Promoting Self-Directed Learning in Simulation-Based Discovery Learning Environments Through Intelligent Support

Providing learners with computer-generated feedback on their learning process in simulation-based discovery environments cannot be based on a detailed model of the learning process due to the “open” character of discovery learning. This paper describes a method for generating adaptive feedback for discovery learning based on an “opportunistic” learning model that takes the current hypothesis of the learner and the experiments performed to test this hypothesis as input. The method was applied in a simulation–based learning environment in the physics domain of collisions. Additionally, the method was compared to an environment in which subjects received predefined feedback on their hypotheses, not taking the experimentation behavior into account. Results showed that overall both groups did not differ on knowledge acquired. A further analysis indicated that, in their learning processes, the learners in the experimental condition built upon their intuitive knowledge base, whereas the learners in the control condition built upon their conceptual knowledge base. In addition, measures of the learning process showed that the subjects in the experimental condition adopted a more inquiry-based learning strategy compared to the subjects in the control condition. We concluded, therefore, that providing learners with adaptive feedback had a different and beneficial effect on the learning process compared to more traditional predefined feedback.     

Fostering the analytical competency of pre-service teachers in a computer-supported case-based learning environment: A matter of perspective?

Analytical competency in classroom situations can be seen as a crucial aspect of teachers' professional competency. While case-based learning is considered to have great potential for teacher education, particularly with respect to the promotion of teachers' analytical skills, there have been very few attempts to investigate the effects of corresponding instructional support. The present empirical study investigated the effects of instructional support in the form of multiple perspectives (i.e. authentic comments made by teachers and learners) and the presentation format of these perspectives in a computer-supported case-based learning environment which was based on the principles of cognitive flexibility theory. Twenty-nine foreign-language student teachers participated in the study. Experimental groups were presented with multiple perspectives in a video (plus audio track) or audio-track format. A control group did not have access to these multiple perspectives. The instructional support with multiple perspectives positively influenced learning processes and outcomes with respect to a central dimension of analytical competency – learners' ability to apply conceptual knowledge to case information. Learners with access to multiple perspectives as “audio only” outperformed learners in the “audio + video” condition, who did not substantially differ from the control group.     

基于智能Agent的远程学习者情感与认知识别模型——眼动追踪与表情识别技术支持下的耦合

情感与认知状态的准确识别是实现远程学习者与教学Agent有效互动的基础。只有有效识别出学习者的情感与认知状态,教学Agent在改变学习者行为态度、帮助学习者获取和理解知识、支持学习者认知发展方面才能取得预期的效果。现有的教学Agent普遍存在两方面问题:一是缺乏情感交互性,容易使远程学习者产生厌倦情绪;二是认知推断功能薄弱,对学习效果的促进作用不稳定。这主要是由于Agent对学习者状态的识别不够充分造成的。已有的学习者状态识别方法虽然在学习者情绪状态的识别方面各有优势,但却无法同时检测学习者的视域、学习情绪与认知状态。学习者的眼动追踪数据是判断学习者实时状态的重要指标,也是学习者与Agent进行情感交互的重要依据。结合表情识别和眼动追踪技术构建的基于智能Agent的远程学习者情感与认知识别模型,将眼动追踪与表情监控迭代识别、情感与认知识别过程相耦合,以提高远程学习者状态的识别准确率,改进Agent对学习者的情感和认知支持,为智能教学Agent与远程学习者交互机制的研究提供新的思路和方法。     

Supporting learning with interactive multimedia through active integration of representations

When learners explore dynamic and interactive visualisations they are often not able to interact with them in a systematic and goal-oriented way. Frequently, even supporting learners in processes of discovery learning does not lead to better learning outcomes. This can be due to missing pre-requisite knowledge such as the coherent mental integration of the pictorial and symbolic sources of information. In order to support learners in this process, we encouraged them to interactively and externally relate different static sources of information to each other before exploring dynamic and interactive visualisations. We evaluated the benefit of this instructional support in two experimental studies concerning the domains of statistics and mechanics. It revealed that the active integration of static representations before processing dynamic visualisations resulted in better performance and can provide a basis for a more systematic and goal-oriented experimentation behaviour during simulation-based discovery learning.in final form: 16 November 2004     

How effective is instructional support for learning with computer simulations?

