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User evaluation of a task for shortlisting papers from researcher's reading list for citing in manuscripts

机译:用户对从研究人员的阅读清单中选出论文以供引用的任务的评估

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Purpose - Although many interventional approaches have been proposed to address the apparent gap between novices and experts for literature review (LR) search tasks, there have been very few approaches proposed for manuscript preparation (MP) related tasks. The purpose of this paper is to describe a task and an incumbent technique for shortlisting important and unique papers from the reading list (RL) of researchers, meant for citation in a manuscript. Design/methodology/approach - A user evaluation study was conducted on the prototype system which was built for supporting the shortlisting papers (SP) task along with two other LR search tasks. A total of 119 researchers who had experience in authoring research papers participated in this study. An online questionnaire was provided to the participants for evaluating the task. Both quantitative and qualitative analyses were performed on the collected evaluation data. Findings - Graduate research students prefer this task more than research and academic staff. The evaluation measures relevance, usefulness and certainty were identified as predictors for the output quality measure "good list". The shortlisting feature and information cues were the preferred aspects while limited data set and rote steps in the study were ascertained as critical aspects from the qualitative feedback of the participants. Originality/value - Findings point out that researchers are clearly interested in this novel task of SP from the final RL prepared during LR. This has implications for digital library, academic databases and reference management software where this task can be included to benefit researchers at the manuscript preparatory stage of the research lifecycle.
机译:目的-尽管已经提出了许多干预方法来解决新手和专家之间文献检索(LR)搜索任务之间明显的差距,但针对手稿准备(MP)相关任务提出的方法却很少。本文的目的是描述一项任务和一种现有技术,用于从研究人员的阅读清单(RL)中筛选出重要且独特的论文,以供引用。设计/方法/方法-对原型系统进行了用户评估研究,该系统旨在支持入围论文(SP)任务以及其他两个LR搜索任务。共有119位具有撰写研究论文经验的研究人员参与了这项研究。已向参与者提供了在线问卷以评估任务。对收集的评估数据进行了定量和定性分析。结果-研究型研究生比研究和学术人员更喜欢此任务。评价措施的相关性,有用性和确定性被确定为产出质量措施“良好清单”的预测指标。入围特征和信息提示是首选方面,而参与者的定性反馈则将有限的数据集和死记硬背确定为关键方面。原创性/价值-研究结果表明,研究人员显然对LR期间准备的最终RL的SP这项新颖任务感兴趣。这对数字图书馆,学术数据库和参考管理软件有影响,在研究生命周期的手稿准备阶段,可以包括此任务以使研究人员受益。

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