BSRLM abstract

I have to put together a 300 word abstract for BSRLM by this afternoon (well deadline is tomorrow but want to get it done today) and I have no idea what to write. I want it to be based on my thesis but the problem is that it is so difficult to cut down something in my thesis to 300 words. I am trying to determine what would be most relevant to BSRLM but can’t figure.

Anyway, I thought I would write something on the analytical framework I used for analysing how students performed on tasks. So, I’m going to use this space to write this. So, here goes.

This paper looks at the development and implementation of a framework for analysing students’ performance on tasks when using mathematical software. Through a literature review, three approaches and one affective factor were identified based on students’ understanding for analysing how students solved tasks and their effect on the students’ performance. These three approaches are 1) processing level approach (deep or surface learning), 2) self-explanation approach (quality of explanations), 3) explorations (extent of using software). The affective behaviour used was mathematics confidence. Using these approaches and affective factor a triangular framework based on the literature was developed which showed that all of these factors were related to performance and their inter-relationships. The literature indicated that only confidence was related to the processing levels but there were not any studies that showed that self-explanations were related to confidence, processing levels or exploration using software. 

Observing 38 students solving conceptual and procedural tasks using software whilst thinking-aloud, the research aimed to determine whether there was a relationship between these approaches and the factors using both qualitative and quatitative data. An updated framework was developed based on the results from this study. Some evidence was found that quality of self explanations was related to the processing levels.  Mathematics confidence was found to be related to software explorations and the quality of self explanations. Software explorations were also found to be related to the quality of self-explanations. The framework can be further used for testing theories on the relationship between performance and how students’ make sense of solving tasks.

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