Point and set reasoning in practical science measurement by entering university freshmen

Abstract

ABSTRACT:The procedural understanding of university students at the freshman level, prior to instruction, has been investigated in the context of experimental work in physics. A written instrument was used to explore students' ideas about data collection, data processing, and data comparison; in particular, the need to repeat measurements and the implications of the scatter associated with numerical and graphical data. Two types of reasoning used by students in the laboratory, viz. point and set reasoning, are proposed and used to classify students' responses. The findings show a high degree of consistency of these modes of reasoning across the experimental phases of data collection and data processing. A framework is suggested from which a laboratory teaching program may be developed.

Concepções de estudantes do Ensino Médio sobre os conceitos de média e dispersão de dados

“…Fred Lubben e membros do seu grupo de pesquisa (ALLIE et al, 1998;BUFFLER et al, 2001;LUBBEN et al, 2001), realizaram uma série de trabalhos que forneceu um importante suporte empírico para o desenvolvimento de um referencial no qual o pensamento e o raciocínio utilizados pelos estudantes durante o processo de medição e análise dos dados podem ser categorizados em dois tipos distintos, segundo os paradigmas Pontual e de Conjunto 2 . As diferenças entre os paradigmas podem ser vistas no Quadro 1.…”

“…Versões modificadas dessas questões podem ser encontradas em outras pesquisas (LEACH et al, 2000;LUBBEN et al, 2001).…”

Learning physics : from the nature and origins of difficulties to an evolution of teaching

“…showed that more than 30% of the students mobilize the point reasoning when they collect and process data [11]. Many other studies have also highlighted pupils' and students' difficulties in analyzing data and understanding the measuring process.…”

The Experimenter Expectancy Effect: An Inevitable Component of School Science?

“…Pupils tend not to realise that data collection is inherently random and often does not produce a single definitive 'right answer'; instead a spread of values are collected that approximate to that right answer (Lubben, Campbell, Buffler & Allie, 2001). This is why science curricula promote repeat measurements during experiments.…”