Large Language Models for Sustainable Assessment and Feedback in Higher Education: Towards a Pedagogical and Technological Framework

Daniele Agostini, Federica Picasso
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引用次数: 1

Abstract

 Nowadays, there is growing attention on enhancing the quality of teaching, learning and assessment processes. As a recent EU Report underlines, the assessment and feedback area remains a problematic issue regarding educational professionals training and adopting new practices. In fact, traditional summative assessment practices are predominantly used in European countries, against the recommendations of the Bologna Process guidelines that promote the implementation of alternative assessment practices that seem crucial in order to engage and provide lifelong learning skills for students, also with the use of technology. Looking at the literature, a series of sustainability problems arise when these requests meet real-world teaching, particularly when academic instructors face the assessment of extensive classes. With the fast advancement in Large Language Models (LLMs) and their increasing availability, affordability and capability, part of the solution to these problems might be at hand. In fact, LLMs can process large amounts of text, summarise and give feedback about it following predetermined criteria. The insights of that analysis can be used both for giving feedback to the student and helping the instructor assess the text. With the proper pedagogical and technological framework, LLMs can disengage instructors from some of the time-related sustainability issues and so from the only choice of the multiple-choice test and similar. For this reason, as a first step, we are designing and validating a theoretical framework and a teaching model for fostering the use of LLMs in assessment practice, with the approaches that can be most beneficial.
高等教育可持续评估和反馈的大型语言模型:建立教学和技术框架
如今,人们越来越关注提高教学、学习和评估过程的质量。正如欧盟最近的一份报告所强调的,评估和反馈领域仍然是教育专业人员培训和采用新做法方面的一个难题。事实上,欧洲国家主要采用传统的终结性评估方法,这与博洛尼亚进程指导方针的建议背道而驰,博洛尼亚进程指导方针提倡实施替代性评估方法,而替代性评估方法似乎对学生的参与和终身学习技能至关重要,而且还可以利用技术。从文献中可以看出,当这些要求与现实世界的教学相遇时,特别是当学术教师面对大量课程的评估时,就会出现一系列可持续发展的问题。随着大语言模型(LLMs)的快速发展,以及其可用性、经济性和能力的不断提高,这些问题的部分解决方案可能就在眼前。事实上,大型语言模型可以处理大量文本,并按照预先确定的标准进行总结和反馈。分析结果既可用于向学生提供反馈,也可用于帮助教师评估文本。有了适当的教学和技术框架,LLM 可以让教师摆脱一些与时间相关的可持续性问题,从而摆脱选择题测试和类似测试的唯一选择。因此,作为第一步,我们正在设计和验证一个理论框架和一个教学模式,以促进在评估实践中使用 LLMs,并采用最有益的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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