Why should I prepare? A mixed method study exploring the motives of medical undergraduate students to prepare for clinical skills training sessions.

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.

The effect of guiding questions on students' performance and attitude towards statistics.

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.

The effect of directive tutor guidance on students' conceptual understanding of statistics in problem-based learning.

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.