because degree outcome is made up of many efficacy variables, which we argue are better captured overall in academic behavioural confidence.