Abstract:
Within education research there has been sustained interest in developing models that
can predict, or alternatively explain, student success.In computing education, attempts have been
made to predict success in programming courses.Models previously used in this area have included
a range of demographic, cognitive and social factors. These models emphasise presage factors. Biggs'
3P general model of student learyiizg, by comparison, measures attitudinal factors. This multinational,
multi-institutional study investigates the effectiveness of an attitudinal measure, deep and
surface approaches to learning'(Biggs R-SPQ-2F questionnaire), to explain the success of students
in introductory programming courses. This is then compared to both a cognitive and a demographic
measure. The results indicate that across the eleven institutions in three countries the strongest
correlation to success was found with the learning approach.
