Semi-automated assessment of programming languages for novice programmers

There has recently been an increased emphasis on the importance of learning programming languages, not only in higher education but also in secondary schools. Students of a variety of departments such as physics, mathematics and engineering have also started learning programming languages as part of their academic courses. Assessment of students programming solutions is therefore important for developing their programming skills. Many Computer Based Assessment (CBA) systems utilise multiple-choice questions (MCQ) to evaluate students performance. However, MCQs lack the ability to comprehensively assess students knowledge. Thus, other forms of programming solutions are required to assess students knowledge. This research aims to develop a semi-automated assessment framework for novice programmers, utilising a computer to support the marking process. The research also focuses on ensuring the consistency of feedback. A novel marking process model is developed based on the semi-automated assessment approach which supports a new way of marking, termed segmented marking . A study is carried out to investigate and demonstrate the feasibility of the segmented marking technique. In addition, the new marking process model is developed based on the results of the feasibility study, and two novel marking process models are presented based on segmented marking, namely the full-marking and partial-marking process models. The Case-Based Reasoning (CBR) cycle is adopted in the marking process models in order to ensure the consistency of feedback. User interfaces of the prototype marking tools (full and partial) are designed and developed based on the marking process models and the user interface design requirements. The experimental results show that the full and partial marking techniques are feasible for use in formative assessment. Furthermore, the results also highlight that the tools are capable of providing consistent and personalised feedback and that they considerably reduce markers workload.