While cost, time, and resources are considered to have a high impact on datascience projects, risks are the key for the successful implementation of a project. The correct handling of risks has been proven to increas...
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The research presented in this paper is motivated by the need for comprehensive quality control and assessment of the downlinked raw data from space science satellites, utilizing limited information before data calibr...
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datascience (DS) aims to extract knowledge from large amounts of data. Organizations can use the retrieved insights to achieve various performance improvements. However, DS projects often fail to fulfill their object...
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Described as the"sexiest job of the 21st century", the data scientist profession has attracted a lot of attention and demand over the past decade. The rapid growth of this profession, coupled with high barri...
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The research aims to optimize agriculture using datascience techniques. Agriculture is a critical sector for sustaining life on earth, and optimizing it can enhance food security and increase the profitability of far...
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This study presents a datascience Chat bot that uses Natural Language Processing techniques, namely the Natural Language Toolkit. As an intelligent conversational agent, the chat bot helps users navigate and derive i...
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We have conducted research on the construction of educational curricula and proposed a stage-wised refinement curriculum model for datascience education at liberal arts universities. The model consists of four stages...
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The disruptive effect and lasting implications of generative artificial intelligence ('Gen AI') tools for higher education are yet unknown. ChatGPT 3.5 was released in November 2022 and soon had over 100 milli...
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In this Innovative-Practice Full Paper, we present the design and implementation of a novel strategy for the assessment of the individual contributions of students working in teams for an interdisciplinary project-bas...
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ISBN:
(纸本)9798350351507
In this Innovative-Practice Full Paper, we present the design and implementation of a novel strategy for the assessment of the individual contributions of students working in teams for an interdisciplinary project-based learning (PBL) course. Team-based and project-based learning have been the cornerstones of experiential learning in recent years. In such courses, the assessment of students is often performed solely at a team level, resulting in student discontent, concerns about fairness, and social loafing. The application of a single method for evaluating individual contributions has its shortcomings, prompting us to incorporate a combination of evidence-based approaches. Thus, to mitigate these problems, we developed an assessment strategy that involves three components - self and peer evaluation (SPA), instructor's evaluation of individual contribution, and class participation. Anonymized SPA was carried out at three different checkpoints over the semester for both formative and summative assessment. The individual contribution of the students is also evaluated by the instructor and/or other mentors based on their interactions with all the students in the team over the entire semester. Class participation is another component of individual contribution incorporated in our scheme, where instructors evaluate the participation of individual students in classroom activities, presentations, and meetings. We collected feedback about the perception of students towards our assessment policies for individual contribution. We observed overall satisfaction and positive attitudes toward our scheme. We noted positive student perceptions of fairness in grading through our scheme and reduced chances of social loafing. Further, in the feedback, the students noted the effectiveness of using SPA as an evaluation tool, the usefulness of instructor's evaluation, and the role of class participation in creating a more engaging classroom and a more enriching experience. We also empha
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