882 resultados para learning analytics framework


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Nistor, N., Dascalu, M., Stavarache, L.L., Serafin, Y., & Trausan-Matu, S. (2015). Informal Learning in Online Knowledge Communities: Predicting Community Response to Visitor Inquiries. In G. Conole, T. Klobucar, C. Rensing, J. Konert & É. Lavoué (Eds.), 10th European Conf. on Technology Enhanced Learning (pp. 447–452). Toledo, Spain: Springer.

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This paper reports on an ongoing, multiphase, project-based action learning and research project. In particular, it summarizes some aspects of the learning climate and outcomes for a case study company In the software industry, Using a participatory action research approach, the learning company framework developed by Pedler et al, (1997) is used to initiate critical reflection in the company at three levels: managing director, senior management team and technical and professional staff. As such, this is one of the first systematic attempts to apply this framework to the entire organization and to a company in the knowledge-based learning economy. Two sets of issues are of general concern to the company: internal issues surrounding the company's reward and recognition policies and practices and the provision of accounting and control information in a business relevant way to all levels of staff; and external issues concerning the extent to which the company and its members actively learn from other companies and effectively capture, disseminate and use information accessed by staff in boundary-spanning roles. The paper concludes with some illustrations of changes being introduced by the company as a result of the feedback on and discussion of these issues.

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En este estudio presentamos una experiencia llevada a cabo con estudiantes de la asignatura “Psicología de la Educación” de diferentes centros universitarios. Tomando como marco de referencia las teorías constructivistas del aprendizaje, el objetivo de nuestro trabajo se centra en comprobar la incidencia de la utilización de diferentes estrategias de enseñanza por parte del profesor y de determinadas estrategias de aprendizaje en el proceso de registrar la información por parte de los estudiantes, en la significatividad del aprendizaje. Los resultados obtenidos muestran que en los grupos donde los profesores han utilizado estrategias de enseñanza diferentes a la clase magistral, se ha producido un cambio positivo en las respuestas de los estudiantes o se ha mantenido el mismo nivel, mientras que el grupo donde se ha utilizado una metodología magistral, el nivel de respuesta es inferior. Así mismo, hemos podido observar como los grupos de estudiantes que utilizan las estrategias de aprendizaje seleccionadas para tomar apuntes mejoran su nivel de respuestas, lo cual no se produce en el grupo control

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The learning preferences of three hundred and thirty eight technology students enrolled in sub-degree programs at an Australian institution of Technical and Further Education were tested using the Canfield Learning Styles Inventory (CLSI). The results have been interpreted in a learning preferences framework and provide supportive evidence for the preferences factors of print-nonprint, collaborative, dependent,and autonomous learning identified by Sadler-Smith & Riding (1999). Although there search focussed on learning preferences the analysis also indicated support for the Wholist-Analytic cognitive style proposed by Riding & Cheema (1991). Gender differences were shown for the Interest subscales of the CLSI. Age-group differences were shown for several Conditions of Learning and Modes of Learning subscales. Implications for the design of training programs, and the skills that may need to be developed in technology learners to enable effective use of flexible delivery, are also discussed.

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In this paper we propose a meta-learning inspired framework for analysing the performance of meta-heuristics for optimization problems, and developing insights into the relationships between search space characteristics of the problem instances and algorithm performance. Preliminary results based on several meta-heuristics for well-known instances of the Quadratic Assignment Problem are presented to illustrate the approach using both supervised and unsupervised learning methods.

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This paper advocates the development of an empirical evidence base to guide and enhance Dimensions of Learning (DoL) implementations. The discussion is two-fold. The American research evidence base supporting DoL is outlined and categorized in relation to specific Dimensions. The paper then discusses two approaches to how extant data might be used to shed light on the efficacy of DoL implementations in this country. The paper argues that using these approaches will enable the development of a situated, empirical evidence base reliable enough to guide and enhance DoL implementations in Australia.

