Exploring the deep-level reasoning questions effect during vicarious learning among eighth to eleventh graders in the domains of computer literacy and Newtonian physics

This paper tested the deep-level reasoning questions effect in the domains of computer literacy between eighth and tenth graders and Newtonian physics for ninth and eleventh graders. This effect claims that learning is facilitated when the materials are organized around questions that invite deep-reasoning. The literature indicates that vicarious learners in college student populations show greater pretest to posttest learning gains when presented with deep-level reasoning questions before each content sentence, than when deep-level questions are omitted, or when learners interact with an intelligent tutoring system. This effect holds for vicarious learners across grade levels and domains.     

Finding the Best Types of Guidance for Constructing Self-Explanations of Subgoals in Programming

Subgoal learning, a technique used to break down problem solving into manageable pieces, has been used to promote retention and transfer in procedural domains, such as programming. The primary method of learning subgoals has been passive, and passive learning methods are typically less effective than constructive methods. To promote constructive methods of learning subgoals, we prompted learners to self-explain the subgoals of a problem-solving procedure. Self-explanation asks learners to make sense of new information based on prior knowledge and logical reasoning. Novices’ self-explanation is typically more effective when they receive guidance, because it helps them to focus on relevant information. In the present experimental study, the types of guidance that students received while self-explaining determined whether the constructive learning method was more effective than the passive method. Participants assigned to the constructive learning method performed best when they either received hints about the subgoals or received correct explanations as feedback, but not when they received both. These findings suggest that constructive learning of subgoals can further improve the benefits of subgoal learning when students receive only guidance that complements their construction of knowledge. This nuance is important for educators who engage their students in constructive learning and self-explanation.     

Design of Support Tools for Knowledge Building in a Virtual University Course

In a WWW-based virtual learning environment where students and teachers are physically separated, the quantity and quality of interaction among students and with instructors affects learning. Lack of constructive activity is often identified as one of the major causes for poor learning. We developed support tools (prompts which support students to use self-explanation and self-monitoring strategies) and studied how support tools facilitate convergent knowledge building processes in a WWW-based virtual university engineering course. A quasi-experimental study was designed. An engineering class of a virtual university was selected as the research site and the students in the class were randomly assigned to two different work environments: (1) without support tools, and (2) with support tools. This study has an implication for theory that the opportunity to engage in interaction itself is not enough for students to either integrate knowledge or develop/improve the coordination of group work in an online learning environment. Frequent interaction with their peers is not enough either for students to integrate knowledge or develop/improve coordination of group work in an online learning environment. The type of interaction matters, especially because convergent type of interaction facilitates students' knowledge integration.     

Interactive Example-Based Learning Environments: Using Interactive Elements to Encourage Effective Processing of Worked Examples

This review describes parts of our research program on example-based learning that relates to recent efforts to incorporate interactive elements into learning environments designed to support learning from worked-out examples. Since most learners spontaneously study or process examples in a very passive or superficial manner, this review focuses on how a variety of specific interactive elements in example-based leaning environments are capable of encouraging learners to actively process the examples. The review begins with an overview of the literature on worked examples and the associated self-explanation, which is important given that the quality of self-explanation is a major factor in determining whether learners benefit from studying examples. The review notes that example-based learning environments tend to be effective but often promote passive processing. It then highlights the strengths and limitations of three types interactivity introduced to example-based learning environments. The review concludes with a discussion of the role that these interactive elements play in these learning environments.     

Interest and Learning From Text

This article deals with the relation between interest and learning from text. In the first section, the concepts of personal and situational interest and their relation to motivation are clarified. Based on my own studies and findings from other studies, the next sections present evidence for substantial relations between interest and text learning. These relations appear to be stronger for deep-level learning than surface-level learning and seem to be largely independent of prior knowledge and cognitive ability. Finally, it is argued that past research has failed to examine the underlying mechanisms of motivation-learning relations. Suggestions and guidelines for future research are given.     

样例学习中自我解释效应的研究

在样例学习过程中,学习者对样例的知识内容进行自我解释,会导致样例学习成绩提高,这就是自我解释效应。Chi等人最初对自我解释效应所进行的研究发现,自我解释效应的影响因素包括先行知识、一般能力和个体差异。对自我解释效应的三种理论解释是:间隙—填充(gap—filling)、图式—结构(schema formation)和相似增强(analogical enhancement)。未来对自我解释效应研究的关注点是:自我解释效应的机制、人为设定自我解释提示能否改进学习效果,以及建构性活动与样例学习效果之间的关系。     

Constructing explanatory models from text-based information: Why instructional tools help

Scientists frequently construct explanatory models based on information they read about scientific phenomena. Modeling is a complex task involving reasoning about what information from multiple texts, including verbal and visual representations, is task-relevant and how it relates to the model. In this study, ninth graders were randomly assigned to a text-based modeling task with or without an instructional tool designed to support selection and elaborative processing of relevant information. Participants completed prompted self-explanation protocols during the modeling task and a learning task afterward. Participants with the instructional tool demonstrated better model construction and learning. Self-explanation analyses indicated more elaborative processing of relevant information for those with the tool. Elaboration of relevant information significantly mediated the instructional tool effect, indicating that it is not the tool, but the forms of processing that it encouraged, that underlies better model construction and learning. Implications for science literacy instruction are discussed.     