The study examined the effects of two different instructional interventions as support for scientific discovery learning using computer simulations. In two well-known categories of difficulty, data interpretation and self-regulation, instructional interventions for learning with computer simulations on the topic “ecosystem water” were developed and tested using a sample of 124 eighth graders in science classes. The results demonstrate the effectiveness of instructional support for domain-specific factual, conceptual, and procedural knowledge acquisition. Students who received either only instructional support for data interpretation or only for self-regulation achieved the highest learning outcomes. However, a combination of instructional support for data interpretation and self-regulation seemed detrimental for knowledge acquisition. Students who received instructional interventions for both data interpretation and self-regulation also showed the highest values of perceived cognitive load. High cognitive load could be a reason for why a combination of particular instructional interventions does not lead to the expected positive learning outcomes.     

The impact of students’ exploration strategies on discovery learning using computer-based simulations

Discovery-based learning designs incorporating active exploration are common within instructional software. However, researchers have highlighted empirical evidence showing that “pure” discovery learning is of limited value and strategies which reduce complexity and provide guidance to learners are important if potential learning benefits are to be achieved. One approach to reducing complexity in discovery learning is limiting the range of possible actions for the learner to ensure that they do not undertake exploratory activities leading to confusion. This article reports on a study in which the learning outcomes from two learning conditions using computer-based simulations were compared. One condition allowed exploration through manipulation of simulation parameters, while the other allowed observation of simulation output from preset parameters, the latter condition designed to limit the complexity of the task. Learning outcomes for the 158 university student participants were assessed via pre-tests and post-tests of conceptual understanding. Students’ exploration activities were recorded and their strategies subsequently coded as either systematic or unsystematic. The results showed that when compared with observation, systematic exploration resulted in learning benefits, while unsystematic exploration did not. These results have implications for the design of discovery learning tasks and instructional guidance within computer-based simulations.     

Designing a constructive learning activity with interactive elements: the effects of perspective-shifting and the quality of source material

When teachers or instructors create computer-based learning environments, they often solely consider technical aspects of interactivity. As a consequence, learners’ main role is to respond to requests of the learning environment (e.g. by answering multiple-choice questions). This aspect of interactivity is, however, not sufficient to understand the complex benefits of interactivity for learners’ knowledge acquisition. In order to create a higher level of interactivity, an instructional task that encourages learners to design learning materials for fellow learners is used in this paper. We will show that this instructional task can induce interactive elements because learners are encouraged to take not only their own perspective into account when designing. In addition, we investigated if the quality of source material affects knowledge acquisition in design tasks. In a two-by-two design, students (n?=?108) had to design either a learning environment for others (i.e. to perform perspective-shifting), or a representation of acquired knowledge for themselves (no perspective-shifting) with less or more coherent information sources. Results indicate that performing perspective-shifting can be a powerful technique for eliciting interactive learning behavior and, thus, for learning. The quality of information sources does not influence knowledge acquisition to a great extent.     

未来课堂教学设计特性：具身认知视角

随着信息技术的飞速发展,传统课堂逐渐趋向于一个充满技术和更加人本化的泛在学习空间,未来课堂概念应运而生。目前对于未来课堂的研究主要侧重于对未来课堂的空间设计、技术应用、特点特性等方面的研究,还缺乏与未来课堂特性相应的教与学方式及教学模式的系统研究。开展具有前瞻性的未来课堂教学设计有利于推动未来课堂实践。教学设计中隐含着关于认知和学习的理论。虽然传统认知观对教师主导的,以传授客观知识为主要目的的传统课堂教学设计做出了重要贡献,但是其作为面向学习者主动建构知识和实现意义理解的教学设计的理论基础不再是充分的。当代认知理论研究已完成了由离身到具身的范式转型。具身认知理论强调身体在认知过程中的关键作用及认知、身体与环境交互的重要性。基于具身认知的视角,未来课堂的教学设计不再仅仅是提供具体的可操作性步骤,而是为在教学中产生更多的可能性而做好准备,其具有学习内容的情境性、学习环境的无意识性、教学目标的生成性、教学过程的动态性以及学习活动的体验性等特性。     

Exploratory learning with a computer simulation for control theory: Learning processes and instructional support