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Abstract
Purpose – The purpose of this paper is to evaluate the critical success factors for sustainable e-learning in an e-learning ecosystem framework. Three critical components of the e-learning ecosystem including principles and methods, processes and systems, and substance and content are considered based on a comprehensive review of the relevant literature in e-learning.
Design/methodology/approach – Systematic interviews are conducted with experts in e-learning for identifying the critical success factors to sustainable e-learning within an e-learning ecosystem framework. This leads to the development of an e-learning success model that describes the underlying relationship between and among the identified critical success factors.
Findings – A comprehensive analysis of the interview results shows that there are several barriers to the effective adoption of the proposed e-learning success model for improving the effectiveness of e- learning. These barriers include a lack of understanding of the technologies behind various pedagogies, insufficiencies of the popular learning management systems, and the sustainability of the learning objects repositories.
Research limitations/implications – The paper highlights the criticality of synergizing the three components of e-learning ecosystems namely pedagogies, technologies and management of learning resources for achieving a sustainable e-learning success.
Practical implications – A better understanding of these barriers would help e-learning stakeholders develop appropriate strategies and policies for the implementation of the proposed e-learning success model towards creating a sustainable e-learning environment.
Originality/value – Specific contributions of this research to the entire e-learning community are discussed with recommendations for concerted policy measures to eliminate the identified barriers in the process of adopting the developed e-learning success model.

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Mathematical reasoning has been emphasised as one of the key proficiencies for mathematics in the Australian curriculum since 2011 and in the Canadian curriculum since 2007. This study explores primary teachers’ perceptions of mathematical reasoning at a time of further curriculum change. Twenty-four primary teachers from Canada and Australia were interviewed after engagement in the first stage of the Mathematical Reasoning Professional Learning Program incorporating demonstration lessons focused on reasoning conducted in their schools. Phenomenographic analysis of interview transcripts exploring variation in the perceptions of mathematical reasoning held by these teachers revealed seven categories of description based on four dimensions of variation. The categories delineate the different perceptions of mathematical reasoning expressed by the participants of this study. The resulting outcome space establishes a framework that facilitates tracking of growth in primary teachers’ awareness of aspects of mathematical reasoning.

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Livelihood resilience draws attention to the factors and processes that keep livelihoods functioning despite change and thus enriches the livelihood approach which puts people, their differential capabilities to cope with shocks and how to reduce poverty and improve adaptive capacity at the centre of analysis. However, the few studies addressing resilience from a livelihood perspective take different approaches and focus only on some dimensions of livelihoods. This paper presents a framework that can be used for a comprehensive empirical analysis of livelihood resilience. We use a concept of resilience that considers agency as well as structure. A review of both theoretical and empirical literature related to livelihoods and resilience served as the basis to integrate the perspectives. The paper identifies the attributes and indicators of the three dimensions of resilience, namely, buffer capacity, self-organisation and capacity for learning. The framework has not yet been systematically tested; however, potentials and limitations of the components of the framework are explored and discussed by drawing on empirical examples from literature on farming systems. Besides providing a basis for applying the resilience concept in livelihood-oriented research, the framework offers a way to communicate with practitioners on identifying and improving the factors that build resilience. It can thus serve as a tool for monitoring the effectiveness of policies and practices aimed at building livelihood resilience.

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In this paper we introduce the online version of our ReaderBench framework, which includes multi-lingual comprehension-centered web services designed to address a wide range of individual and collaborative learning scenarios, as follows. First, students can be engaged in reading a course material, then eliciting their understanding of it; the reading strategies component provides an in-depth perspective of comprehension processes. Second, students can write an essay or a summary; the automated essay grading component provides them access to more than 200 textual complexity indices covering lexical, syntax, semantics and discourse structure measurements. Third, students can start discussing in a chat or a forum; the Computer Supported Collaborative Learning (CSCL) component provides indepth conversation analysis in terms of evaluating each member’s involvement in the CSCL environments. Eventually, the sentiment analysis, as well as the semantic models and topic mining components enable a clearer perspective in terms of learner’s points of view and of underlying interests.

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In her presentation, Emmy discusses a case study where a teacher group is followed in its innovative attempt to start up a new curriculum. Searching for guidelines to facilitate knowledge-creating teacher groups, the ‘Dimensions of Social Learning (DSL) Framework’ is applied as a starting point to assess the group's social configuration. To supplement the DSL Framework towards knowledge creation, social capital and value creation theories were studied. This has resulted in an extended framework that can bring the knowledge creation of teacher groups into view.

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Australia, like many nations across the globe, has a focus on engaging young people in the post compulsory years of school to ensure their transition into further education, training and /or the workforce. Applied Learning programs which are based on the premise of active, transformative learning from authentic experience have emerged as valuable tools in assisting the transition of young people. Understanding of Applied Learning however, not only varies between nations but also disciplines, context, education
settings and curricula. Using a lens of boundary crossing, this chapter draws on research data to provide an account of challenges educators face in an Australian program where there appears little guidance for educators on constructing an Applied Learning pedagogical model for individual practice. From consideration of data and educational theory an Applied Learning pedagogical framework is proposed as a guide for educators in developing Applied Learning programs.

