Van vakgericht naar competentiegericht statistiekonderwijs: Een interventiestudie in een opleiding psychologie

Abstract This thesis describes how statistics education has been redesigned and implemented in the curriculum of the school of psychology of the Open Universiteit Nederland. In stead of autonomous and separate traditional statistics service courses and courses in research methods, both kinds of courses have been integrated into a coherent whole, including psychological theory, to realize a better fit with the educational target goal: the autonomous study of science by carrying out (psychological) research. Chapter 1 describes the arguments for this thesis. The literature refers to three possible causes for the problems that university students have in learning, remembering and using statistics. The first explanation looks at causes which can be ascribed to the students themselves: a deficient preparation in mathematics, a negative attitude, anxiety, low motivation and low self-esteem. The second type of explanation goes back to the contents of the subject of statistics. This subject is abstract and complex, and is taught in a compressed way mainly in the initial phase of the study, at a time when students are not aware of the meaning of research. The third explanation is found in the position of statistics within the curriculum. In this thesis a solution for these problems has been provided by redesigning statistics education into a competence-based learning environment. The underlying idea for redesigning is to create a long-term programme for students in which a series of whole-psychological-research-tasks is carried out in a cumulative way. The expectation is that students in such a learning environment naturally become familiar with selecting and applying appropriate statistics techniques in a variety of psychological research contexts. Additionally the research assignments intend to support a better understanding of the value and importance of statistics in psychological research, to improve motivation for carrying out research and to establish more positive attitudes towards statistics. Based on these expectations, concrete research questions have been formulated. For the (reconstruction of the) design process the Intervention Mapping approach has been used. The purpose of Intervention Mapping is to provide program planners with a framework for effective decision making at each step in intervention planning, implementation, and evaluation. Following the needs assessment chapter 2 describes the first three steps in Intervention Mapping which provide insight in what needs to be changed to solve the problems. The first step consists of a detailed description of the desired behaviours (performance objectives). The second step is to identify important and variable determinants that precede and influence the desired behaviours. Since the positioning of statistics in the psychology curriculum is considered to be the cause of the problem in statistics education, determinants are investigated in the (external) learning environment. The discipline’s position determines to a large extent how teachers can shape their education. The determinants not only define students’ learning outcomes, but also students’ learning strategies which in turn depend on how meaningful, valuable, useful, and secure students think education is (motivation, attitude). As a consequence, changing statistics education’s position in the psychology curriculum, as mentioned in chapter 1, most probably will lead to the desired changes in motivations and attitudes and to a structural solution of recognized problems in statistics education. Finally, in chapter 2 determinants are tuned with the performance objectives. The resulting change objectives are pictured in a matrix. By doing so the goal of the intervention has been made concrete. Chapter 3 focuses on the educational guidelines which will shape the change objectives. Guidelines which may scaffold and support the learning processes which are needed for the abstract and complex statistics content and which are applicable in carrying out psychological research have been found in “Cognitive Load Theory” (Van Merriënboer & Sweller, 2005), ‘Meaningful Learning' (Ausubel, 1960, 1968), the ‘Cognitive Apprenticeship Model’ (Collins, Brown, & Newman, 1989) and the ‘Theory of the Research Environment’ (Gelso, 2006).The most important guidelines are: the activation of prior knowledge, the use of advance organizers, the provision of opportunities to deliberately practise and to apply statistics in a long-term programme of learning and application, the prevention of cognitive overload, and the design of a variety of authentic psychological research tasks. Chapter 4 explains, based on the findings from chapter 2 and 3, how the learning and instructional principles and guidelines have been applied in the redesign of the learning environment. The design adequately fits the ideas of the 4C/ID-model (Van Merriënboer 1997), an instructional model that emphasizes the acquisition of complex skills. The redesign of the curriculum concerns two statistics service courses statistics, a SPSS-course, and three research methods courses. The bachelor thesis has been considered as the final stage of the research competency. In six consecutive research practicals (just as much as the number of integrated courses) the students become familiar with the reallocated statistics contents, research methods and psychology. The design of the integrated research practicals has been tested in two pilots. The formative evaluation of the redesign confirms its usefulness for statistics education for future psychologists. The integration of statistics, research methods, and psychology is appreciated positively, seems to help students overcoming their statistics anxiety, the studyload appears feasible and the electronic learning environment appears to trigger active engagement, exchanges of messages and critical discussions about findings between students. It has been decided to implement the statistics education design into the psychology curriculum using the label ‘research competency’. The pilots did not offer the opportunity to investigate whether students achieved better learning outcomes than in the conventional approach of statistics education. Chapter 5 describes a cross-sectional investigation that was conducted among students who have been taught statistics education in the subject-oriented or traditional way and students who have carried out the first research practical, in which students meet for the first time statistics techniques like correlation, regression and variance-analysis. It is supposed that students in the redesigned competence-based learning environment gain a more positive learning attitude towards statistics, become motivated to conduct psychological research, will use more appropriate learning strategies, will gain more insight in statistics and better established statistics skills than it is the case in the traditional, subject-oriented learning environment. The research results confirm the assumptions: the competence-based learning environment distinguishes itself in a favourable sense in comparison with the traditional learning environment with regard to all these factors, although the effect-sizes are not large. Notable are is the mechanisms of attitude and motivation. It seems that in the subject-oriented approach to statistics education the (negative) attitude towards statistics prevails and that the motivation is hardly triggered, while in the competence-based approach the (negative) attitude has been neutralized and that students use a motivated and deep approach to study statistics. Chapter 6 deals with results of a longitudinal study that was carried out among a group of students from the competence-based statistics education and a group of students from the subject-oriented statistics education. The pre-measurement took place three years earlier among students in one of the pilots and students who had participated in the same period in a research methods course, meaning that this group of students already participated in one or more statistics service courses. Three years later, both groups of students have been studied for the second time using the questionnaire which also has been used in the cross-sectional research. Once again it became clear that the competence-based approach is favourably different from the traditional learning environment. Apparently the learning environment even induced significant interactions over time and again effect sizes were significant, though not impressive. Chapter 7 reflects on the findings and results from the previous chapters and their implications for statistics education not only for psychology students of the Open Universiteit Nederland but also for statistics education in a more general sense. It may be inferred that by integrating statistics and research methods into authentic psychological and professional learning tasks statistics has obtained both a more (psychologically) hidden (integrated) and a more prominent (omnipresent) position within the curriculum. The school of Psychology of the Open Universiteit Nederland has taken the first step in shaping the research competency. Integration of statistics, research methods, and psychology is a challenging step. Integration opens the perspective for shared goals, close cooperation and coordination between teachers of different disciplines and for a better understanding of each other's profession.