Computer simulations create a context that is well fitted for exploratory or discovery learning. The aim of the present two studies was to gain deeper insight into what constitutes exploratory learning and to assess the effects of a number of instructional support measures. The domain involved was control theory at the university level. In the first study we made an inventory of exploratory learning processes by observing 17 students working with a computer simulation and analyzing students' thinking-aloud protocols. Subjects received a structured assignment with hints as an instructional support measure. In the second study, 91 students received an open-ended assignment with instructional support that consisted of an information sheet and a set of fill-in forms. On both sheets and forms, six cells were presented. A cell was given for each of the following six learning processes: identifying variables and parameters, generating hypotheses, designing an experiment, predicting, interpreting data, and drawing of conclusions. Information sheets were either of a domain specific or of a general nature. The set of fill-in forms were either free or had the cell HYPOTHESIS already filled in. The statements of the students on the fill-in forms were analyzed in a stepwise order. Twenty-two detailed learning processes were identified and classified. Two of the main classes of processes are transformative and regulative. Both studies showed that students were reluctant to apply learning processes that are considered characteristic for exploratory learning. Furthermore, students had problems with the exploratory learning processes, especially with the processes of generating hypotheses, interpreting data, and drawing conclusions. Effects of the instructional support measures were not conclusive. Hints did not result in significant improvements of the study process. Supporting learning processes with information sheets appeared to help students in performing learning processes, but no different effects of domain specific and general information could be found. Students who were provided with hypotheses showed a higher global activity level and higher scores in domain correctness of their learning processes.     

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。     

计算机模拟环境中的科学发现学习 --过程、条件与学习支持

如何在计算机模拟情境中嵌入有效的学习支持是当前研究者关注的一个重要问题.科学发现学习活动中有三种基本活动线索:问题表征与假设生成、实验检验、自我监控与反思概括.这种学习活动可能主要受三个内在条件的制约:意义性、系统逻辑性和反思概括,据此,针对计算机模拟环境中的学习支持可以包括三个侧面:解释性支持、实验性支持和反省性支持.     

Applying constructivism: A test for the learner-as-scientist

Constructivist learning theory predicts that knowledge encoded from data by learners themselves will be more flexible, transferable, and useful than knowledge encoded for them by experts and transmitted to them by an instructor or other delivery agent. If this prediction is correct, then learners should be modeled as scientists and use the reasoning and technologies of scientists to construct their own knowledge. However, it cannot be taken for granted that the prediction is correct, or correct in every knowledge domain. The present study attempts to establish conditions in which the prediction can be operationalized and tested. It reports on the adaptation of constructivist principles to instructional design in a particular domain, second language vocabulary acquisition. Students learning English for academic purposes in the Sultanate of Oman followed one of two approaches to vocabulary expansion, learning pre-encoded dictionary definitions of words, or constructing definitions for themselves using an adapted version of the computational tools of lexicographers. After 12 weeks, both groups were equal in definitional knowledge of target words, but lexicography group students were more able to transfer their word knowledge to novel contexts.     

远程学习支持新发展与知识工程

随着网络等双向通信技术在远程教育中的应用，交互逐渐成为远程学习的重要因素，这种变化使得原来以支持独立学习为主的学习支持难以满足远程学习的需求，实践发展需要一种具有智能性和交互性特征的，支持交互、协作和社区化的学习支持，因此，这就需要借鉴和吸收其他学科的理论和方法。知识工程是源于专家系统而形成的一门研究人类智能及人类知识的机理，以及如何用机器模拟人的智能并促进人类知识发展的学科，该领域的研究为学习支持在交互和智能化方面的研究提供了重要的技术和方法基础。因此，本提出远程学习支持的新特征和关键研究领域，并重点探讨了知识工程有关领域在支持未来远程学习支持相关技术的研究和开发方面的潜力。作希望本能够对远程学习支持的理论和研究提供新的视角。     

The expertise reversal effect in prompting focused processing of instructional explanations

Providing prompts to induce focused processing of the central contents of instructional explanations is a promising instructional means to support novice learners in learning from instructional explanations. However, within research on the expertise reversal effect it has been shown that instructional means that are beneficial for novices can be detrimental for learners with more expertise if the instructional means provide guidance that overlaps with the internal guidance provided by the prior knowledge of learners with more expertise. Under such circumstances, prompts to induce focused processing might even be detrimental for learners with expertise whose prior knowledge already provides internal guidance to learn from explanations. On this basis, we aimed at experimentally varying expertise by developing prior knowledge. Specifically, we used a preparation intervention with contrasting cases to enhance learners’ prior knowledge (expertise). Against this background, we tested 71 university students in a 2 × 2 factorial experimental design: (a) Factor of expertise. Working with contrasting cases to develop prior knowledge and expertise to provide internal guidance to learn from instructional explanations (with vs. without), (b) Factor of prompts. Prompts to induce focused processing of the explanations (with vs. without). The results showed that prompts to induce focused processing fostered conceptual knowledge for novice learners whereas prompts hindered the acquisition of conceptual knowledge for learners with expertise that was developed by working with contrasting cases beforehand. Moreover, measures of subjective cognitive load and learning processes suggest that the instructional guidance provided by prompts compensated for the low internal guidance of novice learners and overlapped with the internal guidance of learners with expertise.     

