Description Part 1 initial question Think of how job performance (i.e., performance criteria) was ...
Description Part 1 initial question Think of how job performance (i.e., performance criteria) was measured in either past or current jobs you have held. Describe that performance measurement in terms of deficiency, relevance, and contamination using your text and SIOP (2019), and any other sources, and how it could have been improved. Explain why a test must be reliable before it can be valid. The use of mobile devices (Lawrence & Kinney, 2017) and artificial intelligence (Morelli, 2019) are controversial methods currently being used to hire employees. What personal experience with these methods? What research can you find to support or criticize their use? Select the "Week 2 Discussion" link above. Then, in the Week 2 Discussion forum, select "Reply" to add your response to the discussion questions. You must make a minimum of four substantive contributions on two separate days of the learning week to the discussion topic. Read over the course syllabus and the grading rubric for discussions before posting. For your initial discussion response use the course textbook and one peer-reviewed journals, scholarly source or two peer-reviewed journals, scholarly sources for the information you are paraphrasing and citing is due by Wednesday. Provide three student responses during the week with at least one scholarly source you are paraphrasing and citing each time. Do not post all three responses only on Saturday and Sunday, which doing so does not contribute to effective weekly engagement with your fellow students. All posts need to be completed before 6:00 PM EST on Sunday. Be sure to adhere to American Psychological Association (APA) 7th ed. style. Additionally, you are required to respond to questions asked by your professor. References: Lawrence & Kinney 2017.pdf SIOP 2019 Principles.pdf Morelli 2019.pdf part 2responfd to two peers peer1Hello Professor and classmates, Week 2 Discussion In a previous customer service role, I was judged mainly by how much I sold, how happy customers were, and how well my manager felt I did my job. While these numbers seemed simple to keep track of, they did not tell the whole story about how well the employees were doing their jobs. From a psychometric standpoint, the performance criteria were lacking because they did not pick up important things like how well people worked together, how they solved problems, or how they dealt with changes at work. According to the Society for Industrial and Organizational Psychology (SIOP) (2019), performance evaluations should be relevant, comprehensive, and contamination-free. In this case, the feedback was primarily based on the business side of things, while other factors, like how customers felt or how busy the store got, could affect the scores. SIOP (2019) also warns against over-relying on subjective judgment without a structured framework. These measures could have been improved by using behavioral checks, getting feedback from others, and setting up simple ways for people to give and receive feedback, which better match job-related skills and performance. This would make assessments more accurate and help ensure they measure what they are meant to measure. A test must be reliable before it can be considered valid, because if the same test measures different results every time, then the results will not make any sense. SIOP (2019) defines reliability as the degree to which a test yields consistent scores over time, across raters, or among different items. If a test is not consistent, then it might not measure what it should, so we cannot trust it to show what it says it shows. This is important to remember when making a test. Even if a test appears theoretically aligned with job performance (face validity), it cannot support employment decisions if it does not produce stable results. For example, if you use a test to look for leadership skills, the results should not change much if you test the same people in the same situation. Furthermore, SIOP (2019) highlights that reliability is a prerequisite for interpreting scores accurately, a point echoed by Morelli (2019), who notes that AI-based assessments must meet reliability benchmarks before being considered valid tools for talent evaluation. Without being reliable, the results of a study do not mean anything. In a past job application, I had to use a mobile-based assessment that was unfriendly and hard to work with. This made me feel that the company was not very organized or might not be the best workplace. Mobile-based hiring tools are increasingly popular, but Lawrence and Kinney (2017) emphasize that these tools must be explicitly designed for mobile platforms to ensure fair and equivalent experiences across devices. Candidates from minority and younger demographics are more likely to use mobile devices, and when tools are not optimized, it can introduce an adverse impact, undermining diversity goals (Lawrence & Kinney, 2017). Similarly, artificial intelligence (AI) is now being used to screen candidates, but Morelli (2019) warns that while AI offers efficiency, its use must be approached cautiously. AI tools must demonstrate reliability, fairness, and transparency to align with SIOP (2019) standards. If not properly checked, these tools could accidentally bring unfairness to hiring people. Therefore, organizations must follow scientific steps to test the fairness and accuracy of any digital or AI system they use when choosing people to hire. References Lawrence, A. D., & Kinney, T. B. (2017). Mobile devices and selection. Society for Industrial and Organizational Psychology. https://www.siop.org/wp-content/uploads/2024/12/Mobile-Devices-and-Selection.pdf Morelli, N. A. (2019). Artificial intelligence in talent assessment and selection. Society for Industrial and Organizational Psychology. https://www.siop.org/wp-content/uploads/2024/12/Artificial-Intelligence-in-Talent-Assessment-and-Selection.pdf Society for Industrial and Organizational Psychology. (2018). Principles for validating and using personnel selection procedures (5th ed.). https://www.apa.org/ed/accreditation/personnel-selection-procedures.pdf User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.
