scholarly journals Gamification of personality tests for recruitment

Author(s):  
Jahnavi Ravindra Bodhe
Keyword(s):  
2016 ◽  
Vol 32 (1) ◽  
pp. 52-60 ◽  
Author(s):  
Katarina Krkovic ◽  
Sascha Wüstenberg ◽  
Samuel Greiff

Abstract. Skilful collaborative problem-solving is becoming increasingly important in various life areas. However, researchers are still seeking ways to assess and foster this skill in individuals. In this study, we developed a computer-assisted assessment for collaborative behavior (COLBAS) following the experiment-based assessment of behavior approach (objective personality tests; Cattell, 1958 ). The instrument captures participants’ collaborative behavior in problem-solving tasks using the MicroDYN approach while participants work collaboratively with a computer-agent. COLBAS can thereby assess problem-solving and collaborative behavior expressed through communication acts. To investigate its validity, we administered COLBAS to 483 German seventh graders along with MicroDYN as a measure of individual problem-solving skills and questions regarding the motivation to collaborate. A latent confirmatory factor analysis suggested a five-dimensional construct with two problem-solving dimensions (knowledge acquisition and knowledge application) and three collaboration dimensions (questioning, asserting, and requesting). The results showed that extending MicroDYN to include collaborative aspects did not considerably change the measurement of problem-solving. Finally, students who were more motivated to collaborate interacted more with the computer-agent but also obtained worse problem-solving results.


2012 ◽  
Vol 11 (4) ◽  
pp. 169-175 ◽  
Author(s):  
Katherine A. Sliter ◽  
Neil D. Christiansen

The present study evaluated the impact of reading self-coaching book excerpts on success at faking a personality test. Participants (N = 207) completed an initial honest personality assessment and a subsequent assessment with faking instructions under one of the following self-coaching conditions: no coaching, chapters from a commercial book on how to fake preemployment personality scales, and personality coaching plus a chapter on avoiding lie-detection scales. Results showed that those receiving coaching materials had greater success in raising their personality scores, primarily on the traits that had been targeted in the chapters. In addition, those who read the chapter on avoiding lie-detection scales scored significantly lower on a popular impression management scale while simultaneously increasing their personality scores. Implications for the use of personality tests in personnel selection are discussed.


2012 ◽  
Author(s):  
Stacey R. Kessler ◽  
Matthew H. Reider ◽  
Michael A. Campion
Keyword(s):  

2020 ◽  
Author(s):  
Minhaaj Rehman ◽  
John Anthony Johnson

The NEO-IPIP-300 is a 300-item version scale of freely available personality tests based on the OCEAN Model of 30 distinctive personality traits. The scale measures human personality preferences and groups them into five distinct factors, namely Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. The scale has been translated into many languages before, but there was no translation and norms available for the Urdu language.Paper reports the translation, creation of web version, data collection (N=869), and reliability of Urdu version of NEO-IPIP-300. We also did a CFA Analysis and Measurement Invariance test as part of the paper. Full measurement invariance was met for the full model, and partial measurement invariance was met for neuroticism (metric and scalar) and extraversion (metric). In general, all models fit well and suggest that the Urdu IPIP-300-NEO aligns well with the English IPIP-300-NEO. In some cases, the Urdu inventory performed better (e.g., higher internal consistency) than the English inventory.


2015 ◽  
Vol 23 (3) ◽  
pp. 460
Author(s):  
Jiyue CHEN ◽  
Jianping XU ◽  
Hongyan LI ◽  
Yexin FAN ◽  
Xiaolan LU
Keyword(s):  

2015 ◽  
Vol 47 (11) ◽  
pp. 1395
Author(s):  
Jianping XU ◽  
Jiyue CHEN ◽  
Wei ZHANG ◽  
Wenya LI ◽  
Yu SHENG

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