The potential for computers to assist learning has been recognised for many years (Jenkins, 1997), with reproductive medicine benefiting greatly from Internet technology (Jenkins, 1999). Following a detailed survey of information technology facilities and skills for postgraduate education (Draycott, 1999), a pilot Internet training programme in reproductive medicine demonstrated effective methods to deliver online teaching (Jenkins, 2001). Based on this experience, in 2001 the Obstetrics and Gynaecology in the University of Bristol, U.K. launched a postgraduate masters course in human reproduction and development, delivered principally over the Internet (Jenkins, 2002). This course has been under continuous evaluation and development since its launch, refining the application of learning technology to most appropriately meet students’ needs (Cahill, 2003). A particularly challenging module of the course considers research methods and statistics. This module was independently evaluated from both a student and tutor perspective, with the objective of identifying learning priorities and optimal educational methodology. This article presents strengths and weaknesses of delivering statistics education online, considering how best to develop this in the future.
Teaching statistics to medical and allied healthcare undergraduates and post-graduates has been a challenging area in higher education (Marantz, 2003). Traditionally taught early in the medical course by colleagues from the mathematics department, basic statistical principles are not retained by many medical graduates. A number of reasons have been postulated for this, including the timing of the teaching and lack of practical implications at this stage of training, and lack of motivation among the students (Marantz, 2003; Romero, 2000; Astin, 2002).
As medical students progress through undergraduate education to post-graduate education, the requirement for medical statistics knowledge increases and ranges from day-to-day needs to critique published literature to the ability to design and evaluate research proposals. The knowledge from undergraduate courses is often inadequate to deal with the increased responsibility, and statistics update courses are difficult to attend while working full time as a clinician (Astin, 2002). Many medical statistics textbooks are available; however, they cannot be individually tailored to meet each student’s needs. Many candidates report medical statistics as a difficult subject to learn, and the students notoriously lack motivation with regards studying (Romero, 2000). The practical aspects are not always relevant to the clinical aspects of medicine being studied; thus, retention of knowledge is poor (Astin, 2002). Evaluations of the current methods of teaching medical statistics in undergraduate curriculum have focused upon the need for clinical relevance when teaching at earlier levels. Courses based around data analysis have been criticised, while a greater emphasis upon critical appraisal and data presentation has been recommended (Romero, 2000; Astin, 2002; Bruce, 2002). One course reported improved student preparation and participation when a case discussion method was employed to teach epidemiology and bio-statistics (Marantz, 2003).
Key Terms in this Chapter
Statistics: Branch of mathematics concerned with the collation, analysis and interpretation of quantitative data.
Biomedical: Relating to biomedicine, the application of natural sciences, especially biology and physiology, to clinical medicine.
Cognitive Learning Theory: This provides a framework to understand learning, suggesting that although learning is not directly observable it occurs through active mental processes where knowledge is progressively assimilated, making a change in behaviour possible.
Distance Education: Students learning remotely from their educational establishment, supported by a variety of methods.
Reproductive Medicine: Speciality of medicine dealing with the reproductive system and related medical issues such as infertility, contraception, menopausal problems and menstrual dysfunction.
Self-Directed Learning: Students are empowered to learn at their own pace, catering to the different learning speeds and styles of individuals.
Web-Based Training: Use of material delivered via Web browser to support education. This may support distance learning or can be used within an educational establishment.