Automated Analysis of Middle School Students’ Written Reflections During Game-Based Learning
Automated Analysis of Middle School Students’ Written Reflections During Game-Based Learning
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DOI：
10.1007/978-3-030-52237-7_6
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发表时间：
2020-06-09
期刊：
影响因子：
--
通讯作者：
Lester J
中科院分区：
文献类型：
--
作者：
Carpenter D;Geden M;Rowe J;Azevedo R;Lester J
基于游戏的学习环境使学生能够进行真实的，基于探究的学习。反思性思维在探究式学习中起着至关重要的作用，它鼓励学生批判性地思考他们的知识和经验，以促进更深入的学习过程。自由反应的反思提示可以嵌入到基于游戏的学习环境中，以鼓励学生参与反思并将其反思过程具体化，但自动评估学生的反思提出了重大挑战。在本文中，我们提出了一个框架，自动评估学生的书面反思反应，在基于探究的学习水晶岛，一个基于游戏的学习环境，中学微生物学。使用来自涉及153名中学生的课堂研究的数据，我们比较了学生对反射词的自然语言反应的几种计算表示-GloVe，埃尔莫，tf-idf，unigrams-在几种基于机器学习的回归技术（即，随机森林，支持向量机，多层感知器），以评估学生反思反应的深度。结果表明，评估模型的基础上埃尔莫深语境化的词表示产生更准确的预测学生的书面反思深度比竞争技术。这些发现指出了利用学生反思的自动评估来为基于游戏的学习环境中基于探究的学习提供实时自适应支持的潜力。
Game-based learning environments enable students to engage in authentic, inquiry-based learning. Reflective thinking serves a critical role in inquiry-based learning by encouraging students to think critically about their knowledge and experiences in order to foster deeper learning processes. Free-response reflection prompts can be embedded in game-based learning environments to encourage students to engage in reflection and externalize their reflection processes, but automatically assessing student reflection presents significant challenges. In this paper, we present a framework for automatically assessing students’ written reflection responses during inquiry-based learning in Crystal Island, a game-based learning environment for middle school microbiology. Using data from a classroom study involving 153 middle school students, we compare the effectiveness of several computational representations of students’ natural language responses to reflection prompts—GloVe, ELMo, tf-idf, unigrams—across several machine learning-based regression techniques (i.e., random forest, support vector machine, multi-layer perceptron) to assess the depth of student reflection responses. Results demonstrate that assessment models based on ELMo deep contextualized word representations yield more accurate predictions of students’ written reflection depth than competing techniques. These findings point toward the potential of leveraging automated assessment of student reflection to inform real-time adaptive support for inquiry-based learning in game-based learning environments.
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影响因子：
1.7
作者：
VANMANEN, M
通讯作者：
VANMANEN, M
影响因子：
3.8
作者：
WONG, FKY;KEMBER, D;YAN, L
通讯作者：
YAN, L
影响因子：
12
作者：
Taub, Michelle;Sawyer, Robert;Lester, James
通讯作者：
Lester, James
DOI：
10.1007/s40593-019-00174-2
发表时间：
2019-05-01
影响因子：
4.9
作者：
Ullmann, Thomas Daniel
通讯作者：
Ullmann, Thomas Daniel
影响因子：
8.5
作者：
Zhang, Wen;Yoshida, Taketoshi;Tang, Xijin
通讯作者：
Tang, Xijin