ABSTRACT

This paper explores students’ ability to analyse and interpret empirical data as inadequate data analysis skills and understandings may contribute to the renowned disappointing outcomes of practical work in secondary school physics. Selected competences, derived from a collection of leading curricula, are explored through interviews and practical tasks, each consisting of three probes. The 51 students, aged 15 and commencing post-compulsory science education in the Netherlands, were able to carry out basic skills such as collecting data and representing these. In interpreting the data in terms of the investigated phenomenon or situation however, performance was weak. Students often appeared to be unable to identify the crucial features of a given graph. Conclusions based on the data were often tautological or superficial, lacking salient features. Students failed to infer implications from the data, to interpret data at a higher level of abstraction, or to specify limitations to the validity of the analysis or conclusions. The findings imply that the students’ understanding of data-analysis should be developed further before they can engage successfully in more ‘open’ practical work. The study offers a collection of activities that may help to address the situation, suggesting a baseline for guided development of data analysis abilities.

摘要

本文探讨了学生分析和解释经验数据的能力，因为缺乏足够的数据分析技能和理解可能会导致著名的中学物理实践工作令人失望的结果。通过访谈和实际任务探索从一系列领先课程中选拔的能力，每个任务均由三个探究组成。这名51岁的学生，年龄15岁，在荷兰开始接受义务教育后，能够进行基本技能，例如收集数据和代表这些技能。但是，根据调查的现象或情况来解释数据时，性能较弱。学生似乎常常无法识别给定图的关键特征。根据数据得出的结论通常是重言式的或肤浅的，缺乏明显的特征。学生未能从数据中推断出含义，无法以更高的抽象水平解释数据，也没有为分析或结论的有效性规定限制。调查结果表明，在使学生成功地从事更多“开放式”实践工作之前，应该进一步发展他们对数据分析的理解。该研究提供了可能有助于解决该情况的一系列活动，为指导数据分析能力的发展提供了基线。