20 resultados para Tutor


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This research showed that one solution that can be used to help the students learn how to program is by providing a system that can behave like a tutor to teach the students individually. An intelligent tutoring system named CSTutor was built in this research to assist the students. CSTutor asks the student to write programs in a role playing environment, presenting the most appropriate tasks to the students, and provides help to the students' problems.

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Final report for the Australian Government Office for Learning and Teaching. "This seed project ‘Design thinking frameworks as transformative cross-disciplinary pedagogy’ aimed to examine the way design thinking strategies are used across disciplines to scaffold the development of student attributes in the domain of problem solving and creativity in order to enhance the nation’s capacity for innovation. Generic graduate attributes associated with innovation, creativity and problem solving are considered to be amongst the most important of all targeted attributes (Bradley Review of Higher Education, 2009). The project also aimed to gather data on how academics across disciplines conceptualised design thinking methodologies and strategies. Insights into how design thinking strategies could be embedded at the subject level to improve student outcomes were of particular interest in this regard. A related aim was the investigation of how design thinking strategies could be used by academics when designing new and innovative subjects and courses." Case Study 3: QUT Community Engaged Learning Lab Design Thinking/Design Led Innovation Workshop by Natalie Wright Context "The author, from the discipline area of Interior Design in the QUT School of Design, Faculty of Creative Industries, is a contributing academic and tutor for The Community Engaged Learning Lab, which was initiated at Queensland University of Technology in 2012. The Lab facilitates university-wide service-learning experiences and engages students, academics, and key community organisations in interdisciplinary action research projects to support student learning and to explore complex and ongoing problems nominated by the community partners. In Week 3, Semester One 2013, with the assistance of co-lead Dr Cara Wrigley, Senior Lecturer in Design led Innovation, a Masters of Architecture research student and nine participating industry-embedded Masters of Research (Design led Innovation) facilitators, a Design Thinking/Design led Innovation workshop was conducted for the Community Engaged Learning Lab students, and action research outcomes published at 2013 Tsinghua International Design Management Symposium, December 2013 in Shenzhen, China (Morehen, Wright, & Wrigley, 2013)."

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The metaphor of a feedback loop underpinned a significant curriculum change in a first year teacher-education unit. Assessment for Learning (AfL) practices such as discussing examples of previous student work and giving peer feedback were embedded within the curriculum design. The metaphor of a feedback loop connected these AfL practices into a purposeful process that informed student learning as well as tutor learning about student understanding, that then informed the next teaching episode. Student teachers (n=350) in twelve tutorial groups taught by eight university tutors were able to develop a shared understanding of quality performances before completing each assessment task. As well as providing ongoing insights to improve teaching, data from this action research project enabled the participant tutor-researchers to interrogate the concept of feedback loops. The researchers theorised sociocultural feedback loops as emergent, entangled and dynamic moves in a dance of knowing during which participants negotiated meaning and identities of capability.

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Widening participation brings with it increasing diversity, increased variation in the level of academic preparedness (Clarke, 2011; Nelson, Clarke, & Kift 2010). Cultural capital coupled with negotiating the academic culture creates an environment based on many assumptions about academic writing and university culture. Variations in staff and student expectations relating to the teaching and learning experience is captured in a range of national and institutional data (AUSSE, CEQ, LEX). Nationally, AUSSE data (2009) indicates that communication, writing, speaking and analytic skills, staff expectations are quite a bit higher than students. The research team noted a recognisable shift in the changing cohort of students and their understanding and engagement with feedback and CRAs, as well as variations in teaching staff and student expectations. The current reality of tutor and student roles is that: - Students self select when/how they access lectures and tutorials. - Shorter tutorial times result in reduced opportunity to develop rapport with students. - CRAs are not always used consistently by staff (different marking styles and levels of feedback). - Marking is not always undertaken by the student’s tutor/lecturer. - Student support services might be recommended to students once a poor grade has been given. Students can perceive this as remedial and a further sense of failure. - CRA sheet has a mark /grade attached to it. Stigma attached to low mark. Hard to focus on the CRA feedback with a poor mark etched next to it. - Limited opportunities for sessionals to access professional development to assist with engaging students and feedback. - FYE resources exist, however academic time is a factor in exploring and embedding these resources. Feedback is another area with differing expectations and understandings. Sadler (2009) contends that students are not equipped to decode the statements properly. For students to be able to apply feedback, they need to understand the meaning of the feedback statement. They also need to identify, the particular aspects of their work that need attention. The proposed Checklist/guide would be one page and submitted with each assessment piece thereby providing an interface to engage students and tutors in managing first year understandings and expectations around CRAs, feedback, and academic practice.

