摘要翻译：
在这项工作中，我们处理了一个问题，为初学者建模编程练习指向一个电子学习场景。我们的目的是确定基本需求，提出一些关键问题，并从概念的角度提出潜在的答案。作为一个概貌，我们假设将我们的工作置于一个普遍的背景下，在这个背景下，电子学习教学材料需要调整，以形成CS1级的计算机科学入门(CS)电子学习课程的一部分。Mean是一门潜在的课程，旨在通过使用基于电子学习的方法（至少在概念上）与Activemath（www.Activemath.org）这样的通用主机框架联系起来，提高新手在编程基本知识方面的技能和知识。我们的阐述涵盖了上下文，尤其是认知元素，为衍生项目中的最终研究阶段做准备，如所示。我们将主要精力集中在关于练习复杂性的推理机制上，这些机制最终能够为练习创作任务提供工具支持。我们的需求分析基于我们自己对Activemath提供的练习子系统的理解，特别是在domain reasoner领域。我们通过引入CS1课程中的几个相关的上下文元素、定义和实施来丰富分析。关于认知模型和练习，我们建立在布卢姆分类学原则的基础上，作为一个相对标准化的基础，并将其作为研究和分析基础程序设计练习复杂性的框架。我们的分析包括对领域推理器的需求，这是练习分析所必需的。为此，我们提出了一个考虑练习评估、编程和元编程的三层概念模型。
---
英文标题：
《On Requirements for Programming Exercises from an E-learning Perspective》
---
作者：
Carlos Loria-Saenz
---
最新提交年份：
2009
---
分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
--

---
英文摘要：
  In this work, we deal with the question of modeling programming exercises for novices pointing to an e-learning scenario. Our purpose is to identify basic requirements, raise some key questions and propose potential answers from a conceptual perspective. Presented as a general picture, we hypothetically situate our work in a general context where e-learning instructional material needs to be adapted to form part of an introductory Computer Science (CS) e-learning course at the CS1-level. Meant is a potential course which aims at improving novices skills and knowledge on the essentials of programming by using e-learning based approaches in connection (at least conceptually) with a general host framework like Activemath (www.activemath.org). Our elaboration covers contextual and, particularly, cognitive elements preparing the terrain for eventual research stages in a derived project, as indicated. We concentrate our main efforts on reasoning mechanisms about exercise complexity that can eventually offer tool support for the task of exercise authoring. We base our requirements analysis on our own perception of the exercise subsystem provided by Activemath especially within the domain reasoner area. We enrich the analysis by bringing to the discussion several relevant contextual elements from the CS1 courses, its definition and implementation. Concerning cognitive models and exercises, we build upon the principles of Bloom's Taxonomy as a relatively standardized basis and use them as a framework for study and analysis of complexity in basic programming exercises. Our analysis includes requirements for the domain reasoner which are necessary for the exercise analysis. We propose for such a purpose a three-layered conceptual model considering exercise evaluation, programming and metaprogramming.
---
PDF链接：
https://arxiv.org/pdf/0903.0786