3,891 research outputs found

    Enhancing Programming eTextbooks with ChatGPT Generated Counterfactual-Thinking-Inspired Questions

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    Digital textbooks have become an integral part of everyday learning tasks. In this work, we consider the use of digital textbooks for programming classes. Generally, students struggle with utilizing textbooks on programming to the maximum, with a possible reason being that the example programs provided as illustration of concepts in these textbooks don't offer sufficient interactivity for students, and thereby not sufficiently motivating to explore or understand these programming examples better. In our work, we explore the idea of enhancing the navigability of intelligent textbooks with the use of ``counterfactual'' questions, to make students think critically about these programs and enhance possible program comprehension. Inspired from previous works on nudging students on counter factual thinking, we present the possibility to enhance digital textbooks with questions generated using GPT.Comment: Paper Under Revie

    A Programming Environment Evaluation Methodology for Object-Oriented Systems

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    The object-oriented design strategy as both a problem decomposition and system development paradigm has made impressive inroads into the various areas of the computing sciences. Substantial development productivity improvements have been demonstrated in areas ranging from artificial intelligence to user interface design. However, there has been very little progress in the formal characterization of these productivity improvements and in the identification of the underlying cognitive mechanisms. The development and validation of models and metrics of this sort require large amounts of systematically-gathered structural and productivity data. There has, however, been a notable lack of systematically-gathered information on these development environments. A large part of this problem is attributable to the lack of a systematic programming environment evaluation methodology that is appropriate to the evaluation of object-oriented systems

    Google Translate as a Resource for Writing

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    This action research was prompted by the question “Does using Google Translate improve students’ writing?” When implemented according to guidelines from previous research, students produced writing with fewer syntactic and semantic errors. Data was collected through student work samples, classroom observations, and a questionnaire. Three themes arose through data analysis: that students found value in Google Translate, that one instance of instruction was not sufficient for all students to acquire necessary strategies, and that students’ lack of familiarity with both Google Translate and the Spanish language hampered their success. These findings demonstrate the importance of providing teachers and students with instruction on Google Translate, as well as the need for further research on the effects of translators on vocabulary acquisition

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    THE ROLE OF COGNITIVE APPORTIONMENT IN INFORMATION SYSTEMS

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    As the number of information system users increases, we are witnessing a related increase in the complexity and the diversity of their applications. The increasing functional complexity amplifies the degree of functional and technical understanding required of the user to make productive use of the application tools. Emerging technologies, increased and varied user interests and radical changes in the nature of applications give rise to the opportunity and necessity to re-examine the proper apportionment of cognitive responsibilities in human/system interaction. Examples illustrate the opportunities afforded by such an examination. A framework is presented that illustrates many of the tradeoffs that occur in a reapportionment activity. A knowledge-based architecture is proposed to facilitate both static and dynamic reapportionment decisions

    Human-AI Collaboration for Smart Education: Reframing Applied Learning to Support Metacognition

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    This chapter investigates the profound influence of intelligent virtual assistants (IVAs) on the educational domain, specifically in the realm of individualized learning and the instruction of writing abilities and content creation. IVAs, incorporating generative AI technologies such as ChatGPT and Stable Diffusion, hold the potential to bring about a paradigm shift in educational programs, emphasizing the enhancement of advanced metacognitive capacities rather than the fundamentals of communication. The subsequent recommendations stress the need to cultivate enduring proficiencies and ascertain tailored learning approaches for each learner, which will be indispensable for success in the evolving job market. In this context, prompt engineering is emerging as a vital competency, while continuous reskilling and lifelong learning become professional requisites. The proposed innovative method for teaching writing skills and content generation advocates for a reconfiguration of curricula to concentrate on applied learning techniques that accentuate the value of contextual judgment as a central pedagogical tenet and the mastery of sophisticated metacognitive abilities, which will be pivotal in the future of work

    Paving the Way for Lifelong Learning:Facilitating competence development through a learning path specification

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    Janssen, J. (2010). Paving the Way for Lifelong Learning. Facilitating competence development through a learning path specification. September, 17, 2010, Heerlen, The Netherlands: Open University of the Netherlands, CELSTEC. SIKS Dissertation Series No. 2010-36. ISBN 978-90-79447-43-5Efficient and effective lifelong learning requires that learners can make well informed decisions regarding the selection of a learning path, i.e. a set of learning actions that help attain particular learning goals. In recent decades a strong emphasis on lifelong learning has led educational provision to expand and to become more varied and flexible. Besides, the role of informal learning has become increasingly acknowledged. In light of these developments this thesis addresses the question: How to support learners in finding their way through all available options and selecting a learning path that best fit their needs? The thesis describes two different approaches regarding the provision of way finding support, which can be considered complementary. The first, inductive approach proposes to provide recommendations based on indirect social interaction: analysing the paths followed by other learners and feeding this information back as advice to learners facing navigational decisions. The second, prescriptive approach proposes to use a learning path specification to describe both the contents and the structure of any learning path in a formal and uniform way. This facilitates comparison and selection of learning paths across institutions and systems, but also enables automated provision of way finding support for a chosen learning path. Moreover, it facilitates automated personalisation of a learning path, i.e. adapting the learning path to the needs of a particular learner. Following the first approach a recommender system was developed and tested in an experimental setting. Results showed use of the system significantly enhanced effectiveness of learning. In line with the second approach a learning path specification was developed and validated in three successive evaluations. Firstly, an investigation of lifelong learners’ information needs. Secondly, an evaluation of the specification through a reference (sample) implementation: a tool to describe learning paths according to the specification. Finally, an evaluation of the use and purpose of this tool involving prospective end-users: study advisors and learning designers. Following the various evaluations the Learning Path Specification underwent some changes over time. Results described in this thesis show that the proposed approach of the Learning Path Specification and the reference implementation were well received by end-users.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org
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