Coordinating principles and examples through analogy and self-explanation

Research on expertise suggests that a critical aspect of expert understanding is knowledge of the relations between domain principles and problem features. We investigated two instructional pathways hypothesized to facilitate students’ learning of these relations when studying worked examples. The first path is through self-explaining how worked examples instantiate domain principles and the second is through analogical comparison of worked examples. We compared both of these pathways to a third instructional path where students read worked examples and solved practice problems. Students in an introductory physics class were randomly assigned to one of three worked example conditions (reading, self-explanation, or analogy) when learning about rotational kinematics and then completed a set of problem solving and conceptual tests that measured near, intermediate, and far transfer. Students in the reading and self-explanation groups performed better than the analogy group on near transfer problems solved during the learning activities. However, this problem solving advantage was short lived as all three groups performed similarly on two intermediate transfer problems given at test. On the far transfer test, the self-explanation and analogy groups performed better than the reading group. These results are consistent with the idea that self-explanation and analogical comparison can facilitate conceptual learning without decrements to problem solving skills relative to a more traditional type of instruction in a classroom setting.     

对自我解释研究的分析

自我解释是学生在学习过程中自己向自己解释学习内容的知识获得过程。该文解释了“自我解释”的含义、总结了自我解释的类型、比较了几种自我解释产生的认知机制、归纳了影响因素,从而提出了关于自我解释需要进一步研究的未来问题。     

Learning from instruction: the case of mathematics

Starting from a brief analysis of adaptive competence in mathematics, this article describes a series of research-based characteristics of the kind of learning processes that should be elicited in students to facilitate and support in them the progressive acquisition of such competence. Four major characteristics are discussed in some detail: learning is constructive, self-regulated, situated or contextual, and collaborative. A rather new approach to transfer of learning is then presented in which transfer is conceived as the preparation for future learning. Throughout the article it is argued that, notwithstanding the progress made in research on learning from instruction, numerous and complex issues and problems remain for continued inquiry.     

Preparing pupils to cooperate during cooperative controversy in grade 6: a way to increase positive interactions and learning?

Research has underlined the necessity to prepare pupils to cooperate in order to boost cooperative learning benefits. However, this kind of training may appear very demanding. The present study aims to demonstrate that a short preparation related to social support and targeted cooperative rules relevant for the task increases constructive interactions. Thirty-two pupils from grade 6 (11.8 years) were involved in dyadic cooperative controversy (Johnson and Johnson 2007) on argumentative texts for one session. All pupils were presented with three targeted rules for controversy. Half of the pupils had a short intervention related to the demonstration of social support, and the three targeted cooperative rules for controversy were explained and discussed (listening carefully while affirming understanding, criticizing ideas, but not people, and focusing on common goal). The pupils' interactions during cooperative controversy were videotaped and coded and the individual learning regarding the content of the studied texts was assessed. Results indicated that those pupils who had been prepared to cooperate displayed more support, asked more questions, and paid more attention to their partner. The overall quality of cooperation inside the dyad was also evaluated as more positive, though no difference in learning outcomes was observed. In summary, a short preparation for cooperation elicited more constructive interactions.     

基于数课平台的研究生深度学习研究与设计

为有效促进研究生在学习过程中深入探究,展开批判性思考,实现对知识的深度学习,将数课平台引入学习者在线学习中,以期提供具有指引性的学习支持。通过文献分析并结合研究生深度学习研究现状,构建深化认知的在线学习环境,设计引导兴趣的学习活动,从6个方面开展基于数课平台的研究生深度学习研究。该方法有利于引导学习者积极互动、深入交流,使教师与学习者及时掌握与调整学习情况,促进学习者在线深层次探究与学习。     

Teaching Students to Formulate Questions

Abstract

As STEM educators, we know it is beneficial to train students to think critically and mathematically during their early mathematical lives. To this end, the author teaches the College Algebra/Precalculus course in a flipped classroom version of an inquiry-based learning style. However, the techniques described in this paper can be applied to a variety of freshman and sophomore mathematics courses (and above). In particular, in this model the students read the textbook before class and formulate questions, submitted prior to class via a learning management system, about the material to be covered in class the next day. During class they solve problems about that topic, and solutions are presented and discussed before the end of the period. After class, students complete standard homework about the topic, and are encouraged to bring any unresolved homework, worksheet, or reading questions for the next class period. This paper will discuss this method of engaging students, focusing on how student questions evolve during the semester, and student feedback.     

