A Distribution-Free Approach for Comparing Growth of Knowledge

The longitudinal testing of student achievement requires the solution of several new problem areas. In this article, several small groups of medical students at the University of Limburg Medical School in Maastricht, The Netherlands, are compared with respect to their performances. The results indicate, that, despite the possession of more knowledge at entrance, students with a low rate of growth of knowledge in the first year demonstrate a lower level of knowledge after the second academic year and continue to do so throughout the academic program when compared to students who show a higher rate of growth of knowledge in the first year. The analysis has been carried out using a distribution-free version of a longitudinal IRT-model suggested by Albers, Does, Imbos, and Janssen (1989). Furthermore, growth of knowledge has been described by means of a general regression model. Statistical inferences are possible using a randomization design extended to the situation where the observations are time-dependent proportions of correct answers.     

Self-explanation in the domain of statistics: an expertise reversal effect

This study investigated the effects of four instructional methods on cognitive load, propositional knowledge, and conceptual understanding of statistics, for low prior knowledge students and for high prior knowledge students. The instructional methods were (1) a reading-only control condition, (2) answering open-ended questions, (3) answering open-ended questions and formulating arguments, and (4) studying worked-out examples of the type of arguments students in the third group had to formulate themselves. The results indicate that high prior knowledge students develop more propositional knowledge of statistics than low prior knowledge students. With regard to conceptual understanding, the results indicate an expertise reversal effect: low prior knowledge students learn most from studying worked-out examples, whereas high prior knowledge students profit most from formulating arguments. Thus, novice students should be guided into the subject matter by means of worked-out examples. As soon as students have developed more knowledge of the subject matter, they should be provided with learning tasks that stimulate students to solve problems by formulating arguments.     

The Effect of Guidance in Problem-Based Learning of Statistics

Contrary to classical problem-based learning, in guided problem-based learning, the learning goals are predetermined by the instructor—on the basis of a detailed decomposition of the subject matter to be studied—to activate prior knowledge and to structure self-study and subsequent group discussion. This study investigated the effects of classical problem-based learning and guided problem-based learning, for different prior knowledge levels, on perceived value and usefulness of the learning activity and on conceptual understanding of statistics. Participants randomly assigned 110 students to 10 problem-based learning groups, and subsequently, the 10 groups were allocated randomly to classical problem-based learning or guided problem-based learning. The results indicate that guided problem-based learning tends to enhance conceptual understanding of statistics more thanbreak; classical problem-based learning once students have some prior knowledge of the subject. Furthermore, guided problem-based learning tends to increase students’ awareness of the value and usefulness of the learning activity.     

Prior knowledge moderates instructional effects on conceptual understanding of statistics

This study investigated the effects of different teaching and learning methods for statistics for 2 levels of prior knowledge on cognitive load, propositional knowledge, and conceptual understanding. Teaching methods were whether or not to provide students with propositional information, and learning strategies were self-explaining the learning material and explaining in pairs. The results indicate that prior knowledge facilitates propositional knowledge development and leads to differential effects of teaching and learning methods on conceptual understanding: Only low prior knowledge students profit from additional information in the learning task and/or explaining in pairs. An implication of these findings is that low prior knowledge students should be guided into the subject matter by means of working in pairs on learning tasks that comprise additional information. Once students have developed more knowledge of the subject matter, they should be stimulated to work individually on learning tasks that do not comprise additional information.     

The effect of distributed practice on students’ conceptual understanding of statistics

In this study the effect of the reduced distribution of study activities on students’ conceptual understanding of statistics is investigated in a quasi-experiment. Conceptual understanding depends on coherent and error free knowledge structures. Students need time to construct such knowledge structures. A curriculum reform at our university resulted in statistics courses which were considerably shortened in time, thereby limiting students’ possibility to distribute study activities. Independent samples of students from before and after the reform were compared. To gauge conceptual understanding of statistics, students answered open ended questions in which they were asked to explain and relate important statistical concepts. It was shown that the reduction of distributed practice had a negative effect on students’ understanding. The finding that condensed courses make it more difficult for students to reach proper understanding of the subject matter is of interest for anyone who is engaged in reforming curricula or designing courses.     

The effect of directive tutor guidance in problem-based learning of statistics on students’ perceptions and achievement

In this study directive tutor guidance in problem-based learning (PBL) of statistics is investigated. In a quasi experiment in an educational setting, directive guiding tutors were compared with tutors in a more traditional role. Results showed that the subjective perceptions of the students with regard to the course, the tutor, and the discussions in the tutorial meetings were more positive in the guided condition. The quality of the problems used in the meetings and general tutor functioning were evaluated as equal in both conditions. Achievement was marginally higher in the guided condition. It can be concluded that directive tutor guidance is an effective addition to PBL of statistics.     

The effectiveness of propositional manipulation as a lecturing method in the statistics knowledge domain

The current experiment examined the potential effects of the method of propositional manipulation (MPM) as a lecturing method on motivation to learn and conceptual understanding of statistics. MPM aims to help students develop conceptual understanding by guiding them into self-explanation at two different stages: First, at the stage of propositions (statements referring to single statistical concepts and ideas), and subsequently, at the stage of more complex problems that comprise a set of relevant propositions. A total of 71 bachelor students in psychology who were preparing for the re-sit of their inferential statistics exam participated in one of two possible lectures. Topic, content, lecturer, and duration of both lectures were the same, and in both lectures five true/false hypotheses were presented. Students in the first lecture (control group) discussed interactively the truth or falsity of each hypothesis. In the second lecture (MPM group), this interactive discussion was structured by presenting a number of short open-ended questions along with each hypothesis. Conceptual understanding was measured by means of a twelve items multiple choice test. Further, the intrinsic motivation inventory was administered to examine motivation to learn. The results indicate that MPM does not lead to enhanced motivation to learn but can facilitate conceptual understanding development among students.     

THE EVALUATION SYSTEM AT THE MEDICAL SCHOOL OF MAASTRICHT

The extensive scheme for both formative and summative assessment of medical students established at a new new medical school is described and discussed. The establishment of multi‐disciplinary project groups and the involvement of educationalists and psychometricians are unique features of the project. The wide range of testing procedures, including self‐assessment units, indicate the complexity of an evaluation program which attempts to cover ALL the competency domains relevant to medicine. The revelation of the incongruence of the program with the educational philosophy of the school shows the necessity for involvement of “consumers” in such programs.