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BACKGROUND OR CONTEXT Thermodynamics is a core concept for mechanical engineers yet notoriously difficult. Evidence suggests students struggle to understand and apply the core fundamental concepts of thermodynamics with analysis indicating a problem with student learning/engagement. A contributing factor is that thermodynamics is a ‘science involving concepts based on experiments’ (Mayhew 1990) with subject matter that cannot be completely defined a priori. To succeed, students must engage in a deep-holistic approach while taking ownership of their learning. The difficulty in achieving this often manifests itself in students ‘not getting’ the principles and declaring thermodynamics ‘hard’. PURPOSE OR GOAL Traditionally, students practice and “learn” the application of thermodynamics in their tutorials, however these do not consider prior conceptions (Holman & Pilling 2004). As ‘hands on’ learning is the desired outcome of tutorials it is pertinent to study methods of improving their efficacy. Within the Australian context, the format of thermodynamics tutorials has remained relatively unchanged over the decades, relying anecdotally on a primarily didactic pedagogical approach. Such approaches are not conducive to deep learning (Ramsden 2003) with students often disengaged from the learning process. Evidence suggests (Haglund & Jeppsson 2012), however, that a deeper level and ownership of learning can be achieved using a more constructivist approach for example through self generated analogies. This pilot study aimed to collect data to support the hypothesis that the ‘difficulty’ of thermodynamics is associated with the pedagogical approach of tutorials rather than actual difficulty in subject content or deficiency in students. APPROACH Successful application of thermodynamic principles requires solid knowledge of the core concepts. Typically, tutorial sessions guide students in this application. However, a lack of deep and comprehensive understanding can lead to student confusion in the applications resulting in the learning of the ‘process’ of application without understanding ‘why’. The aim of this study was to gain empirical data on student learning of both concepts and application, within thermodynamic tutorials. The approach taken for data collection and analysis was: - 1 Four concurrent tutorial streams were timetabled to examine student engagement/learning in traditional ‘didactic’ (3 weeks) and non-traditional (3 weeks). In each week, two of the selected four sessions were traditional and two non-traditional. This provided a control group for each week. - 2 The non-traditional tutorials involved activities designed to promote student-centered deep learning. Specific pedagogies employed were: self-generated analogies, constructivist, peer-to-peer learning, inquiry based learning, ownership of learning and active learning. - 3 After a three-week period, teaching styles of the selected groups was switched, to allow each group to experience both approaches with the same tutor. This also acted to mimimise any influence of tutor personality / style on the data. - 4 At the conclusion of the trial participants completed a ‘5 minute essay’ on how they liked the sessions, a small questionnaire, modelled on the modified (Christo & Hoang, 2013)SPQ designed by Biggs (1987) and a small formative quiz to gauge the level of learning achieved. DISCUSSION Preliminary results indicate that overall students respond positively to in class demonstrations (inquiry based learning), and active learning activities. Within the active learning exercises, the current data suggests students preferred individual rather than group or peer-to-peer activities. Preliminary results from the open-ended questions such as “What did you like most/least about this tutorial” and “do you have other comments on how this tutorial could better facilitate your learning”, however, indicated polarising views on the nontraditional tutorial. Some student’s responded that they really like the format and emphasis on understanding the concepts, while others were very vocal that that ‘hated’ the style and just wanted the solutions to be presented by the tutor. RECOMMENDATIONS/IMPLICATIONS/CONCLUSION Preliminary results indicated a mixed, but overall positive response by students with more collaborative tutorials employing tasks promoting inquiry based, peer-to-peer, active, and ownership of learning activities. Preliminary results from student feedback supports evidence that students learn differently, and running tutorials focusing on only one pedagogical approached (typically didactic) may not be beneficial to all students. Further, preliminary data suggests that the learning / teaching style of both students and tutor are important to promoting deep learning in students. Data collection is still ongoing and scheduled for completion at the end of First Semester (Australian academic calendar). The final paper will examine in more detail the results and analysis of this project.