自我解释的研究述评

自我解释是指学习者向自身做出解释,以理解新信息的一种认知活动。研究表明,在学习过程中,自我解释的学习者对学习材料的理解更好,这种现象称为“自我解释效应”。文章从自我解释效应的影响因素,促进自我解释和自我解释的心理机制三个角度出发,回顾了以往关于自我解释的研究。最后,提出了三个有待进一步研究的问题。     

Example-based learning: The benefits of prompting organization before providing examples

Example-based learning often follows a design in which learners first receive instructional explanations that communicate new principles and concepts and second examples thereof. In this setting, using the knowledge components of the instructional explanations to explain the examples (i.e., generating principle-based self-explanations) is considered to be a highly important learning process. However, a potential suboptimality of this learning process is that it scarcely requires learners to organize the content of the instructional explanations into coherent mental representations. Thus, in two experiments we investigated whether prompting learners to organize the content of the instructional explanations before providing them with the examples (and self-explanation prompts) enhances the effectiveness of example-based learning. We consistently found that organization prompts fostered learning regardless of whether the learners also received self-explanation prompts. Hence, in example-based learning, learners should be prompted to not only generate principle-based self-explanations but also to organize the content of the instructional explanations.     

e—Learning新解：网络教学范式的转换

当代学习理论正在发生有意义的变化,学习越来越多的被认为是建构认知、分布式认知和情境认知的过程,而不仅仅是知识的传递;越来越关注知识协同建构的社会本质,知识协同建构受共同体的影响。Web2．0技术在e-Learning中的应用更加关注学习过程的参与性,强调通过师生、生生之间的学习活动来促进知识内容的内化,通过学习活动的序列化,来支持多种实践导向的教学模式。而普适计算技术的发展,使得学习无时不在、无处不在、按需适应成为可能。在学习理论发展和信息技术发展的双重推动下,网络教学正实现从接受认知范式到建构认知范式再到分布式情境认知范式的转换,这反映了e—Learning从技术向教育回归的基本趋势。     

Substituting one mystery for another: the role of self-explanations in solving algebra word-problems

Explanations students provide themselves (self-explanations) in the course of learning or problem-solving have been shown to be positively associated with performance. However, the role self-explanation plays in problem solving has not been fully elaborated. This study aims to analyze the role of self-explanation in solving algebra word problems. We argue that self-explanation may function as verbal mediation that supports the transformation between different external representations of the problem. Our analysis of the problem solving protocols aims to illustrate this point through a multiple case studies design. Specifically we illustrate the way a particular kind of self-explanation (categorical explanation) mediates students' transformation from the sentential representation of the problem to the tabular one.     

样例学习认知负荷理论的研究及其展望

文章回顾了样例学习研究的起源与发展,主要介绍了其理论依据——认知负荷理论,并分别围绕外在认知负荷、内在认知负荷以及相关认知负荷介绍了最新国内外样例学习的设计方法:材料的整合、子目标、不完整样例、错误样例、诱发自我解释问题、多种解题方法比较等,最后在现有研究成果上指出样例学习研究的发展趋势和有待进一步解决的问题。     

Assisting self-explanation prompts are more effective than open prompts when learning with multiple representations

Learning with multiple representations is usually employed in order to foster understanding. However, it also imposes high demands on the learners and often does not lead to the expected results, especially because the learners do not integrate the different representations. Thus, it is necessary to support the learners’ self-explanation activity, which concerns the integration and understanding of multiple representations. In the present experiment, we employed multi-representational worked-out examples and tested the effects of two types of self-explanation prompts as help procedures for integrating and understanding multiple representations. The participants (N = 62) learned about probability theory under three conditions: (a) open self-explanation prompts, (b) self-explanation prompts in an assistance-giving-assistance-withholding procedure (assisting self-explanation prompts), or (c) no prompts (control group). Both types of self-explanation prompts fostered procedural knowledge. This effect was mediated by self-explanations directed to domain principles. Conceptual knowledge was particularly fostered by assisting self-explanation prompts which was mediated by self-explanations on the rationale of a principle. Thus, for enhancing high-quality self-explanations and both procedural knowledge and conceptual understanding, we conclude that assisting self-explanation prompts should be provided. We call this the assisting self-explanation prompt effect which refers to the elicitation of high-quality self-explanations and the acquisition of deep understanding.     

Team regulation, regulation of social activities or co-regulation: Different labels for effective regulation of learning in CSCL

Computer-supported collaborative learning (CSCL) is an approach to learning in which learners can actively and collaboratively construct knowledge by means of interaction and joint problem solving. Regulation of learning is especially important in the domain of CSCL. Next to the regulation of task performance, the interaction between learners who work in a CSCL environment needs to be regulated as well. Despite its importance, the regulation of learning in CSCL has received relatively little attention in research. In the contributions of this special issue different labels are used for various forms of regulation of learning during CSCL. During collaborative learning, the regulation of activities can take place at different levels of social interaction: the individual level, the dyadic level, and the group level. Regulative activities of all three levels are presented in the three studies. All studies have investigated whether the use of regulative activities affected performance, and have found that regulation at the dyadic and/or group level was positively related to group performance. In sum, these three contributions provide a constructive overview of the role of regulation of the (collaborative) learning process in CSCL, both in terms of the impact of regulation on learning processes and learning results as well as the influence of different kinds of support on the regulation of collaborative learning.