Tertiary Students’ studying statistics usually process statistical information in different ways depending on their programme of study. Teaching methodologies for transmitting statistical information to students also vary considerably depending on the type of programme being taught, a trade-off between the two must be sought for, it is therefore necessary to determine what is most likely to trigger each student’s concentration, and how to maintain it. The study examined the distribution of learning styles of accounting, statistics and engineering students among the four learning styles and its implication to teaching in higher institutions. Data for the study was collected using Solomon and Felder’s ILS questionnaire. Purposive sampling technique was used to select the respondents; the responses from each person’s questionnaire were entered into Felder’s self-scoring web based instrument. The output was further analyzed via SPSS version 17. The results showed that there were remarkable differences in the distribution of the programme of study to the learning styles. Majority of the students belonged to the active, visual, sensing and sequential learners. There was sufficient evidence to believe that differences existed among the active-reflective learners and program of study. The multiple comparisons method gave pair-wise significance among the active-reflective group of learners. The pair business and statistics was pair-wise significant (P = 0.016 < 0.05), the pair Business and Engineering learners was not significant (p = 0.197 > 0.05) finally, the pair Engineering-Statistics Learners was highly significant (p = 0.004< 0.05). For statistics to have practical relevance and provide the various categories of students with the opportunity to understand how the concepts can be applied in the world of work. It is highly recommended to lecturers to conduct need assessments to find the learning styles of their students and structure their teaching methods to satisfy the needs of the students.
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