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Background: A major challenge for assessing students’ conceptual understanding of STEM subjects is the capacity of assessment tools to reliably and robustly evaluate student thinking and reasoning. Multiple-choice tests are typically used to assess student learning and are designed to include distractors that can indicate students’ incomplete understanding of a topic or concept based on which distractor the student selects. However, these tests fail to provide the critical information uncovering the how and why of students’ reasoning for their multiple-choice selections. Open-ended or structured response questions are one method for capturing higher level thinking, but are often costly in terms of time and attention to properly assess student responses. Purpose: The goal of this study is to evaluate methods for automatically assessing open-ended responses, e.g. students’ written explanations and reasoning for multiple-choice selections. Design/Method: We incorporated an open response component for an online signals and systems multiple-choice test to capture written explanations of students’ selections. The effectiveness of an automated approach for identifying and assessing student conceptual understanding was evaluated by comparing results of lexical analysis software packages (Leximancer and NVivo) to expert human analysis of student responses. In order to understand and delineate the process for effectively analysing text provided by students, the researchers evaluated strengths and weakness for both the human and automated approaches. Results: Human and automated analyses revealed both correct and incorrect associations for certain conceptual areas. For some questions, that were not anticipated or included in the distractor selections, showing how multiple-choice questions alone fail to capture the comprehensive picture of student understanding. The comparison of textual analysis methods revealed the capability of automated lexical analysis software to assist in the identification of concepts and their relationships for large textual data sets. We also identified several challenges to using automated analysis as well as the manual and computer-assisted analysis. Conclusions: This study highlighted the usefulness incorporating and analysing students’ reasoning or explanations in understanding how students think about certain conceptual ideas. The ultimate value of automating the evaluation of written explanations is that it can be applied more frequently and at various stages of instruction to formatively evaluate conceptual understanding and engage students in reflective

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Research on attrition has focused on the economic significance of low graduation rates in terms of costs to students (fees that do not culminate in a credential) and impact on future income. For a student who fails a unit and repeats the unit multiple times, the financial impact is significant and lasting (Bexley, Daroesman, Arkoudis & James 2013). There are obvious advantages for the timely completion of a degree, both for the student and the institution. Advantages to students include fee minimisation, enhanced engagement opportunities, effectual pathway to employment and a sense of worth, morale and cohort-identity benefits. Work undertaken by the QUT Analytics Project in 2013 and 2014 explored student engagement patterns capturing a variety of data sources and specifically, the use of LMS amongst students in 804 undergraduate units in one semester. Units with high failure rates were given further attention and it was found that students who were repeating a unit were less likely to pass the unit than students attempting it for the first time. In this repeating cohort, academic and behavioural variables were consistently more significant in the modelling than were any demographic variables, indicating that a student’s performance at university is far more impacted by what they do once they arrive than it is by where they come from. The aim of this poster session is to examine the findings and commonalities of a number of case studies that articulated the engagement activities of repeating students (which included collating data from Individual Unit Reports, academic and peer advising programs and engagement with virtual learning resources). Understanding the profile of the repeating student cohort is therefore as important as considering the characteristics of successful students so that the institution might be better placed to target the repeating students and make proactive interventions as early as possible.

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One of the aims of Deleuze. Guattari. Schizoanalysis. Education. is to focus on the radical reconfiguration that education is undergoing, impacting educator, administrator, institution and ‘sector’ alike. More to the point, it is the responses to that process of reconfiguration - this newly emerging assemblage - that are a key focal point in this issue. Essential to these responses, we propose, is Deleuze and Guattari’s method of schizonalysis, which offers a way to not only understand the rules of this new game, but also, hopefully, some escape from the promise of a brave new world of continuous education and motivation. A brave new world of digitised courses, impersonal and corporate expertise, updatable performance metrics, Massive Open Online Courses (MOOCs), learning analytics, transformative teaching and learning, online high-stakes testing in the name of transforming and augmenting human capital overlays the corporeal practices of institutional surveillance, examination and categorical sorting. A brave new world, importantly, where people’s continuous education is instituted less, or not simply, through disciplinary practices, and increasingly through a constant and continuous sampling and profiling of not simply performance but their activity, measured against the profiled activity of a ‘like’ age group, person, or an institution. This continuous education, including the sampling that accompanies it, we are all informed through various information and marketing campaigns, is in our best interest. An interest that is driven and governed by an ever-increasing corporatisation and monetisation of ‘the knowledge sector’, as well as an interest that is sustained through an ever-increasing, as well as continuous, debt.