行业资讯
提高研究生选拔效度情景判断测验的开发与实证研究
发布时间:2023-10-30 来源: 访问:
表2知识测验、SJT得分与创新绩效的回归分析表
变量 知识测验(考研分数)
第一步 第二步 第三步
性别 -0.10 -0.13* -0.14*
年级 0.04 0.03 -0.01
专业相关度 0.19** 0.15** 0.12*
陈述性知识(考研分数) 0.19** 0.13*
程序性知识(SJT得分) 0.33***
R2 0.04 0.08 0.19
0.04 0.04 0.11
F 4.37** 6.08*** 12.84***
4.37** 10.77** 36.85***
注:***P<0. 001;** P<0. 01;* P<0. 05。
五、结论与讨论
本研究引入情景判断测验的方法,探究了提升研究生选拔效度的途径。实证结果表明:(1)基于研究生选拔场景所开发的情景判断测验具有良好的信度(=0.73)和效标关联效度(r=0.37,p<0.01),能有效预测研究生的创新绩效;(2)情景判断测验对现有的研究生统一考试有增值效度,可以提高对研究生创新绩效约11%的解释力。
基于以上研究结论,为提高研究生的培养质量和创新绩效水平,在进行研究生选拔和培养时可以获得以下几点启示:
第一,研究生选拔中既要注重对考生陈述性知识的考察,也要注重程序性知识的考察。这有利更全面、有效地对考生的创新潜力做出评估。陈述性知识是个体创新的基础,只有具备良好的知识储备和专业技能,才能不断地发现和提出新的问题、新的想法。而程序性知识是个体创新的重要推动力,可以使个体在创新过程中做出有效的行为选择,推动创新想法提升和实现。研究生选拔中不仅要强化对考生基础知识、专业知识等陈述性知识考量,还要注意加强对科研实践能力以及科研活动中的程序性知识的考量。
第二,高校应深化研究生招生机制改革,引入SJT等更加多元化的测评方式,通过不同测评方法之间的优势互补,提高研究生选拔的有效性。研究生入学选拔是研究生教育的起点,也是事关研究生生源质量和培养水平的关键环节。目前我国知识测验加结构化面试的研究生选拔形式下,存在着知识测验过于宽泛、缺乏针对性,面试中主观干扰太强、难以量化等弊端。而SJT作为一种模拟测验,可以通过对个体在与研究生创新活动中的关键情景的行为判断和行为选择的考察,衡量考生是否具备创新工作所需要的程序性知识,评估考生未来的创新潜力。在研究生选拔中引入SJT可以弥补现有研究生选拔方式的不足,是对现有的研究生选拔方式进行有效补充。
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