Pieter Spooren

On the Validity of Student Evaluation of Teaching The State of the Art

This article provides an extensive overview of the recent literature on student evaluation of teaching (SET) in higher education. The review is based on the SET meta-validation model, drawing upon research reports published in peer-reviewed journals since 2000. Through the lens of validity, we consider both the more traditional research themes in the field of SET (i.e., the dimensionality debate, the ‘bias’ question, and questionnaire design) and some recent trends in SET research, such as online SET and bias investigations into additional teacher personal characteristics. The review provides a clear idea of the state of the art with regard to research on SET, thus allowing researchers to formulate suggestions for future research. It is argued that SET remains a current yet delicate topic in higher education, as well as in education research. Many stakeholders are not convinced of the usefulness and validity of SET for both formative and summative purposes. Research on SET has thus far failed to provide clear answers to several critical questions concerning the validity of SET.

A revalidation of the SET37-questionnaire for student evaluations of teaching

In this study, the authors report on the validity and reliability of a paper‐and‐pencil instrument called SET37 used for Student Evaluation of Teaching (SET) in higher education. Using confirmatory factor analysis on 2525 questionnaires, a revalidation of the SET37 shows construct and discriminant validity of the 12 dimensions included in the instrument. The retest of the instrument reveals (again) the existence of a second‐order factor explaining a substantial amount of the variance in seven dimensions of the instrument. In sum, the results provide strong support for both the relevance of the questionnaire and the hypothesis that the SET37 has a multidimensional structure but is compatible with a general underlying factor called “Teacher professionalism”.

‘Content’ versus ‘style’: acquiescence in student evaluation of teaching?

Structural equation modelling is used to measure the existence of a response style (in particular, acquiescence) behind three balanced Likert scales measuring different concepts in a questionnaire for student evaluation of teaching in higher education. Exploration with one sample (n = 1125) and confirmation in a second sample (n = 710) from a different population (different students, different courses) shows the existence of a common factor behind these scales. However, the weak correlation with the variable ‘sum of agreements’ does not support the idea of acquiescence in student evaluation of teaching. Instead, the common factor could be interpreted as a halo factor influencing different scales in the questionnaire. The implications of this exploratory study for future research on acquiescence in student evaluations of teaching are discussed.

Factor Structure of the Affective Style Questionnaire in Flemish Adolescents

Emotion regulation plays an important role in both healthy and problematic adolescent psychological functioning. Emotion regulation tendencies can be assessed with the Affective Style Questionnaire (ASQ; Hofmann & Kashdan, 2010), but its validity in Dutch speaking adolescents has not been investigated so far. Two methods, namely traditional confirmatory factor analysis (CFA) and the recently developed exploratory structural equations modeling (ESEM), were compared to examine the dimensional structure of the ASQ in a Flemish adolescent sample (N = 1,601). Although, as expected, the ESEM-model fit the data better than the CFA-model, the fit indices indicated that both models did not have an acceptable fit. With a shortened version of the ASQ, model fit improved substantially, but only the ESEM solution provided a good fit. The ESEM results support the use of the adapted ASQ to effectively assess the affective styles of concealing, adjusting and tolerating in Dutch-speaking adolescents.

Learning from Simulations of Decision-Making

This volume deals with simulations as active learning tools to teach political science students. It presents perspectives of both political and educational scientists on simulations as instruments to teach about politics and more in particular about political decision-making. In this introduction to part 1, we first discuss the nature of politics, the discipline of political science, and the topic of political decision-making. Next, we touch upon how academic political science curricula deal with decision-making and how they can be complemented with and benefit from simulations. Finally, we introduce the different dimensions of simulations that are discussed in the chapters of part 1 – Design and Assessment of Simulations.

Simulations of Decision-Making in Political Science Education

This chapter provides a definition of simulations of decision-making in political science education as student-centred and active learning environments, introduces their design features and summarizes the challenges in current effect research. The chapter concludes with an overview of the parts (and chapters) included in this volume, highlighting their specific contribution to both simulation practice and future research in this field.

Simulations of Decision-Making in Political Science Education: Premises, Promises and Challenges

In this concluding chapter, we provide a concise review of all chapters in this volume and reflect on the ways in which simulations of decision-making in political science are given shape and are tested on their effects with respect to the participant’s learning. We also present some conclusive findings based on the different chapters as well as some perspectives for both future practice and future research in this field.

How Simulations of Decision-Making Affect Learning

In this chapter we shortly introduce current perspectives in learning environment research in higher education and propose a general educational research model enabling to situate the various possible pathways in which effects of student learning in simulation-based learning environments can be investigated. In a next step, we discuss what kind of learning outcomes is important to address when focussing on the effectivity of simulation-based learning environments and which research perspectives are important to address. In a third step, we discuss how the subsequent chapters in this section can be situated in this educational research model and how they are a further illustration of the different pathways currently taken in the field.

Motivations to become a master in social work : a typology of students

ABSTRACT In the field of social work education, many studies address students’ motivations to become social workers. Most of these studies focus on bachelor‘s students in social work and confirm that altruistic and expressive motivations underlie students’ decisions to enter the social work profession. However, few studies focus on students earning a Master in Social Work (MSW). The purpose of this paper is to explore why students want to earn a master’s degree in social work. An online questionnaire was developed, and the results of six focus group discussions were used. The sample includes 116 graduates from the past 8 years and current students from the MSW programme at the University of Antwerp. We use exploratory factor analysis and identify two types of motivation. In line with earlier studies, we find that the first type is an expressive motivation. These students want to learn more about poverty and social justice and are motivated to improve the life conditions of vulnerable target groups. The second type is an instrumental motivation. These students are oriented towards the development of their professional careers.