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Dr. Annika Goeze Petra Hetfleisch Prof. Dr. Josef Schrader 《Zeitschrift für Erziehungswissenschaft》2013,16(1):79-113
Case-based learning with videos is regarded as a promising way to promote the analytical abilities of teaching staff as a basis for their professional actions. For that purpose, the competence to assess and diagnose situations of learning and instruction is crucial, i.e., especially the ability to apply conceptual knowledge to pedagogical cases and to take teacher as well as learner perspectives into account. The article reports on the results of an experimental field intervention study aimed to convey this competence effectively by providing different forms of instructional support to over 100 students of English Studies (2?×?2 design, conceptual knowledge: present/not present; teacher and learner perspectives: present/not present). The central focus is on identifying further effects that personal characteristics (individual learning conditions, e.g., prior knowledge, tolerance of ambiguity) and process characteristics (cognitive load; cognitive, emotional, and motivational activation) have on the development of this competence, and how strong these effects are. Multiple linear regression analyses show that this type of learning with case-based videos places less demand on personal factors, and that the quality of the learning process plays a decisive role. 相似文献
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Malcolm L. Fleming 《Instructional Science》1980,9(4):311-326
This article presents a conceptual schema of the instructional process which is intended to make a number of relevant findings from research more readily understood and applied by designers of instruction and instructional materials. It is based on severll summary sources of research-based findings and principles from the perception, memory, and concept formation literature. The basic conception is that learning is the product of an ongoing interactive process between learner and environment, and that instruction is a temporary and purposeful intervention in that process, the aim of which is the optimization of the learner-environment interaction.The schema is organized around relevant characteristics of the learner, i.e., four basic learner requirements (stimulation, order, strategy, and meaning). These basic learner requirements are subdivided into twenty limitations, particularities and qualities of the human information processing systems. The resulting picture of the human learner provides the basis for describing what the other part of the interaction — the instructional environment — should be like in order to provide an optimum fit between learner and environment. The schema subsumes and interrelates many of the research-based principles found in the literature and hence may make them more memorable and usable.1 Because of the generality of research findings referred to in this schema, few specific references will be given. However, the principles on which the schema is based are all properly credited in the sources noted earlier, e.g. Fleming and Levie (1978).This article is based on a paper presented at the IWAPP Festival 1980, Amsterdam, The Netherlands, January 1980.Note 相似文献
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Engagement as an essential factor for active and meaningful learning of English-as-a-Foreign-Language (EFL) is affected by both learner external (e.g., teacher support) and internal (e.g., growth language mindset and L2 grit) factors. This study examined the relationship between perceived teacher support, growth language mindset, and academic engagement by considering the mediating role of L2 grit. The participants were 295 Iranian EFL learners selected via multi-stage cluster sampling. The SEM results indicated that perceived teacher support and growth language mindset directly and positively predicted academic engagement. Additionally, L2 grit mediated the relationships ‘between perceived teacher support and academic engagement’ and ‘between growth language mindset and academic engagement’. EFL learners receiving more teacher support and endorsing higher levels of growth language mindset can successfully overcome failures and difficulties in their learning process by showing more persistence in dealing with challenges and sustaining their interest, which could considerably enhance their engagement in learning. 相似文献
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Contrary to system-controlled multimedia learning environments, hypermedia systems are characterized by a high level of interactivity.
This interactivity is referred to as learner control in the respective literature. For several reasons this learner control
is seen as a major advantage of hypermedia for learning and instruction. For instance, learner control might increase students’
interest and motivation, facilitate adaptive instruction, or provide affordances for active and constructive information processing.
In this paper we analyze the instructional potentials of learner-controlled hypermedia environments as well as possible reasons
for the ambiguous results of studies that have aimed at determining the effectiveness of hypermedia learning. According to
our analysis, the potential effectiveness of self-controlled learning with hypermedia might be difficult to demonstrate due
to (1) usability problems (i.e., disorientation, distraction, cognitive overload), (2) moderating learner characteristics
(i.e., prior knowledge, self-regulatory skills, cognitive styles, and attitudes towards learning), (3) a lack of conceptual
foundations, and (4) methodological shortcomings of many hypermedia studies. The findings reviewed in this paper and the corresponding
claim that hypermedia may be effective only if used in a sensible way are used to derive a couple of guidelines for further
research on hypermedia learning. 相似文献
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孙珂 《成都教育学院学报》2014,(2):72-76
主动学习是学习者自动发起,并自主掌握其过程的学习行为。宁波诺丁汉大学采取多种措施促进学生主动学习,具体包括双管齐下创建互动情境、内外结合促进主动参与、巧妙讲授激发深层思考、问题学习实现知识迁移等。 相似文献
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Game-based learning has been gradually adopted in energy education as an effective learning tool because digital games have the potential to increase energy literacy and encourage behavior change. However, not every learner can benefit from this support. There is a need to examine how human factors affect learners’ reactions to digital games for supporting learning. This study addresses this issue by developing a digital educational game and examining the effects of locus of control on behavioral intention and learning performance of energy knowledge in game-based learning. The results demonstrated that learners with internal locus of control (ILC) outperformed external locus of control (ELC) learners in energy knowledge after interacting with the game. Moreover, the proposed game can reasonably reduce the differences in the behavioral intention of the ILC and ELC learners, indicating that ELC learners significantly improved their behavioral intention after playing the game, especially their external behavioral intention in the aspects of persuasion, legal action, and political action. The findings of this study are discussed to enhance the understanding of locus of control on behavioral intention and energy knowledge in the context of digital games. 相似文献
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Thomas J. Shuell 《Asia Pacific Journal of Education》1992,12(2):1-10
Cognitive conceptions of human learning are discussed with regard to their implications for instructional-design theory. These cognitive conceptions of learning view learning as an active, constructive, cumulative, and goal-oriented process in which the learner plays a critical role. The nature of meaningful learning and the importance of affective and motivational - as well as cognitive - engagement are discussed. It is suggested that in order for students to learn from instruction, various psychological functions (attention, monitoring, etc.) must be engaged by either the instructional agent (e.g., teacher, textbook, etc.) or the student. One characteristic of these learning functions is that there is not a single best way to perform a given function; each may be accomplished in a number of equally appropriate and effective ways. 相似文献
10.
