Learner preferences regarding integrating, sequencing and aligning virtual patients with other activities in the undergraduate medical curriculum: A focus group study

CONTEXT: E-learning resources, such as virtual patients (VPs), can be more effective when they are integrated in the curriculum. To gain insights that can inform guidelines for the curricular integration of VPs, we explored students' perceptions of scenarios with integrated and non-integrated VPs aimed at promoting clinical reasoning skills. METHODS: During their paediatric clerkship, 116 fifth-year medical students were given at least ten VPs embedded in eight integrated scenarios and as non-integrated add-ons. The scenarios differed in the sequencing and alignment of VPs and related educational activities, tutor involvement, number of VPs, relevance to assessment and involvement of real patients. We sought students' perceptions on the VP scenarios in focus group interviews with eight groups of 4-7 randomly selected students (n = 39). The interviews were recorded, transcribed and analysed qualitatively. RESULTS: The analysis resulted in six themes reflecting students' perceptions of important features for effective curricular integration of VPs: (i) continuous and stable online access, (ii) increasing complexity, adapted to students' knowledge, (iii) VP-related workload offset by elimination of other activities, (iv) optimal sequencing (e.g.: lecture--1 to 2 VP(s)--tutor-led small group discussion--real patient) and (V) optimal alignment of VPs and educational activities, (vi) inclusion of VP topics in assessment. CONCLUSIONS: The themes appear to offer starting points for the development of a framework to guide the curricular integration of VPs. Their impact needs to be confirmed by studies using quantitative controlled designs.

An investigation into the factors that encourage learner participation in a large group medical classroom

BACKGROUND: Effective lectures often incorporate activities that encourage learner participation. A challenge for educators is how to facilitate this in the large group lecture setting. This study investigates the individual student characteristics involved in encouraging (or dissuading) learners to interact, ask questions, and make comments in class. METHODS: Students enrolled in a Doctor of Veterinary Medicine program at Ross University School of Veterinary Medicine, St Kitts, were invited to complete a questionnaire canvassing their participation in the large group classroom. Data from the questionnaire were analyzed using Excel (Microsoft, Redmond, WA, USA) and the R software environment (http://www.r-project.org/). RESULTS: One hundred and ninety-two students completed the questionnaire (response rate, 85.7%). The results showed statistically significant differences between male and female students when asked to self-report their level of participation (P=0.011) and their confidence to participate (P<0.001) in class. No statistically significant difference was identified between different age groups of students (P=0.594). Student responses reflected that an "aversion to public speaking" acted as the main deterrent to participating during a lecture. Female participants were 3.56 times more likely to report a fear of public speaking than male participants (odds ratio 3.56, 95% confidence interval 1.28-12.33, P=0.01). Students also reported "smaller sizes of class and small group activities" and "other students participating" as factors that made it easier for them to participate during a lecture. CONCLUSION: In this study, sex likely played a role in learner participation in the large group veterinary classroom. Male students were more likely to participate in class and reported feeling more confident to participate than female students. Female students in this study commonly identified aversion to public speaking as a factor which held them back from participating in the large group lecture setting. These are important findings for veterinary and medical educators aiming to improve learner participation in the classroom. Potential ways of addressing this challenge include addition of small group activities and audience response systems during lectures, and inclusion of training interventions in public speaking at an early stage of veterinary and medical curricula.

Projecting a relevant "next": Instruction sequences in driving lessons

Car interaction and the organisation of multi-activity in cars have become a fertile topic of research within CA and EM (Laurier 2005, Haddington & Keisanen 2009). While previous research has focused exclusively on everyday car rides, in this paper we will analyse a specific kind of car interaction, namely driving lessons. In addition to"driving" and"talking", as the two main parallel activities in everyday car rides (Mondada in press), in driving lessons a central activity is"instructing", that we understand to be a collaborative accomplishment (Sanchez Svensson et al. 2009). Drawing on a corpus of 7 video-recorded driving lessons, we will analyse the sequential organisation of"instruction sequences", i.e. of those actions that are initiated by the driving instructor with a turn projecting the next relevant action to be executed by the learner. Learners carry out next actions in two different ways: a) as"single" actions (e.g. using the indicator); b) as a complex series of overlapping or parallel actions. We will show that"single" actions occur as responses to instructions concerning the learner's command of the car, while complex actions occur when the instructors formulate direction indications. The aims of our analyses are twofold. Firstly, we will analyse how instruction sequences are fitted to the emerging contingencies of the car ride (movement in space, changing environment): we will show that a) the turn format of the instruction initiation displays the degree of"urgency" of the requested action; b) learners have the possibility to start the relevant"next" before the instruction initiation comes to completion. Secondly, we will focus on those"seconds" that the driving instructor treats as problematic by initiating a repair sequence (e.g. an improper use of the indicator). Our research contributes to the discussion about the multimodal resources that participants can employ to fulfil a projected action. In addition, it offers insights in a hitherto scarcely investigated topic, namely the organisation of instructions and the ecology of apprenticeship. References HADDINGTON, P. & KEISANEN, T. (2009) Location, mobility and the body as resources in selecting a route. Journal of Pragmatics 41 (10), 1938-1961. LAURIER, Eric (2005): Searching for a parking space. Intellectica 41-42/2-3: 101-116. MONDADA, Lorenza (in press). Talking and driving: multi-activity in the car. Semiotica. SANCHEZ SVENSSON, M. et al. (2009) "Embedding instruction in practice: contingency and collaboration during surgical training", Sociology of Health & Illness, 31/6: 889-906.

Individual Video Training iVT - Development of a National Infrastructure for Video-Supported Learning

Introduction: Video‐Supported Learning is particularly effective when it comes to skills and behaviors. Video registration of patient‐physician interviews, class room instruction or practical skills allow it to learners themselves, their peers, and their tutors to assess the quality of the learner's performance, to give specific feedback, and to make suggestions for improvement. Methods: In Switzerland, four pedagogical universities and two medical faculties joined to initiate the development of a national infrastructure for Video Supported Learning. The goal was to have a system that is simple to use, has most steps automated, provides the videos over the Internet, and has a sophisticated access control. Together with SWITCH, the national IT‐Support‐Organisation for Swiss Universities, the program iVT (Individual Video Training) was developed by integrating two preexisting technologies. The first technology is SWITCHcast, a podcast system. With SWITCHcast, videos are automatically uploaded to a server as soon as the registration is over. There the videos are processed and converted to different formats. The second technology is the national Single Logon System AAI (Authentification and Authorization Infrastructure) that enables iVT to link each video with the corresponding learner. The learner starts the registration with his Single Logon. Thus, the video can unambiguously be assigned. Via his institution's Learning Management System (LMS), the learner can access his video and give access to his video to peers and tutors. Results: iVT is now used at all involved institutions. The system works flawlessly. In Bern, we use iVT for the communications skills training in the forth and sixth year. Since students meet with patient actors alone, iVT is also used to certify attendance. Students are encouraged to watch the videos of the interview and the feedback of the patient actor. The offer to discuss a video with a tutor was not used by the students. Discussion: We plan to expand the use of iVT by making peer assessment compulsory. To support this, annotation capabilities are currently added to iVT. We also want to use iVT in training of practical skills, again for self as well as for peer assessment.  At present, we use iVT for quality control of patient actor's performance.

Decision Support Models for Composing and Navigating through e-Learning Objects

Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed. Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative. Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects. The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.