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In nursing research many concepts are measured by questionnaires. Respondents are asked to respond to a set of related statements or questions. In unidimensional scaling these statements or questions are indicants of the same concept. Scaling means to assign numbers to respondents, according to their position on the continuum underlying the concept. It is very common to use the summative Likert scaling procedure. The sumscore of the responses to the items is the estimator of the position of the patient on the continuum. The rationale behind this procedure is classical test theory. The main assumption in this theory is that all items are parallel instruments. The Rasch model offers an alternative scaling procedure. With Rasch both respondents and items are scaled on the same continuum. Whereas in Likert scaling all items have the same weight in the summating procedure, in the Rasch model items are differentiated from each other by 'difficulty.' The model holds that the probability of a positive response to an item is dependent on the difference between the difficulty of the item and the value of the person on the latent trait. The rationale behind this procedure is item response theory. In this paper both scaling procedures and their rationales are discussed. [ABSTRACT FROM AUTHOR]

Background: Although preparation for educational activities is considered beneficial for student learning, many students do not perform preparatory assignments. This phenomenon has received little attention in the literature although it might provide medical educators with the opportunity to enhance student learning. Therefore, we explored why students prepare or not prepare., Methods: An explorative mixed methods study was performed. In a qualitative study, 24 short group interviews with medical undergraduate students (n=209) were conducted on why they prepared for skills training sessions. In a subsequent quantitative study the resulting themes were used to construct a questionnaire. The questionnaire was presented to all undergraduate medical students at Maastricht University and 847 students completed it. Scales were constructed by a combination of exploratory factor analysis, reliability analysis, and content analysis. Between-class differences in the scale scores were investigated using ANOVA., Results: The qualitative study showed that students' opinions on preparation are influenced by both personal factors, categorized as 'personal learning style', 'attitudes and beliefs', and 'planning and organization', as well as external factors, including 'preparatory advice', 'pressure, consequence, and checking of preparation', 'teacher-related motivations', and 'contents and schedule of the training sessions'. The quantitative study showed that 'the objective structured clinical examination' and 'facilitation of both understanding and memorizing the learning material', were the two most motivating items. The two most demotivating aspects were 'other students saying that preparation was not useful' and 'indistinct preparatory advices'. Factor analyses yielded three scales: 'urge to learn', 'expected difficulties', and 'lack of motivation'. Between group differences were found between the three classes on the first two scales., Conclusions: Students make an active and complex choice whether to prepare or not, based on multiple factors. Practical implications for educational practice are discussed.

Background: In this study, the effect of guidance on students' performance was investigated. This effect was hypothesized to be manifested through a reduction of cognitive load and enhancement of self-explanations., Aim: The goal of this study was to investigate the effect of guiding questions on students' understanding of statistics., Sample and Method: In an experimental setting, two randomly selected groups of students (N= 49) answered achievement and transfer questions on statistics as a measure of performance. Students in the intervention condition were given guiding questions to direct their way of reasoning before they answered the achievement questions. The students in the control condition were asked to write down their way of thinking before they answered the same achievement questions. In this way, both groups were stimulated to self-explain, but only the reasoning processes of the students in the intervention condition were guided., Results and Conclusion: It was found that students in the intervention condition performed significantly better on achievement and transfer questions and that this effect of guidance was mediated by self-explanations. Attitude towards statistics was positively related to performance., (©2011 The British Psychological Society.)

Background: Education is aimed at students reaching conceptual understanding of the subject matter, because this leads to better performance and application of knowledge. Conceptual understanding depends on coherent and error-free knowledge structures. The construction of such knowledge structures can only be accomplished through active learning and when new knowledge can be integrated into prior knowledge., Aims: The intervention in this study was directed at both the activation of students as well as the integration of knowledge., Sample: Undergraduate university students from an introductory statistics course, in an authentic problem-based learning (PBL) environment, were randomly assigned to conditions and measurement time points., Method: In the PBL tutorial meetings, half of the tutors guided the discussions of the students in a traditional way. The other half guided the discussions more actively by asking directive and activating questions. To gauge conceptual understanding, the students answered open-ended questions asking them to explain and relate important statistical concepts., Results and Conclusions: Results of the quantitative analysis show that providing directive tutor guidance improved understanding. Qualitative data of students' misconceptions seem to support this finding. Long-term retention of the subject matter seemed to be inadequate., (©2010 The British Psychological Society.)

The objective of the study was to develop and validate a 21-item nutrition knowledge test to measure people's knowledge of the fat content of food-products. After pretesting and provisional development, the test was administered twice to study test-retest reliability. Furthermore, various sub-populations with expected differences in nutrition knowledge completed the test in order to study the construct validity of the questionnaire. The subpopulations consisted of lay-people (N = 81), students of human nutrition and dietetics (N = 108), and professional experts (N = 79) on human nutrition. The internal consistency and uni-dimensionality of the test were determined by calculating the KR-20 statistic and the log-likelihood ratio statistic for the Rasch model. Pearson's correlation and gross misclassification between T1 and T2 were calculated to assess the test-retest reliability. Analysis of variance was used to test for differences in mean knowledge scores between subpopulations. Test-retest reliability was found to be sufficient (R = .85). The internal consistency was moderate (KR20 = .68). According to the Rasch model, two items had to be removed from the test before the log-likelihood ratio statistic of the Rasch model indicated that knowledge about the fat content of food products as assessed by the questionnaire is a uni-dimensional construct. The differences in mean knowledge scores between the subpopulations were significant (p < .01) and in the expected direction (experts > students > lay people). It can be concluded that the test is a reliable and valid instrument to measure knowledge about total fat content in food products and that the Rasch model is a comprehensive method to indicate the reliability of nutritional knowledge tests.

Growth patterns of medical interviewing skills during a 6-year undergraduate curriculum are assessed by studying 563 medical students taken from five year-groups, interviewing simulated patients. In a cross-sectional, quasi-experimental design their skills are rated by means of the Maastricht History-taking and Advice Checklist (MAAS), an observation instrument which measures five categories of interviewing skills pertaining to initial medical consultations. The findings suggest that the skills for 'history-taking', 'presenting solutions' and 'structuring of the interview' are effectively learned. These learning effects result from a continuous small group teaching program with expert and peer review of videotaped encounters with simulated patients. The teaching effects of this program seem less for the skills pertinent to the phase of 'exploring the reasons for encounter' and to the 'basic interviewing skills', because the students' growing medical knowledge and the increasing ability to solve medical problems exert a counteracting influence on the acquisition of these easily deteriorating skills. The results might be helpful to curriculum planners in order to make their programs for medical interviewing skills more effective.