Loredana Mihalca Christoph Mengelkamp Wolfgang Schnotz 《Metacognition and Learning》2017,12(3):357-379
A possible explanation for why students do not benefit from learner-controlled instruction is that they are not able to accurately monitor their own performance. The purpose of this study was to investigate whether and how the accuracy of metacognitive judgments made during training moderates the effect of learner control on performance when solving genetics tasks. Eighty-six undergraduate students solved self-selected genetics tasks using either a full learner control or a restricted learner control. Results indicated that learner control effectiveness was moderated by the absolute accuracy (i.e., absolute bias) of metacognitive judgments, and this accuracy was a better predictor of learning performance for full learner control than for restricted learner control. Furthermore, students’ prior knowledge predicted absolute accuracy of both ease-of-learning judgments (EOLs) and retrospective confidence judgments (RCJs) during training, with higher prior knowledge resulting in a better absolute accuracy. Overall, monitoring guided control, that is, EOLs predicted time-on-task and invested mental effort regardless of the degree of learner control, whereas RCJs predicted the total training time, but not the number of tasks selected during training. These results suggest that monitoring accuracy plays an important role in effective regulation of learning from problem-solving tasks, and provide further evidence that metacognitive judgments affect study time allocation in problem solving context. 相似文献
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Recent literature on learning with instructional manipulatives seems to call for a moderate view on the effects of perceptual and interactive richness of instructional manipulatives on learning. This “moderate view” holds that manipulatives’ perceptual and interactive richness may compromise learning in two ways: (1) by imposing a very high cognitive load on the learner, and (2) by hindering drawing of symbolic inferences that are supposed to play a key role in transfer (i.e., application of knowledge to new situations in the absence of instructional manipulatives). This paper presents a contrasting view. Drawing on recent insights from Embedded Embodied perspectives on cognition, it is argued that (1) perceptual and interactive richness may provide opportunities for alleviating cognitive load (Embedded Cognition), and (2) transfer of learning is not reliant on decontextualized knowledge but may draw on previous sensorimotor experiences of the kind afforded by perceptual and interactive richness of manipulatives (Embodied Cognition). By negotiating the Embedded Embodied Cognition view with the moderate view, implications for research are derived. 相似文献
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Troubleshooting is a common form of problem solving. Technicians (e.g., automotive mechanics, electricians) and professionals (physician, therapists, ombudspersons) diagnose faulty systems and take direct, corrective action to eliminate any faults in order to return the systems to their normal states. Traditional approaches to troubleshooting instruction have emphasized either theoretical or domain knowledge about the system or specific troubleshooting procedures. These methods have failed to develop transferable troubleshooting skills in learners. In this article, we propose an architecture for designing learning environments for troubleshooting. The architecture integrates experiential, domain, and device knowledge in a learning system that enables learners to generate and test hypotheses for every action they take, relate every action to a conceptual model of the system, and query experienced troubleshooters about what they would do. The architecture includes three essential components: A multi-layered conceptual model of the system that includes topographic, function, strategic, and procedural representations; a simulator that requires the learner to generate hypotheses, reconcile the hypotheses to the system mode, test the hypotheses, and interpret the results from the test; and a case library that uses a case-based reasoning engine to access relevant stories of troubleshooting experiences as advice for the learner. This novel architecture can be used to develop learning environments for different kinds of troubleshooting. 相似文献
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学习者模型是自适应学习系统的重要组成部分,然而传统的学习者模型往往是封闭的,学习者无法知晓模型的具体内容。文章从学习者模型内容开放的视角,设计了能够表征学习者认知状态和知识结构并推送学习路径与学习同伴的开放学习者模型——学习认知地图。基于学习元平台,文章从认知状态评测、知识结构计算和可视化呈现三个方面对学习认知地图的构建过程进行了阐述。之后,文章将构建的学习认知地图应用于中学信息技术课堂,实践结果表明:学习认知地图能够提升学生的学习态度,同时学生对具有学习认知地图支持的在线学习方式满意度更高。文章设计并检验了作为一种开放学习者模型实践样态的学习认知地图的效果,以期为开放学习者模型的进一步研究提供参考。 相似文献
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E-learning allows learners individually to learn “anywhere, anytime” and offers immediate access to specific information. However, learners have different behaviors, learning styles, attitudes, and aptitudes, which affect their learning process, and therefore learning environments need to adapt according to these differences, so as to increase the results of the learning process. In addition, providing the same learning content to all the learners may lead to a reduction in the learner's performance. Hence, there is a need to classify the learners based on their performance and knowledge level. Learner profiles play an important role in making the e-learning environment adaptive. Providing an adaptive learning environment, catering to the changing needs and behavior of the learner can be achieved by evolving dynamic learner profiles. Navigation