How Effective are Instructional Explanations in Example-Based Learning? A Meta-Analytic Review

The worked example effect within cognitive load theory is a very well-established finding. The concrete effectiveness of worked examples in a learning situation, however, heavily depends on further moderating factors. For example, if learners improve their processing of worked examples by actively explaining the worked examples to themselves, they are usually better able to solve transfer problems. Another way to enhance example processing is to present learners with instructional explanations instead of prompting them to produce these explanations on their own. In this article, we review 21 experimental studies to address the issue whether instructional explanations support example-based learning. Meta-analytic results lead to three important conclusions: First, the benefits of instructional explanations for example-based learning per se are minimal. Second, instructional explanations are more helpful for acquiring conceptual knowledge than for acquiring procedural knowledge. Third, instructional explanations are not necessarily more effective than other methods supporting example processing such as self-explaining.     

Development and evaluation of a case‐based digital learning tool about children's mathematical thinking for elementary school teachers (L‐TEST)

It is important for teachers of mathematics to know how pupils react to certain mathematical situations and what these reactions imply, in order to design more effective instructional environments based on their learning needs. This study reports the development processes of a digital learning tool (Learning Tool for Elementary School Teachers (L‐TEST)) that shows children's mathematical thinking for the ages of 4–11 years across certain problem situations. L‐TEST is designed as a support tool to be used in teacher education. A case‐based instructional model was used in designing the instructional tool. Video recordings were digitised to provide a rich environment where learners observe exemplary cases. These exemplified videos included children's mathematical development in the subjects of numbers and shapes, combined with discussions in line with the current research findings. Finally, a usability test for the learning tool was carried out.     

Expertise reversal for different forms of instructional designs in dynamic visual representations

The recent advances in software and computer technology have enabled the incorporation of dynamic representations into a multitude of educational and training environments. Cognitive load theory has been extensively used to enhance learning from complex dynamic representations by providing appropriate instructional designs to manage learner cognitive load. The available evidence, however, indicates that the suggested instructional designs that are effective for novice learners can reverse and become ineffective for learners with higher levels of prior knowledge. This phenomenon is called the expertise reversal effect. This paper reviews a series of recent experimental studies that have found interactions between levels of learners' organized knowledge structures (endogenous support) and effectiveness of different instructional designs (exogenous support), leading to the expertise reversal effect. It is argued that adapting instructional designs to learners with different amount of prior knowledge is a crucial part of effective learning.     

Simulation-Based Evaluation of Learning Sequences for Instructional Technologies

Instructional technologies critically depend on systematic design and learning hierarchies are a commonly advocated tool for designing instructional sequences. But hierarchies routinely allow numerous sequences and choosing an optimal sequence remains an unsolved problem. This study explores a simulation-based approach to modeling learning hierarchies and the sequencing problem with a special focus on mastery learning over time. Computer simulations of eight hierarchies from the literature address two general questions about hierarchies and sequences: Do different valid instructional sequences for a given hierarchy lead to significant differences in simulated learning outcomes?, and How do hierarchy structures and student ability influence learning? Two findings emerge from the simulations: equally valid instructional sequences can produce widely divergent learning outcomes, and student ability can interact with sequence and hierarchy structure to disadvantage lower-ability learners. The paper concludes with observations on the role of simulations in the analysis and validation of instructional design and large-scale instructional systems.     

学案式教学的知识生态学分析

学案式教学是以＂学案＂为导向来实施教学过程的一种教学模式。从知识生态学的角度来分析学案式教学是一个新的视角。知识生态学把知识分为数据资料、信息、知识和智能四种不同的知识形态,其核心是探讨知识如何向更有价值的形态转化及其所需的条件。学案式教学营造了从信息向知识、技能和态度转化的生态环境,并使其教学关注信息、知识如何经过集体和个体交融的学习活动,转化为学习者的能力、意愿、素质、心态以及集体高成效可持续的学习习惯。