Factors Influencing Poor Examination Performance in Commercial Subjects in Tanzania Ordinary Level Secondary Schools: A Case Study of Ilala Municipality

Mhonyiwa, Juliana Masasi (2014) Factors Influencing Poor Examination Performance in Commercial Subjects in Tanzania Ordinary Level Secondary Schools: A Case Study of Ilala Municipality. Masters thesis, The Open University of Tanzania.

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Abstract

This study explored the factors that influenced poor examination performance in commercial subjects in secondary schools in Ilala Municipality, Dar-es-Salaam, Tanzania. It examined teacher’s qualities in teaching commercial subjects, availability of teaching and learning resources in relation to commercial subjects, students’ interest in commercial subjects and the extent to which commercial subjects are inspected, and how these affect performance in ordinary level examinations. The study used qualitative approach, using interviews, focus group discussion, observation and documentary data. Thematic approach was used in data analysis. The major findings were related mostly to teachers’ qualities, as some of the teachers were not conversant with English language, as well as subject matter. One of the teachers was a diploma failure, and another did not study commercial subjects at A- Level. English language was also an obstacle for students and some of the teachers, as they could not communicate well with their students in class. Hence, they used mostly Kiswahili instead of English as the medium of instruction. Apart from these factors, also teaching and learning resources were a problem; commercial subject textbooks were not readily available for students use. On top of these, old syllabus was used; there was no recent knowledge on the subject. Teachers lacked seminars and in-service training. These added to lack of intrinsic motivation among government teachers. The study recommended several remedies for that situation. Also the study recommended further research on the topic based on a large sample by using a survey research approach in order to generalize the obtained data to a large sample.

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