72,286 research outputs found

    Data mining technology for the evaluation of web-based teaching and learning systems

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    Instructional design for Web-based teaching and learning environments causes problems for two reasons. Firstly, virtual forms of teaching and learning result in little or no direct contact between instructor and learner, making the evaluation of course effectiveness difficult. Secondly, the Web as a relatively new teaching and learning medium still requires more research into learning processes with this technology. We propose data mining – techniques to discover and extract knowledge from a database – as a tool to support the analysis of student learning processes and the evaluation of the effectiveness and usability of Web-based courses. We present and illustrate different data mining techniques for the evaluation of Web-based teaching and learning systems

    Dynamic interactive learning systems

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    Data mining technology for the evaluation of learning content interaction

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    Interactivity is central for the success of learning. In e-learning and other educational multimedia environments, the evaluation of interaction and behaviour is particularly crucial. Data mining – a non-intrusive, objective analysis technology – shall be proposed as the central evaluation technology for the analysis of the usage of computer-based educational environments and in particular of the interaction with educational content. Basic mining techniques are reviewed and their application in a Web-based third-level course environment is illustrated. Analytic models capturing interaction aspects from the application domain (learning) and the software infrastructure (interactive multimedia) are required for the meaningful interpretation of mining results

    Developing digital literacy in construction management education: a design thinking led approach

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    Alongside the digital innovations in AEC (Architectural, Engineering and Construction) practice, are calls for a new type of digital literacy, including a new information-based literacy informed by creativity, critical analysis and the theoretical and practical knowledge of the construction profession. This paper explores the role of design thinking and the promotion of abductive problem situations when developing digital literacies in construction education. The impacts of advanced digital modelling technologies on construction management practices and education are investigated before an examination of design thinking, the role of abductive reasoning and the rise of normative models of design thinking workflows. The paper then explores the role that design thinking can play in the development of new digital literacies in contemporary construction studies. A three-part framework for the implementation of a design thinking approach to construction is presented. The paper closes with a discussion of the importance of models of design thinking for learning and knowledge production, emphasising how construction management education can benefit from them

    Training Competences in Industrial Risk Prevention with LegoÂź Serious PlayÂź: A Case Study

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    This paper proposes the use of the Lego¼ Serious Play¼ (LSP) methodology as a facilitating tool for the introduction of competences for Industrial Risk Prevention by engineering students from the industrial branch (electrical, electronic, mechanical and technological engineering), presenting the results obtained in the Universities of Cadiz and Seville in the academic years 2017–2019. Current Spanish legislation does not reserve any special legal attribution, nor does it require specific competence in occupational risk prevention for the regulated profession of a technical industrial engineer (Order CIN 351:2009), and only does so in a generic way for that of an industrial engineer (Order CIN 311:2009). However, these universities consider the training in occupational health and safety for these future graduates as an essential objective in order to develop them for their careers in the industry. The approach is based on a series of challenges proposed (risk assessments, safety inspections, accident investigations and fire protection measures, among others), thanks to the use of “gamification” dynamics with Lego¼ Serious Play¼. In order to carry the training out, a set of specific variables (industrial sector, legal and regulatory framework, business organization and production system), and transversal ones (leadership, teamwork, critical thinking and communication), are incorporated. Through group models, it is possible to identify dangerous situations, establish causes, share and discuss alternative proposals and analyze the economic, environmental and organizational impact of the technical solutions studied, as well as take the appropriate decisions, in a creative, stimulating, inclusive and innovative context. In this way, the theoretical knowledge which is acquired is applied to improve safety and health at work and foster the prevention of occupational risks, promoting the commitment, effort, motivation and proactive participation of the student teams.Spanish Ministry of Science, Innovation and Universities / European Social Fund: Ramón y Cajal contract (RYC-2017-22222

    Training Competences in Industrial Risk Prevention with Lego (R) Serious Play (R): A Case Study

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    This paper proposes the use of the Lego (R) Serious Play (R) (LSP) methodology as a facilitating tool for the introduction of competences for Industrial Risk Prevention by engineering students from the industrial branch (electrical, electronic, mechanical and technological engineering), presenting the results obtained in the Universities of Cadiz and Seville in the academic years 2017-2019. Current Spanish legislation does not reserve any special legal attribution, nor does it require specific competence in occupational risk prevention for the regulated profession of a technical industrial engineer (Order CIN 351:2009), and only does so in a generic way for that of an industrial engineer (Order CIN 311:2009). However, these universities consider the training in occupational health and safety for these future graduates as an essential objective in order to develop them for their careers in the industry. The approach is based on a series of challenges proposed (risk assessments, safety inspections, accident investigations and fire protection measures, among others), thanks to the use of "gamification" dynamics with Lego (R) Serious Play (R). In order to carry the training out, a set of specific variables (industrial sector, legal and regulatory framework, business organization and production system), and transversal ones (leadership, teamwork, critical thinking and communication), are incorporated. Through group models, it is possible to identify dangerous situations, establish causes, share and discuss alternative proposals and analyze the economic, environmental and organizational impact of the technical solutions studied, as well as take the appropriate decisions, in a creative, stimulating, inclusive and innovative context. In this way, the theoretical knowledge which is acquired is applied to improve safety and health at work and foster the prevention of occupational risks, promoting the commitment, effort, motivation and proactive participation of the student teams

    Dialogue as Data in Learning Analytics for Productive Educational Dialogue

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    This paper provides a novel, conceptually driven stance on the state of the contemporary analytic challenges faced in the treatment of dialogue as a form of data across on- and offline sites of learning. In prior research, preliminary steps have been taken to detect occurrences of such dialogue using automated analysis techniques. Such advances have the potential to foster effective dialogue using learning analytic techniques that scaffold, give feedback on, and provide pedagogic contexts promoting such dialogue. However, the translation of much prior learning science research to online contexts is complex, requiring the operationalization of constructs theorized in different contexts (often face-to-face), and based on different datasets and structures (often spoken dialogue). In this paper, we explore what could constitute the effective analysis of productive online dialogues, arguing that it requires consideration of three key facets of the dialogue: features indicative of productive dialogue; the unit of segmentation; and the interplay of features and segmentation with the temporal underpinning of learning contexts. The paper thus foregrounds key considerations regarding the analysis of dialogue data in emerging learning analytics environments, both for learning-science and for computationally oriented researchers
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