Background: South Africa’s participation across a number of international large-scale assessment programmes provides continued evidence of poor student achievement across grades and phases. Despite discouraging achievement results, evidence of slow progress begins to emerge, yet systemic inequalities persist. Aim: This article aims to unpack the possible value of large-scale assessment data in measuring equal educational opportunity as conceptualised by the opportunity to learn (OTL). Setting: While overall scores on international large-scale assessment in countries like South Africa are often driven by aptitude, student motivation and social class, OTL, as described in this article, should provide a more accurate reflection of the nature of performance and the kinds of opportunities afforded to students across an unequal sector to learn. Methods: A multiple linear regression was conducted using the South African PIRLS 2016 teacher and student questionnaire data and the PIRLS Literacy Grade 4 overall reading literacy performance score as the dependent variable. Results: While socio economic status makes a substantial contribution in the current model, the only predictor that was significant is the scale based on student reports on lessons about reading. Conclusion: Through the use of multiple regression analysis, this article concludes that a more effective use of large-scale assessment data from an OTL perspective, specifically in developing contexts, is still problematic using teacher and student questionnaire data. Issues of social desirability and overly positive reporting make any claims about the teachers’ role in providing opportunities to learn and exposure to the curriculum in the classroom difficult to gauge.

中文翻译：

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超越排行榜榜首：学习机会的衡量方法如何有助于教育质量和政策指示？

背景：南非参与了许多国际大规模评估计划，这提供了持续的证据，表明各个年级和阶段的学生成绩都很差。尽管成就成绩令人沮丧，但进展缓慢的证据开始出现，但系统性不平等现象依然存在。目的：本文旨在挖掘大规模评估数据在衡量平等学习机会（如学习机会（OTL）概念化）中的可能价值。设置：虽然南非等国家/地区的国际大规模评估总分通常受能力，学生动机和社会阶层的影响，但本文所述的OTL应该更准确地反映表现的性质和种类不平等部门的学生有多少学习机会。方法：使用南非PIRLS 2016师生问卷数据和PIRLS读写能力4级整体阅读素养表现得分作为因变量进行多元线性回归。结果：尽管社会经济状况在当前模型中做出了巨大贡献，但唯一有意义的预测因素是根据学生关于阅读课程的报告编制的量表。结论：通过多元回归分析，本文得出结论，从OTL角度更有效地使用大规模评估数据，特别是在发展中的情况下，使用师生问卷数据仍然存在问题。