logs can be used to analyze learners’ behavior over a period of time. In this work, we propose dynamic learner profiling to cater to changing learner behaviors, styles, goals, preferences, performances, knowledge level, learner's state, content difficulty, and feedbacks. Based on the continuous observation of learner preferences and requirements, the learner profile is dynamically updated. Furthermore, we propose an automatic learner classification to construct the learner profile and identify the complexity level of learning content, using the Bayesian belief network and decision tree techniques. We evaluated our system with two traditional adaptive e-learning systems, using static profiles and behavioral aspects, through our performance evaluation method of different learner types. In addition, we compared the actual learners’ data with the system generated results for various types of learners, and showed the increased interest in their learning outcomes. 相似文献
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This special issue comprises a set of six papers, in which studies are presented that use eye tracking to analyse multimedia learning processes in detail. Most of the papers focus on the effects on visual attention of animations with different design features such as spoken vs. written text, different kinds of cues, or different presentation speeds. Two contributions concern effects of learner characteristics (prior knowledge) on visual attention when learning with video and complex graphics. In addition, in some papers eye tracking is not only used as a process measure in itself, but also as input for verbal reports (i.e., cued retrospective reporting). In the two commentaries, the contributions are discussed from a multimedia learning perspective and an eye tracking perspective, by prominent researchers in those fields. Together, the contributions to this issue give an overview of the various possibilities eye tracking opens up for research on multimedia learning and instruction. 相似文献
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The Interactive Two Feedback Loops Model (Narciss, 2008, 2013) suggests that not only providing external feedback but also prompting students to generate internal feedback may influence learning and motivation. This study aims at investigating the effects of internal and external feedback on achievement, strategy, and motivation in concept learning. Using a 2 × 3 experimental design with 121 teacher students we investigated the effects of combining internal feedback (i.e. self-explaining why a task solution is correct or incorrect) with three types of external feedback (no feedback; knowledge of result (KR); KR + knowledge about mistakes (KM)). Combining internal and external types of feedback was more beneficial for concept learning achievement, strategy use, as well as students’ intrinsic motivation, and perceived competence, than providing either internal or external feedback. Most notably, if students are asked to generate internal feedback in terms of self-explaining their responses, simple external KR feedback is as beneficial as elaborated KM-feedback. 相似文献
18.
Affordances of Augmented Reality in Science Learning: Suggestions for Future Research 总被引：2，自引：2，他引：0
Augmented reality (AR) is currently considered as having potential for pedagogical applications. However, in science education, research regarding AR-aided learning is in its infancy. To understand how AR could help science learning, this review paper firstly has identified two major approaches of utilizing AR technology in science education, which are named as image-based AR and location-based AR. These approaches may result in different affordances for science learning. It is then found that students’ spatial ability, practical skills, and conceptual understanding are often afforded by image-based AR and location-based AR usually supports inquiry-based scientific activities. After examining what has been done in science learning with AR supports, several suggestions for future research are proposed. For example, more research is required to explore learning experience (e.g., motivation or cognitive load) and learner characteristics (e.g., spatial ability or perceived presence) involved in AR. Mixed methods of investigating learning process (e.g., a content analysis and a sequential analysis) and in-depth examination of user experience beyond usability (e.g., affective variables of esthetic pleasure or emotional fulfillment) should be considered. Combining image-based and location-based AR technology may bring new possibility for supporting science learning. Theories including mental models, spatial cognition, situated cognition, and social constructivist learning are suggested for the profitable uses of future AR research in science education. 相似文献
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This special issue of Learning and Instruction examines the role of emotions in academic learning, with a special focus on emotions in computer-supported academic learning (or e-learning). Three central research challenges concerning emotion in e-learning are: identification (e.g., what are the key emotions in e-learning?), measurement (e.g., how can we tell how strongly a learner is experiencing each key emotion during e-learning?), and explanation (e.g., what are the causes and consequences of the learner's emotional state during learning?). A useful goal of research on emotions in e-learning is to test an affective-cognitive model of e-learning with links among an e-learning episode, the learner's emotional reaction during learning, the learner's cognitive processing during learning, and the learning outcome. 相似文献