Assessing students’ ability to use computing tools within the framework of statistical thinking

Ken W Li
Hong Kong Institute of Vocational Education
Hong Kong SAR, China

Although statistics education should keep pace with the development of information technology (IT) to strengthen students’ capacity to understand statistical processes and conduct statistical investigations, many students think that the use of IT can accomplish statistical calculations without the need for statistical thinking — which is why they cannot carry out regression tasks leading to the construction of a regression model feasible for making predictions. But, in fact, one of the educational objectives in the statistics curriculum is to teach students how to think statistically. Therefore, the present study aims to assess students’ proficiency in using computing tools and provide feedback to teachers about the parts of statistical thinking they cannot fully develop so as to improve pedagogy to support learning.

A test was conducted in a computing laboratory to assess the operational level of students’ statistical thinking in regression modelling, in addition to their proficiency in using Excel graphing and calculation tools, as well as their knowledge of Excel syntax and programming skills. A sample of 23 students studying in a tertiary academic institution in Hong Kong was selected to attempt seven questions on an individual basis. A qualitative analysis of students’ responses to each question was carried out within the assessment framework of Putt et al. to check which of the four levels of statistical thinking the students had: idiosyncratic thinking, transitional thinking, quantitative thinking and analytical thinking. The results of the analysis showed that most students could manage Excel syntax, as well as calculation and graphing tools, and attain either quantitative thinking or analytical thinking when handling more technical tasks — that is, displaying data and reducing data — but not the tasks of reasoning about data, reasoning about results, and reasoning about conclusions. These reasoning tasks demand statistical communication that should be emphasized and monitored throughout their studies. Statistics lessons and written work should be assigned to students so that teachers can provide feedback on their writing, such as helping them to conceptualize material, make links among concepts, and internalize thinking.